From a72c60677c958d2fbdbf343864c2ee656e930477 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Tue, 9 Dec 2025 11:46:36 -0800
Subject: [PATCH 01/21] fix accessibility

---
 src/views/About.tsx          | 480 +++++++++--------------------------
 src/views/DataFormulator.tsx |   2 +-
 2 files changed, 121 insertions(+), 361 deletions(-)

diff --git a/src/views/About.tsx b/src/views/About.tsx
index 8277733..689c076 100644
--- a/src/views/About.tsx
+++ b/src/views/About.tsx
@@ -1,16 +1,13 @@
 // Copyright (c) Microsoft Corporation.
 // Licensed under the MIT License.
 
-import { Box, Typography, Button, useTheme, alpha, IconButton, Divider } from "@mui/material";
-import React, { FC, useState, useEffect, useRef } from "react";
-import ArrowBackIosNewIcon from '@mui/icons-material/ArrowBackIosNew';
-import ArrowForwardIosIcon from '@mui/icons-material/ArrowForwardIos';
+import { Box, Typography, Button, useTheme, alpha, Divider } from "@mui/material";
+import React, { FC } from "react";
 import GridViewIcon from '@mui/icons-material/GridView';
 import GitHubIcon from '@mui/icons-material/GitHub';
 import YouTubeIcon from '@mui/icons-material/YouTube';
 import PrecisionManufacturingIcon from '@mui/icons-material/PrecisionManufacturing';
 
-import dfLogo from '../assets/df-logo.png';
 import { toolName } from "../app/App";
 import { useSelector } from "react-redux";
 import { DataFormulatorState } from "../app/dfSlice";
@@ -50,241 +47,129 @@ const features: Feature[] = [
     }
 ];
 
-const screenshots: {url: string, description: string}[] = [
-    {url: "/data-formulator-screenshot-v0.5.webp", description: "Explore consumer price trends from 2005 to 2025"},
-    {url: "/screenshot-movies-report.webp", description: "Report: Top directors by their revenue"},
-    {url: "/screenshot-renewable-energy.webp", description: "Renewable energy percentage by country"},
-    {url: '/screenshot-unemployment.webp', description: 'Report: Unemployment rate affected by 2008 financial crisis'},
-    {url: '/screenshot-claude-performance.webp', description: 'Compare Claude models\' performance on different tasks'},
-];
-
 export const About: FC<{}> = function About({ }) {
     const theme = useTheme();
-    const [currentFeature, setCurrentFeature] = useState(0);
-    const [currentScreenshot, setCurrentScreenshot] = useState(0);
-    const videoRef = useRef<HTMLVideoElement | null>(null);
-    const videoDurationsRef = useRef<Map<string, number>>(new Map());
-
-    const handlePrevious = () => {
-        setCurrentFeature((prev) => (prev === 0 ? features.length - 1 : prev - 1));
-    };
-
-    const handleNext = () => {
-        setCurrentFeature((prev) => (prev === features.length - 1 ? 0 : prev + 1));
-    };
-
-    // Auto-advance features based on video duration
-    useEffect(() => {
-        const currentMedia = features[currentFeature].media;
-        const isVideo = features[currentFeature].mediaType === 'video';
-        
-        // Default duration for images or if video duration is not yet loaded
-        let duration = 10000; // 10 seconds for images
-        
-        if (isVideo && videoDurationsRef.current.has(currentMedia)) {
-            // Use the stored video duration (in milliseconds)
-            duration = videoDurationsRef.current.get(currentMedia)! * 1000;
-            duration = duration + 3000; // add 3 seconds to the video duration
-        }
-
-        const timeoutId = setTimeout(() => {
-            setCurrentFeature((prev) => (prev + 1) % features.length);
-        }, duration);
-
-        return () => clearTimeout(timeoutId);
-    }, [currentFeature]);
-
-    // Preload adjacent carousel items for smoother transitions
-    useEffect(() => {
-        const preloadMedia = (index: number) => {
-            const feature = features[index];
-            if (feature.mediaType === 'video') {
-                const video = document.createElement('video');
-                video.src = feature.media;
-                video.preload = 'metadata';
-            } else {
-                const img = new Image();
-                img.src = feature.media;
-            }
-        };
-
-        // Preload next and previous features
-        const nextIndex = (currentFeature + 1) % features.length;
-        const prevIndex = currentFeature === 0 ? features.length - 1 : currentFeature - 1;
-        
-        preloadMedia(nextIndex);
-        preloadMedia(prevIndex);
-
-        // Preload next and previous screenshots
-        const nextScreenshot = (currentScreenshot + 1) % screenshots.length;
-        const prevScreenshot = currentScreenshot === 0 ? screenshots.length - 1 : currentScreenshot - 1;
-        
-        const img1 = new Image();
-        img1.src = screenshots[nextScreenshot].url;
-        const img2 = new Image();
-        img2.src = screenshots[prevScreenshot].url;
-    }, [currentFeature, currentScreenshot]);
-
     const serverConfig = useSelector((state: DataFormulatorState) => state.serverConfig);
 
     let actionButtons = !serverConfig.PROJECT_FRONT_PAGE ? (
-        <Box sx={{ display: 'flex', justifyContent: 'center', gap: 1, mb: 4, flexWrap: 'wrap' }}>
+        <Box component="nav" aria-label="Primary actions" sx={{ display: 'flex', justifyContent: 'center', gap: 1.5, mb: 4, flexWrap: 'wrap' }}>
             <Button size="large" variant="contained" color="primary" 
-                startIcon={<PrecisionManufacturingIcon sx={{ fontSize: '1rem' }} />}
+                startIcon={<PrecisionManufacturingIcon aria-hidden="true" />}
                 href="/app"
             >Start Exploration</Button>
         </Box>
     ) : (
-        <Box sx={{ display: 'flex', justifyContent: 'center', gap: 2, mb: 4, flexWrap: 'wrap', '.MuiButton-root': { textTransform: 'none' } }}>
+        <Box component="nav" aria-label="Primary actions" sx={{ display: 'flex', justifyContent: 'center', gap: 1.5, mb: 4, flexWrap: 'wrap' }}>
             <Button size="large" variant="outlined" color="primary" 
-                startIcon={<YouTubeIcon sx={{ fontSize: '1rem', color: '#FF0000' }} />}
+                sx={{ textTransform: 'none' }}
+                startIcon={<Box component="img" sx={{ width: 20, height: 20 }} alt="" aria-hidden="true" src="/pip-logo.svg" />}
                 target="_blank"
                 rel="noopener noreferrer"
-                href="https://www.youtube.com/watch?v=GfTE2FLyMrs"
-            >What's New in v0.5?</Button>
+                aria-label="Install Locally via pip (opens in new tab)"
+                href="https://pypi.org/project/data-formulator/"
+            >Install Locally</Button>
+            <Button size="large" variant="contained" color="primary" 
+                sx={{ textTransform: 'none' }}
+                startIcon={<GridViewIcon aria-hidden="true" />}
+                href="/app"
+            >Try Online Demo</Button>
             <Button size="large" variant="outlined" color="primary" 
-                startIcon={<GitHubIcon sx={{ fontSize: '1rem', color: '#000000' }} />}
+                sx={{ textTransform: 'none' }}
+                startIcon={<YouTubeIcon sx={{ color: '#FF0000' }} aria-hidden="true" />}
                 target="_blank"
                 rel="noopener noreferrer"
-                href="https://github.com/microsoft/data-formulator"
-            >GitHub</Button>
-            <Divider orientation="vertical" sx={{ mx: 1 }} flexItem />
+                aria-label="Watch Video on YouTube (opens in new tab)"
+                href="https://www.youtube.com/watch?v=GfTE2FLyMrs"
+            >Video</Button>
             <Button size="large" variant="outlined" color="primary" 
-                startIcon={<Box component="img" sx={{ width: 24, height: 24 }} alt="" src="/pip-logo.svg" />}
+                sx={{ textTransform: 'none' }}
+                startIcon={<GitHubIcon aria-hidden="true" />}
                 target="_blank"
                 rel="noopener noreferrer"
-                href="https://pypi.org/project/data-formulator/"
-            >Install Locally</Button>
-            <Button size="large" variant="outlined" color="primary" 
-                sx={{
-                    animation: 'subtleGlow 2s ease-in-out infinite',
-                    '@keyframes subtleGlow': {
-                        '0%, 100%': {
-                            boxShadow: `0 0 8px ${alpha(theme.palette.primary.main, 0.4)}, 0 0 16px ${alpha(theme.palette.primary.main, 0.2)}`,
-                        },
-                        '50%': {
-                            boxShadow: `0 0 12px ${alpha(theme.palette.primary.main, 0.6)}, 0 0 24px ${alpha(theme.palette.primary.main, 0.3)}, 0 0 32px ${alpha(theme.palette.primary.main, 0.1)}`,
-                        }
-                    },
-                    '&:hover': {
-                        animation: 'subtleGlow 1.5s ease-in-out infinite',
-                        boxShadow: `0 0 16px ${alpha(theme.palette.primary.main, 0.7)}, 0 0 32px ${alpha(theme.palette.primary.main, 0.4)} !important`,
-                    }
-                }}
-                startIcon={<GridViewIcon sx={{ fontSize: '1rem' }} />}
-                href="/app"
-            >Try Online Demo</Button>
-            <Typography variant="caption" sx={{ mt: 1.5, color: 'text.secondary', fontStyle: 'italic' }}>
-                Psst — install locally for the full experience ✨. The online demo has limited features (at the moment).
-            </Typography>
+                aria-label="View on GitHub (opens in new tab)"
+                href="https://github.com/microsoft/data-formulator"
+            >GitHub</Button>
         </Box>
     );
 
     return (
-        <Box sx={{
-            display: "flex", 
-            flexDirection: "column", 
-            textAlign: "center", 
-            overflowY: "auto",
-            width: '100%',
-            height: '100%',
-            background: `
-                linear-gradient(90deg, ${alpha(theme.palette.text.secondary, 0.01)} 1px, transparent 1px),
-                linear-gradient(0deg, ${alpha(theme.palette.text.secondary, 0.01)} 1px, transparent 1px)
-            `,
-            backgroundSize: '16px 16px',
-        }}>
-            <Box sx={{margin:'auto', pb: '5%', display: "flex", flexDirection: "column", textAlign: "center", maxWidth: 1200}}>
-                {/* Header with logo and title */}
-                <Box sx={{display: 'flex', mx: 'auto', mt: 4}}>
-                    <Typography fontSize={84} sx={{ml: 2, letterSpacing: '0.05em'}}>{toolName}</Typography> 
+        <Box 
+            component="main"
+            role="main"
+            sx={{
+                display: "flex", 
+                flexDirection: "column", 
+                overflowY: "auto",
+                width: '100%',
+                height: '100%',
+                background: `
+                    linear-gradient(90deg, ${alpha(theme.palette.text.secondary, 0.01)} 1px, transparent 1px),
+                    linear-gradient(0deg, ${alpha(theme.palette.text.secondary, 0.01)} 1px, transparent 1px)
+                `,
+                backgroundSize: '16px 16px',
+            }}
+        >
+            <Box sx={{margin:'auto', py: 4, display: "flex", flexDirection: "column", textAlign: "center", maxWidth: 1000, width: '100%', px: 3}}>
+                {/* Header with title */}
+                <Box component="header" sx={{display: 'flex', flexDirection: 'column', mx: 'auto', mt: 2}}>
+                    <Typography component="h1" fontSize={84} sx={{letterSpacing: '0.05em'}}>{toolName}</Typography> 
+                    <Typography component="p" sx={{ 
+                        fontSize: 24, color: theme.palette.text.secondary, 
+                        textAlign: 'center', mb: 4}}>
+                        Explore data with visualizations, powered by AI agents. 
+                    </Typography>
                 </Box>
-                <Typography sx={{ 
-                    fontSize: 24, color: theme.palette.text.secondary, 
-                    textAlign: 'center', mb: 4}}>
-                    Explore data with visualizations, powered by AI agents. 
-                </Typography>
                 
                 {actionButtons}
 
-                {/* Interactive Features Carousel */}
-                <Box sx={{
-                    mx: 'auto',
-                    maxWidth: 1200,
-                    borderRadius: 3, 
-                    position: 'relative',
-                }}>
-                    <Box sx={{ 
-                        display: 'flex', 
-                        alignItems: 'center', 
-                        gap: 3,
-                        height: '40vh',
-                        minHeight: 320,
-                    }}>
-                        {/* Left Arrow */}
-                        <IconButton 
-                            onClick={handlePrevious}
+                {/* Features Grid - 2 columns, 4 rows */}
+                <Box 
+                    component="section" 
+                    aria-label="Features"
+                    sx={{ display: 'flex', flexDirection: 'column', gap: 5, mt: 2 }}
+                >
+                    {features.map((feature, index) => (
+                        <Box 
+                            component="article"
+                            key={index}
+                            aria-labelledby={`feature-title-${index}`}
                             sx={{ 
-                                flexShrink: 0,
-                                bgcolor: alpha(theme.palette.primary.main, 0.1),
-                                '&:hover': {
-                                    bgcolor: alpha(theme.palette.primary.main, 0.2),
-                                }
+                                display: 'flex', 
+                                flexDirection: index % 2 === 0 ? 'row' : 'row-reverse',
+                                gap: 4,
+                                alignItems: 'center',
                             }}
                         >
-                            <ArrowBackIosNewIcon />
-                        </IconButton>
-
-                        {/* Feature Content */}
-                        <Box sx={{ 
-                            flex: 1, 
-                            display: 'flex', 
-                            flexDirection: 'row',
-                            gap: 4,
-                            alignItems: 'center',
-                        }}>
                             {/* Text Content */}
                             <Box sx={{ 
                                 flex: 1,
-                                textAlign: 'left',
-                                minWidth: 300,
+                                textAlign: index % 2 === 0 ? 'left' : 'right',
+                                display: 'flex',
+                                flexDirection: 'column',
+                                justifyContent: 'center',
                             }}>
                                 <Typography 
-                                    variant="h4" 
-                                    sx={{ mb: 2 }}
+                                    component="h2"
+                                    id={`feature-title-${index}`}
+                                    sx={{ 
+                                        fontSize: 28,
+                                        fontWeight: 500,
+                                        mb: 1.5,
+                                        color: theme.palette.text.primary,
+                                    }}
                                 >
-                                    {features[currentFeature].title}
+                                    {feature.title}
                                 </Typography>
                                 <Typography 
-                                    variant="body1" 
-                                    sx={{ color: 'text.secondary', lineHeight: 1.8 }}
+                                    component="p"
+                                    sx={{ 
+                                        fontSize: 17,
+                                        color: 'text.secondary', 
+                                        lineHeight: 1.7,
+                                    }}
                                 >
-                                    {features[currentFeature].description}
+                                    {feature.description}
                                 </Typography>
-                                
-                                {/* Feature Indicators */}
-                                <Box sx={{ display: 'flex', gap: 1, mt: 3 }}>
-                                    {features.map((_, index) => (
-                                        <Box
-                                            key={index}
-                                            onClick={() => setCurrentFeature(index)}
-                                            sx={{
-                                                width: 32,
-                                                height: 4,
-                                                borderRadius: 2,
-                                                bgcolor: index === currentFeature 
-                                                    ? theme.palette.primary.main 
-                                                    : alpha(theme.palette.text.secondary, 0.2),
-                                                cursor: 'pointer',
-                                                '&:hover': {
-                                                    bgcolor: index === currentFeature 
-                                                        ? theme.palette.primary.main 
-                                                        : alpha(theme.palette.text.secondary, 0.4),
-                                                }
-                                            }}
-                                        />
-                                    ))}
-                                </Box>
                             </Box>
 
                             {/* Media Content */}
@@ -292,30 +177,18 @@ export const About: FC<{}> = function About({ }) {
                                 flex: 1,
                                 borderRadius: 2,
                                 overflow: 'hidden',
-                                boxShadow: '0 4px 12px rgba(0,0,0,0.1)',
-                                minWidth: 300,
-                                maxWidth: 500,
+                                border: '1px solid rgba(0,0,0,0.1)',
                             }}>
-                                {features[currentFeature].mediaType === 'video' ? (
+                                {feature.mediaType === 'video' ? (
                                     <Box
                                         component="video"
-                                        key={features[currentFeature].media}
-                                        src={features[currentFeature].media}
-                                        ref={videoRef}
+                                        src={feature.media}
                                         autoPlay
                                         loop
                                         muted
                                         playsInline
                                         preload="metadata"
-                                        onLoadedMetadata={(e) => {
-                                            const video = e.currentTarget as HTMLVideoElement;
-                                            if (video.duration && !isNaN(video.duration)) {
-                                                videoDurationsRef.current.set(
-                                                    features[currentFeature].media,
-                                                    video.duration
-                                                );
-                                            }
-                                        }}
+                                        aria-label={`Video demonstration: ${feature.title}`}
                                         sx={{
                                             width: '100%',
                                             height: 'auto',
@@ -325,8 +198,8 @@ export const About: FC<{}> = function About({ }) {
                                 ) : (
                                     <Box
                                         component="img"
-                                        src={features[currentFeature].media}
-                                        alt={features[currentFeature].title}
+                                        src={feature.media}
+                                        alt={feature.title}
                                         loading="lazy"
                                         sx={{
                                             width: '100%',
@@ -337,161 +210,48 @@ export const About: FC<{}> = function About({ }) {
                                 )}
                             </Box>
                         </Box>
-
-                        {/* Right Arrow */}
-                        <IconButton 
-                            onClick={handleNext}
-                            sx={{ 
-                                flexShrink: 0,
-                                bgcolor: alpha(theme.palette.primary.main, 0.1),
-                                '&:hover': {
-                                    bgcolor: alpha(theme.palette.primary.main, 0.2),
-                                }
-                            }}
-                        >
-                            <ArrowForwardIosIcon />
-                        </IconButton>
-                    </Box>
-                </Box>
-                
-                {/* Screenshots Carousel Section */}
-                <Box sx={{ mt: 6, mx: 2 }}>
-                    <Box sx={{ 
-                        display: 'flex',
-                        flexDirection: 'column',
-                        alignItems: 'center',
-                        gap: 3
-                    }}>
-                        {/* Screenshot Container */}
-                        <Box 
-                            key={currentScreenshot}
-                            onClick={() => setCurrentScreenshot((currentScreenshot + 1) % screenshots.length)}
-                            sx={{
-                                height: 680,
-                                width: 'auto',
-                                borderRadius: 8,
-                                cursor: 'pointer',
-                                overflow: 'hidden',
-                                border: '1px solid rgba(0,0,0,0.1)',
-                                boxShadow: '0 4px 12px rgba(0,0,0,0.1)',
-                                position: 'relative',
-                                display: 'flex',
-                                justifyContent: 'center',
-                                textDecoration: 'none',
-                                animation: 'fadeSlideIn 0.1s ease-out',
-                                '&:hover': {
-                                    boxShadow: '0 8px 24px rgba(0,0,0,0.2)',
-                                    '& .description-overlay': {
-                                        opacity: 1,
-                                    }
-                                }
-                            }}
-                        >
-                            <Box 
-                                component="img" 
-                                sx={{
-                                    display: 'block',
-                                    clipPath: 'inset(2px 0 0 0)'
-                                }} 
-                                alt={screenshots[currentScreenshot].description} 
-                                src={screenshots[currentScreenshot].url}
-                                loading="lazy"
-                            />
-                            <Box
-                                className="description-overlay"
-                                sx={{
-                                    position: 'absolute',
-                                    bottom: 0,
-                                    left: 0,
-                                    right: 0,
-                                    backgroundColor: 'rgba(250, 250, 250, 0.6)',
-                                    backdropFilter: 'blur(8px)',
-                                    padding: 2,
-                                    opacity: 0,
-                                    transition: 'opacity 0.3s ease',
-                                }}
-                            >
-                                <Typography 
-                                    variant="body1" 
-                                    color="text.secondary"
-                                    sx={{ 
-                                        fontSize: '2rem',
-                                        fontWeight: 400,
-                                        textAlign: 'center'
-                                    }}
-                                >
-                                    {screenshots[currentScreenshot].description}
-                                </Typography>
-                            </Box>
-                        </Box>
-
-                        {/* Screenshot Indicators */}
-                        <Box sx={{ display: 'flex', gap: 1 }}>
-                            {screenshots.map((_, index) => (
-                                <Box
-                                    key={index}
-                                    onClick={() => setCurrentScreenshot(index)}
-                                    sx={{
-                                        width: 32,
-                                        height: 4,
-                                        borderRadius: 2,
-                                        bgcolor: index === currentScreenshot 
-                                            ? theme.palette.primary.main 
-                                            : alpha(theme.palette.text.secondary, 0.2),
-                                        cursor: 'pointer',
-                                        transition: 'all 0.3s ease',
-                                        '&:hover': {
-                                            bgcolor: index === currentScreenshot 
-                                                ? theme.palette.primary.main 
-                                                : alpha(theme.palette.text.secondary, 0.4),
-                                        }
-                                    }}
-                                />
-                            ))}
-                        </Box>
-                    </Box>
+                    ))}
                 </Box>
 
                 <Box sx={{ mt: 6, mx: 2 }}>
-                    <Box sx={{ display: 'flex', flexDirection: 'column', alignItems: 'center' }}>
-                        <Typography variant="caption">
-                            How does Data Formulator handle your data?
-                        </Typography>
-                        <Typography 
-                            variant="caption" 
-                            sx={{ mt: 1, textAlign: 'left' }}
-                        >
-                            <li><strong>Data Storage:</strong> Uploaded data (csv, xlsx, json, clipboard, messy data etc.) is stored in browser's local storage only</li>
-                            <li><strong>Data Processing:</strong> Local installation runs Python on your machine; online demo sends the data to server for data transformations (but not stored)</li>
-                            <li><strong>Database:</strong> Only available for locally installed Data Formulator (a DuckDB database file is created in temp directory to store data); not available in online demo</li>
-                            <li><strong>LLM Endpoints:</strong> Small data samples are sent to LLM endpoints along with the prompt. Use your trusted model provider if working with private data.</li>
-                        </Typography>
-                        <Typography variant="caption" sx={{ mt: 4, color: 'text.secondary' }}>
-                            Research Prototype from Microsoft Research
-                        </Typography>
-                    </Box>
+                    <Typography variant="body2" sx={{ color: 'text.secondary' }}>
+                        <strong>Data handling:</strong> Data stored in browser only • Local install runs Python locally; online demo processes server-side (not stored) • LLM receives small samples with prompts
+                    </Typography>
+                    <Typography variant="body2" sx={{ display: 'block', mt: 1, color: 'text.secondary' }}>
+                        Research Prototype from Microsoft Research
+                    </Typography>
                 </Box>
             </Box>
 
             {/* Footer */}
-            <Box sx={{ color: 'text.secondary', display: 'flex', 
-                        backgroundColor: 'rgba(255, 255, 255, 0.89)',
-                        alignItems: 'center', justifyContent: 'center' }}>
+            <Box 
+                component="footer"
+                role="contentinfo"
+                sx={{ color: 'text.secondary', display: 'flex', 
+                    backgroundColor: 'rgba(255, 255, 255, 0.89)',
+                    alignItems: 'center', justifyContent: 'center' }}
+            >
                 <Button size="small" color="inherit" 
-                        sx={{ textTransform: 'none'}} 
-                        target="_blank" rel="noopener noreferrer" 
+                        sx={{ textTransform: 'none' }} 
+                        target="_blank" 
+                        rel="noopener noreferrer" 
+                        aria-label="Privacy & Cookies (opens in new tab)"
                         href="https://www.microsoft.com/en-us/privacy/privacystatement">Privacy & Cookies</Button>
-                <Divider orientation="vertical" variant="middle" flexItem sx={{ mx: 1 }} />
+                <Divider orientation="vertical" variant="middle" flexItem sx={{ mx: 1 }} aria-hidden="true" />
                 <Button size="small" color="inherit" 
-                        sx={{ textTransform: 'none'}} 
-                        target="_blank" rel="noopener noreferrer" 
+                        sx={{ textTransform: 'none' }} 
+                        target="_blank" 
+                        rel="noopener noreferrer" 
+                        aria-label="Terms of Use (opens in new tab)"
                         href="https://www.microsoft.com/en-us/legal/intellectualproperty/copyright">Terms of Use</Button>
-                <Divider orientation="vertical" variant="middle" flexItem sx={{ mx: 1 }} />
+                <Divider orientation="vertical" variant="middle" flexItem sx={{ mx: 1 }} aria-hidden="true" />
                 <Button size="small" color="inherit" 
-                        sx={{ textTransform: 'none'}} 
-                        target="_blank" rel="noopener noreferrer" 
+                        sx={{ textTransform: 'none' }} 
+                        target="_blank" 
+                        rel="noopener noreferrer" 
+                        aria-label="Contact Us (opens in new tab)"
                         href="https://github.com/microsoft/data-formulator/issues">Contact Us</Button>
-                <Typography sx={{ display: 'inline', fontSize: '12px', ml: 1 }}> @ {new Date().getFullYear()}</Typography>
+                <Typography component="span" sx={{ fontSize: '12px', ml: 1 }}>© {new Date().getFullYear()}</Typography>
             </Box>
         </Box>)
 }
diff --git a/src/views/DataFormulator.tsx b/src/views/DataFormulator.tsx
index ead4e94..0ea145b 100644
--- a/src/views/DataFormulator.tsx
+++ b/src/views/DataFormulator.tsx
@@ -331,7 +331,7 @@ export const DataFormulatorFC = ({ }) => {
                         zIndex: 1000,
                     }}>
                         <Box sx={{margin:'auto', pb: '5%', display: "flex", flexDirection: "column", textAlign: "center"}}>
-                            <Box component="img" sx={{  width: 196, margin: "auto" }} alt="" src={dfLogo} fetchPriority="high" />
+                            <Box component="img" sx={{  width: 196, margin: "auto" }} alt="Data Formulator logo" src={dfLogo} fetchPriority="high" />
                             <Typography variant="h3" sx={{marginTop: "20px", fontWeight: 200, letterSpacing: '0.05em'}}>
                                 {toolName}
                             </Typography>

From dedf01627dbd0dbd6513a4a3d35c01218eba2361 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Tue, 9 Dec 2025 11:51:14 -0800
Subject: [PATCH 02/21] update vega-lite

---
 package.json |   2 +-
 yarn.lock    | 154 +++++++++++++++++++++++----------------------------
 2 files changed, 71 insertions(+), 85 deletions(-)

diff --git a/package.json b/package.json
index 66bfcfd..f8a7b0e 100644
--- a/package.json
+++ b/package.json
@@ -46,7 +46,7 @@
         "validator": "^13.15.20",
         "vega": "^6.2.0",
         "vega-embed": "^6.21.0",
-        "vega-lite": "^5.5.0",
+        "vega-lite": "6.4.1",
         "vm-browserify": "^1.1.2"
     },
     "scripts": {
diff --git a/yarn.lock b/yarn.lock
index f1d9bfb..069c709 100644
--- a/yarn.lock
+++ b/yarn.lock
@@ -1134,7 +1134,7 @@
   dependencies:
     dompurify "*"
 
-"@types/estree@1.0.8", "@types/estree@^1.0.0", "@types/estree@^1.0.6", "@types/estree@^1.0.8":
+"@types/estree@1.0.8", "@types/estree@^1.0.6", "@types/estree@^1.0.8":
   version "1.0.8"
   resolved "https://registry.npmjs.org/@types/estree/-/estree-1.0.8.tgz"
   integrity sha512-dWHzHa2WqEXI/O1E9OjrocMTKJl2mSrEolh1Iomrv6U+JuNwaHXsXx9bLu5gG7BUWFIN0skIQJQ/L1rIex4X6w==
@@ -1367,10 +1367,10 @@ allotment@^1.20.4:
     lodash.isequal "^4.5.0"
     use-resize-observer "^9.0.0"
 
-ansi-regex@^5.0.1:
-  version "5.0.1"
-  resolved "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.1.tgz"
-  integrity sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ==
+ansi-regex@^6.0.1:
+  version "6.2.2"
+  resolved "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.2.2.tgz#60216eea464d864597ce2832000738a0589650c1"
+  integrity sha512-Bq3SmSpyFHaWjPk8If9yc6svM8c56dB5BAtW4Qbw5jHTwwXXcTLoRMkpDJp6VL0XzlWaCHTXrkFURMYmD0sLqg==
 
 ansi-styles@^3.2.1:
   version "3.2.1"
@@ -1379,13 +1379,18 @@ ansi-styles@^3.2.1:
   dependencies:
     color-convert "^1.9.0"
 
-ansi-styles@^4.0.0, ansi-styles@^4.1.0:
+ansi-styles@^4.1.0:
   version "4.3.0"
   resolved "https://registry.npmjs.org/ansi-styles/-/ansi-styles-4.3.0.tgz"
   integrity sha512-zbB9rCJAT1rbjiVDb2hqKFHNYLxgtk8NURxZ3IZwD3F6NtxbXZQCnnSi1Lkx+IDohdPlFp222wVALIheZJQSEg==
   dependencies:
     color-convert "^2.0.1"
 
+ansi-styles@^6.2.1:
+  version "6.2.3"
+  resolved "https://registry.npmjs.org/ansi-styles/-/ansi-styles-6.2.3.tgz#c044d5dcc521a076413472597a1acb1f103c4041"
+  integrity sha512-4Dj6M28JB+oAH8kFkTLUo+a2jwOFkuqb3yucU0CANcRRUbxS0cP0nZYCGjcc3BNXwRIsUVmDGgzawme7zvJHvg==
+
 archiver-utils@^2.1.0:
   version "2.1.0"
   resolved "https://registry.npmjs.org/archiver-utils/-/archiver-utils-2.1.0.tgz"
@@ -1733,14 +1738,14 @@ classnames@^2.3.0:
   resolved "https://registry.npmjs.org/classnames/-/classnames-2.5.1.tgz"
   integrity sha512-saHYOzhIQs6wy2sVxTM6bUDsQO4F50V9RQ22qBpEdCW+I+/Wmke2HOl6lS6dTpdxVhb88/I6+Hs+438c3lfUow==
 
-cliui@^8.0.1:
-  version "8.0.1"
-  resolved "https://registry.npmjs.org/cliui/-/cliui-8.0.1.tgz"
-  integrity sha512-BSeNnyus75C4//NQ9gQt1/csTXyo/8Sb+afLAkzAptFuMsod9HFokGNudZpi/oQV73hnVK+sR+5PVRMd+Dr7YQ==
+cliui@^9.0.1:
+  version "9.0.1"
+  resolved "https://registry.npmjs.org/cliui/-/cliui-9.0.1.tgz#6f7890f386f6f1f79953adc1f78dec46fcc2d291"
+  integrity sha512-k7ndgKhwoQveBL+/1tqGJYNz097I7WOvwbmmU2AR5+magtbjPWQTS1C5vzGkBC8Ym8UWRzfKUzUUqFLypY4Q+w==
   dependencies:
-    string-width "^4.2.0"
-    strip-ansi "^6.0.1"
-    wrap-ansi "^7.0.0"
+    string-width "^7.2.0"
+    strip-ansi "^7.1.0"
+    wrap-ansi "^9.0.0"
 
 clsx@^2.0.0, clsx@^2.1.1:
   version "2.1.1"
@@ -2320,10 +2325,10 @@ duplexer2@~0.1.4:
   dependencies:
     readable-stream "^2.0.2"
 
-emoji-regex@^8.0.0:
-  version "8.0.0"
-  resolved "https://registry.npmjs.org/emoji-regex/-/emoji-regex-8.0.0.tgz"
-  integrity sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A==
+emoji-regex@^10.3.0:
+  version "10.6.0"
+  resolved "https://registry.npmjs.org/emoji-regex/-/emoji-regex-10.6.0.tgz#bf3d6e8f7f8fd22a65d9703475bc0147357a6b0d"
+  integrity sha512-toUI84YS5YmxW219erniWD0CIVOo46xGKColeNQRgOzDorgBi1v4D71/OFzgD9GO2UGKIv1C3Sp8DAn0+j5w7A==
 
 emoji-regex@^9.2.2:
   version "9.2.2"
@@ -2824,6 +2829,11 @@ get-caller-file@^2.0.5:
   resolved "https://registry.npmjs.org/get-caller-file/-/get-caller-file-2.0.5.tgz"
   integrity sha512-DyFP3BM/3YHTQOCUL/w0OZHR0lpKeGrxotcHWcqNEdnltqFwXVfhEBQ94eIo34AfQpo0rGki4cyIiftY06h2Fg==
 
+get-east-asian-width@^1.0.0:
+  version "1.4.0"
+  resolved "https://registry.npmjs.org/get-east-asian-width/-/get-east-asian-width-1.4.0.tgz#9bc4caa131702b4b61729cb7e42735bc550c9ee6"
+  integrity sha512-QZjmEOC+IT1uk6Rx0sX22V6uHWVwbdbxf1faPqJ1QhLdGgsRGCZoyaQBm/piRdJy/D2um6hM1UP7ZEeQ4EkP+Q==
+
 get-intrinsic@^1.2.4, get-intrinsic@^1.2.5, get-intrinsic@^1.2.6, get-intrinsic@^1.2.7, get-intrinsic@^1.3.0:
   version "1.3.0"
   resolved "https://registry.npmjs.org/get-intrinsic/-/get-intrinsic-1.3.0.tgz"
@@ -3147,11 +3157,6 @@ is-finalizationregistry@^1.1.0:
   dependencies:
     call-bound "^1.0.3"
 
-is-fullwidth-code-point@^3.0.0:
-  version "3.0.0"
-  resolved "https://registry.npmjs.org/is-fullwidth-code-point/-/is-fullwidth-code-point-3.0.0.tgz"
-  integrity sha512-zymm5+u+sCsSWyD9qNaejV3DFvhCKclKdizYaJUuHA83RLjb7nSuGnddCHGv0hk+KY7BMAlsWeK4Ueg6EV6XQg==
-
 is-generator-function@^1.0.10:
   version "1.1.2"
   resolved "https://registry.npmjs.org/is-generator-function/-/is-generator-function-1.1.2.tgz"
@@ -4171,11 +4176,6 @@ regexp.prototype.flags@^1.5.3, regexp.prototype.flags@^1.5.4:
     gopd "^1.2.0"
     set-function-name "^2.0.2"
 
-require-directory@^2.1.1:
-  version "2.1.1"
-  resolved "https://registry.npmjs.org/require-directory/-/require-directory-2.1.1.tgz"
-  integrity sha512-fGxEI7+wsG9xrvdjsrlmL22OMTTiHRwAMroiEeMgq8gzoLC/PQr7RsRDSTLUg/bZAZtF+TVIkHc6/4RIKrui+Q==
-
 reselect@^4.1.8:
   version "4.1.8"
   resolved "https://registry.npmjs.org/reselect/-/reselect-4.1.8.tgz"
@@ -4458,14 +4458,14 @@ stop-iteration-iterator@^1.1.0:
     es-errors "^1.3.0"
     internal-slot "^1.1.0"
 
-string-width@^4.1.0, string-width@^4.2.0, string-width@^4.2.3:
-  version "4.2.3"
-  resolved "https://registry.npmjs.org/string-width/-/string-width-4.2.3.tgz"
-  integrity sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g==
+string-width@^7.0.0, string-width@^7.2.0:
+  version "7.2.0"
+  resolved "https://registry.npmjs.org/string-width/-/string-width-7.2.0.tgz#b5bb8e2165ce275d4d43476dd2700ad9091db6dc"
+  integrity sha512-tsaTIkKW9b4N+AEj+SVA+WhJzV7/zMhcSu78mLKWSk7cXMOSHsBKFWUs0fWwq8QyK3MgJBQRX6Gbi4kYbdvGkQ==
   dependencies:
-    emoji-regex "^8.0.0"
-    is-fullwidth-code-point "^3.0.0"
-    strip-ansi "^6.0.1"
+    emoji-regex "^10.3.0"
+    get-east-asian-width "^1.0.0"
+    strip-ansi "^7.1.0"
 
 string.prototype.includes@^2.0.1:
   version "2.0.1"
@@ -4549,12 +4549,12 @@ string_decoder@~1.1.1:
   dependencies:
     safe-buffer "~5.1.0"
 
-strip-ansi@^6.0.0, strip-ansi@^6.0.1:
-  version "6.0.1"
-  resolved "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz"
-  integrity sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==
+strip-ansi@^7.1.0:
+  version "7.1.2"
+  resolved "https://registry.npmjs.org/strip-ansi/-/strip-ansi-7.1.2.tgz#132875abde678c7ea8d691533f2e7e22bb744dba"
+  integrity sha512-gmBGslpoQJtgnMAvOVqGZpEz9dyoKTCzy2nfz/n8aIFhN/jCE/rCmcxabB6jOOHV+0WNnylOxaxBQPSvcWklhA==
   dependencies:
-    ansi-regex "^5.0.1"
+    ansi-regex "^6.0.1"
 
 strip-json-comments@^3.1.1:
   version "3.1.1"
@@ -4801,10 +4801,10 @@ uuid@^8.3.0:
   resolved "https://registry.npmjs.org/uuid/-/uuid-8.3.2.tgz"
   integrity sha512-+NYs2QeMWy+GWFOEm9xnn6HCDp0l7QBD7ml8zLUmJ+93Q5NF0NocErnwkTkXVFNiX3/fpC6afS8Dhb/gz7R7eg==
 
-validator@^13.15.22:
-  version "13.15.22"
-  resolved "https://registry.yarnpkg.com/validator/-/validator-13.15.22.tgz#5f847cf4a799107e5716fc87e5cf2a337a71eb14"
-  integrity sha512-uT/YQjiyLJP7HSrv/dPZqK9L28xf8hsNca01HSz1dfmI0DgMfjopp1rO/z13NeGF1tVystF0Ejx3y4rUKPw+bQ==
+validator@^13.15.20:
+  version "13.15.23"
+  resolved "https://registry.npmjs.org/validator/-/validator-13.15.23.tgz#59a874f84e4594588e3409ab1edbe64e96d0c62d"
+  integrity sha512-4yoz1kEWqUjzi5zsPbAS/903QXSYp0UOtHsPpp7p9rHAw/W+dkInskAE386Fat3oKRROwO98d9ZB0G4cObgUyw==
 
 vega-canvas@^2.0.0:
   version "2.0.0"
@@ -4871,11 +4871,6 @@ vega-event-selector@^4.0.0, vega-event-selector@~4.0.0:
   resolved "https://registry.yarnpkg.com/vega-event-selector/-/vega-event-selector-4.0.0.tgz#425e9f2671e858a1a45b4b6a7fc452ca0b22abbf"
   integrity sha512-CcWF4m4KL/al1Oa5qSzZ5R776q8lRxCj3IafCHs5xipoEHrkgu1BWa7F/IH5HrDNXeIDnqOpSV1pFsAWRak4gQ==
 
-vega-event-selector@~3.0.1:
-  version "3.0.1"
-  resolved "https://registry.npmjs.org/vega-event-selector/-/vega-event-selector-3.0.1.tgz"
-  integrity sha512-K5zd7s5tjr1LiOOkjGpcVls8GsH/f2CWCrWcpKy74gTCp+llCdwz0Enqo013ZlGaRNjfgD/o1caJRt3GSaec4A==
-
 vega-expression@^6.1.0, vega-expression@~6.1.0:
   version "6.1.0"
   resolved "https://registry.yarnpkg.com/vega-expression/-/vega-expression-6.1.0.tgz#6ce358a39b9b953806bff200f6f84f44163c9e38"
@@ -4884,14 +4879,6 @@ vega-expression@^6.1.0, vega-expression@~6.1.0:
     "@types/estree" "^1.0.8"
     vega-util "^2.1.0"
 
-vega-expression@~5.1.1:
-  version "5.1.2"
-  resolved "https://registry.npmjs.org/vega-expression/-/vega-expression-5.1.2.tgz"
-  integrity sha512-fFeDTh4UtOxlZWL54jf1ZqJHinyerWq/ROiqrQxqLkNJRJ86RmxYTgXwt65UoZ/l4VUv9eAd2qoJeDEf610Umw==
-  dependencies:
-    "@types/estree" "^1.0.0"
-    vega-util "^1.17.3"
-
 vega-force@~5.1.0:
   version "5.1.0"
   resolved "https://registry.yarnpkg.com/vega-force/-/vega-force-5.1.0.tgz#aa7cf8edbe2ae3bada070f343565dfb841e501a9"
@@ -4969,17 +4956,17 @@ vega-label@~2.1.0:
     vega-scenegraph "^5.1.0"
     vega-util "^2.1.0"
 
-vega-lite@^5.5.0:
-  version "5.23.0"
-  resolved "https://registry.npmjs.org/vega-lite/-/vega-lite-5.23.0.tgz"
-  integrity sha512-l4J6+AWE3DIjvovEoHl2LdtCUkfm4zs8Xxx7INwZEAv+XVb6kR6vIN1gt3t2gN2gs/y4DYTs/RPoTeYAuEg6mA==
+vega-lite@6.4.1:
+  version "6.4.1"
+  resolved "https://registry.npmjs.org/vega-lite/-/vega-lite-6.4.1.tgz#549634ecaefd46d00f17e7922577d0c97a4663c5"
+  integrity sha512-KO3ybHNouRK4A0al/+2fN9UqgTEfxrd/ntGLY933Hg5UOYotDVQdshR3zn7OfXwQ7uj0W96Vfa5R+QxO8am3IQ==
   dependencies:
     json-stringify-pretty-compact "~4.0.0"
     tslib "~2.8.1"
-    vega-event-selector "~3.0.1"
-    vega-expression "~5.1.1"
-    vega-util "~1.17.2"
-    yargs "~17.7.2"
+    vega-event-selector "~4.0.0"
+    vega-expression "~6.1.0"
+    vega-util "~2.1.0"
+    yargs "~18.0.0"
 
 vega-loader@^5.1.0, vega-loader@~5.1.0:
   version "5.1.0"
@@ -5130,7 +5117,7 @@ vega-typings@~2.1.0:
     vega-expression "^6.1.0"
     vega-util "^2.1.0"
 
-vega-util@^1.13.1, vega-util@^1.17.2, vega-util@^1.17.3, vega-util@^1.17.4, vega-util@~1.17.2:
+vega-util@^1.13.1, vega-util@^1.17.2, vega-util@^1.17.4:
   version "1.17.4"
   resolved "https://registry.npmjs.org/vega-util/-/vega-util-1.17.4.tgz"
   integrity sha512-+y3ZW7dEqM8Ck+KRsd+jkMfxfE7MrQxUyIpNjkfhIpGEreym+aTn7XUw1DKXqclr8mqTQvbilPo16B3lnBr0wA==
@@ -5332,14 +5319,14 @@ word-wrap@^1.2.5:
   resolved "https://registry.npmjs.org/word-wrap/-/word-wrap-1.2.5.tgz"
   integrity sha512-BN22B5eaMMI9UMtjrGd5g5eCYPpCPDUy0FJXbYsaT5zYxjFOckS53SQDE3pWkVoWpHXVb3BrYcEN4Twa55B5cA==
 
-wrap-ansi@^7.0.0:
-  version "7.0.0"
-  resolved "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz"
-  integrity sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q==
+wrap-ansi@^9.0.0:
+  version "9.0.2"
+  resolved "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-9.0.2.tgz#956832dea9494306e6d209eb871643bb873d7c98"
+  integrity sha512-42AtmgqjV+X1VpdOfyTGOYRi0/zsoLqtXQckTmqTeybT+BDIbM/Guxo7x3pE2vtpr1ok6xRqM9OpBe+Jyoqyww==
   dependencies:
-    ansi-styles "^4.0.0"
-    string-width "^4.1.0"
-    strip-ansi "^6.0.0"
+    ansi-styles "^6.2.1"
+    string-width "^7.0.0"
+    strip-ansi "^7.1.0"
 
 wrappy@1:
   version "1.0.2"
@@ -5361,23 +5348,22 @@ yaml@^1.10.0:
   resolved "https://registry.npmjs.org/yaml/-/yaml-1.10.2.tgz"
   integrity sha512-r3vXyErRCYJ7wg28yvBY5VSoAF8ZvlcW9/BwUzEtUsjvX/DKs24dIkuwjtuprwJJHsbyUbLApepYTR1BN4uHrg==
 
-yargs-parser@^21.1.1:
-  version "21.1.1"
-  resolved "https://registry.npmjs.org/yargs-parser/-/yargs-parser-21.1.1.tgz"
-  integrity sha512-tVpsJW7DdjecAiFpbIB1e3qxIQsE6NoPc5/eTdrbbIC4h0LVsWhnoa3g+m2HclBIujHzsxZ4VJVA+GUuc2/LBw==
+yargs-parser@^22.0.0:
+  version "22.0.0"
+  resolved "https://registry.npmjs.org/yargs-parser/-/yargs-parser-22.0.0.tgz#87b82094051b0567717346ecd00fd14804b357c8"
+  integrity sha512-rwu/ClNdSMpkSrUb+d6BRsSkLUq1fmfsY6TOpYzTwvwkg1/NRG85KBy3kq++A8LKQwX6lsu+aWad+2khvuXrqw==
 
-yargs@~17.7.2:
-  version "17.7.2"
-  resolved "https://registry.npmjs.org/yargs/-/yargs-17.7.2.tgz"
-  integrity sha512-7dSzzRQ++CKnNI/krKnYRV7JKKPUXMEh61soaHKg9mrWEhzFWhFnxPxGl+69cD1Ou63C13NUPCnmIcrvqCuM6w==
+yargs@~18.0.0:
+  version "18.0.0"
+  resolved "https://registry.npmjs.org/yargs/-/yargs-18.0.0.tgz#6c84259806273a746b09f579087b68a3c2d25bd1"
+  integrity sha512-4UEqdc2RYGHZc7Doyqkrqiln3p9X2DZVxaGbwhn2pi7MrRagKaOcIKe8L3OxYcbhXLgLFUS3zAYuQjKBQgmuNg==
   dependencies:
-    cliui "^8.0.1"
+    cliui "^9.0.1"
     escalade "^3.1.1"
     get-caller-file "^2.0.5"
-    require-directory "^2.1.1"
-    string-width "^4.2.3"
+    string-width "^7.2.0"
     y18n "^5.0.5"
-    yargs-parser "^21.1.1"
+    yargs-parser "^22.0.0"
 
 yocto-queue@^0.1.0:
   version "0.1.0"

From 125290237bf02aaa02ec47a1f760bf8f4af85963 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Fri, 16 Jan 2026 17:52:07 -0800
Subject: [PATCH 03/21] planning on some data input redesign

---
 .../agents/agent_py_data_rec.py               |  13 +-
 .../agents/agent_py_data_transform.py         |   2 +-
 py-src/data_formulator/tables_routes.py       |  82 +++
 pyproject.toml                                |   2 +-
 src/app/App.tsx                               |  75 +-
 src/app/dfSlice.tsx                           |  23 +
 src/app/utils.tsx                             |   3 +
 src/data/utils.ts                             |  66 +-
 src/scss/App.scss                             |  23 +
 src/views/DBTableManager.tsx                  | 283 +-------
 src/views/DataFormulator.tsx                  |  34 +-
 src/views/DataLoadingChat.tsx                 |  85 +--
 src/views/DataThread.tsx                      | 280 +++++++-
 src/views/DerivedDataDialog.tsx               | 191 -----
 src/views/TableSelectionView.tsx              | 666 +-----------------
 src/views/VisualizationView.tsx               |   2 +-
 16 files changed, 491 insertions(+), 1339 deletions(-)
 delete mode 100644 src/views/DerivedDataDialog.tsx

diff --git a/py-src/data_formulator/agents/agent_py_data_rec.py b/py-src/data_formulator/agents/agent_py_data_rec.py
index 3fb1e5a..2fce791 100644
--- a/py-src/data_formulator/agents/agent_py_data_rec.py
+++ b/py-src/data_formulator/agents/agent_py_data_rec.py
@@ -33,7 +33,7 @@
     "display_instruction": "..." // string, the even shorter verb phrase describing the users' goal.
     "recommendation": "..." // string, explain why this recommendation is made
     "output_fields": [...] // string[], describe the desired output fields that the output data should have (i.e., the goal of transformed data), it's a good idea to preseve intermediate fields here
-    "chart_type": "" // string, one of "point", "bar", "line", "area", "heatmap", "group_bar". "chart_type" should either be inferred from user instruction, or recommend if the user didn't specify any.
+    "chart_type": "" // string, one of "point", "bar", "line", "area", "heatmap", "group_bar", 'boxplot'. "chart_type" should either be inferred from user instruction, or recommend if the user didn't specify any.
     "chart_encodings": {
         "x": "",
         "y": "",
@@ -65,7 +65,7 @@
         - if you mention column names from the input or the output data, highlight the text in **bold**.
             * the column can either be a column in the input data, or a new column that will be computed in the output data.
             * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned "average score" in the text while the column to be computed is "Avg_Score", you should still highlight "**average score**" in the text.
-    - "chart_type" must be one of "point", "bar", "line", "area", "heatmap", "group_bar"
+    - "chart_type" must be one of "point", "bar", "line", "area", "heatmap", "group_bar", "boxplot"
     - "chart_encodings" should specify which fields should be used to create the visualization
         - decide which visual channels should be used to create the visualization appropriate for the chart type.
             - point: x, y, color, size, facet
@@ -75,6 +75,7 @@
             - area: x, y, color, facet
             - heatmap: x, y, color, facet
             - group_bar: x, y, color, facet
+            - boxplot: x, y, color, facet
         - note that all fields used in "chart_encodings" should be included in "output_fields".
             - all fields you need for visualizations should be transformed into the output fields!
             - "output_fields" should include important intermediate fields that are not used in visualization but are used for data transformation.
@@ -108,6 +109,10 @@
                 - best for: Trends over time, continuous data
             - (heatmap) Heatmaps: x,y: Categorical (you need to convert quantitative to nominal), color: Quantitative intensity, 
                 - best for: Pattern discovery in matrix data
+            - (boxplot) Box plots: x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical (optional for creating grouped boxplots), 
+                - best for: Distribution of a quantitative field
+                - use x values directly if x values are categorical, and transform the data into bins if the field values are quantitative.
+                - when color is specified, the boxplot will be grouped automatically (items with the same x values will be grouped).
         - facet channel is available for all chart types, it supports a categorical field with small cardinality to visualize the data in different facets.
         - if you really need additional legend fields:
             - you can use opacity for legend (support Quantitative and Categorical).
@@ -135,7 +140,7 @@
             
     2. Then, write a python function based on the inferred goal, the function input is a dataframe "df" (or multiple dataframes based on tables presented in the [CONTEXT] section) and the output is the transformed dataframe "transformed_df". 
 "transformed_df" should contain all "output_fields" from the refined user intent in the json object.
-The python function must follow the template provided in [TEMPLATE], do not import any other libraries or modify function name. The function should be as simple as possible and easily readable. 
+The python function must follow the template provided in [TEMPLATE]. The function should be as simple as possible and easily readable. 
 If there is no data transformation needed based on "output_fields", the transformation function can simply "return df".
 
 [TEMPLATE]
@@ -144,7 +149,7 @@
 import pandas as pd
 import collections
 import numpy as np
-from sklearn import ... # import necessary libraries from sklearn if needed
+# from sklearn import ... # import from sklearn if you need it.
 
 def transform_data(df1, df2, ...): 
     # complete the template here
diff --git a/py-src/data_formulator/agents/agent_py_data_transform.py b/py-src/data_formulator/agents/agent_py_data_transform.py
index 6bed538..b492857 100644
--- a/py-src/data_formulator/agents/agent_py_data_transform.py
+++ b/py-src/data_formulator/agents/agent_py_data_transform.py
@@ -89,7 +89,7 @@
 import pandas as pd
 import collections
 import numpy as np
-from sklearn import ... # import necessary libraries from sklearn if needed
+# from sklearn import ... # import from sklearn if you need it.
 
 def transform_data(df1, df2, ...): 
     # complete the template here
diff --git a/py-src/data_formulator/tables_routes.py b/py-src/data_formulator/tables_routes.py
index 74f31f2..b065e04 100644
--- a/py-src/data_formulator/tables_routes.py
+++ b/py-src/data_formulator/tables_routes.py
@@ -841,4 +841,86 @@ def data_loader_ingest_data_from_query():
         return jsonify({
             "status": "error", 
             "message": safe_msg
+        }), status_code
+
+
+@tables_bp.route('/refresh-derived-data', methods=['POST'])
+def refresh_derived_data():
+    """
+    Re-run Python transformation code with new input data to refresh a derived table.
+    
+    This endpoint takes:
+    - input_tables: list of {name: string, rows: list} objects representing the parent tables
+    - code: the Python transformation code to execute
+    
+    Returns:
+    - status: 'ok' or 'error'
+    - rows: the resulting rows if successful
+    - message: error message if failed
+    """
+    try:
+        from data_formulator.py_sandbox import run_transform_in_sandbox2020
+        from flask import current_app
+        
+        data = request.get_json()
+        input_tables = data.get('input_tables', [])
+        code = data.get('code', '')
+        
+        if not input_tables:
+            return jsonify({
+                "status": "error",
+                "message": "No input tables provided"
+            }), 400
+            
+        if not code:
+            return jsonify({
+                "status": "error", 
+                "message": "No transformation code provided"
+            }), 400
+        
+        # Convert input tables to pandas DataFrames
+        df_list = []
+        for table in input_tables:
+            table_name = table.get('name', '')
+            table_rows = table.get('rows', [])
+            
+            if not table_rows:
+                return jsonify({
+                    "status": "error",
+                    "message": f"Table '{table_name}' has no rows"
+                }), 400
+                
+            df = pd.DataFrame.from_records(table_rows)
+            df_list.append(df)
+        
+        # Get exec_python_in_subprocess setting from app config
+        exec_python_in_subprocess = current_app.config.get('CLI_ARGS', {}).get('exec_python_in_subprocess', False)
+        
+        # Run the transformation code
+        result = run_transform_in_sandbox2020(code, df_list, exec_python_in_subprocess)
+        
+        if result['status'] == 'ok':
+            result_df = result['content']
+            
+            # Convert result DataFrame to list of records
+            rows = json.loads(result_df.to_json(orient='records', date_format='iso'))
+            
+            return jsonify({
+                "status": "ok",
+                "rows": rows,
+                "message": "Successfully refreshed derived data"
+            })
+        else:
+            return jsonify({
+                "status": "error",
+                "message": result.get('content', 'Unknown error during transformation')
+            }), 400
+            
+    except Exception as e:
+        logger.error(f"Error refreshing derived data: {str(e)}")
+        logger.error(traceback.format_exc())
+        safe_msg, status_code = sanitize_db_error_message(e)
+        return jsonify({
+            "status": "error",
+            "message": safe_msg
         }), status_code
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
index 71e11f8..37c8b16 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "data_formulator"
-version = "0.5.1"
+version = "0.5.1.1"
 
 requires-python = ">=3.9"
 authors = [
diff --git a/src/app/App.tsx b/src/app/App.tsx
index fdf0396..0bcfea5 100644
--- a/src/app/App.tsx
+++ b/src/app/App.tsx
@@ -64,16 +64,17 @@ import { DictTable } from '../components/ComponentType';
 import { AppDispatch } from './store';
 import dfLogo from '../assets/df-logo.png';
 import { ModelSelectionButton } from '../views/ModelSelectionDialog';
-import { TableCopyDialogV2 } from '../views/TableSelectionView';
-import { TableUploadDialog } from '../views/TableSelectionView';
 import KeyboardArrowDownIcon from '@mui/icons-material/KeyboardArrowDown';
 import ContentPasteIcon from '@mui/icons-material/ContentPaste';
 import UploadFileIcon from '@mui/icons-material/UploadFile';
 import DownloadIcon from '@mui/icons-material/Download';
-import { DBTableSelectionDialog, handleDBDownload } from '../views/DBTableManager';
+import { handleDBDownload } from '../views/DBTableManager';
 import CloudQueueIcon from '@mui/icons-material/CloudQueue';
 import { getUrls } from './utils';
-import { DataLoadingChatDialog } from '../views/DataLoadingChat';
+import { UnifiedDataUploadDialog, UploadTabType } from '../views/UnifiedDataUploadDialog';
+import LinkIcon from '@mui/icons-material/Link';
+import ImageSearchIcon from '@mui/icons-material/ImageSearch';
+import ExploreIcon from '@mui/icons-material/Explore';
 import ChatIcon from '@mui/icons-material/Chat';
 import { AgentRulesDialog } from '../views/AgentRulesDialog';
 import ArticleIcon from '@mui/icons-material/Article';
@@ -221,18 +222,14 @@ export interface AppFCProps {
 // Extract menu components into separate components to prevent full app re-renders
 const TableMenu: React.FC = () => {
     const [anchorEl, setAnchorEl] = useState<null | HTMLElement>(null);
-    const [openDialog, setOpenDialog] = useState<'database' | 'extract' | 'paste' | 'upload' | null>(null);
-    const fileInputRef = React.useRef<HTMLInputElement>(null);
+    const [dialogOpen, setDialogOpen] = useState<boolean>(false);
+    const [initialTab, setInitialTab] = useState<UploadTabType>('menu');
     const open = Boolean(anchorEl);
 
-    const handleOpenDialog = (dialog: 'database' | 'extract' | 'paste' | 'upload') => {
+    const handleOpenDialog = (tab: UploadTabType) => {
         setAnchorEl(null);
-        if (dialog === 'upload') {
-            // For file upload, trigger the hidden file input
-            fileInputRef.current?.click();
-        } else {
-            setOpenDialog(dialog);
-        }
+        setInitialTab(tab);
+        setDialogOpen(true);
     };
     
     return (
@@ -262,43 +259,45 @@ const TableMenu: React.FC = () => {
                     '& .MuiTypography-root': { fontSize: 14, display: 'flex', alignItems: 'center', textTransform: 'none', gap: 1 }
                 }}
             >
-                <MenuItem onClick={() => handleOpenDialog('database')}>
+                <MenuItem onClick={() => handleOpenDialog('upload')}>
                     <Typography fontSize="inherit">
-                        connect to database <CloudQueueIcon fontSize="inherit" /> 
+                        <UploadFileIcon fontSize="inherit" /> upload file <span style={{fontSize: '11px'}}>(csv/json/xlsx)</span>
                     </Typography>
                 </MenuItem>
-                <MenuItem onClick={() => handleOpenDialog('extract')}>
+                <MenuItem onClick={() => handleOpenDialog('paste')}>
                     <Typography fontSize="inherit">
-                        extract data <span style={{fontSize: '11px'}}>(image/messy text)</span>
+                        <ContentPasteIcon fontSize="inherit" /> paste data <span style={{fontSize: '11px'}}>(csv/tsv/json)</span>
                     </Typography>
                 </MenuItem>
-                <MenuItem onClick={() => handleOpenDialog('paste')}>
-                    <Typography>
-                        paste data <span style={{fontSize: '11px'}}>(csv/tsv)</span>
+                <MenuItem onClick={() => handleOpenDialog('url')}>
+                    <Typography fontSize="inherit">
+                        <LinkIcon fontSize="inherit" /> from URL
                     </Typography>
                 </MenuItem>
-                <MenuItem onClick={() => handleOpenDialog('upload')}>
-                    <Typography>
-                        upload data file <span style={{fontSize: '11px'}}>(csv/tsv/json)</span>
+                <Divider />
+                <MenuItem onClick={() => handleOpenDialog('database')}>
+                    <Typography fontSize="inherit">
+                        <CloudQueueIcon fontSize="inherit" /> database
+                    </Typography>
+                </MenuItem>
+                <MenuItem onClick={() => handleOpenDialog('extract')}>
+                    <Typography fontSize="inherit">
+                        <ImageSearchIcon fontSize="inherit" /> extract data <span style={{fontSize: '11px'}}>(image/text)</span>
+                    </Typography>
+                </MenuItem>
+                <Divider />
+                <MenuItem onClick={() => handleOpenDialog('explore')}>
+                    <Typography fontSize="inherit">
+                        <ExploreIcon fontSize="inherit" /> explore samples
                     </Typography>
                 </MenuItem>
             </Menu>
             
-            {/* Dialogs rendered outside the Menu to avoid keyboard event issues */}
-            <DBTableSelectionDialog 
-                open={openDialog === 'database'} 
-                onClose={() => setOpenDialog(null)} 
-            />
-            <DataLoadingChatDialog 
-                open={openDialog === 'extract'} 
-                onClose={() => setOpenDialog(null)} 
-            />
-            <TableCopyDialogV2 
-                open={openDialog === 'paste'} 
-                onClose={() => setOpenDialog(null)} 
-            />
-            <TableUploadDialog 
-                fileInputRef={fileInputRef}
+            {/* Unified Data Upload Dialog */}
+            <UnifiedDataUploadDialog 
+                open={dialogOpen}
+                onClose={() => setDialogOpen(false)}
+                initialTab={initialTab}
             />
         </>
     );
diff --git a/src/app/dfSlice.tsx b/src/app/dfSlice.tsx
index 393d134..7664b0f 100644
--- a/src/app/dfSlice.tsx
+++ b/src/app/dfSlice.tsx
@@ -475,6 +475,29 @@ export const dataFormulatorSlice = createSlice({
             let attachedMetadata = action.payload.attachedMetadata;
             state.tables = state.tables.map(t => t.id == tableId ? {...t, attachedMetadata} : t);
         },
+        updateTableRows: (state, action: PayloadAction<{tableId: string, rows: any[]}>) => {
+            // Update the rows of a table while preserving all other table properties
+            // This is used for refreshing data in original (non-derived) tables
+            let tableId = action.payload.tableId;
+            let newRows = action.payload.rows;
+            
+            state.tables = state.tables.map(t => {
+                if (t.id == tableId) {
+                    // Update metadata type inference based on new data
+                    let newMetadata = { ...t.metadata };
+                    for (let name of t.names) {
+                        if (newRows.length > 0 && name in newRows[0]) {
+                            newMetadata[name] = {
+                                ...newMetadata[name],
+                                type: inferTypeFromValueArray(newRows.map(r => r[name])),
+                            };
+                        }
+                    }
+                    return { ...t, rows: newRows, metadata: newMetadata };
+                }
+                return t;
+            });
+        },
         extendTableWithNewFields: (state, action: PayloadAction<{tableId: string, columnName: string, values: any[], previousName: string | undefined, parentIDs: string[]}>) => {
             // extend the existing extTable with new columns from the new table
             let newValues = action.payload.values;
diff --git a/src/app/utils.tsx b/src/app/utils.tsx
index 8344af1..aeee817 100644
--- a/src/app/utils.tsx
+++ b/src/app/utils.tsx
@@ -56,6 +56,9 @@ export function getUrls() {
         QUERY_COMPLETION: `/api/agent/query-completion`,
         GET_RECOMMENDATION_QUESTIONS: `/api/agent/get-recommendation-questions`,
         GENERATE_REPORT_STREAM: `/api/agent/generate-report-stream`,
+
+        // Refresh data endpoint
+        REFRESH_DERIVED_DATA: `/api/tables/refresh-derived-data`,
     };
 }
 
diff --git a/src/data/utils.ts b/src/data/utils.ts
index 4c9743f..1b98deb 100644
--- a/src/data/utils.ts
+++ b/src/data/utils.ts
@@ -204,35 +204,47 @@ export const loadBinaryDataWrapper = async (title: string, arrayBuffer: ArrayBuf
         // Create tables for each sheet
         const tables: DictTable[] = [];
         
-        workbook.eachSheet((worksheet, sheetId) => {
-            const jsonData: any[] = [];
-            
-            // Get the first row as headers
-            const headerRow = worksheet.getRow(1);
-            const headers: string[] = [];
-            headerRow.eachCell((cell, colNumber) => {
-                headers[colNumber - 1] = cell.value?.toString() || `Column${colNumber}`;
-            });
-            
-            // Process data rows (skip header row)
-            worksheet.eachRow((row, rowNumber) => {
-                if (rowNumber === 1) return; // Skip header row
-                
-                const rowData: any = {};
-                row.eachCell((cell, colNumber) => {
-                    const header = headers[colNumber - 1] || `Column${colNumber}`;
-                    rowData[header] = cell.value;
+        workbook.eachSheet((worksheet) => {
+            try {
+                const jsonData: any[] = [];
+
+                // Get the first row as headers
+                const headerRow = worksheet.getRow(1);
+                const headers: string[] = [];
+                headerRow.eachCell((cell, colNumber) => {
+                    headers[colNumber - 1] = cell.value?.toString() || `Column${colNumber}`;
+                });
+
+                if (headers.length === 0) {
+                    return;
+                }
+
+                // Process data rows (skip header row)
+                worksheet.eachRow((row, rowNumber) => {
+                    if (rowNumber === 1) return; // Skip header row
+
+                    const rowData: any = {};
+                    row.eachCell((cell, colNumber) => {
+                        const header = headers[colNumber - 1] || `Column${colNumber}`;
+                        rowData[header] = cell.value;
+                    });
+
+                    // Only add row if it has data
+                    if (Object.keys(rowData).length > 0) {
+                        jsonData.push(rowData);
+                    }
                 });
-                
-                // Only add row if it has data
-                if (Object.keys(rowData).length > 0) {
-                    jsonData.push(rowData);
+
+                if (jsonData.length === 0) {
+                    return;
                 }
-            });
-            
-            // Create a table from the JSON data with sheet name included in the title
-            const sheetTable = createTableFromFromObjectArray(`${title}-${worksheet.name}`, jsonData, true);
-            tables.push(sheetTable);
+
+                // Create a table from the JSON data with sheet name included in the title
+                const sheetTable = createTableFromFromObjectArray(`${title}-${worksheet.name}`, jsonData, true);
+                tables.push(sheetTable);
+            } catch (error) {
+                console.error(`Error processing sheet ${worksheet.name}:`, error);
+            }
         });
         
         return tables;
diff --git a/src/scss/App.scss b/src/scss/App.scss
index 28edf46..31ca838 100644
--- a/src/scss/App.scss
+++ b/src/scss/App.scss
@@ -148,3 +148,26 @@ h2.view-title {
     transform-origin: bottom right;
     animation: writing-pencil 0.8s ease-in-out infinite;
 }
+
+// Fix MUI Dialog bottom scrolling issues
+.MuiDialog-paper {
+    display: flex;
+    flex-direction: column;
+    max-height: calc(100% - 64px);
+    
+    .MuiDialogTitle-root {
+        flex-shrink: 0;
+    }
+    
+    .MuiDialogContent-root {
+        flex: 1 1 auto;
+        overflow-y: auto;
+        overflow-x: hidden;
+        box-sizing: border-box;
+        min-height: 0; // Ensures content can shrink in flex container
+    }
+    
+    .MuiDialogActions-root {
+        flex-shrink: 0;
+    }
+}
diff --git a/src/views/DBTableManager.tsx b/src/views/DBTableManager.tsx
index da5bc8c..b883aa1 100644
--- a/src/views/DBTableManager.tsx
+++ b/src/views/DBTableManager.tsx
@@ -31,8 +31,6 @@ import {
   Chip,
   Collapse,
   styled,
-  ToggleButtonGroup,
-  ToggleButton,
   useTheme,
   Link,
   Checkbox
@@ -58,13 +56,8 @@ import { alpha } from '@mui/material';
 import { DataFormulatorState } from '../app/dfSlice';
 import { fetchFieldSemanticType } from '../app/dfSlice';
 import { AppDispatch } from '../app/store';
-import Editor from 'react-simple-code-editor';
 import Markdown from 'markdown-to-jsx';
 
-import Prism from 'prismjs'
-import 'prismjs/components/prism-javascript' // Language
-import 'prismjs/themes/prism.css'; //Example style, you can use another
-import PrecisionManufacturingIcon from '@mui/icons-material/PrecisionManufacturing';
 import CheckIcon from '@mui/icons-material/Check';
 import MuiMarkdown from 'mui-markdown';
 import CleaningServicesIcon from '@mui/icons-material/CleaningServices';
@@ -1050,43 +1043,13 @@ export const DataLoaderForm: React.FC<{
     const [displayAuthInstructions, setDisplayAuthInstructions] = useState(false);
 
     let [isConnecting, setIsConnecting] = useState(false);
-    let [mode, setMode] = useState<"view tables" | "query">("view tables");
 
     const toggleDisplaySamples = (tableName: string) => {
         setDisplaySamples({...displaySamples, [tableName]: !displaySamples[tableName]});
     }
 
-    const handleModeChange = (event: React.MouseEvent<HTMLElement>, newMode: "view tables" | "query") => {
-        if (newMode != null) {
-            setMode(newMode);
-        }
-    };
-
     let tableMetadataBox = [
-        <Box sx={{my: 2}}>
-            <ToggleButtonGroup
-                color="primary"
-                value={mode}
-                exclusive
-                size="small"
-                onChange={handleModeChange}
-                aria-label="Platform"
-                sx={{
-                    '& .MuiButtonBase-root': {
-                    lineHeight: 1,
-                    color: "text.primary",
-                    textTransform: 'none',
-                    '&.Mui-selected': {
-                        fontWeight: 'bold',
-                    }
-                }}}
-            >
-                <ToggleButton value="view tables">View Tables</ToggleButton>
-                <ToggleButton value="query">Query Data</ToggleButton>
-            </ToggleButtonGroup>
-            <Typography variant="body2" sx={{mb: 1,}}></Typography>
-        </Box>,
-        mode === "view tables" && <TableContainer component={Paper} sx={{maxHeight: 360, overflowY: "auto"}} >
+        <TableContainer component={Paper} sx={{maxHeight: 360, overflowY: "auto"}} >
             <Table sx={{ minWidth: 650 }} size="small" aria-label="simple table">
             <TableBody>
                 {Object.entries(tableMetadata).map(([tableName, metadata]) => {
@@ -1154,7 +1117,7 @@ export const DataLoaderForm: React.FC<{
                 </TableBody>
                 </Table>
             </TableContainer>,
-        mode === "view tables" && Object.keys(tableMetadata).length > 0 && <Box sx={{ display: 'flex', justifyContent: 'flex-end', mt: 1 }}>
+        Object.keys(tableMetadata).length > 0 && <Box sx={{ display: 'flex', justifyContent: 'flex-end', mt: 1 }}>
             <Button 
                 variant="contained" 
                 size="small"
@@ -1196,11 +1159,7 @@ export const DataLoaderForm: React.FC<{
             >
                 Import Selected ({selectedTables.size})
             </Button>
-        </Box>,
-        mode === "query" && <DataQueryForm 
-            dataLoaderType={dataLoaderType} 
-            availableTables={Object.keys(tableMetadata).map(t => ({name: t, fields: tableMetadata[t].columns.map((c: any) => c.name)}))} 
-            dataLoaderParams={params} onImport={onImport} onFinish={onFinish} />
+        </Box>
     ]
 
     return (
@@ -1338,240 +1297,4 @@ export const DataLoaderForm: React.FC<{
             {Object.keys(tableMetadata).length > 0 && tableMetadataBox }
         </Box>
     );
-}
-
-export const DataQueryForm: React.FC<{
-    dataLoaderType: string,
-    availableTables: {name: string, fields: string[]}[],
-    dataLoaderParams: Record<string, string>,
-    onImport: () => void,
-    onFinish: (status: "success" | "error", message: string) => void
-}> = ({dataLoaderType, availableTables, dataLoaderParams, onImport, onFinish}) => {
-
-    let activeModel = useSelector(dfSelectors.getActiveModel);
-
-    const [selectedTables, setSelectedTables] = useState<string[]>(availableTables.map(t => t.name).slice(0, 5));
-
-    const [waiting, setWaiting] = useState(false);
-
-    const [query, setQuery] = useState("-- query the data source / describe your goal and ask AI to help you write the query\n");
-    const [queryResult, setQueryResult] = useState<{
-        status: string,
-        message: string,
-        sample: any[],
-        code: string,
-    } | undefined>(undefined);
-    const [queryResultName, setQueryResultName] = useState("");
-    
-    const aiCompleteQuery = (query: string) => {
-        if (queryResult?.status === "error") {
-            setQueryResult(undefined);
-        }
-        let data = {
-            data_source_metadata: {
-                data_loader_type: dataLoaderType,
-                tables: availableTables.filter(t => selectedTables.includes(t.name))
-            },
-            query: query,
-            model: activeModel
-        }
-        setWaiting(true);
-        fetch(getUrls().QUERY_COMPLETION, {
-            method: 'POST',
-            headers: {
-                'Content-Type': 'application/json',
-            },
-            body: JSON.stringify(data)
-        })
-        .then(response => response.json())
-        .then(data => {
-            setWaiting(false);
-            if (data.status === "ok") {
-                setQuery(data.query);
-            } else {
-                onFinish("error", data.reasoning);
-            }
-        })
-        .catch(error => {
-            setWaiting(false);
-            onFinish("error", `Failed to complete query please try again.`);
-        });
-    }
-
-    const handleViewQuerySample = (query: string) => {
-        setQueryResult(undefined);
-        setWaiting(true);
-        fetch(getUrls().DATA_LOADER_VIEW_QUERY_SAMPLE, {
-            method: 'POST',
-            headers: {
-                'Content-Type': 'application/json',
-            },
-            body: JSON.stringify({
-                data_loader_type: dataLoaderType,
-                data_loader_params: dataLoaderParams,
-                query: query
-            })
-        })
-        .then(response => response.json())
-        .then(data => {
-            setWaiting(false);
-            if (data.status === "success") {
-                setQueryResult({
-                    status: "success",
-                    message: "Data loaded successfully",
-                    sample: data.sample,
-                    code: query
-                });
-                let newName = `r_${Math.random().toString(36).substring(2, 4)}`;
-                setQueryResultName(newName);
-            } else {
-                setQueryResult({
-                    status: "error",
-                    message: data.message,
-                    sample: [],
-                    code: query
-                });
-            }
-        })
-        .catch(error => {
-            setWaiting(false);
-            setQueryResult({
-                status: "error",
-                message: `Failed to view query sample, please try again.`,
-                sample: [],
-                code: query
-            });
-        });
-    }
-
-    const handleImportQueryResult = () => {
-        setWaiting(true);
-        fetch(getUrls().DATA_LOADER_INGEST_DATA_FROM_QUERY, {
-            method: 'POST',
-            headers: {
-                'Content-Type': 'application/json',
-            },
-            body: JSON.stringify({
-                data_loader_type: dataLoaderType,
-                data_loader_params: dataLoaderParams,
-                query: queryResult?.code ?? query,
-                name_as: queryResultName
-            })
-        })
-        .then(response => response.json())
-        .then(data => {
-            setWaiting(false);
-            if (data.status === "success") {
-                onFinish("success", "Data imported successfully");
-            } else {
-                onFinish("error", data.reasoning);
-            }
-        })
-        .catch(error => {
-            setWaiting(false);
-            onFinish("error", `Failed to import data, please try again.`);
-        });
-    }
-
-    let queryResultBox = queryResult?.status === "success" && queryResult.sample.length > 0 ? [
-         <Box key="query-result-table" sx={{display: "flex", flexDirection: "row", gap: 1, justifyContent: "space-between"}}>
-            <CustomReactTable rows={queryResult.sample} columnDefs={Object.keys(queryResult.sample[0]).map((t: any) => ({id: t, label: t}))} rowsPerPageNum={-1} compact={false} />
-        </Box>,
-        <Box key="query-result-controls" sx={{display: "flex", flexDirection: "row", gap: 1, alignItems: "center"}}>
-            <Button variant="outlined" color="primary" size="small" sx={{textTransform: "none", minWidth: 120, mr: 'auto'}}
-                onClick={() => {
-                    setQueryResult(undefined);
-                    setQueryResultName("");
-                }}>
-                clear result
-            </Button>
-            <TextField
-                size="small"
-                label="import as"
-                sx={{width: 120, ml: 'auto', '& .MuiInputBase-root': {fontSize: 12, height: 32}, 
-                     '& .MuiInputLabel-root': {fontSize: 12, transform: "translate(14px, -6px) scale(0.75)"}}}
-                slotProps={{
-                    inputLabel: {shrink: true},
-                }}
-                value={queryResultName}
-                onChange={(event: any) => setQueryResultName(event.target.value)}
-            />
-            <Button variant="contained" color="primary" size="small" disabled={queryResultName === ""} sx={{textTransform: "none", width: 120}}
-                onClick={() => handleImportQueryResult()}>
-            import data
-            </Button> 
-        </Box>
-    ] : [];
-    
-    return (
-        <Paper sx={{display: "flex", flexDirection: "column", gap: 1, p: 1, position: "relative"}}>
-            {waiting && <Box sx={{position: "absolute", top: 0, left: 0, width: "100%", height: "100%",
-                display: "flex", alignItems: "center", justifyContent: "center", zIndex: 1000,
-                backgroundColor: "rgba(255, 255, 255, 0.7)"}}>
-                <CircularProgress size={20} />
-            </Box>}
-            <Typography variant="body2" sx={{color: "text.secondary"}}>
-                <Typography variant="caption" sx={{color: "text.primary", fontSize: 11, mx: 0.5}}>
-                    query from tables:
-                </Typography>
-                {availableTables.map((table) => (
-                    <Chip key={table.name} label={table.name} //icon={selectedTables.includes(table.name) ? <CheckIcon /> : undefined}
-                        color={selectedTables.includes(table.name) ? "primary" : "default"} variant="outlined" 
-                        sx={{ fontSize: 11, margin: 0.25, 
-                            height: 20, borderRadius: 0.5, 
-                            borderColor: selectedTables.includes(table.name) ? "primary.main" : "rgba(0, 0, 0, 0.1)",
-                            color: selectedTables.includes(table.name) ? "primary.main" : "text.secondary",
-                            '&:hover': {
-                                backgroundColor: "rgba(0, 0, 0, 0.07)",
-                            }
-                        }}
-                        size="small" 
-                        onClick={() => {
-                            setSelectedTables(selectedTables.includes(table.name) ? selectedTables.filter(t => t !== table.name) : [...selectedTables, table.name]);
-                        }}
-                    />
-                ))}
-            </Typography>
-            <Box sx={{display: "flex", flexDirection: "column", gap: 1, }}>
-                <Box sx={{maxHeight: 300, overflowY: "auto"}}>
-                    <Editor
-                        value={query}
-                        onValueChange={(tempCode: string) => {
-                            setQuery(tempCode);
-                        }}
-                        highlight={code => Prism.highlight(code, Prism.languages.sql, 'sql')}
-                        padding={10}
-                        style={{
-                            minHeight: queryResult ? 60 : 200,
-                            fontFamily: '"Fira code", "Fira Mono", monospace',
-                            fontSize: 12,
-                            paddingBottom: '24px',
-                            backgroundColor: "rgba(0, 0, 0, 0.03)",
-                            overflowY: "auto"
-                        }}
-                    />
-                </Box>
-                {queryResult?.status === "error" && <Box sx={{display: "flex", flexDirection: "row", gap: 1, alignItems: "center", overflow: "auto"}}>
-                        <Typography variant="body2" sx={{color: "text.secondary", fontSize: 11, backgroundColor: "rgba(255, 0, 0, 0.1)", p: 0.5, borderRadius: 0.5}}>
-                            {queryResult?.message} 
-                        </Typography>
-                    </Box>}
-                <Box sx={{display: "flex", flexDirection: "row", gap: 1, justifyContent: "flex-end"}}>
-                    <Button variant="outlined" color="primary" size="small" sx={{textTransform: "none"}} disabled={queryResult?.status === "error"}
-                        startIcon={<PrecisionManufacturingIcon />} onClick={() => aiCompleteQuery(query)}>
-                        help me complete the query from selected tables
-                    </Button>
-                    {queryResult?.status === "error" && <Button variant="contained" color="primary" size="small" sx={{textTransform: "none",minWidth: 120}} 
-                        startIcon={<PrecisionManufacturingIcon />} onClick={() => aiCompleteQuery(queryResult.code + "\n error:" + queryResult.message)}>
-                        help me fix the error
-                    </Button>}
-                    <Button variant="contained" color="primary" size="small" sx={{textTransform: "none", ml: 'auto', width: 80}}
-                        onClick={() => handleViewQuerySample(query)}>
-                        run query
-                    </Button>
-                </Box>
-                {queryResult && queryResultBox}
-            </Box>
-        </Paper>
-    )
 }
\ No newline at end of file
diff --git a/src/views/DataFormulator.tsx b/src/views/DataFormulator.tsx
index 0ea145b..20aa40e 100644
--- a/src/views/DataFormulator.tsx
+++ b/src/views/DataFormulator.tsx
@@ -41,17 +41,14 @@ import { VisualizationViewFC } from './VisualizationView';
 import { ConceptShelf } from './ConceptShelf';
 import { DndProvider } from 'react-dnd'
 import { HTML5Backend } from 'react-dnd-html5-backend'
-import { TableCopyDialogV2, DatasetSelectionDialog } from './TableSelectionView';
-import { TableUploadDialog } from './TableSelectionView';
 import { toolName } from '../app/App';
 import { DataThread } from './DataThread';
 
 import dfLogo from '../assets/df-logo.png';
 import exampleImageTable from "../assets/example-image-table.png";
 import { ModelSelectionButton } from './ModelSelectionDialog';
-import { DBTableSelectionDialog } from './DBTableManager';
 import { getUrls } from '../app/utils';
-import { DataLoadingChatDialog } from './DataLoadingChat';
+import { UnifiedDataUploadDialog, UploadTabType } from './UnifiedDataUploadDialog';
 import { ReportView } from './ReportView';
 import { ExampleSession, exampleSessions, ExampleSessionCard } from './ExampleSessions';
 
@@ -65,6 +62,15 @@ export const DataFormulatorFC = ({ }) => {
 
     const dispatch = useDispatch();
 
+    // State for unified data upload dialog
+    const [uploadDialogOpen, setUploadDialogOpen] = useState(false);
+    const [uploadDialogInitialTab, setUploadDialogInitialTab] = useState<UploadTabType>('menu');
+
+    const openUploadDialog = (tab: UploadTabType) => {
+        setUploadDialogInitialTab(tab);
+        setUploadDialogOpen(true);
+    };
+
     const handleLoadExampleSession = (session: ExampleSession) => {
         dispatch(dfActions.addMessages({
             timestamp: Date.now(),
@@ -274,19 +280,23 @@ export const DataFormulatorFC = ({ }) => {
             </Typography>
             <Box sx={{my: 4}}>
                 <Typography sx={{ 
-                    maxWidth: 1100, fontSize: 28, color: alpha(theme.palette.text.primary, 0.8), 
-                    '& span': { textDecoration: 'underline', textUnderlineOffset: '0.2em', cursor: 'pointer' }}}>
+                    maxWidth: 1100, fontSize: 32, color: alpha(theme.palette.text.primary, 0.8), 
+                    '& span': { textDecoration: 'underline', textUnderlineOffset: '0.2em', cursor: 'pointer', color: theme.palette.primary.main }}}>
                     To begin, 
-                    <DataLoadingChatDialog buttonElement={<span>extract</span>}/>{' '}
+                    {' '}<span onClick={() => openUploadDialog('extract')}>extract</span>{' '}
                     data from images or text documents, load {' '}
-                    <DatasetSelectionDialog buttonElement={<span>examples</span>}/>, 
+                    {' '}<span onClick={() => openUploadDialog('explore')}>examples</span>{' '}, 
                     upload data from{' '}
-                    <TableCopyDialogV2 buttonElement={<span>clipboard</span>} disabled={false}/> or {' '}
-                    <TableUploadDialog buttonElement={<span>files</span>} disabled={false}/>, 
-                    
+                    {' '}<span onClick={() => openUploadDialog('paste')}>clipboard</span> or {' '}
+                    {' '}<span onClick={() => openUploadDialog('upload')}>files</span>{' '}, 
                     or connect to a{' '}
-                    <DBTableSelectionDialog buttonElement={<span>database</span>}/>.
+                    {' '}<span onClick={() => openUploadDialog('database')}>database</span>{' '}.
                 </Typography>
+                <UnifiedDataUploadDialog 
+                    open={uploadDialogOpen}
+                    onClose={() => setUploadDialogOpen(false)}
+                    initialTab={uploadDialogInitialTab}
+                />
             </Box>
             <Box sx={{mt: 4}}>
                 <Divider sx={{width: '200px', mx: 'auto', mb: 3, fontSize: '1.2rem'}}>
diff --git a/src/views/DataLoadingChat.tsx b/src/views/DataLoadingChat.tsx
index a3273a5..1a014ba 100644
--- a/src/views/DataLoadingChat.tsx
+++ b/src/views/DataLoadingChat.tsx
@@ -4,9 +4,7 @@
 import * as React from 'react';
 import { useEffect, useRef, useState } from 'react';
 
-import { Box, Button, Divider, IconButton, Typography, Dialog, DialogTitle, DialogContent, Tooltip, CircularProgress } from '@mui/material';
-import RestartAltIcon from '@mui/icons-material/RestartAlt';
-import CloseIcon from '@mui/icons-material/Close';
+import { Box, Button, Divider, IconButton, Typography, Tooltip, CircularProgress } from '@mui/material';
 
 
 import { useDispatch, useSelector } from 'react-redux';
@@ -266,84 +264,3 @@ export const DataLoadingChat: React.FC = () => {
     return chatCard;
 };
 
-export interface DataLoadingChatDialogProps {
-    buttonElement?: any;
-    disabled?: boolean;
-    onOpen?: () => void;
-    // Controlled mode props
-    open?: boolean;
-    onClose?: () => void;
-}
-
-export const DataLoadingChatDialog: React.FC<DataLoadingChatDialogProps> = ({ 
-    buttonElement, 
-    disabled = false, 
-    onOpen,
-    open: controlledOpen,
-    onClose,
-}) => {
-    const [internalOpen, setInternalOpen] = useState<boolean>(false);
-    const dispatch = useDispatch<AppDispatch>();
-    const dataCleanBlocks = useSelector((state: DataFormulatorState) => state.dataCleanBlocks);
-
-    // Support both controlled and uncontrolled modes
-    const isControlled = controlledOpen !== undefined;
-    const dialogOpen = isControlled ? controlledOpen : internalOpen;
-    const setDialogOpen = isControlled 
-        ? (open: boolean) => { if (!open && onClose) onClose(); }
-        : setInternalOpen;
-
-    return (
-        <>
-            {buttonElement && (
-                <Button 
-                    sx={{fontSize: "inherit"}} 
-                    variant="text" 
-                    color="primary" 
-                    disabled={disabled}
-                    onClick={() => {
-                        setDialogOpen(true);
-                        onOpen?.();
-                    }}
-                >
-                    {buttonElement}
-                </Button>
-            )}
-            <Dialog 
-                key="data-loading-chat-dialog" 
-                onClose={() => setDialogOpen(false)} 
-                open={dialogOpen}
-                sx={{ '& .MuiDialog-paper': { maxWidth: '100%', maxHeight: 840, minWidth: 800 } }}
-            >
-                <DialogTitle sx={{display: "flex"}}>
-                    Extract Data
-                    {dataCleanBlocks.length > 0 && <Tooltip title="Reset dialog">  
-                        <IconButton size="small" color='warning' 
-                            sx={{
-                            '&:hover': {  transform: 'rotate(180deg)', 
-                                        transition: 'transform 0.4s cubic-bezier(0.4, 0, 0.2, 1)' } }} onClick={() => {
-                                            dispatch(dfActions.resetDataCleanBlocks());
-                                        }}>
-                            <RestartAltIcon fontSize="small" />
-                        </IconButton>
-                    </Tooltip>}
-                    <IconButton
-                        sx={{marginLeft: "auto"}}
-                        edge="start"
-                        size="small"
-                        color="inherit"
-                        onClick={() => setDialogOpen(false)}
-                        aria-label="close"
-                    >
-                        <CloseIcon fontSize="inherit"/>
-                    </IconButton>
-                </DialogTitle>
-                <DialogContent sx={{overflowX: "hidden", padding: 1}}>
-                    <DataLoadingChat />
-                </DialogContent>
-            </Dialog>
-        </>
-    );
-};
-
-
diff --git a/src/views/DataThread.tsx b/src/views/DataThread.tsx
index d873edb..df772a5 100644
--- a/src/views/DataThread.tsx
+++ b/src/views/DataThread.tsx
@@ -22,7 +22,9 @@ import {
     Popper,
     Paper,
     ClickAwayListener,
-    Badge
+    Badge,
+    Menu,
+    MenuItem,
 } from '@mui/material';
 
 import { VegaLite } from 'react-vega'
@@ -61,10 +63,15 @@ import ChevronLeftIcon from '@mui/icons-material/ChevronLeft';
 import ChevronRightIcon from '@mui/icons-material/ChevronRight';
 import CloudQueueIcon from '@mui/icons-material/CloudQueue';
 import AttachFileIcon from '@mui/icons-material/AttachFile';
+import MoreVertIcon from '@mui/icons-material/MoreVert';
+import RefreshIcon from '@mui/icons-material/Refresh';
 
 import { alpha } from '@mui/material/styles';
 
 import { dfSelectors } from '../app/dfSlice';
+import { RefreshDataDialog } from './RefreshDataDialog';
+import { getUrls } from '../app/utils';
+import { AppDispatch } from '../app/store';
 
 export const ThinkingBanner = (message: string, sx?: SxProps) => (
     <Box sx={{ 
@@ -490,6 +497,16 @@ let SingleThreadGroupView: FC<{
     const [selectedTableForMetadata, setSelectedTableForMetadata] = useState<DictTable | null>(null);
     const [metadataAnchorEl, setMetadataAnchorEl] = useState<HTMLElement | null>(null);
 
+    // Table menu state
+    const [tableMenuAnchorEl, setTableMenuAnchorEl] = useState<HTMLElement | null>(null);
+    const [selectedTableForMenu, setSelectedTableForMenu] = useState<DictTable | null>(null);
+
+    // Refresh data dialog state
+    const [refreshDialogOpen, setRefreshDialogOpen] = useState(false);
+    const [selectedTableForRefresh, setSelectedTableForRefresh] = useState<DictTable | null>(null);
+    const [isRefreshing, setIsRefreshing] = useState(false);
+
+    const activeModel = useSelector(dfSelectors.getActiveModel);
 
     let handleUpdateTableDisplayId = (tableId: string, displayId: string) => {
         dispatch(dfActions.updateTableDisplayId({
@@ -519,6 +536,127 @@ let SingleThreadGroupView: FC<{
         }
     };
 
+    // Table menu handlers
+    const handleOpenTableMenu = (table: DictTable, anchorEl: HTMLElement) => {
+        setSelectedTableForMenu(table);
+        setTableMenuAnchorEl(anchorEl);
+    };
+
+    const handleCloseTableMenu = () => {
+        setTableMenuAnchorEl(null);
+        setSelectedTableForMenu(null);
+    };
+
+    // Refresh data handlers
+    const handleOpenRefreshDialog = (table: DictTable) => {
+        setSelectedTableForRefresh(table);
+        setRefreshDialogOpen(true);
+        handleCloseTableMenu();
+    };
+
+    const handleCloseRefreshDialog = () => {
+        setRefreshDialogOpen(false);
+        setSelectedTableForRefresh(null);
+    };
+
+    // Function to refresh derived tables
+    const refreshDerivedTables = async (sourceTableId: string, newRows: any[]) => {
+        // Find all tables that are derived from this source table
+        const derivedTables = tables.filter(t => t.derive?.source?.includes(sourceTableId));
+        
+        for (const derivedTable of derivedTables) {
+            if (derivedTable.derive && derivedTable.derive.code) {
+                // Gather all parent tables for this derived table
+                const parentTableData = derivedTable.derive.source.map(sourceId => {
+                    const sourceTable = tables.find(t => t.id === sourceId);
+                    if (sourceTable) {
+                        // Use the new rows if this is the table being refreshed
+                        const rows = sourceId === sourceTableId ? newRows : sourceTable.rows;
+                        return {
+                            name: sourceTable.id,
+                            rows: rows
+                        };
+                    }
+                    return null;
+                }).filter(t => t !== null);
+
+                if (parentTableData.length > 0) {
+                    try {
+                        const response = await fetch(getUrls().REFRESH_DERIVED_DATA, {
+                            method: 'POST',
+                            headers: { 'Content-Type': 'application/json' },
+                            body: JSON.stringify({
+                                input_tables: parentTableData,
+                                code: derivedTable.derive.code
+                            })
+                        });
+
+                        const result = await response.json();
+                        if (result.status === 'ok' && result.rows) {
+                            // Update the derived table with new rows
+                            dispatch(dfActions.updateTableRows({
+                                tableId: derivedTable.id,
+                                rows: result.rows
+                            }));
+
+                            // Recursively refresh tables derived from this one
+                            await refreshDerivedTables(derivedTable.id, result.rows);
+                        } else {
+                            console.error(`Failed to refresh derived table ${derivedTable.id}:`, result.message);
+                            dispatch(dfActions.addMessages({
+                                timestamp: Date.now(),
+                                type: 'error',
+                                component: 'data refresh',
+                                value: `Failed to refresh derived table "${derivedTable.displayId || derivedTable.id}": ${result.message || 'Unknown error'}`
+                            }));
+                        }
+                    } catch (error) {
+                        console.error(`Error refreshing derived table ${derivedTable.id}:`, error);
+                        dispatch(dfActions.addMessages({
+                            timestamp: Date.now(),
+                            type: 'error',
+                            component: 'data refresh',
+                            value: `Error refreshing derived table "${derivedTable.displayId || derivedTable.id}"`
+                        }));
+                    }
+                }
+            }
+        }
+    };
+
+    const handleRefreshComplete = async (newRows: any[]) => {
+        if (!selectedTableForRefresh) return;
+
+        setIsRefreshing(true);
+        try {
+            // Update the source table with new rows
+            dispatch(dfActions.updateTableRows({
+                tableId: selectedTableForRefresh.id,
+                rows: newRows
+            }));
+
+            // Refresh all derived tables
+            await refreshDerivedTables(selectedTableForRefresh.id, newRows);
+
+            dispatch(dfActions.addMessages({
+                timestamp: Date.now(),
+                type: 'success',
+                component: 'data refresh',
+                value: `Successfully refreshed data for "${selectedTableForRefresh.displayId || selectedTableForRefresh.id}" and updated derived tables.`
+            }));
+        } catch (error) {
+            console.error('Error during refresh:', error);
+            dispatch(dfActions.addMessages({
+                timestamp: Date.now(),
+                type: 'error',
+                component: 'data refresh',
+                value: `Error refreshing data: ${error}`
+            }));
+        } finally {
+            setIsRefreshing(false);
+        }
+    };
+
     let buildTriggerCard = (trigger: Trigger) => {
         let selectedClassName = trigger.chart?.id == focusedChartId ? 'selected-card' : '';
         
@@ -673,43 +811,8 @@ let SingleThreadGroupView: FC<{
                         </Box>
                     </Stack>
                     <ButtonGroup aria-label="Basic button group" variant="text" sx={{ textAlign: 'end', margin: "auto 2px auto auto" }}>
-                        {table?.derive == undefined && <Tooltip key="attach-metadata-btn-tooltip" title={table?.attachedMetadata ? "edit table metadata" : "attach table metadata"}>
-                            <IconButton aria-label="attach metadata" size="small" sx={{ 
-                                padding: 0.25, 
-                                '&:hover': {
-                                    transform: 'scale(1.2)',
-                                    transition: 'all 0.1s linear'
-                                } 
-                            }}
-                                onClick={(event) => {
-                                    event.stopPropagation();
-                                    handleOpenMetadataPopup(table!, event.currentTarget);
-                                }}
-                            >
-                                <AttachFileIcon fontSize="small" sx={{ 
-                                    fontSize: 18,
-                                    color: table?.attachedMetadata ? 'secondary.main' : 'text.secondary',
-                                    opacity: table?.attachedMetadata ? 1 : 0.7
-                                }}/>
-                            </IconButton>
-                        </Tooltip>}
-                        
-                        {tableDeleteEnabled && <Tooltip key="delete-table-btn-tooltip" title="delete table">
-                            <IconButton aria-label="share" size="small" sx={{ padding: 0.25, '&:hover': {
-                                transform: 'scale(1.2)',
-                                transition: 'all 0.1s linear'
-                                } }}
-                                onClick={(event) => {
-                                    event.stopPropagation();
-                                    dispatch(dfActions.deleteTable(tableId));
-                                }}
-                            >
-                                <DeleteIcon fontSize="small" sx={{ fontSize: 18 }} color='warning'/>
-                            </IconButton>
-                        </Tooltip>}
-                        
                         <Tooltip key="create-new-chart-btn-tooltip" title="create a new chart">
-                            <IconButton aria-label="share" size="small" sx={{ padding: 0.25, '&:hover': {
+                            <IconButton aria-label="create chart" size="small" sx={{ padding: 0.25, '&:hover': {
                                 transform: 'scale(1.2)',
                                 transition: 'all 0.1s linear'
                                 } }}
@@ -722,6 +825,48 @@ let SingleThreadGroupView: FC<{
                                 <AddchartIcon fontSize="small" sx={{ fontSize: 18 }} color='primary'/>
                             </IconButton>
                         </Tooltip>
+                        
+                        {/* For non-derived, non-virtual tables: show dropdown menu with metadata, refresh, delete */}
+                        {table?.derive == undefined && !table?.virtual && (
+                            <Tooltip key="table-menu-btn-tooltip" title="more options">
+                                <IconButton 
+                                    aria-label="more options" 
+                                    size="small" 
+                                    sx={{ 
+                                        padding: 0.25, 
+                                        '&:hover': {
+                                            transform: 'scale(1.2)',
+                                            transition: 'all 0.1s linear'
+                                        } 
+                                    }}
+                                    onClick={(event) => {
+                                        event.stopPropagation();
+                                        handleOpenTableMenu(table!, event.currentTarget);
+                                    }}
+                                >
+                                    <MoreVertIcon fontSize="small" sx={{ fontSize: 18, color: 'text.secondary' }}/>
+                                </IconButton>
+                            </Tooltip>
+                        )}
+
+                        {/* For derived tables or virtual tables: show individual buttons */}
+                        {(table?.derive != undefined || table?.virtual) && (
+                            <>
+                                {tableDeleteEnabled && <Tooltip key="delete-table-btn-tooltip" title="delete table">
+                                    <IconButton aria-label="delete" size="small" sx={{ padding: 0.25, '&:hover': {
+                                        transform: 'scale(1.2)',
+                                        transition: 'all 0.1s linear'
+                                        } }}
+                                        onClick={(event) => {
+                                            event.stopPropagation();
+                                            dispatch(dfActions.deleteTable(tableId));
+                                        }}
+                                    >
+                                        <DeleteIcon fontSize="small" sx={{ fontSize: 18 }} color='warning'/>
+                                    </IconButton>
+                                </Tooltip>}
+                            </>
+                        )}
                     </ButtonGroup>
                 </Box>
             </Card>
@@ -888,6 +1033,67 @@ let SingleThreadGroupView: FC<{
             initialValue={selectedTableForMetadata?.attachedMetadata || ''}
             tableName={selectedTableForMetadata?.displayId || selectedTableForMetadata?.id || ''}
         />
+
+        {/* Table actions menu for non-derived, non-virtual tables */}
+        <Menu
+            anchorEl={tableMenuAnchorEl}
+            open={Boolean(tableMenuAnchorEl)}
+            onClose={handleCloseTableMenu}
+            onClick={(e) => e.stopPropagation()}
+        >
+            <MenuItem 
+                onClick={(e) => {
+                    e.stopPropagation();
+                    if (selectedTableForMenu) {
+                        handleOpenMetadataPopup(selectedTableForMenu, tableMenuAnchorEl!);
+                    }
+                    handleCloseTableMenu();
+                }}
+                sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
+            >
+                <AttachFileIcon sx={{ 
+                    fontSize: 16,
+                    color: selectedTableForMenu?.attachedMetadata ? 'secondary.main' : 'text.secondary',
+                }}/>
+                {selectedTableForMenu?.attachedMetadata ? "Edit metadata" : "Attach metadata"}
+            </MenuItem>
+            <MenuItem 
+                onClick={(e) => {
+                    e.stopPropagation();
+                    if (selectedTableForMenu) {
+                        handleOpenRefreshDialog(selectedTableForMenu);
+                    }
+                }}
+                sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
+            >
+                <RefreshIcon sx={{ fontSize: 16, color: 'primary.main' }}/>
+                Refresh data
+            </MenuItem>
+            <MenuItem 
+                onClick={(e) => {
+                    e.stopPropagation();
+                    if (selectedTableForMenu) {
+                        dispatch(dfActions.deleteTable(selectedTableForMenu.id));
+                    }
+                    handleCloseTableMenu();
+                }}
+                disabled={selectedTableForMenu ? tables.some(t => t.derive?.trigger.tableId === selectedTableForMenu.id) : true}
+                sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1, color: 'warning.main' }}
+            >
+                <DeleteIcon sx={{ fontSize: 16 }} color='warning'/>
+                Delete table
+            </MenuItem>
+        </Menu>
+
+        {/* Refresh data dialog */}
+        {selectedTableForRefresh && (
+            <RefreshDataDialog
+                open={refreshDialogOpen}
+                onClose={handleCloseRefreshDialog}
+                table={selectedTableForRefresh}
+                onRefreshComplete={handleRefreshComplete}
+            />
+        )}
     </Box>
 }
 
diff --git a/src/views/DerivedDataDialog.tsx b/src/views/DerivedDataDialog.tsx
deleted file mode 100644
index aeb7785..0000000
--- a/src/views/DerivedDataDialog.tsx
+++ /dev/null
@@ -1,191 +0,0 @@
-// Copyright (c) Microsoft Corporation.
-// Licensed under the MIT License.
-
-import { FC } from 'react'
-import {
-		Card,
-		Box,
-		Typography,
-		Dialog,
-        DialogTitle,
-        DialogContent,
-        DialogActions,
-        Button,
-        Radio,
-        styled,
-        FormControlLabel,
-        CardContent,
-        ButtonGroup,
-} from '@mui/material';
-
-import React from 'react';
-
-import { assembleVegaChart } from '../app/utils';
-import { Chart } from '../components/ComponentType';
-import { useSelector } from 'react-redux';
-import { DataFormulatorState } from '../app/dfSlice';
-
-import { createDictTable, DictTable } from '../components/ComponentType';
-import { CodeBox } from './VisualizationView';
-import embed from 'vega-embed';
-import { CustomReactTable } from './ReactTable';
-
-import DeleteIcon from '@mui/icons-material/Delete';
-import SaveIcon from '@mui/icons-material/Save';
-
-export interface DerivedDataDialogProps {
-    chart: Chart,
-    candidateTables: DictTable[],
-    open: boolean,
-    handleCloseDialog: () => void,
-    handleSelection: (selectIndex: number) => void,
-    handleDeleteChart: () => void,
-    bodyOnly?: boolean,
-}
-
-export const DerivedDataDialog: FC<DerivedDataDialogProps> = function DerivedDataDialog({ 
-        chart, candidateTables, open, handleCloseDialog, handleSelection, handleDeleteChart, bodyOnly }) {
-
-    let direction = candidateTables.length > 1 ? "horizontal" : "horizontal" ;
-
-    let [selectionIdx, setSelectionIdx] = React.useState(0);
-    const conceptShelfItems = useSelector((state: DataFormulatorState) => state.conceptShelfItems);
-
-    let body = 
-        <Box sx={{display: "flex", overflowX: "auto", flexDirection: direction == "horizontal" ? "column" : "row", 
-                  justifyContent: "space-between", position: "relative", marginTop: "10px", minHeight: "50px"}}>
-            
-            {candidateTables.map((table, idx) => {
-                let code = table.derive?.code || "";
-                let extTable = structuredClone(table.rows);
-            
-                let assembledChart: any = assembleVegaChart(chart.chartType, chart.encodingMap, conceptShelfItems, extTable, table.metadata);
-                assembledChart["background"] = "transparent";
-                // chart["autosize"] = {
-                //     "type": "fit",
-                //     "contains": "padding"
-                // };
-                const id = `chart-dialog-element-${idx}`;
-                
-                const element =
-                        <Box className="vega-thumbnail-no-hover"
-                            id={id} key={`chart-thumbnail-${idx}`} 
-                            sx={{ minWidth: '220px', margin: "auto", backgroundColor: "white", display: 'flex', justifyContent: 'center' }}
-                            onClick={() => setSelectionIdx(idx)}>
-                        </Box>;
-
-                embed('#' + id, assembledChart, { actions: false, renderer: "canvas" }).then(function (result) {
-                    // Access the Vega view instance (https://vega.github.io/vega/docs/api/view/) as result.view
-                    if (result.view.container()?.getElementsByTagName("canvas")) {
-                        let comp = result.view.container()?.getElementsByTagName("canvas")[0];
-
-                        // Doesn't seem like width & height are actual numbers here on Edge bug
-                        // let width = parseInt(comp?.style.width as string);
-                        // let height = parseInt(comp?.style.height as string);
-                        if (comp) {
-                            const { width, height } = comp.getBoundingClientRect();
-                            //console.log(`THUMB: width = ${width} height = ${height}`);
-                            if (width > 240 || height > 180) {
-                                let ratio = width / height;
-                                let fixedWidth = width;
-                                if (ratio * 180 < width) {
-                                    fixedWidth = ratio * 180;
-                                }
-                                if (fixedWidth > 240) {
-                                    fixedWidth = 240;
-                                }
-                                comp?.setAttribute("style", `max-width: 240px; max-height: 180px; width: ${Math.round(fixedWidth)}px; height: ${Math.round(fixedWidth / ratio)}px; `);
-                            }
-
-                        } else {
-                            console.log("THUMB: Could not get Canvas HTML5 element")
-                        }
-                    }
-                }).catch((reason) => {
-                    // console.log(reason)
-                    // console.error(reason)
-                });
-
-                let simpleTableView = (t: DictTable) => {
-                    let colDefs = t.names.map(name => {
-                        return {
-                            id: name, label: name, minWidth: 30, align: undefined, 
-                            format: (value: any) => `${value}`, source: conceptShelfItems.find(f => f.name == name)?.source
-                        }
-                    })
-                    return <Box sx={{ position: "relative", display: "flex", flexDirection: "column" }}>
-                        <CustomReactTable rows={t.rows} columnDefs={colDefs} rowsPerPageNum={10} compact />
-                    </Box>
-                }
-
-                return <Card variant="outlined" key={`candidate-dialog-${idx}`} onClick={()=>{setSelectionIdx(idx)}} 
-                    sx={{minWidth: "280px", maxWidth: "1920px", display: "flex", flexGrow: 1, margin: "6px", 
-                        border: selectionIdx == idx ? "2px solid rgb(2 136 209 / 0.7)": "1px solid rgba(33, 33, 33, 0.1)"}}>
-                    <CardContent sx={{display: "flex", flexDirection: "column", flexGrow: 1, maxHeight: 800, padding: '2px 8px', paddingBottom: '2px !important'}}>
-                        <FormControlLabel 
-                            sx={{marginLeft: 0, fontSize: 12, position: direction == "horizontal" ? 'absolute' : 'relative',
-                                "& svg": { width: "0.5em",  height: "0.5em" },
-                                '& .MuiTypography-root': { fontSize: "inherit"}, 
-                                '& .MuiFormLabel-root': { fontSize: "inherit" } }}
-                            value={idx} control={<Radio checked={selectionIdx == idx} />} 
-                            label={<Typography color={idx == selectionIdx ? 'primary' : 'inherit'} >{`candidate-${idx+1} (${candidateTables[idx].id})`}</Typography>} />
-                        <Box sx={{display: 'flex', flexDirection: direction == "horizontal" ? "row" : "column", alignItems: "center", flex: 'auto'}}>
-                            <Box sx={{}}>
-                                {element}
-                            </Box>
-                            <Box sx={{margin: '12px', width: '100%'}}>
-                                <Box sx={{maxHeight: 300, minWidth: '200px', width: "100%", overflow: "auto", flexGrow: 1,fontSize: 10 }}>
-                                    {simpleTableView(createDictTable(table.id, extTable))}
-                                </Box>
-                            </Box>
-                            <Box sx={{maxWidth: 400, width: 'fit-content',  display: 'flex', maxHeight: 300, overflow: 'initial'}}>
-                                <CodeBox code={code} language="python" />
-                            </Box>
-                        </Box>
-                    </CardContent>
-                </Card>
-            })}
-            
-        </Box>
-
-    if (bodyOnly) {
-        return <Box sx={{marginTop: 2}}>
-            <Box sx={{width: '100%', display: 'flex', alignItems: 'center'}}>
-                <Typography fontSize="small" sx={{color: 'gray'}}>Transformation from <Typography component="span" fontSize="inherit" sx={{textDecoration: 'underline'}}>{candidateTables[0].derive?.source}</Typography></Typography>
-            </Box>
-            {body}
-            <Box sx={{width: '100%', display: 'flex', alignItems: 'center'}}>
-                <Box sx={{ display: 'flex', margin: 'auto'}}>
-                    <ButtonGroup size="small" sx={{margin: 'auto'}}>
-                        {/* <Button sx={{textTransform: 'none'}} onClick={()=>{ handleCloseDialog() }}>Cancel</Button> */}
-                        <Button sx={{textTransform: 'none', margin: 'auto',}} variant="text" startIcon={<DeleteIcon/>} color="error"
-                                onClick={() => { handleDeleteChart()} }>
-                            {`Delete all`}
-                        </Button>
-                        <Button sx={{textTransform: 'none', width: '300px', margin: 'auto',}} variant="text" startIcon={<SaveIcon />}
-                                onClick={() => { handleSelection(selectionIdx)} }>
-                            Save <Typography component="span" fontSize="inherit" sx={{margin: '0px 2px', padding: '0px 2px'}}>{`candidate ${selectionIdx + 1} (${candidateTables[selectionIdx].id})`}</Typography> as the result
-                        </Button>
-                    </ButtonGroup>
-                </Box>
-            </Box>
-        </Box>;
-    }
-
-    return (
-        <Dialog
-            sx={{ '& .MuiDialog-paper': { maxWidth: '95%', maxHeight: 860, minWidth: 300 } }}
-            maxWidth={false}
-            open={open}
-        >
-            <DialogTitle><Typography>Derived Data Candidates</Typography></DialogTitle>
-            <DialogContent sx={{overflowX: "hidden"}} dividers>
-                {body}
-            </DialogContent>
-            <DialogActions>
-                <Button onClick={()=>{ handleCloseDialog() }}>Cancel</Button>
-                <Button onClick={() => { handleSelection(selectionIdx)} }>Ok</Button>
-            </DialogActions>
-        </Dialog>
-    );
-}
\ No newline at end of file
diff --git a/src/views/TableSelectionView.tsx b/src/views/TableSelectionView.tsx
index 4245025..79a127f 100644
--- a/src/views/TableSelectionView.tsx
+++ b/src/views/TableSelectionView.tsx
@@ -2,63 +2,13 @@
 // Licensed under the MIT License.
 
 import * as React from 'react';
-import validator from 'validator';
-import DOMPurify from 'dompurify';
+import { useEffect } from 'react';
 
-import Tabs from '@mui/material/Tabs';
-import Tab from '@mui/material/Tab';
 import Typography from '@mui/material/Typography';
 import Box from '@mui/material/Box';
-import { alpha, Button, Collapse, Dialog, DialogActions, DialogContent, DialogTitle, Divider, 
-         IconButton, Input, CircularProgress, LinearProgress, Paper, TextField, useTheme, 
-         Card, Tooltip, Link} from '@mui/material';
+import { Button, Paper } from '@mui/material';
 import { CustomReactTable } from './ReactTable';
-import { DictTable } from "../components/ComponentType";
-
-import DeleteIcon from '@mui/icons-material/Delete';
-import { getUrls } from '../app/utils';
-import { createTableFromFromObjectArray, createTableFromText, loadTextDataWrapper, loadBinaryDataWrapper } from '../data/utils';
-
-import CloseIcon from '@mui/icons-material/Close';
-
-import { DataFormulatorState, dfActions, dfSelectors, fetchFieldSemanticType } from '../app/dfSlice';
-import { useDispatch, useSelector } from 'react-redux';
-import { useEffect, useState, useCallback } from 'react';
-import { AppDispatch } from '../app/store';
-
-interface TabPanelProps {
-  children?: React.ReactNode;
-  index: number;
-  value: number;
-}
-
-function TabPanel(props: TabPanelProps) {
-  const { children, value, index, ...other } = props;
-
-    return (
-	    <div
-            role="tabpanel"
-            hidden={value !== index}
-            id={`vertical-tabpanel-${index}`}
-            aria-labelledby={`vertical-tab-${index}`}
-            style={{maxWidth: 'calc(100% - 120px)'}}
-            {...other}
-        >
-            {value === index && (
-                <Box sx={{ p: 2 }}>
-                    {children}
-                </Box>
-            )}
-        </div>
-    );
-}
-
-function a11yProps(index: number) {
-  return {
-	id: `vertical-tab-${index}`,
-	'aria-controls': `vertical-tabpanel-${index}`,
-  };
-}
+import { createTableFromFromObjectArray } from '../data/utils';
 
 // Update the interface to support multiple tables per dataset
 export interface DatasetMetadata {
@@ -197,613 +147,3 @@ export const DatasetSelectionView: React.FC<DatasetSelectionViewProps> = functio
         </Box>
     );
 }
-
-export const DatasetSelectionDialog: React.FC<{ buttonElement: any }> = function DatasetSelectionDialog({ buttonElement }) {
-
-    const [datasetPreviews, setDatasetPreviews] = React.useState<DatasetMetadata[]>([]);
-    const [tableDialogOpen, setTableDialogOpen] = useState<boolean>(false);
-
-    React.useEffect(() => {
-        // Show a loading animation/message while loading
-        fetch(`${getUrls().EXAMPLE_DATASETS}`)
-            .then((response) => response.json())
-            .then((result) => {
-                let datasets : DatasetMetadata[] = result.map((info: any) => {
-                    let tables = info["tables"].map((table: any) => {
-
-                        if (table["format"] == "json") {
-                            return {
-                                table_name: table["name"],
-                                url: table["url"],
-                                format: table["format"],
-                                sample: table["sample"],
-                            }
-                        }
-                        else if (table["format"] == "csv" || table["format"] == "tsv") {
-                            const delimiter = table["format"] === "csv" ? "," : "\t";
-                            const rows = table["sample"]
-                                .split("\n")
-                                .map((row: string) => row.split(delimiter));
-                            
-                            // Treat first row as headers and convert to object array
-                            if (rows.length > 0) {
-                                const headers = rows[0];
-                                const dataRows = rows.slice(1);
-                                const sampleData = dataRows.map((row: string[]) => {
-                                    const obj: any = {};
-                                    headers.forEach((header: string, index: number) => {
-                                        obj[header] = row[index] || '';
-                                    });
-                                    return obj;
-                                });
-                                
-                                return {
-                                    table_name: table["name"],
-                                    url: table["url"],
-                                    format: table["format"],
-                                    sample: sampleData,
-                                };
-                            }
-                            
-                            return {
-                                table_name: table["name"],
-                                url: table["url"],
-                                format: table["format"],
-                                sample: [],
-                            };
-                        }
-                    })
-                    return {tables: tables, name: info["name"], description: info["description"], source: info["source"]}
-                }).filter((t : DatasetMetadata | undefined) => t != undefined);
-                setDatasetPreviews(datasets);
-            });
-      }, []);
-
-    let dispatch = useDispatch<AppDispatch>();
-
-    return <>
-        <Button sx={{fontSize: "inherit"}} onClick={() => {
-            setTableDialogOpen(true);
-        }}>
-            {buttonElement}
-        </Button>
-        <Dialog key="sample-dataset-selection-dialog" onClose={() => {setTableDialogOpen(false)}} 
-                open={tableDialogOpen}
-                sx={{ '& .MuiDialog-paper': { maxWidth: '100%', maxHeight: 840, minWidth: 800 } }}
-            >
-                <DialogTitle sx={{display: "flex"}}>Explore
-                    <IconButton
-                        sx={{marginLeft: "auto"}}
-                        edge="start"
-                        size="small"
-                        color="inherit"
-                        onClick={() => {setTableDialogOpen(false)}}
-                        aria-label="close"
-                    >
-                        <CloseIcon fontSize="inherit"/>
-                    </IconButton>
-                </DialogTitle>
-                <DialogContent sx={{overflowX: "hidden", padding: 1}}>
-                    <DatasetSelectionView datasets={datasetPreviews} hideRowNum
-                        handleSelectDataset={(dataset) => {
-                            setTableDialogOpen(false);
-                            for (let table of dataset.tables) { 
-                                fetch(table.url)
-                                .then(res => res.text())
-                                .then(textData => {
-                                    let tableName = table.url.split("/").pop()?.split(".")[0] || 'table-' + Date.now().toString().substring(0, 8);
-                                    let dictTable;
-                                    if (table.format == "csv") {
-                                        dictTable = createTableFromText(tableName, textData);
-                                    } else if (table.format == "json") {
-                                        dictTable = createTableFromFromObjectArray(tableName, JSON.parse(textData), true);
-                                    } 
-                                    if (dictTable) {
-                                        dispatch(dfActions.loadTable(dictTable));
-                                        dispatch(fetchFieldSemanticType(dictTable));
-                                    }
-                                    
-                                });
-                            } 
-                        }}/>
-                </DialogContent>
-            </Dialog>
-    </>
-}
-
-export interface TableUploadDialogProps {
-    buttonElement?: any;
-    disabled?: boolean;
-    onOpen?: () => void;
-    // For external control of file input
-    fileInputRef?: React.RefObject<HTMLInputElement>;
-}
-
-const getUniqueTableName = (baseName: string, existingNames: Set<string>): string => {
-    let uniqueName = baseName;
-    let counter = 1;
-    while (existingNames.has(uniqueName)) {
-        uniqueName = `${baseName}_${counter}`;
-        counter++;
-    }
-    return uniqueName;
-};
-
-export const TableUploadDialog: React.FC<TableUploadDialogProps> = ({ buttonElement, disabled, onOpen, fileInputRef }) => {
-    const dispatch = useDispatch<AppDispatch>();
-    const internalRef = React.useRef<HTMLInputElement>(null);
-    const inputRef = fileInputRef || internalRef;
-    const existingTables = useSelector((state: DataFormulatorState) => state.tables);
-    const existingNames = new Set(existingTables.map(t => t.id));
-    const serverConfig = useSelector((state: DataFormulatorState) => state.serverConfig);
-
-    let handleFileUpload = (event: React.ChangeEvent<HTMLInputElement>): void => {
-        const files = event.target.files;
-
-        if (files) {
-            for (let file of files) {
-                const uniqueName = getUniqueTableName(file.name, existingNames);
-                
-                // Check if file is a text type (csv, tsv, json)
-                if (file.type === 'text/csv' || 
-                    file.type === 'text/tab-separated-values' || 
-                    file.type === 'application/json' ||
-                    file.name.endsWith('.csv') || 
-                    file.name.endsWith('.tsv') || 
-                    file.name.endsWith('.json')) {
-
-                    // Check if file is larger than 5MB
-                    const MAX_FILE_SIZE = 5 * 1024 * 1024; // 5MB in bytes
-                    if (file.size > MAX_FILE_SIZE) {
-                        dispatch(dfActions.addMessages({
-                            "timestamp": Date.now(),
-                            "type": "error",
-                            "component": "data loader",
-                            "value": `File ${file.name} is too large (${(file.size / (1024 * 1024)).toFixed(2)}MB), upload it via DATABASE option instead.`
-                        }));
-                        continue; // Skip this file and process the next one
-                    }
-                    
-                    // Handle text files
-                    file.text().then((text) => {
-                        let table = loadTextDataWrapper(uniqueName, text, file.type);
-                        if (table) {
-                            dispatch(dfActions.loadTable(table));
-                            dispatch(fetchFieldSemanticType(table));
-                        }
-                    });
-                } else if (file.type === 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet' ||
-                           file.type === 'application/vnd.ms-excel' ||
-                           file.name.endsWith('.xlsx') || 
-                           file.name.endsWith('.xls')) {
-                    // Handle Excel files
-                    const reader = new FileReader();
-                    reader.onload = async (e) => {
-                        const arrayBuffer = e.target?.result as ArrayBuffer;
-                        if (arrayBuffer) {
-                            try {
-                                let tables = await loadBinaryDataWrapper(uniqueName, arrayBuffer);
-                                for (let table of tables) {
-                                    dispatch(dfActions.loadTable(table));
-                                    dispatch(fetchFieldSemanticType(table));
-                                }
-                                if (tables.length == 0) {
-                                    dispatch(dfActions.addMessages({
-                                        "timestamp": Date.now(),
-                                        "type": "error",
-                                        "component": "data loader",
-                                        "value": `Failed to parse Excel file ${file.name}. Please check the file format.`
-                                    }));
-                                }
-                            } catch (error) {
-                                console.error('Error processing Excel file:', error);
-                                dispatch(dfActions.addMessages({
-                                    "timestamp": Date.now(),
-                                    "type": "error",
-                                    "component": "data loader",
-                                    "value": `Failed to parse Excel file ${file.name}. Please check the file format.`
-                                }));
-                            }
-                        }
-                    };
-                    reader.readAsArrayBuffer(file);
-                } else {
-                    // Unsupported file type
-                    dispatch(dfActions.addMessages({
-                        "timestamp": Date.now(),
-                        "type": "error",
-                        "component": "data loader",
-                        "value": `Unsupported file format: ${file.name}. Please use CSV, TSV, JSON, or Excel files.`
-                    }));
-                }
-            }
-        }
-        if (inputRef.current) {
-            inputRef.current.value = '';
-        }
-    };
-
-    return (
-        <>
-            <Input
-                inputProps={{ 
-                    accept: '.csv,.tsv,.json,.xlsx,.xls',
-                    multiple: true,
-                }}
-                id="upload-data-file"
-                type="file"
-                sx={{ display: 'none' }}
-                inputRef={inputRef}
-                onChange={handleFileUpload}
-            />
-            {buttonElement && (
-                <Tooltip 
-                    title={serverConfig.DISABLE_FILE_UPLOAD ? (
-                        <Typography sx={{ fontSize: '11px' }}>
-                            Install Data Formulator locally to enable file upload. <br />
-                            Link: <Link 
-                                href="https://github.com/microsoft/data-formulator" 
-                                target="_blank" 
-                                rel="noopener noreferrer"
-                                sx={{ color: 'inherit', textDecoration: 'underline' }}
-                                onClick={(e) => e.stopPropagation()}
-                            >
-                                https://github.com/microsoft/data-formulator
-                            </Link>
-                        </Typography>
-                    ) : ""}
-                    placement="top"
-                >
-                    <span style={{cursor: serverConfig.DISABLE_FILE_UPLOAD ? 'help' : 'pointer'}}>
-                        <Button 
-                            sx={{fontSize: "inherit"}} 
-                            variant="text" 
-                            color="primary" 
-                            disabled={disabled || serverConfig.DISABLE_FILE_UPLOAD}
-                            onClick={() => {
-                                inputRef.current?.click();
-                                onOpen?.();
-                            }}
-                        >
-                            {buttonElement}
-                        </Button>
-                    </span>
-                </Tooltip>
-            )}
-        </>
-    );
-}
-
-
-export interface TableCopyDialogProps {
-    buttonElement?: any;
-    disabled?: boolean;
-    onOpen?: () => void;
-    // Controlled mode props
-    open?: boolean;
-    onClose?: () => void;
-}
-
-export interface TableURLDialogProps {
-    buttonElement: any;
-    disabled: boolean;
-}
-
-export const TableURLDialog: React.FC<TableURLDialogProps> = ({ buttonElement, disabled }) => {
-
-    const [dialogOpen, setDialogOpen] = useState<boolean>(false);
-    const [tableURL, setTableURL] = useState<string>("");
-
-    const dispatch = useDispatch<AppDispatch>();
-
-    let handleSubmitContent = (): void => {
-
-        let  parts = tableURL.split('/');
-
-        // Get the last part of the URL, which should be the file name with extension
-        const tableName = parts[parts.length - 1];
-
-        fetch(tableURL)
-        .then(res => res.text())
-        .then(content => {
-            let table : undefined | DictTable = undefined;
-            try {
-                let jsonContent = JSON.parse(content);
-                table = createTableFromFromObjectArray(tableName || 'dataset', jsonContent, true);
-            } catch (error) {
-                table = createTableFromText(tableName || 'dataset', content);
-            }
-
-            if (table) {
-                dispatch(dfActions.loadTable(table));
-                dispatch(fetchFieldSemanticType(table));
-            }        
-        })
-    };
-
-    let hasValidSuffix = tableURL.endsWith('.csv') || tableURL.endsWith('.tsv') || tableURL.endsWith(".json");
-
-    let dialog = <Dialog key="table-url-dialog" onClose={()=>{setDialogOpen(false)}} open={dialogOpen}
-            sx={{ '& .MuiDialog-paper': { maxWidth: '80%', maxHeight: 800, minWidth: 800 } }} disableRestoreFocus
-        >
-            <DialogTitle  sx={{display: "flex"}}>Upload data URL
-                <IconButton
-                    sx={{marginLeft: "auto"}}
-                    edge="start"
-                    size="small"
-                    color="inherit"
-                    onClick={()=>{ setDialogOpen(false); }}
-                    aria-label="close"
-                >
-                    <CloseIcon fontSize="inherit"/>
-                </IconButton>
-            </DialogTitle>
-            <DialogContent sx={{overflowX: "hidden", padding: 2, display: "flex", flexDirection: "column"}} dividers>
-                <TextField error={tableURL != "" && !hasValidSuffix} autoFocus placeholder='Please enter URL of the dataset' 
-                            helperText={hasValidSuffix ? "" : "the url should links to a csv, tsv or json file"}
-                            sx={{marginBottom: 1}} size="small" value={tableURL} onChange={(event) => { setTableURL(event.target.value.trim()); }} 
-                            id="dataset-url" label="data url" variant="outlined" />
-            </ DialogContent>
-            <DialogActions>
-                <Button variant="contained" size="small" onClick={()=>{ setDialogOpen(false); }}>cancel</Button>
-                <Button variant="contained" size="small" onClick={()=>{ setDialogOpen(false); handleSubmitContent(); }} >
-                    upload
-                </Button>
-            </DialogActions>
-        </Dialog>;
-
-    return <>
-        <Button sx={{fontSize: "inherit"}} variant="text" color="primary" 
-                    disabled={disabled} onClick={()=>{setDialogOpen(true)}}>
-            {buttonElement}
-        </Button>
-        {dialog}
-    </>;
-}
-
-
-export const TableCopyDialogV2: React.FC<TableCopyDialogProps> = ({ 
-    buttonElement, 
-    disabled, 
-    onOpen,
-    open: controlledOpen,
-    onClose,
-}) => {
-
-    const [internalOpen, setInternalOpen] = useState<boolean>(false);
-    
-    // Support both controlled and uncontrolled modes
-    const isControlled = controlledOpen !== undefined;
-    const dialogOpen = isControlled ? controlledOpen : internalOpen;
-    
-    const [tableContent, setTableContent] = useState<string>("");
-    const [tableContentType, setTableContentType] = useState<'text' | 'image'>('text');
-
-    const [cleaningInProgress, setCleaningInProgress] = useState<boolean>(false);
-
-    // Add new state for display optimization
-    const [displayContent, setDisplayContent] = useState<string>("");
-    const [isLargeContent, setIsLargeContent] = useState<boolean>(false);
-    const [showFullContent, setShowFullContent] = useState<boolean>(false);
-    const [isOverSizeLimit, setIsOverSizeLimit] = useState<boolean>(false);
-    
-    // Constants for content size limits
-    const MAX_DISPLAY_LINES = 20; // Reduced from 30
-    const LARGE_CONTENT_THRESHOLD = 50000; // ~50KB threshold
-    const MAX_CONTENT_SIZE = 2 * 1024 * 1024; // 2MB in bytes (same as file upload limit)
-
-    const dispatch = useDispatch<AppDispatch>();
-    const existingTables = useSelector((state: DataFormulatorState) => state.tables);
-    const existingNames = new Set(existingTables.map(t => t.id));
-
-    let handleSubmitContent = (tableStr: string): void => {
-        let table: undefined | DictTable = undefined;
-        
-        // Generate a short unique name based on content and time if no name provided
-        const defaultName = (() => {
-            const hashStr = tableStr.substring(0, 100) + Date.now();
-            const hashCode = hashStr.split('').reduce((acc, char) => {
-                return ((acc << 5) - acc) + char.charCodeAt(0) | 0;
-            }, 0);
-            const shortHash = Math.abs(hashCode).toString(36).substring(0, 4);
-            return `data-${shortHash}`;
-        })();
-
-        const baseName = defaultName;
-        const uniqueName = getUniqueTableName(baseName, existingNames);
-
-        try {
-            let content = JSON.parse(tableStr);
-            table = createTableFromFromObjectArray(uniqueName, content, true);
-        } catch (error) {
-            table = createTableFromText(uniqueName, tableStr);
-        }
-        if (table) {
-            dispatch(dfActions.loadTable(table));
-            dispatch(fetchFieldSemanticType(table));
-        }        
-    };
-
-    // Optimized content change handler
-    const handleContentChange = useCallback((event: React.ChangeEvent<HTMLInputElement>) => {
-        const newContent = event.target.value;
-        setTableContent(newContent);
-        
-        // Check if content exceeds size limit
-        const contentSizeBytes = new Blob([newContent]).size;
-        const isOverLimit = contentSizeBytes > MAX_CONTENT_SIZE;
-        setIsOverSizeLimit(isOverLimit);
-        
-        // Check if content is large
-        const isLarge = newContent.length > LARGE_CONTENT_THRESHOLD;
-        setIsLargeContent(isLarge);
-        
-        if (isLarge && !showFullContent) {
-            // For large content, only show a preview in the TextField
-            const lines = newContent.split('\n');
-            const previewLines = lines.slice(0, MAX_DISPLAY_LINES);
-            const preview = previewLines.join('\n') + (lines.length > MAX_DISPLAY_LINES ? '\n... (truncated for performance)' : '');
-            setDisplayContent(preview);
-        } else {
-            setDisplayContent(newContent);
-        }
-    }, [showFullContent, dispatch, MAX_CONTENT_SIZE]);
-
-    // Toggle between preview and full content
-    const toggleFullContent = useCallback(() => {
-        setShowFullContent(!showFullContent);
-        if (!showFullContent) {
-            setDisplayContent(tableContent);
-        } else {
-            const lines = tableContent.split('\n');
-            const previewLines = lines.slice(0, MAX_DISPLAY_LINES);
-            const preview = previewLines.join('\n') + (lines.length > MAX_DISPLAY_LINES ? '\n... (truncated for performance)' : '');
-            setDisplayContent(preview);
-        }
-    }, [showFullContent, tableContent]);
-
-
-    const handleCloseDialog = useCallback(() => {
-        if (isControlled) {
-            onClose?.();
-        } else {
-            setInternalOpen(false);
-        }
-        // Reset state when closing
-        setTableContent("");
-        setDisplayContent("");
-        setIsLargeContent(false);
-        setIsOverSizeLimit(false);
-        setShowFullContent(false);
-    }, [isControlled, onClose]);
-
-    let dialog = <Dialog key="table-selection-dialog" onClose={handleCloseDialog} open={dialogOpen}
-            sx={{ '& .MuiDialog-paper': { maxWidth: '80%', maxHeight: 800, minWidth: 800 } }}
-        >
-            <DialogTitle  sx={{display: "flex"}}>Paste & Upload Data
-                <IconButton
-                    sx={{marginLeft: "auto"}}
-                    edge="start"
-                    size="small"
-                    color="inherit"
-                    onClick={handleCloseDialog}
-                    aria-label="close"
-                >
-                    <CloseIcon fontSize="inherit"/>
-                </IconButton>
-            </DialogTitle>
-            <DialogContent sx={{overflowX: "hidden", padding: 2, display: "flex", 
-                                flexDirection: "column", 
-                                "& .MuiOutlinedInput-root.Mui-disabled": {backgroundColor: 'rgba(0,0,0,0.05)'}}} dividers>
-                <Box sx={{width: '100%',  display:'flex', position: 'relative', overflow: 'auto'}}>
-                    {cleaningInProgress && tableContentType == "text" ? <LinearProgress sx={{ width: '100%', height: "calc(100% - 8px)", marginTop: 1, minHeight: 200, opacity: 0.1, position: 'absolute', zIndex: 1 }} /> : ""}
-                    <Box sx={{ flex: 1, display: 'flex', flexDirection: 'column' }}>
-                        {/* Size limit warning */}
-                        {isOverSizeLimit && (
-                            <Box sx={{ display: 'flex', alignItems: 'center', marginBottom: 1, padding: 1, backgroundColor: 'rgba(244, 67, 54, 0.1)', borderRadius: 1, border: '1px solid rgba(244, 67, 54, 0.3)' }}>
-                                <Typography variant="caption" sx={{ flex: 1, color: 'error.main', fontWeight: 500 }}>
-                                    ⚠️ Content exceeds {(MAX_CONTENT_SIZE / (1024 * 1024)).toFixed(0)}MB size limit. 
-                                    Current size: {(new Blob([tableContent]).size / (1024 * 1024)).toFixed(2)}MB. 
-                                    Please use the DATABASE option for large datasets.
-                                </Typography>
-                            </Box>
-                        )}
-                        {/* Content size indicator */}
-                        {isLargeContent && !isOverSizeLimit && (
-                            <Box sx={{ display: 'flex', alignItems: 'center', marginBottom: 1, padding: 1, backgroundColor: 'rgba(255, 193, 7, 0.1)', borderRadius: 1 }}>
-                                <Typography variant="caption" sx={{ flex: 1 }}>
-                                    Large content detected ({Math.round(tableContent.length / 1000)}KB). 
-                                    {showFullContent ? 'Showing full content (may be slow)' : 'Showing preview for performance'}
-                                </Typography>
-                                <Button 
-                                    size="small" 
-                                    variant="outlined" 
-                                    onClick={toggleFullContent}
-                                    sx={{ textTransform: 'none', minWidth: 'auto' }}
-                                >
-                                    {showFullContent ? 'Show Preview' : 'Show Full'}
-                                </Button>
-                            </Box>
-                        )}
-                        
-                        <TextField 
-                            disabled={cleaningInProgress} 
-                            autoFocus 
-                            size="small" 
-                            sx={{ 
-                                marginTop: 1, 
-                                flex: 1, 
-                                "& .MuiInputBase-input": {
-                                    fontSize: 12, 
-                                    lineHeight: 1.2,
-                                    // Limit height for performance
-                                    maxHeight: isLargeContent && !showFullContent ? '300px' : '400px',
-                                    overflow: 'auto'
-                                }
-                            }} 
-                            id="upload content" 
-                            value={displayContent} 
-                            maxRows={isLargeContent && !showFullContent ? MAX_DISPLAY_LINES : 25} // Dynamic max rows
-                            minRows={10} // Reduced from 15
-                            onChange={handleContentChange}
-                            slotProps={{
-                                inputLabel: {
-                                    shrink: true
-                                }
-                            }}
-                            placeholder="paste data (csv, tsv, or json) and upload it!"
-                            onPasteCapture={(e) => {
-                                if (e.clipboardData.files.length > 0) {
-                                    let file = e.clipboardData.files[0];
-                                    let read = new FileReader();
-
-                                    read.readAsDataURL(file);
-                                    read.onloadend = function(){
-                                        let res = read.result;
-                                        console.log(res);
-                                        if (res) { 
-                                            setTableContent(res as string); 
-                                            setTableContentType("image");
-                                        }
-                                    }
-                                }
-                            }}
-                            autoComplete='off'
-                            label="data content" 
-                            variant="outlined" 
-                            multiline 
-                        />
-                    </Box>
-                </Box>
-            </DialogContent>
-            <DialogActions>
-                <Button variant="text" sx={{textTransform: 'none'}} size="small" onClick={handleCloseDialog}>cancel</Button>
-                <Tooltip title={isOverSizeLimit ? `Content exceeds ${(MAX_CONTENT_SIZE / (1024 * 1024)).toFixed(0)}MB size limit` : ""} placement="top">
-                    <span>
-                        <Button disabled={tableContentType != "text" || tableContent.trim() == "" || isOverSizeLimit} variant="contained" sx={{textTransform: 'none'}} size="small" 
-                            onClick={()=>{ 
-                                handleCloseDialog(); 
-                                handleSubmitContent(tableContent); // Always use full content for processing
-                            }} >
-                            {"upload"}
-                        </Button>
-                    </span>
-                </Tooltip>
-            </DialogActions>
-            
-        </Dialog>;
-
-    return <>
-        {buttonElement && (
-            <Button sx={{fontSize: "inherit"}} variant="text" color="primary" 
-                        disabled={disabled} onClick={()=>{
-                            setInternalOpen(true);
-                            onOpen?.();
-                        }}>
-                    {buttonElement}
-            </Button>
-        )}
-        {dialog}
-    </>;
-}
-
diff --git a/src/views/VisualizationView.tsx b/src/views/VisualizationView.tsx
index 07f9819..fa55183 100644
--- a/src/views/VisualizationView.tsx
+++ b/src/views/VisualizationView.tsx
@@ -553,7 +553,7 @@ export const ChartEditorFC: FC<{}> = function ChartEditorFC({}) {
             setVisTableTotalRowCount(table.virtual?.rowCount || table.rows.length);
             setDataVersion(versionId);
         }
-    }, [dataRequirements])
+    }, [dataRequirements, table.rows])
     
 
 

From f92c55fd27a9c7687f7116fca581956720c7864c Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Fri, 16 Jan 2026 17:52:35 -0800
Subject: [PATCH 04/21] redesign data loader

---
 src/views/RefreshDataDialog.tsx       |  487 +++++++
 src/views/UnifiedDataUploadDialog.tsx | 1720 +++++++++++++++++++++++++
 2 files changed, 2207 insertions(+)
 create mode 100644 src/views/RefreshDataDialog.tsx
 create mode 100644 src/views/UnifiedDataUploadDialog.tsx

diff --git a/src/views/RefreshDataDialog.tsx b/src/views/RefreshDataDialog.tsx
new file mode 100644
index 0000000..92fb32b
--- /dev/null
+++ b/src/views/RefreshDataDialog.tsx
@@ -0,0 +1,487 @@
+// Copyright (c) Microsoft Corporation.
+// Licensed under the MIT License.
+
+import React, { useState, useCallback, useRef } from 'react';
+import {
+    Dialog,
+    DialogTitle,
+    DialogContent,
+    DialogActions,
+    Button,
+    IconButton,
+    Typography,
+    Box,
+    TextField,
+    Tabs,
+    Tab,
+    LinearProgress,
+    Input,
+    Alert,
+    Tooltip,
+    Link,
+} from '@mui/material';
+import CloseIcon from '@mui/icons-material/Close';
+import { useDispatch, useSelector } from 'react-redux';
+import { AppDispatch } from '../app/store';
+import { DataFormulatorState, dfActions, dfSelectors, fetchFieldSemanticType } from '../app/dfSlice';
+import { DictTable } from '../components/ComponentType';
+import { createTableFromFromObjectArray, createTableFromText, loadTextDataWrapper, loadBinaryDataWrapper } from '../data/utils';
+import { getUrls } from '../app/utils';
+
+interface TabPanelProps {
+    children?: React.ReactNode;
+    index: number;
+    value: number;
+}
+
+function TabPanel(props: TabPanelProps) {
+    const { children, value, index, ...other } = props;
+    return (
+        <div
+            role="tabpanel"
+            hidden={value !== index}
+            id={`refresh-tabpanel-${index}`}
+            aria-labelledby={`refresh-tab-${index}`}
+            {...other}
+        >
+            {value === index && <Box sx={{ p: 2 }}>{children}</Box>}
+        </div>
+    );
+}
+
+export interface RefreshDataDialogProps {
+    open: boolean;
+    onClose: () => void;
+    table: DictTable;
+    onRefreshComplete: (newRows: any[]) => void;
+}
+
+export const RefreshDataDialog: React.FC<RefreshDataDialogProps> = ({
+    open,
+    onClose,
+    table,
+    onRefreshComplete,
+}) => {
+    const dispatch = useDispatch<AppDispatch>();
+    const [tabValue, setTabValue] = useState(0);
+    const [pasteContent, setPasteContent] = useState('');
+    const [urlContent, setUrlContent] = useState('');
+    const [isLoading, setIsLoading] = useState(false);
+    const [error, setError] = useState<string | null>(null);
+    const fileInputRef = useRef<HTMLInputElement>(null);
+    const serverConfig = useSelector((state: DataFormulatorState) => state.serverConfig);
+
+    // Constants for content size limits
+    const MAX_DISPLAY_LINES = 20;
+    const LARGE_CONTENT_THRESHOLD = 50000;
+    const MAX_CONTENT_SIZE = 2 * 1024 * 1024; // 2MB
+
+    const [displayContent, setDisplayContent] = useState('');
+    const [isLargeContent, setIsLargeContent] = useState(false);
+    const [showFullContent, setShowFullContent] = useState(false);
+    const [isOverSizeLimit, setIsOverSizeLimit] = useState(false);
+
+    const validateColumns = (newRows: any[]): { valid: boolean; message: string } => {
+        if (!newRows || newRows.length === 0) {
+            return { valid: false, message: 'No data found in the uploaded content.' };
+        }
+
+        const newColumns = Object.keys(newRows[0]).sort();
+        const existingColumns = [...table.names].sort();
+
+        if (newColumns.length !== existingColumns.length) {
+            return {
+                valid: false,
+                message: `Column count mismatch. Expected ${existingColumns.length} columns (${existingColumns.join(', ')}), but got ${newColumns.length} columns (${newColumns.join(', ')}).`,
+            };
+        }
+
+        const missingColumns = existingColumns.filter(col => !newColumns.includes(col));
+        const extraColumns = newColumns.filter(col => !existingColumns.includes(col));
+
+        if (missingColumns.length > 0 || extraColumns.length > 0) {
+            let message = 'Column names do not match.';
+            if (missingColumns.length > 0) {
+                message += ` Missing: ${missingColumns.join(', ')}.`;
+            }
+            if (extraColumns.length > 0) {
+                message += ` Unexpected: ${extraColumns.join(', ')}.`;
+            }
+            return { valid: false, message };
+        }
+
+        return { valid: true, message: '' };
+    };
+
+    const processAndValidateData = (newRows: any[]): boolean => {
+        const validation = validateColumns(newRows);
+        if (!validation.valid) {
+            setError(validation.message);
+            return false;
+        }
+        setError(null);
+        onRefreshComplete(newRows);
+        handleClose();
+        return true;
+    };
+
+    const handleClose = () => {
+        setPasteContent('');
+        setUrlContent('');
+        setDisplayContent('');
+        setError(null);
+        setIsLoading(false);
+        setIsLargeContent(false);
+        setShowFullContent(false);
+        setIsOverSizeLimit(false);
+        onClose();
+    };
+
+    const handleTabChange = (_event: React.SyntheticEvent, newValue: number) => {
+        setTabValue(newValue);
+        setError(null);
+    };
+
+    // Handle paste content change with optimization for large content
+    const handlePasteContentChange = useCallback((event: React.ChangeEvent<HTMLInputElement>) => {
+        const newContent = event.target.value;
+        setPasteContent(newContent);
+
+        const contentSizeBytes = new Blob([newContent]).size;
+        const isOverLimit = contentSizeBytes > MAX_CONTENT_SIZE;
+        setIsOverSizeLimit(isOverLimit);
+
+        const isLarge = newContent.length > LARGE_CONTENT_THRESHOLD;
+        setIsLargeContent(isLarge);
+
+        if (isLarge && !showFullContent) {
+            const lines = newContent.split('\n');
+            const previewLines = lines.slice(0, MAX_DISPLAY_LINES);
+            const preview = previewLines.join('\n') + (lines.length > MAX_DISPLAY_LINES ? '\n... (truncated for performance)' : '');
+            setDisplayContent(preview);
+        } else {
+            setDisplayContent(newContent);
+        }
+    }, [showFullContent]);
+
+    const toggleFullContent = useCallback(() => {
+        setShowFullContent(!showFullContent);
+        if (!showFullContent) {
+            setDisplayContent(pasteContent);
+        } else {
+            const lines = pasteContent.split('\n');
+            const previewLines = lines.slice(0, MAX_DISPLAY_LINES);
+            const preview = previewLines.join('\n') + (lines.length > MAX_DISPLAY_LINES ? '\n... (truncated for performance)' : '');
+            setDisplayContent(preview);
+        }
+    }, [showFullContent, pasteContent]);
+
+    // Handle paste submit
+    const handlePasteSubmit = () => {
+        if (!pasteContent.trim()) {
+            setError('Please paste some data.');
+            return;
+        }
+
+        setIsLoading(true);
+        try {
+            let newRows: any[] = [];
+            try {
+                const jsonContent = JSON.parse(pasteContent);
+                if (Array.isArray(jsonContent)) {
+                    newRows = jsonContent;
+                } else {
+                    setError('JSON content must be an array of objects.');
+                    setIsLoading(false);
+                    return;
+                }
+            } catch {
+                // Try parsing as CSV/TSV
+                const tempTable = createTableFromText('temp', pasteContent);
+                if (tempTable) {
+                    newRows = tempTable.rows;
+                } else {
+                    setError('Could not parse the pasted content as JSON or CSV/TSV.');
+                    setIsLoading(false);
+                    return;
+                }
+            }
+            processAndValidateData(newRows);
+        } catch (err) {
+            setError('Failed to parse the pasted content.');
+        } finally {
+            setIsLoading(false);
+        }
+    };
+
+    // Handle URL submit
+    const handleUrlSubmit = () => {
+        if (!urlContent.trim()) {
+            setError('Please enter a URL.');
+            return;
+        }
+
+        const hasValidSuffix = urlContent.endsWith('.csv') || urlContent.endsWith('.tsv') || urlContent.endsWith('.json');
+        if (!hasValidSuffix) {
+            setError('URL must point to a .csv, .tsv, or .json file.');
+            return;
+        }
+
+        setIsLoading(true);
+        fetch(urlContent)
+            .then(res => res.text())
+            .then(content => {
+                let newRows: any[] = [];
+                try {
+                    const jsonContent = JSON.parse(content);
+                    if (Array.isArray(jsonContent)) {
+                        newRows = jsonContent;
+                    } else {
+                        setError('JSON content must be an array of objects.');
+                        setIsLoading(false);
+                        return;
+                    }
+                } catch {
+                    const tempTable = createTableFromText('temp', content);
+                    if (tempTable) {
+                        newRows = tempTable.rows;
+                    } else {
+                        setError('Could not parse the URL content as JSON or CSV/TSV.');
+                        setIsLoading(false);
+                        return;
+                    }
+                }
+                processAndValidateData(newRows);
+            })
+            .catch(err => {
+                setError(`Failed to fetch data from URL: ${err.message}`);
+            })
+            .finally(() => {
+                setIsLoading(false);
+            });
+    };
+
+    // Handle file upload
+    const handleFileUpload = (event: React.ChangeEvent<HTMLInputElement>) => {
+        const files = event.target.files;
+        if (!files || files.length === 0) return;
+
+        const file = files[0];
+        setIsLoading(true);
+
+        if (file.type === 'text/csv' ||
+            file.type === 'text/tab-separated-values' ||
+            file.type === 'application/json' ||
+            file.name.endsWith('.csv') ||
+            file.name.endsWith('.tsv') ||
+            file.name.endsWith('.json')) {
+
+            const MAX_FILE_SIZE = 5 * 1024 * 1024;
+            if (file.size > MAX_FILE_SIZE) {
+                setError(`File is too large (${(file.size / (1024 * 1024)).toFixed(2)}MB). Maximum size is 5MB.`);
+                setIsLoading(false);
+                return;
+            }
+
+            file.text().then((text) => {
+                let newRows: any[] = [];
+                try {
+                    const jsonContent = JSON.parse(text);
+                    if (Array.isArray(jsonContent)) {
+                        newRows = jsonContent;
+                    } else {
+                        setError('JSON content must be an array of objects.');
+                        setIsLoading(false);
+                        return;
+                    }
+                } catch {
+                    const tempTable = loadTextDataWrapper('temp', text, file.type);
+                    if (tempTable) {
+                        newRows = tempTable.rows;
+                    } else {
+                        setError('Could not parse the file content.');
+                        setIsLoading(false);
+                        return;
+                    }
+                }
+                processAndValidateData(newRows);
+            }).catch(err => {
+                setError(`Failed to read file: ${err.message}`);
+            }).finally(() => {
+                setIsLoading(false);
+            });
+        } else if (file.type === 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet' ||
+            file.type === 'application/vnd.ms-excel' ||
+            file.name.endsWith('.xlsx') ||
+            file.name.endsWith('.xls')) {
+
+            const reader = new FileReader();
+            reader.onload = async (e) => {
+                const arrayBuffer = e.target?.result as ArrayBuffer;
+                if (arrayBuffer) {
+                    try {
+                        const tables = await loadBinaryDataWrapper('temp', arrayBuffer);
+                        if (tables.length > 0) {
+                            processAndValidateData(tables[0].rows);
+                        } else {
+                            setError('Failed to parse Excel file.');
+                        }
+                    } catch (err) {
+                        setError('Failed to parse Excel file.');
+                    }
+                }
+                setIsLoading(false);
+            };
+            reader.readAsArrayBuffer(file);
+        } else {
+            setError('Unsupported file format. Please use CSV, TSV, JSON, or Excel files.');
+            setIsLoading(false);
+        }
+
+        // Reset file input
+        if (fileInputRef.current) {
+            fileInputRef.current.value = '';
+        }
+    };
+
+    const hasValidUrlSuffix = urlContent.endsWith('.csv') || urlContent.endsWith('.tsv') || urlContent.endsWith('.json');
+
+    return (
+        <Dialog
+            open={open}
+            onClose={handleClose}
+            maxWidth="md"
+            fullWidth
+            sx={{ '& .MuiDialog-paper': { minHeight: 400 } }}
+        >
+            <DialogTitle sx={{ display: 'flex', alignItems: 'center' }}>
+                Refresh Data for "{table.displayId || table.id}"
+                <IconButton
+                    sx={{ marginLeft: 'auto' }}
+                    size="small"
+                    onClick={handleClose}
+                >
+                    <CloseIcon fontSize="inherit" />
+                </IconButton>
+            </DialogTitle>
+            <DialogContent dividers>
+                <Alert severity="info" sx={{ mb: 2, fontSize: 12 }}>
+                    Upload new data to replace the current table content. The new data must have the same columns: <strong>{table.names.join(', ')}</strong>
+                </Alert>
+
+                {error && (
+                    <Alert severity="error" sx={{ mb: 2, fontSize: 12 }}>
+                        {error}
+                    </Alert>
+                )}
+
+                {isLoading && <LinearProgress sx={{ mb: 2 }} />}
+
+                <Tabs value={tabValue} onChange={handleTabChange} sx={{ borderBottom: 1, borderColor: 'divider' }}>
+                    <Tab label="Paste Data" sx={{ textTransform: 'none', fontSize: 12 }} />
+                    <Tab label="Upload File" sx={{ textTransform: 'none', fontSize: 12 }} />
+                    <Tab label="From URL" sx={{ textTransform: 'none', fontSize: 12 }} />
+                </Tabs>
+
+                <TabPanel value={tabValue} index={0}>
+                    {isOverSizeLimit && (
+                        <Box sx={{ display: 'flex', alignItems: 'center', mb: 1, p: 1, backgroundColor: 'rgba(244, 67, 54, 0.1)', borderRadius: 1 }}>
+                            <Typography variant="caption" sx={{ color: 'error.main' }}>
+                                ⚠️ Content exceeds 2MB size limit.
+                            </Typography>
+                        </Box>
+                    )}
+                    {isLargeContent && !isOverSizeLimit && (
+                        <Box sx={{ display: 'flex', alignItems: 'center', mb: 1, p: 1, backgroundColor: 'rgba(255, 193, 7, 0.1)', borderRadius: 1 }}>
+                            <Typography variant="caption" sx={{ flex: 1 }}>
+                                Large content detected. {showFullContent ? 'Showing full content' : 'Showing preview'}
+                            </Typography>
+                            <Button size="small" variant="outlined" onClick={toggleFullContent} sx={{ textTransform: 'none' }}>
+                                {showFullContent ? 'Show Preview' : 'Show Full'}
+                            </Button>
+                        </Box>
+                    )}
+                    <TextField
+                        fullWidth
+                        multiline
+                        minRows={8}
+                        maxRows={15}
+                        placeholder="Paste CSV, TSV, or JSON data here..."
+                        value={displayContent}
+                        onChange={handlePasteContentChange}
+                        disabled={isLoading}
+                        sx={{ '& .MuiInputBase-input': { fontSize: 12, fontFamily: 'monospace' } }}
+                    />
+                </TabPanel>
+
+                <TabPanel value={tabValue} index={1}>
+                    <Box sx={{ display: 'flex', flexDirection: 'column', alignItems: 'center', gap: 2, py: 4 }}>
+                        <Typography variant="body2" color="text.secondary">
+                            Upload a CSV, TSV, JSON, or Excel file
+                        </Typography>
+                        <Input
+                            inputProps={{ accept: '.csv,.tsv,.json,.xlsx,.xls' }}
+                            type="file"
+                            sx={{ display: 'none' }}
+                            inputRef={fileInputRef}
+                            onChange={handleFileUpload}
+                        />
+                        <Tooltip
+                            title={serverConfig.DISABLE_FILE_UPLOAD ? (
+                                <Typography sx={{ fontSize: '11px' }}>
+                                    Install Data Formulator locally to enable file upload.
+                                </Typography>
+                            ) : ""}
+                        >
+                            <span>
+                                <Button
+                                    variant="contained"
+                                    disabled={isLoading || serverConfig.DISABLE_FILE_UPLOAD}
+                                    onClick={() => fileInputRef.current?.click()}
+                                >
+                                    Choose File
+                                </Button>
+                            </span>
+                        </Tooltip>
+                    </Box>
+                </TabPanel>
+
+                <TabPanel value={tabValue} index={2}>
+                    <TextField
+                        fullWidth
+                        placeholder="Enter URL to CSV, TSV, or JSON file"
+                        value={urlContent}
+                        onChange={(e) => setUrlContent(e.target.value.trim())}
+                        disabled={isLoading}
+                        error={urlContent !== '' && !hasValidUrlSuffix}
+                        helperText={urlContent !== '' && !hasValidUrlSuffix ? 'URL should link to a .csv, .tsv, or .json file' : ''}
+                        sx={{ '& .MuiInputBase-input': { fontSize: 12 } }}
+                    />
+                </TabPanel>
+            </DialogContent>
+            <DialogActions>
+                <Button onClick={handleClose} disabled={isLoading}>
+                    Cancel
+                </Button>
+                {tabValue === 0 && (
+                    <Button
+                        variant="contained"
+                        onClick={handlePasteSubmit}
+                        disabled={isLoading || !pasteContent.trim() || isOverSizeLimit}
+                    >
+                        Refresh Data
+                    </Button>
+                )}
+                {tabValue === 2 && (
+                    <Button
+                        variant="contained"
+                        onClick={handleUrlSubmit}
+                        disabled={isLoading || !urlContent.trim() || !hasValidUrlSuffix}
+                    >
+                        Refresh Data
+                    </Button>
+                )}
+            </DialogActions>
+        </Dialog>
+    );
+};
diff --git a/src/views/UnifiedDataUploadDialog.tsx b/src/views/UnifiedDataUploadDialog.tsx
new file mode 100644
index 0000000..5424840
--- /dev/null
+++ b/src/views/UnifiedDataUploadDialog.tsx
@@ -0,0 +1,1720 @@
+// Copyright (c) Microsoft Corporation.
+// Licensed under the MIT License.
+
+import * as React from 'react';
+import { useState, useCallback, useEffect, useRef } from 'react';
+import {
+    Box,
+    Button,
+    Dialog,
+    DialogContent,
+    DialogTitle,
+    DialogActions,
+    IconButton,
+    TextField,
+    Typography,
+    Tooltip,
+    LinearProgress,
+    Link,
+    Input,
+    alpha,
+    useTheme,
+} from '@mui/material';
+
+import CloseIcon from '@mui/icons-material/Close';
+import UploadFileIcon from '@mui/icons-material/UploadFile';
+import ContentPasteIcon from '@mui/icons-material/ContentPaste';
+import LinkIcon from '@mui/icons-material/Link';
+import StorageIcon from '@mui/icons-material/Storage';
+import ImageSearchIcon from '@mui/icons-material/ImageSearch';
+import ExploreIcon from '@mui/icons-material/Explore';
+import RestartAltIcon from '@mui/icons-material/RestartAlt';
+import RefreshIcon from '@mui/icons-material/Refresh';
+import DeleteIcon from '@mui/icons-material/Delete';
+import AnalyticsIcon from '@mui/icons-material/Analytics';
+import CleaningServicesIcon from '@mui/icons-material/CleaningServices';
+import SearchIcon from '@mui/icons-material/Search';
+import ArrowBackIcon from '@mui/icons-material/ArrowBack';
+import Paper from '@mui/material/Paper';
+import CircularProgress from '@mui/material/CircularProgress';
+
+import { useDispatch, useSelector } from 'react-redux';
+import { DataFormulatorState, dfActions, fetchFieldSemanticType } from '../app/dfSlice';
+import { AppDispatch } from '../app/store';
+import { DictTable } from '../components/ComponentType';
+import { createTableFromFromObjectArray, createTableFromText, loadTextDataWrapper, loadBinaryDataWrapper } from '../data/utils';
+import { DataLoadingChat } from './DataLoadingChat';
+import { DatasetSelectionView, DatasetMetadata } from './TableSelectionView';
+import { getUrls } from '../app/utils';
+import { CustomReactTable } from './ReactTable';
+import { Type } from '../data/types';
+import { TableStatisticsView, DataLoaderForm, handleDBDownload } from './DBTableManager';
+
+export type UploadTabType = 'menu' | 'upload' | 'paste' | 'url' | 'database' | 'extract' | 'explore';
+
+interface TabPanelProps {
+    children?: React.ReactNode;
+    index: UploadTabType;
+    value: UploadTabType;
+}
+
+function TabPanel(props: TabPanelProps) {
+    const { children, value, index, ...other } = props;
+
+    return (
+        <div
+            role="tabpanel"
+            hidden={value !== index}
+            id={`data-upload-tabpanel-${index}`}
+            aria-labelledby={`data-upload-tab-${index}`}
+            style={{ height: '100%', overflow: 'auto', boxSizing: 'border-box' }}
+            {...other}
+        >
+            {value === index && children}
+        </div>
+    );
+}
+
+// Data source menu card component
+interface DataSourceCardProps {
+    icon: React.ReactNode;
+    title: string;
+    description: string;
+    onClick: () => void;
+    disabled?: boolean;
+    disabledReason?: string;
+}
+
+interface PreviewPanelProps {
+    title: string;
+    loading: boolean;
+    error: string | null;
+    table?: DictTable | null;
+    tables?: DictTable[] | null;
+    emptyLabel: string;
+    meta?: string;
+    onRemoveTable?: (index: number) => void;
+}
+
+const PreviewPanel: React.FC<PreviewPanelProps> = ({
+    title,
+    loading,
+    error,
+    table,
+    tables,
+    emptyLabel,
+    meta,
+    onRemoveTable,
+}) => {
+    const previewTables = tables ?? (table ? [table] : null);
+    const [activeIndex, setActiveIndex] = useState(0);
+
+    useEffect(() => {
+        if (!previewTables || previewTables.length === 0) {
+            setActiveIndex(0);
+            return;
+        }
+        if (activeIndex > previewTables.length - 1) {
+            setActiveIndex(previewTables.length - 1);
+        }
+    }, [previewTables, activeIndex]);
+
+    const activeTable = previewTables && previewTables.length > 0 ? previewTables[activeIndex] : null;
+    return (
+        <Box
+            sx={{
+                border: '1px solid',
+                borderColor: 'divider',
+                borderRadius: 1,
+                p: 1,
+                display: 'flex',
+                flexDirection: 'column',
+                gap: 1,
+                minHeight: 120,
+            }}
+        >
+            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1 }}>
+                <Typography variant="body2" sx={{ fontWeight: 600 }}>
+                    {title}
+                </Typography>
+            </Box>
+
+            {loading && <LinearProgress />}
+
+            {error && (
+                <Typography variant="caption" color="error">
+                    {error}
+                </Typography>
+            )}
+
+            {!loading && !error && (!previewTables || previewTables.length === 0) && (
+                <Typography variant="caption" color="text.secondary">
+                    {emptyLabel}
+                </Typography>
+            )}
+
+            {previewTables && previewTables.length > 0 && (
+                <Box>
+                    {previewTables.length > 1 && (
+                        <Box
+                            sx={{
+                                display: 'flex',
+                                flexWrap: 'nowrap',
+                                gap: 0.25,
+                                mb: 0.5,
+                                pb: 0.25,
+                                overflowX: 'auto',
+                                overflowY: 'hidden',
+                                '&::-webkit-scrollbar': { height: 4 },
+                                '&::-webkit-scrollbar-thumb': {
+                                    backgroundColor: 'action.disabled',
+                                    borderRadius: 4,
+                                },
+                            }}
+                        >
+                            {previewTables.map((t, idx) => {
+                                const label = t.displayId || t.id;
+                                return (
+                                    <Tooltip key={`${t.id}-${idx}`} title={label} placement="top" arrow>
+                                        <Button
+                                            size="small"
+                                            variant="text"
+                                            onClick={() => setActiveIndex(idx)}
+                                            sx={{
+                                                textTransform: 'none',
+                                                minWidth: 'auto',
+                                                px: 1,
+                                                py: 0.5,
+                                                borderRadius: 1,
+                                                borderBottom: '2px solid',
+                                                borderBottomColor: idx === activeIndex ? (theme) => alpha(theme.palette.primary.main, 0.6) : 'transparent',
+                                                backgroundColor: idx === activeIndex ? (theme) => alpha(theme.palette.primary.main, 0.08) : 'transparent',
+                                                color: idx === activeIndex ? 'text.primary' : 'text.secondary',
+                                                fontWeight: idx === activeIndex ? 600 : 500,
+                                                fontSize: 12,
+                                                lineHeight: 1.2,
+                                                maxWidth: 160,
+                                                overflow: 'hidden',
+                                                '&:hover': {
+                                                    backgroundColor: (theme) => alpha(theme.palette.primary.main, 0.06),
+                                                },
+                                                '& .MuiButton-label': {
+                                                    overflow: 'hidden',
+                                                },
+                                            }}
+                                        >
+                                            <Box
+                                                component="span"
+                                                sx={{
+                                                    display: 'inline-block',
+                                                    maxWidth: 140,
+                                                    overflow: 'hidden',
+                                                    textOverflow: 'ellipsis',
+                                                    whiteSpace: 'nowrap',
+                                                }}
+                                            >
+                                                {label}
+                                            </Box>
+                                        </Button>
+                                    </Tooltip>
+                                );
+                            })}
+                        </Box>
+                    )}
+
+                    {activeTable && (
+                        <Box sx={{ pb: 1 }}>
+                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, mb: 0.5 }}>
+                                <Typography variant="caption" color="text.secondary">
+                                    {activeTable.rows.length} rows × {activeTable.names.length} columns
+                                    {previewTables && previewTables.length === 1
+                                        ? ` • ${activeTable.displayId || activeTable.id}`
+                                        : ''}
+                                </Typography>
+                                {onRemoveTable && previewTables.length > 1 && (
+                                    <IconButton
+                                        size="small"
+                                        color="error"
+                                        onClick={() => onRemoveTable(activeIndex)}
+                                        sx={{ ml: 'auto' }}
+                                    >
+                                        <DeleteIcon fontSize="small" />
+                                    </IconButton>
+                                )}
+                            </Box>
+                            <CustomReactTable
+                                rows={activeTable.rows.slice(0, 12)}
+                                columnDefs={activeTable.names.map(name => ({
+                                    id: name,
+                                    label: name,
+                                    minWidth: 60,
+                                }))}
+                                rowsPerPageNum={-1}
+                                compact={true}
+                                isIncompleteTable={activeTable.rows.length > 12}
+                                maxHeight={200}
+                            />
+                        </Box>
+                    )}
+                </Box>
+            )}
+        </Box>
+    );
+};
+
+const DataSourceCard: React.FC<DataSourceCardProps> = ({ 
+    icon, 
+    title, 
+    description, 
+    onClick, 
+    disabled = false,
+    disabledReason 
+}) => {
+    const theme = useTheme();
+    
+    const card = (
+        <Paper
+            elevation={0}
+            onClick={disabled ? undefined : onClick}
+            sx={{
+                p: 1.5,
+                cursor: disabled ? 'not-allowed' : 'pointer',
+                border: '1px solid',
+                borderColor: 'divider',
+                borderRadius: 1,
+                opacity: disabled ? 0.5 : 1,
+                transition: 'all 0.15s ease',
+                display: 'flex',
+                alignItems: 'center',
+                gap: 1.5,
+                '&:hover': disabled ? {} : {
+                    borderColor: 'primary.main',
+                    backgroundColor: alpha(theme.palette.primary.main, 0.04),
+                }
+            }}
+        >
+            <Box sx={{ 
+                color: disabled ? 'text.disabled' : 'primary.main',
+                display: 'flex',
+                alignItems: 'center',
+                justifyContent: 'center',
+                width: 32,
+                height: 32,
+                borderRadius: 1,
+                backgroundColor: alpha(theme.palette.primary.main, 0.08),
+                flexShrink: 0,
+                '& .MuiSvgIcon-root': { fontSize: 18 }
+            }}>
+                {icon}
+            </Box>
+            <Box sx={{ flex: 1, minWidth: 0 }}>
+                <Typography 
+                    variant="body2" 
+                    sx={{ 
+                        fontWeight: 500,
+                        color: disabled ? 'text.disabled' : 'text.primary',
+                    }}
+                >
+                    {title}
+                </Typography>
+                <Typography
+                    variant="caption"
+                    sx={{
+                        color: disabled ? 'text.disabled' : 'text.secondary',
+                        display: '-webkit-box',
+                        WebkitLineClamp: 2,
+                        WebkitBoxOrient: 'vertical',
+                        overflow: 'hidden',
+                        lineHeight: 1.3,
+                        mt: 0.25,
+                    }}
+                >
+                    {description}
+                </Typography>
+            </Box>
+        </Paper>
+    );
+
+    if (disabled && disabledReason) {
+        return (
+            <Tooltip title={disabledReason} placement="top">
+                <span>{card}</span>
+            </Tooltip>
+        );
+    }
+
+    return card;
+};
+
+const getUniqueTableName = (baseName: string, existingNames: Set<string>): string => {
+    let uniqueName = baseName;
+    let counter = 1;
+    while (existingNames.has(uniqueName)) {
+        uniqueName = `${baseName}_${counter}`;
+        counter++;
+    }
+    return uniqueName;
+};
+
+export interface UnifiedDataUploadDialogProps {
+    open: boolean;
+    onClose: () => void;
+    initialTab?: UploadTabType;
+}
+
+export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = ({
+    open,
+    onClose,
+    initialTab = 'menu',
+}) => {
+    const theme = useTheme();
+    const dispatch = useDispatch<AppDispatch>();
+    const existingTables = useSelector((state: DataFormulatorState) => state.tables);
+    const serverConfig = useSelector((state: DataFormulatorState) => state.serverConfig);
+    const dataCleanBlocks = useSelector((state: DataFormulatorState) => state.dataCleanBlocks);
+    const existingNames = new Set(existingTables.map(t => t.id));
+
+    const [activeTab, setActiveTab] = useState<UploadTabType>(initialTab === 'menu' ? 'menu' : initialTab);
+    const fileInputRef = useRef<HTMLInputElement>(null);
+
+    // Paste tab state
+    const [pasteContent, setPasteContent] = useState<string>("");
+    const [displayContent, setDisplayContent] = useState<string>("");
+    const [isLargeContent, setIsLargeContent] = useState<boolean>(false);
+    const [showFullContent, setShowFullContent] = useState<boolean>(false);
+    const [isOverSizeLimit, setIsOverSizeLimit] = useState<boolean>(false);
+    
+    // URL tab state
+    const [tableURL, setTableURL] = useState<string>("");
+    const [urlPreviewTable, setUrlPreviewTable] = useState<DictTable | null>(null);
+    const [urlPreviewLoading, setUrlPreviewLoading] = useState<boolean>(false);
+    const [urlPreviewError, setUrlPreviewError] = useState<string | null>(null);
+    const [urlPreviewUrl, setUrlPreviewUrl] = useState<string>("");
+
+    // File preview state
+    const [filePreviewTables, setFilePreviewTables] = useState<DictTable[] | null>(null);
+    const [filePreviewLoading, setFilePreviewLoading] = useState<boolean>(false);
+    const [filePreviewError, setFilePreviewError] = useState<string | null>(null);
+    const [filePreviewFiles, setFilePreviewFiles] = useState<File[]>([]);
+
+    // Sample datasets state
+    const [datasetPreviews, setDatasetPreviews] = useState<DatasetMetadata[]>([]);
+
+    // Constants
+    const MAX_DISPLAY_LINES = 20;
+    const LARGE_CONTENT_THRESHOLD = 50000;
+    const MAX_CONTENT_SIZE = 2 * 1024 * 1024;
+
+    // Update active tab when initialTab changes
+    useEffect(() => {
+        if (open) {
+            setActiveTab(initialTab === 'menu' ? 'menu' : initialTab);
+        }
+    }, [initialTab, open]);
+
+    useEffect(() => {
+        if (tableURL !== urlPreviewUrl) {
+            setUrlPreviewTable(null);
+            setUrlPreviewError(null);
+        }
+    }, [tableURL, urlPreviewUrl]);
+
+    // Load sample datasets
+    useEffect(() => {
+        if (open && activeTab === 'explore') {
+            fetch(`${getUrls().EXAMPLE_DATASETS}`)
+                .then((response) => response.json())
+                .then((result) => {
+                    let datasets: DatasetMetadata[] = result.map((info: any) => {
+                        let tables = info["tables"].map((table: any) => {
+                            if (table["format"] == "json") {
+                                return {
+                                    table_name: table["name"],
+                                    url: table["url"],
+                                    format: table["format"],
+                                    sample: table["sample"],
+                                }
+                            }
+                            else if (table["format"] == "csv" || table["format"] == "tsv") {
+                                const delimiter = table["format"] === "csv" ? "," : "\t";
+                                const rows = table["sample"]
+                                    .split("\n")
+                                    .map((row: string) => row.split(delimiter));
+                                
+                                if (rows.length > 0) {
+                                    const headers = rows[0];
+                                    const dataRows = rows.slice(1);
+                                    const sampleData = dataRows.map((row: string[]) => {
+                                        const obj: any = {};
+                                        headers.forEach((header: string, index: number) => {
+                                            obj[header] = row[index] || '';
+                                        });
+                                        return obj;
+                                    });
+                                    
+                                    return {
+                                        table_name: table["name"],
+                                        url: table["url"],
+                                        format: table["format"],
+                                        sample: sampleData,
+                                    };
+                                }
+                                
+                                return {
+                                    table_name: table["name"],
+                                    url: table["url"],
+                                    format: table["format"],
+                                    sample: [],
+                                };
+                            }
+                        })
+                        return { tables: tables, name: info["name"], description: info["description"], source: info["source"] }
+                    }).filter((t: DatasetMetadata | undefined) => t != undefined);
+                    setDatasetPreviews(datasets);
+                });
+        }
+    }, [open, activeTab]);
+
+    const handleClose = useCallback(() => {
+        // Reset state when closing
+        setPasteContent("");
+        setDisplayContent("");
+        setIsLargeContent(false);
+        setIsOverSizeLimit(false);
+        setShowFullContent(false);
+        setTableURL("");
+        setUrlPreviewTable(null);
+        setUrlPreviewLoading(false);
+        setUrlPreviewError(null);
+        setUrlPreviewUrl("");
+        setFilePreviewTables(null);
+        setFilePreviewLoading(false);
+        setFilePreviewError(null);
+        setFilePreviewFiles([]);
+        onClose();
+    }, [onClose]);
+
+    // File upload handler
+    const handleFileUpload = (event: React.ChangeEvent<HTMLInputElement>): void => {
+        const files = event.target.files;
+
+        if (files && files.length > 0) {
+            const selectedFiles = Array.from(files);
+            setFilePreviewFiles(selectedFiles);
+            setFilePreviewError(null);
+            setFilePreviewTables(null);
+            setFilePreviewLoading(true);
+
+            const MAX_FILE_SIZE = 5 * 1024 * 1024;
+            const previewTables: DictTable[] = [];
+            const errors: string[] = [];
+
+            const processFiles = async () => {
+                for (const file of selectedFiles) {
+                    const uniqueName = getUniqueTableName(file.name, existingNames);
+                    const isTextFile = file.type === 'text/csv' || 
+                        file.type === 'text/tab-separated-values' || 
+                        file.type === 'application/json' ||
+                        file.name.endsWith('.csv') || 
+                        file.name.endsWith('.tsv') || 
+                        file.name.endsWith('.json');
+                    const isExcelFile = file.type === 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet' ||
+                        file.type === 'application/vnd.ms-excel' ||
+                        file.name.endsWith('.xlsx') || 
+                        file.name.endsWith('.xls');
+
+                    if (file.size > MAX_FILE_SIZE && isTextFile) {
+                        errors.push(`File ${file.name} is too large (${(file.size / (1024 * 1024)).toFixed(2)}MB). Use Database for large files.`);
+                        continue;
+                    }
+
+                    if (isTextFile) {
+                        try {
+                            const text = await file.text();
+                            const table = loadTextDataWrapper(uniqueName, text, file.type);
+                            if (table) {
+                                previewTables.push(table);
+                            } else {
+                                errors.push(`Failed to parse ${file.name}.`);
+                            }
+                        } catch {
+                            errors.push(`Failed to read ${file.name}.`);
+                        }
+                        continue;
+                    }
+
+                    if (isExcelFile) {
+                        try {
+                            const arrayBuffer = await file.arrayBuffer();
+                            const tables = await loadBinaryDataWrapper(uniqueName, arrayBuffer);
+                            if (tables.length > 0) {
+                                previewTables.push(...tables);
+                            } else {
+                                errors.push(`Failed to parse Excel file ${file.name}.`);
+                            }
+                        } catch {
+                            errors.push(`Failed to parse Excel file ${file.name}.`);
+                        }
+                        continue;
+                    }
+
+                    errors.push(`Unsupported file format: ${file.name}.`);
+                }
+
+                setFilePreviewTables(previewTables.length > 0 ? previewTables : null);
+                setFilePreviewError(errors.length > 0 ? errors.join(' ') : null);
+                setFilePreviewLoading(false);
+            };
+
+            processFiles();
+        }
+        if (fileInputRef.current) {
+            fileInputRef.current.value = '';
+        }
+    };
+
+    const handleFileLoadSubmit = (): void => {
+        if (!filePreviewTables || filePreviewTables.length === 0) {
+            return;
+        }
+        for (let table of filePreviewTables) {
+            dispatch(dfActions.loadTable(table));
+            dispatch(fetchFieldSemanticType(table));
+        }
+        handleClose();
+    };
+
+    const handleRemoveFilePreviewTable = (index: number): void => {
+        setFilePreviewTables((prev) => {
+            if (!prev) return prev;
+            const next = prev.filter((_, i) => i !== index);
+            return next.length > 0 ? next : null;
+        });
+    };
+
+    // Paste content handler
+    const handleContentChange = useCallback((event: React.ChangeEvent<HTMLInputElement>) => {
+        const newContent = event.target.value;
+        setPasteContent(newContent);
+        
+        const contentSizeBytes = new Blob([newContent]).size;
+        const isOverLimit = contentSizeBytes > MAX_CONTENT_SIZE;
+        setIsOverSizeLimit(isOverLimit);
+        
+        const isLarge = newContent.length > LARGE_CONTENT_THRESHOLD;
+        setIsLargeContent(isLarge);
+        
+        if (isLarge && !showFullContent) {
+            const lines = newContent.split('\n');
+            const previewLines = lines.slice(0, MAX_DISPLAY_LINES);
+            const preview = previewLines.join('\n') + (lines.length > MAX_DISPLAY_LINES ? '\n... (truncated for performance)' : '');
+            setDisplayContent(preview);
+        } else {
+            setDisplayContent(newContent);
+        }
+    }, [showFullContent, MAX_CONTENT_SIZE]);
+
+    const toggleFullContent = useCallback(() => {
+        setShowFullContent(!showFullContent);
+        if (!showFullContent) {
+            setDisplayContent(pasteContent);
+        } else {
+            const lines = pasteContent.split('\n');
+            const previewLines = lines.slice(0, MAX_DISPLAY_LINES);
+            const preview = previewLines.join('\n') + (lines.length > MAX_DISPLAY_LINES ? '\n... (truncated for performance)' : '');
+            setDisplayContent(preview);
+        }
+    }, [showFullContent, pasteContent]);
+
+    const handlePasteSubmit = (): void => {
+        let table: undefined | DictTable = undefined;
+        
+        const defaultName = (() => {
+            const hashStr = pasteContent.substring(0, 100) + Date.now();
+            const hashCode = hashStr.split('').reduce((acc, char) => {
+                return ((acc << 5) - acc) + char.charCodeAt(0) | 0;
+            }, 0);
+            const shortHash = Math.abs(hashCode).toString(36).substring(0, 4);
+            return `data-${shortHash}`;
+        })();
+
+        const uniqueName = getUniqueTableName(defaultName, existingNames);
+
+        try {
+            let content = JSON.parse(pasteContent);
+            table = createTableFromFromObjectArray(uniqueName, content, true);
+        } catch (error) {
+            table = createTableFromText(uniqueName, pasteContent);
+        }
+        if (table) {
+            dispatch(dfActions.loadTable(table));
+            dispatch(fetchFieldSemanticType(table));
+            handleClose();
+        }
+    };
+
+    // URL submit handler
+    const handleURLSubmit = (): void => {
+        if (urlPreviewTable && urlPreviewUrl === tableURL) {
+            dispatch(dfActions.loadTable(urlPreviewTable));
+            dispatch(fetchFieldSemanticType(urlPreviewTable));
+            handleClose();
+        }
+    };
+
+    const handleURLPreview = (): void => {
+        setUrlPreviewLoading(true);
+        setUrlPreviewError(null);
+        setUrlPreviewTable(null);
+
+        let parts = tableURL.split('/');
+        const baseName = parts[parts.length - 1] || 'dataset';
+        const tableName = getUniqueTableName(baseName, existingNames);
+
+        fetch(tableURL)
+            .then(res => res.text())
+            .then(content => {
+                let table: undefined | DictTable = undefined;
+                try {
+                    let jsonContent = JSON.parse(content);
+                    if (!Array.isArray(jsonContent)) {
+                        throw new Error('JSON content must be an array of objects.');
+                    }
+                    table = createTableFromFromObjectArray(tableName, jsonContent, true);
+                } catch (error) {
+                    table = createTableFromText(tableName, content);
+                }
+
+                if (table) {
+                    setUrlPreviewTable(table);
+                    setUrlPreviewUrl(tableURL);
+                } else {
+                    setUrlPreviewError('Unable to parse data from the provided URL.');
+                }
+            })
+            .catch(() => {
+                setUrlPreviewError('Failed to fetch data from the URL.');
+            })
+            .finally(() => {
+                setUrlPreviewLoading(false);
+            });
+    };
+
+    const hasValidUrlSuffix = tableURL.endsWith('.csv') || tableURL.endsWith('.tsv') || tableURL.endsWith(".json");
+    const hasMultipleFileTables = (filePreviewTables?.length || 0) > 1;
+    const showFilePreview = filePreviewLoading || !!filePreviewError || (filePreviewTables && filePreviewTables.length > 0);
+    const showUrlPreview = urlPreviewLoading || !!urlPreviewError || (urlPreviewTable && urlPreviewUrl === tableURL);
+    const hasPasteContent = pasteContent.trim() !== '';
+
+    // Data source configurations for the menu
+    const dataSourceConfig = [
+        { 
+            value: 'explore' as UploadTabType, 
+            title: 'Sample Datasets', 
+            description: 'Explore and load curated example datasets',
+            icon: <ExploreIcon />, 
+            disabled: false 
+        },
+        { 
+            value: 'upload' as UploadTabType, 
+            title: 'Upload File', 
+            description: 'Upload CSV, TSV, JSON, or Excel files from your computer',
+            icon: <UploadFileIcon />, 
+            disabled: serverConfig.DISABLE_FILE_UPLOAD,
+            disabledReason: 'File upload is disabled in this environment'
+        },
+        { 
+            value: 'paste' as UploadTabType, 
+            title: 'Paste Data', 
+            description: 'Paste tabular data directly from clipboard',
+            icon: <ContentPasteIcon />, 
+            disabled: false 
+        },
+        { 
+            value: 'url' as UploadTabType, 
+            title: 'From URL', 
+            description: 'Load data from a web URL (CSV, TSV, or JSON)',
+            icon: <LinkIcon />, 
+            disabled: false 
+        },
+        { 
+            value: 'database' as UploadTabType, 
+            title: 'Database', 
+            description: 'Connect to databases or data services',
+            icon: <StorageIcon />, 
+            disabled: serverConfig.DISABLE_DATABASE,
+            disabledReason: 'Database connection is disabled in this environment'
+        },
+        { 
+            value: 'extract' as UploadTabType, 
+            title: 'Extract from Documents', 
+            description: 'Extract tables from images, PDFs, or documents using AI',
+            icon: <ImageSearchIcon />, 
+            disabled: false 
+        },
+    ];
+
+    // Get current tab title for header
+    const getCurrentTabTitle = () => {
+        const tab = dataSourceConfig.find(t => t.value === activeTab);
+        return tab?.title || 'Add Data';
+    };
+
+    return (
+        <Dialog
+            open={open}
+            onClose={handleClose}
+            maxWidth={false}
+            sx={{ 
+                '& .MuiDialog-paper': { 
+                    width: activeTab === 'menu' ? 720 : 1100,
+                    maxWidth: '95vw',
+                    height: activeTab === 'menu' ? 'auto' : 700, 
+                    maxHeight: '90vh',
+                    display: 'flex',
+                    flexDirection: 'column',
+                    transition: 'width 0.2s ease',
+                } 
+            }}
+        >
+            <DialogTitle sx={{ display: 'flex', alignItems: 'center', gap: 1, pb: 1 }}>
+                {activeTab !== 'menu' && (
+                    <IconButton
+                        size="small"
+                        onClick={() => setActiveTab('menu')}
+                        sx={{ mr: 0.5 }}
+                    >
+                        <ArrowBackIcon fontSize="small" />
+                    </IconButton>
+                )}
+                <Typography variant="h6" component="span">
+                    {activeTab === 'menu' ? 'Add Data' : getCurrentTabTitle()}
+                </Typography>
+                {activeTab === 'extract' && dataCleanBlocks.length > 0 && (
+                    <Tooltip title="Reset extraction">
+                        <IconButton 
+                            size="small" 
+                            color='warning' 
+                            sx={{
+                                '&:hover': { 
+                                    transform: 'rotate(180deg)', 
+                                    transition: 'transform 0.4s cubic-bezier(0.4, 0, 0.2, 1)' 
+                                } 
+                            }} 
+                            onClick={() => dispatch(dfActions.resetDataCleanBlocks())}
+                        >
+                            <RestartAltIcon fontSize="small" />
+                        </IconButton>
+                    </Tooltip>
+                )}
+                <IconButton
+                    sx={{ marginLeft: 'auto' }}
+                    size="small"
+                    onClick={handleClose}
+                    aria-label="close"
+                >
+                    <CloseIcon fontSize="small" />
+                </IconButton>
+            </DialogTitle>
+
+            <DialogContent sx={{ flex: 1, overflow: 'hidden', p: 0 }}>
+                {/* Main Menu */}
+                <TabPanel value={activeTab} index="menu">
+                    <Box sx={{ p: 2 }}>
+                        <Box sx={{ 
+                            display: 'grid', 
+                            gridTemplateColumns: 'repeat(2, minmax(0, 1fr))',
+                            gap: 1,
+                        }}>
+                            {dataSourceConfig.map((source) => (
+                                <DataSourceCard
+                                    key={source.value}
+                                    icon={source.icon}
+                                    title={source.title}
+                                    description={source.description}
+                                    onClick={() => setActiveTab(source.value)}
+                                    disabled={source.disabled}
+                                    disabledReason={source.disabledReason}
+                                />
+                            ))}
+                        </Box>
+                    </Box>
+                </TabPanel>
+
+                {/* Upload File Tab */}
+                <TabPanel value={activeTab} index="upload">
+                    <Box sx={{
+                        display: 'flex',
+                        flexDirection: 'column',
+                        height: '100%',
+                        boxSizing: 'border-box',
+                        gap: 2,
+                        p: 2,
+                        justifyContent: 'center',
+                    }}>
+                        <Box sx={{ width: '100%', maxWidth: 760, alignSelf: 'center', display: 'flex', flexDirection: 'column', gap: 2 }}>
+                        <Input
+                            inputProps={{ 
+                                accept: '.csv,.tsv,.json,.xlsx,.xls',
+                                multiple: true,
+                            }}
+                            id="unified-upload-data-file"
+                            type="file"
+                            sx={{ display: 'none' }}
+                            inputRef={fileInputRef}
+                            onChange={handleFileUpload}
+                        />
+                        {serverConfig.DISABLE_FILE_UPLOAD ? (
+                            <Box sx={{ textAlign: 'center', py: 4 }}>
+                                <Typography color="text.secondary" sx={{ mb: 2 }}>
+                                    File upload is disabled in this environment.
+                                </Typography>
+                                <Typography variant="body2" color="text.secondary">
+                                    Install Data Formulator locally to enable file upload. <br />
+                                    <Link 
+                                        href="https://github.com/microsoft/data-formulator" 
+                                        target="_blank" 
+                                        rel="noopener noreferrer"
+                                    >
+                                        https://github.com/microsoft/data-formulator
+                                    </Link>
+                                </Typography>
+                            </Box>
+                        ) : (
+                            <Box
+                                sx={{
+                                    border: '2px dashed',
+                                    borderColor: 'divider',
+                                    borderRadius: 2,
+                                    p: 3,
+                                    textAlign: 'center',
+                                    cursor: 'pointer',
+                                    transition: 'all 0.2s',
+                                    '&:hover': {
+                                        borderColor: 'primary.main',
+                                        backgroundColor: alpha(theme.palette.primary.main, 0.04),
+                                    }
+                                }}
+                                onClick={() => fileInputRef.current?.click()}
+                            >
+                                <UploadFileIcon sx={{ fontSize: 36, color: 'text.secondary', mb: 1 }} />
+                                <Typography variant="subtitle1" gutterBottom>
+                                    Click to upload or drag and drop
+                                </Typography>
+                                <Typography variant="body2" color="text.secondary">
+                                    Supported formats: CSV, TSV, JSON, Excel (xlsx, xls)
+                                </Typography>
+                                <Typography variant="caption" color="text.secondary" sx={{ mt: 1, display: 'block' }}>
+                                    Maximum file size: 5MB (use Database tab for larger files)
+                                </Typography>
+                            </Box>
+                        )}
+
+                        {showFilePreview && (
+                            <PreviewPanel
+                                title="Preview"
+                                loading={filePreviewLoading}
+                                error={filePreviewError}
+                                tables={filePreviewTables}
+                                emptyLabel={serverConfig.DISABLE_FILE_UPLOAD ? 'File upload is disabled.' : 'Select a file to preview.'}
+                                meta={filePreviewTables && filePreviewTables.length > 0 ? `${filePreviewTables.length} table${filePreviewTables.length > 1 ? 's' : ''} previewed${hasMultipleFileTables ? ' • Multiple sheets detected' : ''}` : undefined}
+                                onRemoveTable={handleRemoveFilePreviewTable}
+                            />
+                        )}
+
+                        {filePreviewTables && filePreviewTables.length > 0 && (
+                            <Box sx={{ display: 'flex', justifyContent: 'flex-end', gap: 1 }}>
+                                <Button
+                                    variant="contained"
+                                    size="small"
+                                    onClick={handleFileLoadSubmit}
+                                    disabled={serverConfig.DISABLE_FILE_UPLOAD || filePreviewLoading}
+                                    sx={{ textTransform: 'none' }}
+                                >
+                                    {hasMultipleFileTables ? 'Load Files' : 'Load File'}
+                                </Button>
+                            </Box>
+                        )}
+                        </Box>
+                    </Box>
+                </TabPanel>
+
+                {/* URL Tab */}
+                <TabPanel value={activeTab} index="url">
+                    <Box sx={{
+                        display: 'flex',
+                        flexDirection: 'column',
+                        height: '100%',
+                        boxSizing: 'border-box',
+                        gap: 2,
+                        p: 2,
+                        justifyContent: 'center',
+                    }}>
+                        <Box sx={{ width: '100%', maxWidth: 760, alignSelf: 'center', display: 'flex', flexDirection: 'column', gap: 2 }}>
+                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1 }}>
+                                <TextField
+                                    fullWidth
+                                    label="Data URL"
+                                    placeholder="https://example.com/data.csv"
+                                    value={tableURL}
+                                    onChange={(e) => setTableURL(e.target.value.trim())}
+                                    error={tableURL !== "" && !hasValidUrlSuffix}
+                                    size="small"
+                                />
+                                <Button
+                                    variant="outlined"
+                                    size="small"
+                                    onClick={handleURLPreview}
+                                    disabled={!hasValidUrlSuffix || urlPreviewLoading}
+                                    sx={{ textTransform: 'none', whiteSpace: 'nowrap' }}
+                                >
+                                    Preview
+                                </Button>
+                            </Box>
+
+                            {tableURL !== "" && !hasValidUrlSuffix && (
+                                <Typography variant="caption" color="error">
+                                    URL should link to a .csv, .tsv, or .json file.
+                                </Typography>
+                            )}
+
+                            <Typography variant="caption" color="text.secondary">
+                                Supported URLs: direct links to .csv, .tsv, or .json files.
+                            </Typography>
+
+                            {showUrlPreview && (
+                                <PreviewPanel
+                                    title="Preview"
+                                    loading={urlPreviewLoading}
+                                    error={urlPreviewError}
+                                    table={urlPreviewUrl === tableURL ? urlPreviewTable : null}
+                                    emptyLabel="Click Preview to fetch a sample."
+                                    meta={urlPreviewTable && urlPreviewUrl === tableURL ? `${urlPreviewTable.rows.length} rows × ${urlPreviewTable.names.length} columns` : undefined}
+                                />
+                            )}
+
+                            {urlPreviewTable && urlPreviewUrl === tableURL && (
+                                <Box sx={{ display: 'flex', justifyContent: 'center', gap: 1 }}>
+                                    <Button
+                                        variant="contained"
+                                        size="small"
+                                        onClick={handleURLSubmit}
+                                        disabled={!hasValidUrlSuffix}
+                                        sx={{ textTransform: 'none' }}
+                                    >
+                                        Load from URL
+                                    </Button>
+                                </Box>
+                            )}
+                        </Box>
+                    </Box>
+                </TabPanel>
+
+                {/* Paste Data Tab */}
+                <TabPanel value={activeTab} index="paste">
+                    <Box sx={{
+                        display: 'flex',
+                        flexDirection: 'column',
+                        height: '100%',
+                        boxSizing: 'border-box',
+                        p: 2,
+                        justifyContent: hasPasteContent ? 'flex-start' : 'center',
+                        alignItems: hasPasteContent ? 'stretch' : 'center',
+                    }}>
+                        {isOverSizeLimit && (
+                            <Box sx={{ 
+                                display: 'flex', 
+                                alignItems: 'center', 
+                                mb: 1, 
+                                p: 1, 
+                                backgroundColor: 'rgba(244, 67, 54, 0.1)', 
+                                borderRadius: 1, 
+                                border: '1px solid rgba(244, 67, 54, 0.3)' 
+                            }}>
+                                <Typography variant="caption" sx={{ flex: 1, color: 'error.main', fontWeight: 500 }}>
+                                    ⚠️ Content exceeds {(MAX_CONTENT_SIZE / (1024 * 1024)).toFixed(0)}MB size limit. 
+                                    Current size: {(new Blob([pasteContent]).size / (1024 * 1024)).toFixed(2)}MB. 
+                                    Please use the DATABASE tab for large datasets.
+                                </Typography>
+                            </Box>
+                        )}
+                        
+                        {isLargeContent && !isOverSizeLimit && (
+                            <Box sx={{ 
+                                display: 'flex', 
+                                alignItems: 'center', 
+                                mb: 1, 
+                                p: 1, 
+                                backgroundColor: 'rgba(255, 193, 7, 0.1)', 
+                                borderRadius: 1 
+                            }}>
+                                <Typography variant="caption" sx={{ flex: 1 }}>
+                                    Large content detected ({Math.round(pasteContent.length / 1000)}KB). 
+                                    {showFullContent ? 'Showing full content (may be slow)' : 'Showing preview for performance'}
+                                </Typography>
+                                <Button 
+                                    size="small" 
+                                    variant="outlined" 
+                                    onClick={toggleFullContent}
+                                    sx={{ textTransform: 'none', minWidth: 'auto' }}
+                                >
+                                    {showFullContent ? 'Show Preview' : 'Show Full'}
+                                </Button>
+                            </Box>
+                        )}
+
+                        <Box sx={{ width: '100%', maxWidth: hasPasteContent ? 'none' : 720 }}>
+                            <TextField
+                                autoFocus
+                                multiline
+                                fullWidth
+                                value={displayContent}
+                                onChange={handleContentChange}
+                                placeholder="Paste your data here (CSV, TSV, or JSON format)"
+                                sx={{
+                                    flex: hasPasteContent ? 1 : 'none',
+                                    '& .MuiInputBase-root': {
+                                        height: hasPasteContent ? '100%' : 220,
+                                        alignItems: 'flex-start',
+                                    },
+                                    '& .MuiInputBase-input': {
+                                        fontSize: 12,
+                                        fontFamily: 'monospace',
+                                        height: hasPasteContent ? '100% !important' : 'auto !important',
+                                        overflow: 'auto !important',
+                                    }
+                                }}
+                            />
+                        </Box>
+
+                        <Box sx={{ display: 'flex', justifyContent: 'flex-end', mt: 2, gap: 1 }}>
+                            <Button
+                                variant="contained"
+                                onClick={handlePasteSubmit}
+                                disabled={pasteContent.trim() === '' || isOverSizeLimit}
+                                sx={{ textTransform: 'none' }}
+                            >
+                                Upload Data
+                            </Button>
+                        </Box>
+                    </Box>
+                </TabPanel>
+
+                {/* Database Tab */}
+                <TabPanel value={activeTab} index="database">
+                    {serverConfig.DISABLE_DATABASE ? (
+                        <Box sx={{ textAlign: 'center', py: 4, px: 2 }}>
+                            <Typography color="text.secondary" sx={{ mb: 2 }}>
+                                Database connection is disabled in this environment.
+                            </Typography>
+                            <Typography variant="body2" color="text.secondary">
+                                Install Data Formulator locally to use database features. <br />
+                                <Link 
+                                    href="https://github.com/microsoft/data-formulator" 
+                                    target="_blank" 
+                                    rel="noopener noreferrer"
+                                >
+                                    https://github.com/microsoft/data-formulator
+                                </Link>
+                            </Typography>
+                        </Box>
+                    ) : (
+                        <DatabaseTabContent onClose={handleClose} />
+                    )}
+                </TabPanel>
+
+                {/* Extract Data Tab */}
+                <TabPanel value={activeTab} index="extract">
+                    <DataLoadingChat />
+                </TabPanel>
+
+                {/* Explore Sample Datasets Tab */}
+                <TabPanel value={activeTab} index="explore">
+                    <Box sx={{ p: 2 }}>
+                        <DatasetSelectionView 
+                        datasets={datasetPreviews} 
+                        hideRowNum
+                        handleSelectDataset={(dataset) => {
+                            for (let table of dataset.tables) { 
+                                fetch(table.url)
+                                    .then(res => res.text())
+                                    .then(textData => {
+                                        let tableName = table.url.split("/").pop()?.split(".")[0] || 'table-' + Date.now().toString().substring(0, 8);
+                                        let dictTable;
+                                        if (table.format == "csv") {
+                                            dictTable = createTableFromText(tableName, textData);
+                                        } else if (table.format == "json") {
+                                            dictTable = createTableFromFromObjectArray(tableName, JSON.parse(textData), true);
+                                        } 
+                                        if (dictTable) {
+                                            dispatch(dfActions.loadTable(dictTable));
+                                            dispatch(fetchFieldSemanticType(dictTable));
+                                        }
+                                    });
+                            }
+                            handleClose();
+                        }}
+                    />
+                    </Box>
+                </TabPanel>
+            </DialogContent>
+        </Dialog>
+    );
+};
+
+interface DBTable {
+    name: string;
+    columns: { name: string; type: string; }[];
+    row_count: number;
+    sample_rows: any[];
+    view_source: string | null;
+}
+
+interface ColumnStatistics {
+    column: string;
+    type: string;
+    statistics: {
+        count: number;
+        unique_count: number;
+        null_count: number;
+        min?: number;
+        max?: number;
+        avg?: number;
+    };
+}
+
+// Separate component for Database tab content
+const DatabaseTabContent: React.FC<{ onClose: () => void }> = ({ onClose }) => {
+    const theme = useTheme();
+    const dispatch = useDispatch<AppDispatch>();
+    const sessionId = useSelector((state: DataFormulatorState) => state.sessionId);
+    const tables = useSelector((state: DataFormulatorState) => state.tables);
+    const serverConfig = useSelector((state: DataFormulatorState) => state.serverConfig);
+
+    const [dbTables, setDbTables] = React.useState<DBTable[]>([]);
+    const [selectedTabKey, setSelectedTabKey] = React.useState("");
+    const [isUploading, setIsUploading] = React.useState<boolean>(false);
+    const [tableAnalysisMap, setTableAnalysisMap] = React.useState<Record<string, ColumnStatistics[] | null>>({});
+    const [dataLoaderMetadata, setDataLoaderMetadata] = React.useState<Record<string, {
+        params: {name: string, default: string, type: string, required: boolean, description: string}[], 
+        auth_instructions: string}>>({});
+
+    const setSystemMessage = (content: string, severity: "error" | "warning" | "info" | "success") => {
+        dispatch(dfActions.addMessages({
+            "timestamp": Date.now(),
+            "component": "DB manager",
+            "type": severity,
+            "value": content
+        }));
+    };
+
+    React.useEffect(() => {
+        fetchTables();
+        fetchDataLoaders();
+    }, []);
+
+    React.useEffect(() => {
+        if (!selectedTabKey.startsWith("dataLoader:") && dbTables.length == 0) {
+            setSelectedTabKey("");
+        } else if (!selectedTabKey.startsWith("dataLoader:") && dbTables.find(t => t.name === selectedTabKey) == undefined) {
+            if (dbTables.length > 0) {
+                setSelectedTabKey(dbTables[0].name);
+            }
+        }
+    }, [dbTables]);
+
+    const fetchTables = async () => {
+        if (serverConfig.DISABLE_DATABASE) return;
+        try {
+            const response = await fetch(getUrls().LIST_TABLES);
+            const data = await response.json();
+            if (data.status === 'success') {
+                setDbTables(data.tables);
+            }
+        } catch (error) {
+            setSystemMessage('Failed to fetch tables, please check if the server is running', "error");
+        }
+    };
+
+    const fetchDataLoaders = async () => {
+        fetch(getUrls().DATA_LOADER_LIST_DATA_LOADERS, {
+            method: 'GET',
+            headers: { 'Content-Type': 'application/json' },
+        })
+        .then(response => response.json())
+        .then(data => {
+            if (data.status === "success") {
+                setDataLoaderMetadata(data.data_loaders);
+            }
+        })
+        .catch(error => {
+            console.error('Failed to fetch data loader params:', error);
+        });
+    };
+
+    const handleDBFileUpload = async (event: React.ChangeEvent<HTMLInputElement>) => {
+        const file = event.target.files?.[0];
+        if (!file) return;
+    
+        const formData = new FormData();
+        formData.append('file', file);
+        formData.append('table_name', file.name.split('.')[0]);
+    
+        try {
+            setIsUploading(true);
+            const response = await fetch(getUrls().CREATE_TABLE, {
+                method: 'POST',
+                body: formData
+            });
+            const data = await response.json();
+            if (data.status === 'success') {
+                if (data.is_renamed) {
+                    setSystemMessage(`Table ${data.original_name} already exists. Renamed to ${data.table_name}`, "warning");
+                } 
+                fetchTables();
+            } else {
+                setSystemMessage(data.error || 'Failed to upload table', "error");
+            }
+        } catch (error) {
+            setSystemMessage('Failed to upload table, please check if the server is running', "error");
+        } finally {
+            setIsUploading(false);
+            if (event.target) {
+                event.target.value = '';
+            }
+        }
+    };
+
+    const handleDropTable = async (tableName: string) => {
+        if (tables.some(t => t.id === tableName)) {
+            if (!confirm(`Are you sure you want to delete ${tableName}? \n ${tableName} is currently loaded and will be removed from the database.`)) return;
+        }
+
+        try {
+            const response = await fetch(getUrls().DELETE_TABLE, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ table_name: tableName })
+            });
+            const data = await response.json();
+            if (data.status === 'success') {
+                fetchTables();
+                setSelectedTabKey(dbTables.length > 0 ? dbTables[0].name : "");
+            } else {
+                setSystemMessage(data.error || 'Failed to delete table', "error");
+            }
+        } catch (error) {
+            setSystemMessage('Failed to delete table, please check if the server is running', "error");
+        }
+    };
+
+    const handleAnalyzeData = async (tableName: string) => {
+        if (!tableName) return;
+        if (tableAnalysisMap[tableName]) return;
+        
+        try {
+            const response = await fetch(getUrls().GET_COLUMN_STATS, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ table_name: tableName })
+            });
+            const data = await response.json();
+            if (data.status === 'success') {
+                setTableAnalysisMap(prevMap => ({
+                    ...prevMap,
+                    [tableName]: data.statistics
+                }));
+            }
+        } catch (error) {
+            setSystemMessage('Failed to analyze table data', "error");
+        }
+    };
+
+    const toggleAnalysisView = (tableName: string) => {
+        if (tableAnalysisMap[tableName]) {
+            setTableAnalysisMap(prevMap => {
+                const newMap = { ...prevMap };
+                delete newMap[tableName];
+                return newMap;
+            });
+        } else {
+            handleAnalyzeData(tableName);
+        }
+    };
+
+    const handleAddTableToDF = (dbTable: DBTable) => {
+        const convertSqlTypeToAppType = (sqlType: string): Type => {
+            sqlType = sqlType.toUpperCase();
+            if (sqlType.includes('INT') || sqlType === 'BIGINT' || sqlType === 'SMALLINT' || sqlType === 'TINYINT') {
+                return Type.Integer;
+            } else if (sqlType.includes('FLOAT') || sqlType.includes('DOUBLE') || sqlType.includes('DECIMAL') || sqlType.includes('NUMERIC') || sqlType.includes('REAL')) {
+                return Type.Number;
+            } else if (sqlType.includes('BOOL')) {
+                return Type.Boolean;
+            } else if (sqlType.includes('DATE') || sqlType.includes('TIME') || sqlType.includes('TIMESTAMP')) {
+                return Type.Date;
+            } else {
+                return Type.String;
+            }
+        };
+
+        let table: DictTable = {
+            id: dbTable.name,
+            displayId: dbTable.name,
+            names: dbTable.columns.map((col: any) => col.name),
+            metadata: dbTable.columns.reduce((acc: Record<string, {type: Type, semanticType: string, levels: any[]}>, col: any) => ({
+                ...acc,
+                [col.name]: {
+                    type: convertSqlTypeToAppType(col.type),
+                    semanticType: "",
+                    levels: []
+                }
+            }), {}),
+            rows: dbTable.sample_rows,
+            virtual: {
+                tableId: dbTable.name,
+                rowCount: dbTable.row_count,
+            },
+            anchored: true,
+            createdBy: 'user',
+            attachedMetadata: ''
+        }
+        dispatch(dfActions.loadTable(table));
+        dispatch(fetchFieldSemanticType(table));
+        onClose();
+    };
+
+    const handleCleanDerivedViews = async () => {
+        let unreferencedViews = dbTables.filter(t => t.view_source !== null && t.view_source !== undefined && !tables.some(t2 => t2.id === t.name));
+
+        if (unreferencedViews.length > 0) {
+            if (confirm(`Are you sure you want to delete the following unreferenced derived views? \n${unreferencedViews.map(v => `- ${v.name}`).join("\n")}`)) {
+                let deletedViews = [];
+                for (let view of unreferencedViews) {
+                    try {
+                        const response = await fetch(getUrls().DELETE_TABLE, {
+                            method: 'POST',
+                            headers: { 'Content-Type': 'application/json' },
+                            body: JSON.stringify({ table_name: view.name })
+                        });
+                        const data = await response.json();
+                        if (data.status === 'success') {
+                            deletedViews.push(view.name);
+                        }
+                    } catch (error) {
+                        setSystemMessage('Failed to delete table', "error");
+                    }
+                }
+                if (deletedViews.length > 0) {
+                    setSystemMessage(`Deleted ${deletedViews.length} unreferenced derived views`, "success");
+                }
+                fetchTables();
+            }
+        }
+    };
+
+    const handleDBReset = async () => {
+        try {
+            const response = await fetch(getUrls().RESET_DB_FILE, { method: 'POST' });
+            const data = await response.json();
+            if (data.status === 'success') {
+                fetchTables();
+            } else {
+                setSystemMessage(data.error || 'Failed to reset database', "error");
+            }
+        } catch (error) {
+            setSystemMessage('Failed to reset database', "error");
+        }
+    };
+
+    const handleDBUpload = async (event: React.ChangeEvent<HTMLInputElement>) => {
+        const file = event.target.files?.[0];
+        if (!file) return;
+    
+        const formData = new FormData();
+        formData.append('file', file);
+    
+        try {
+            setIsUploading(true);
+            const response = await fetch(getUrls().UPLOAD_DB_FILE, {
+                method: 'POST',
+                body: formData
+            });
+            const data = await response.json();
+            if (data.status === 'success') {
+                fetchTables();
+            } else {
+                setSystemMessage(data.error || 'Failed to upload database', "error");
+            }
+        } catch (error) {
+            setSystemMessage('Failed to upload database', "error");
+        } finally {
+            setIsUploading(false);
+        }
+    };
+
+    const hasDerivedViews = dbTables.filter(t => t.view_source !== null).length > 0;
+
+    const dataLoaderPanel = (
+        <Box sx={{ p: 1, display: 'flex', flexDirection: 'column', backgroundColor: alpha(theme.palette.secondary.main, 0.02) }}>
+            <Box sx={{ display: 'flex', alignItems: 'center', px: 1, mb: 1 }}>
+                <Typography variant="caption" sx={{ color: "text.disabled", fontWeight: "500", flexGrow: 1, fontSize: "0.75rem" }}>
+                    Data Connectors
+                </Typography>
+            </Box>
+            
+            {["file upload", ...Object.keys(dataLoaderMetadata ?? {})].map((dataLoaderType) => (
+                <Button
+                    key={`dataLoader:${dataLoaderType}`}
+                    variant="text"
+                    size="small"
+                    onClick={() => setSelectedTabKey('dataLoader:' + dataLoaderType)}
+                    color='secondary'
+                    sx={{
+                        textTransform: "none",
+                        width: 120,
+                        justifyContent: 'flex-start',
+                        textAlign: 'left',
+                        borderRadius: 0,
+                        py: 0.5,
+                        px: 2,
+                        color: selectedTabKey === 'dataLoader:' + dataLoaderType ? 'secondary.main' : 'text.secondary',
+                        borderRight: selectedTabKey === 'dataLoader:' + dataLoaderType ? 2 : 0,
+                        borderColor: 'secondary.main',
+                    }}
+                >
+                    <Typography fontSize='inherit' sx={{ textTransform: "none", width: "calc(100% - 4px)", textAlign: 'left', textOverflow: 'ellipsis', overflow: 'hidden', whiteSpace: 'nowrap' }}>
+                        {dataLoaderType}
+                    </Typography>
+                </Button>
+            ))}
+        </Box>
+    );
+
+    const tableSelectionPanel = (
+        <Box sx={{ px: 0.5, pt: 1, display: 'flex', flexDirection: 'column', backgroundColor: alpha(theme.palette.primary.main, 0.02) }}>
+            <Box sx={{ display: 'flex', alignItems: 'center', px: 1, mb: 1 }}>
+                <Typography variant="caption" sx={{ color: "text.disabled", fontWeight: "500", flexGrow: 1, fontSize: "0.75rem" }}>
+                    Data Tables
+                </Typography>
+                <Tooltip title="refresh the table list">
+                    <IconButton size="small" color="primary" sx={{ '&:hover': { transform: 'rotate(180deg)' }, transition: 'transform 0.3s ease-in-out' }} onClick={fetchTables}>
+                        <RefreshIcon sx={{ fontSize: 14 }} />
+                    </IconButton>
+                </Tooltip>
+            </Box>
+            
+            {dbTables.length == 0 && 
+                <Typography variant="caption" sx={{ color: "lightgray", px: 2, py: 0.5, fontStyle: "italic" }}>
+                    no tables available
+                </Typography>
+            }
+            
+            {dbTables.filter(t => t.view_source === null).map((t) => (
+                <Button
+                    key={t.name}
+                    variant="text"
+                    size="small"
+                    color='primary'
+                    onClick={() => setSelectedTabKey(t.name)}
+                    sx={{
+                        textTransform: "none",
+                        width: 160,
+                        justifyContent: 'flex-start',
+                        textAlign: 'left',
+                        borderRadius: 0,
+                        py: 0.5,
+                        px: 2,
+                        color: selectedTabKey === t.name ? 'primary.main' : 'text.secondary',
+                        borderRight: selectedTabKey === t.name ? 2 : 0,
+                    }}
+                >
+                    <Typography fontSize='inherit' sx={{ width: "calc(100% - 4px)", textAlign: 'left', textOverflow: 'ellipsis', overflow: 'hidden', whiteSpace: 'nowrap' }}>
+                        {t.name}
+                    </Typography>
+                </Button>
+            ))}
+            
+            {hasDerivedViews && (
+                <Box sx={{ mt: 2, display: 'flex', flexDirection: 'column' }}>
+                    <Box sx={{ display: 'flex', alignItems: 'center', px: 1, mb: 1 }}>
+                        <Typography variant="caption" sx={{ color: "text.disabled", fontWeight: "500", flexGrow: 1, fontSize: "0.75rem" }}>
+                            Derived Views
+                        </Typography>
+                        <Tooltip title="clean up unreferenced derived views">
+                            <IconButton size="small" color="primary" disabled={dbTables.filter(t => t.view_source !== null).length === 0} onClick={handleCleanDerivedViews}>
+                                <CleaningServicesIcon sx={{ fontSize: 14 }} />
+                            </IconButton>
+                        </Tooltip>
+                    </Box>
+                    
+                    {dbTables.filter(t => t.view_source !== null).map((t) => (
+                        <Button
+                            key={t.name}
+                            variant="text"
+                            size="small"
+                            onClick={() => setSelectedTabKey(t.name)}
+                            sx={{
+                                textTransform: "none",
+                                width: 160,
+                                justifyContent: 'flex-start',
+                                textAlign: 'left',
+                                borderRadius: 0,
+                                py: 0.5,
+                                px: 2,
+                                color: selectedTabKey === t.name ? 'primary.main' : 'text.secondary',
+                                borderRight: selectedTabKey === t.name ? 2 : 0,
+                            }}
+                        >
+                            <Typography fontSize='inherit' sx={{ width: "calc(100% - 4px)", textAlign: 'left', textOverflow: 'ellipsis', overflow: 'hidden', whiteSpace: 'nowrap' }}>
+                                {t.name}
+                            </Typography>
+                        </Button>
+                    ))}
+                </Box>
+            )}
+        </Box>
+    );
+
+    const tableView = (
+        <Box sx={{ flex: 1, minWidth: 0, overflow: 'auto', p: 2 }}>
+            {selectedTabKey === '' && (
+                <Typography variant="caption" sx={{ color: "text.secondary", px: 1 }}>
+                    The database is empty, refresh the table list or import some data to get started.
+                </Typography>
+            )}
+            
+            {selectedTabKey === 'dataLoader:file upload' && (
+                <Box sx={{ display: 'flex', flexDirection: 'column', alignItems: 'center', gap: 2, py: 4 }}>
+                    <Tooltip title="upload a csv/xlsx file to the local database">
+                        <Button variant="outlined" component="label" disabled={isUploading}>
+                            <UploadFileIcon sx={{ mr: 1 }} />
+                            {isUploading ? 'Uploading...' : 'Upload CSV/XLSX to Database'}
+                            <input type="file" hidden onChange={handleDBFileUpload} accept=".csv,.xlsx,.json" disabled={isUploading} />
+                        </Button>
+                    </Tooltip>
+                    <Typography variant="caption" color="text.secondary">
+                        Files uploaded here are stored in the database and can handle larger datasets
+                    </Typography>
+                </Box>
+            )}
+            
+            {dataLoaderMetadata && Object.entries(dataLoaderMetadata).map(([dataLoaderType, metadata]) => (
+                selectedTabKey === 'dataLoader:' + dataLoaderType && (
+                    <Box key={`dataLoader:${dataLoaderType}`} sx={{ position: "relative", maxWidth: '100%' }}>
+                        <DataLoaderForm 
+                            key={`data-loader-form-${dataLoaderType}`}
+                            dataLoaderType={dataLoaderType} 
+                            paramDefs={metadata.params}
+                            authInstructions={metadata.auth_instructions}
+                            onImport={() => setIsUploading(true)} 
+                            onFinish={(status, message, importedTables) => {
+                                setIsUploading(false);
+                                fetchTables().then(() => {
+                                    if (status === "success" && importedTables && importedTables.length > 0) {
+                                        setSelectedTabKey(importedTables[0]);
+                                    }
+                                });
+                                if (status === "error") {
+                                    setSystemMessage(message, "error");
+                                }
+                            }} 
+                        />
+                    </Box>
+                )
+            ))}
+            
+            {dbTables.map((t) => {
+                if (selectedTabKey !== t.name) return null;
+                
+                const showingAnalysis = tableAnalysisMap[t.name] !== undefined;
+                return (
+                    <Box key={t.name} sx={{ maxWidth: '100%', overflowX: 'auto', display: 'flex', flexDirection: 'column', gap: 1 }}>
+                        <Paper variant="outlined">
+                            <Box sx={{ px: 1, display: 'flex', alignItems: 'center', borderBottom: '1px solid rgba(0,0,0,0.1)' }}>
+                                <Typography variant="caption">
+                                    {showingAnalysis ? "column stats for " : "sample data from "} 
+                                    <Typography component="span" sx={{ fontSize: 12, fontWeight: "bold" }}>{t.name}</Typography>
+                                    <Typography component="span" sx={{ ml: 1, fontSize: 10, color: "text.secondary" }}>
+                                        ({t.columns.length} columns × {t.row_count} rows)
+                                    </Typography>
+                                </Typography>
+                                <Box sx={{ marginLeft: 'auto', display: 'flex', gap: 1 }}>
+                                    <Button 
+                                        size="small"
+                                        color={showingAnalysis ? "secondary" : "primary"}
+                                        onClick={() => toggleAnalysisView(t.name)}
+                                        startIcon={<AnalyticsIcon fontSize="small" />}
+                                        sx={{ textTransform: "none" }}
+                                    >
+                                        {showingAnalysis ? "show data samples" : "show column stats"}
+                                    </Button>
+                                    <IconButton size="small" color="error" onClick={() => handleDropTable(t.name)} title="Drop Table">
+                                        <DeleteIcon fontSize="small" />
+                                    </IconButton>
+                                </Box>
+                            </Box>
+                            {showingAnalysis ? (
+                                <TableStatisticsView tableName={t.name} columnStats={tableAnalysisMap[t.name] ?? []} />
+                            ) : (
+                                <CustomReactTable 
+                                    rows={t.sample_rows.map((row: any) => Object.fromEntries(Object.entries(row).map(([key, value]: [string, any]) => [key, String(value)]))).slice(0, 9)} 
+                                    columnDefs={t.columns.map(col => ({ id: col.name, label: col.name, minWidth: 60 }))}
+                                    rowsPerPageNum={-1}
+                                    compact={false}
+                                    isIncompleteTable={t.row_count > 10}
+                                />
+                            )}
+                        </Paper>
+                        <Button 
+                            variant="contained"
+                            size="small"
+                            sx={{ ml: 'auto' }}
+                            disabled={isUploading}
+                            onClick={() => handleAddTableToDF(t)}
+                        >
+                            Load Table
+                        </Button>
+                    </Box>
+                );
+            })}
+        </Box>
+    );
+
+    return (
+        <Box sx={{ display: 'flex', flexDirection: 'row', height: '100%', position: 'relative' }}>
+            {isUploading && (
+                <Box sx={{ position: 'absolute', top: 0, left: 0, width: '100%', height: '100%', display: 'flex', alignItems: 'center', justifyContent: 'center', backgroundColor: 'rgba(255, 255, 255, 0.7)', zIndex: 1000 }}>
+                    <CircularProgress size={40} />
+                </Box>
+            )}
+            <Box sx={{ display: 'flex', flexDirection: 'column', borderRight: 1, borderColor: 'divider' }}>
+                <Box sx={{ minWidth: 180, display: 'flex', flexDirection: 'row', flexWrap: 'nowrap', overflowY: 'auto', flexGrow: 1 }}>
+                    {dataLoaderPanel}
+                    {tableSelectionPanel}
+                </Box>
+                <Typography variant="caption" sx={{ mr: 'auto', mt: 'auto', mb: 1, px: 1, textWrap: 'wrap', '& .MuiButton-root': { minWidth: 'auto', textTransform: "none" } }}>
+                    <Tooltip title="import a duckdb .db file">
+                        <Button variant="text" size="small" component="label" disabled={isUploading}>
+                            Import
+                            <input type="file" hidden onChange={handleDBUpload} accept=".db" disabled={isUploading} />
+                        </Button>
+                    </Tooltip>
+                    ,
+                    <Tooltip title="save database to .db file">
+                        <Button variant="text" size="small" onClick={() => handleDBDownload(sessionId ?? '')} disabled={isUploading || dbTables.length === 0}>
+                            Export
+                        </Button>
+                    </Tooltip>
+                    or
+                    <Button variant="text" size="small" color="warning" onClick={handleDBReset} disabled={isUploading}>
+                        Reset
+                    </Button>
+                </Typography>
+            </Box>
+            {tableView}
+        </Box>
+    );
+};
+
+export default UnifiedDataUploadDialog;

From ad342b9dae1ab942e9809370c23f67182fbe04a3 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Fri, 16 Jan 2026 17:58:22 -0800
Subject: [PATCH 05/21] keep this for now..

---
 src/views/UnifiedDataUploadDialog.tsx | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/src/views/UnifiedDataUploadDialog.tsx b/src/views/UnifiedDataUploadDialog.tsx
index 5424840..ab9e55d 100644
--- a/src/views/UnifiedDataUploadDialog.tsx
+++ b/src/views/UnifiedDataUploadDialog.tsx
@@ -767,9 +767,9 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
             maxWidth={false}
             sx={{ 
                 '& .MuiDialog-paper': { 
-                    width: activeTab === 'menu' ? 720 : 1100,
+                    width: 1100,
                     maxWidth: '95vw',
-                    height: activeTab === 'menu' ? 'auto' : 700, 
+                    height: 700, 
                     maxHeight: '90vh',
                     display: 'flex',
                     flexDirection: 'column',
@@ -820,11 +820,13 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
             <DialogContent sx={{ flex: 1, overflow: 'hidden', p: 0 }}>
                 {/* Main Menu */}
                 <TabPanel value={activeTab} index="menu">
-                    <Box sx={{ p: 2 }}>
+                    <Box sx={{ p: 2, boxSizing: 'border-box', width: '100%', height: '100%', display: 'flex', justifyContent: 'center', alignItems: 'center' }}>
                         <Box sx={{ 
+                            width: '100%',
+                            maxWidth: 860,
                             display: 'grid', 
                             gridTemplateColumns: 'repeat(2, minmax(0, 1fr))',
-                            gap: 1,
+                            gap: 1.5,
                         }}>
                             {dataSourceConfig.map((source) => (
                                 <DataSourceCard

From 0cb1183266207c3ad4ce405a101e8827df7625f5 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Sat, 17 Jan 2026 09:42:55 -0800
Subject: [PATCH 06/21] ok

---
 src/app/App.tsx                       |    5 -
 src/views/DBTableManager.tsx          | 1539 ++++++++++++++-----------
 src/views/UnifiedDataUploadDialog.tsx |  907 +++------------
 3 files changed, 1042 insertions(+), 1409 deletions(-)

diff --git a/src/app/App.tsx b/src/app/App.tsx
index 0bcfea5..1a8707f 100644
--- a/src/app/App.tsx
+++ b/src/app/App.tsx
@@ -269,11 +269,6 @@ const TableMenu: React.FC = () => {
                         <ContentPasteIcon fontSize="inherit" /> paste data <span style={{fontSize: '11px'}}>(csv/tsv/json)</span>
                     </Typography>
                 </MenuItem>
-                <MenuItem onClick={() => handleOpenDialog('url')}>
-                    <Typography fontSize="inherit">
-                        <LinkIcon fontSize="inherit" /> from URL
-                    </Typography>
-                </MenuItem>
                 <Divider />
                 <MenuItem onClick={() => handleOpenDialog('database')}>
                     <Typography fontSize="inherit">
diff --git a/src/views/DBTableManager.tsx b/src/views/DBTableManager.tsx
index b883aa1..29b4a89 100644
--- a/src/views/DBTableManager.tsx
+++ b/src/views/DBTableManager.tsx
@@ -1,5 +1,5 @@
 // TableManager.tsx
-import React, { useState, useEffect, FC } from 'react';
+import React, { useState, useEffect, useCallback, FC, useRef } from 'react';
 import { 
   Card, 
   CardContent, 
@@ -9,13 +9,7 @@ import {
   Box,
   IconButton,
   Paper,
-  Tabs,
-  Tab,
   TextField,
-  Dialog,
-  DialogActions,
-  DialogContent,
-  DialogTitle,
   Divider,
   SxProps,
   Table,
@@ -26,24 +20,26 @@ import {
   TableRow,
   CircularProgress,
   ButtonGroup,
+  ToggleButton,
+  ToggleButtonGroup,
   Tooltip,
   MenuItem,
+  Menu,
   Chip,
   Collapse,
   styled,
   useTheme,
   Link,
-  Checkbox
+  Checkbox,
+  Popover
 } from '@mui/material';
 
 import DeleteIcon from '@mui/icons-material/Delete';
 import CloseIcon from '@mui/icons-material/Close';
-import AnalyticsIcon from '@mui/icons-material/Analytics';
 import ExpandLessIcon from '@mui/icons-material/ExpandLess';
 import ExpandMoreIcon from '@mui/icons-material/ExpandMore';
 import TableRowsIcon from '@mui/icons-material/TableRows';
 import RefreshIcon from '@mui/icons-material/Refresh';
-import ArrowForwardIcon from '@mui/icons-material/ArrowForward';
 import SearchIcon from '@mui/icons-material/Search';
 
 import { getUrls } from '../app/utils';
@@ -61,6 +57,49 @@ import Markdown from 'markdown-to-jsx';
 import CheckIcon from '@mui/icons-material/Check';
 import MuiMarkdown from 'mui-markdown';
 import CleaningServicesIcon from '@mui/icons-material/CleaningServices';
+import MoreVertIcon from '@mui/icons-material/MoreVert';
+import UploadFileIcon from '@mui/icons-material/UploadFile';
+import DownloadIcon from '@mui/icons-material/Download';
+import RestartAltIcon from '@mui/icons-material/RestartAlt';
+import StorageIcon from '@mui/icons-material/Storage';
+import CloudUploadIcon from '@mui/icons-material/CloudUpload';
+import SettingsIcon from '@mui/icons-material/Settings';
+
+// Industry-standard database icons
+const TableIcon: React.FC<{ sx?: SxProps }> = ({ sx }) => (
+    <Box
+        component="svg"
+        viewBox="0 0 16 16"
+        sx={{
+            width: 16,
+            height: 16,
+            ...sx
+        }}
+    >
+        {/* Single rectangle with grid lines - standard table icon */}
+        <rect x="2" y="2" width="12" height="12" fill="none" stroke="currentColor" strokeWidth="1.2" rx="0.5"/>
+        <line x1="2" y1="6" x2="14" y2="6" stroke="currentColor" strokeWidth="1"/>
+        <line x1="2" y1="10" x2="14" y2="10" stroke="currentColor" strokeWidth="1"/>
+        <line x1="6" y1="2" x2="6" y2="14" stroke="currentColor" strokeWidth="1"/>
+        <line x1="10" y1="2" x2="10" y2="14" stroke="currentColor" strokeWidth="1"/>
+    </Box>
+);
+
+const ViewIcon: React.FC<{ sx?: SxProps }> = ({ sx }) => (
+    <Box
+        component="svg"
+        viewBox="0 0 16 16"
+        sx={{
+            width: 16,
+            height: 16,
+            ...sx
+        }}
+    >
+        {/* Two overlapping rectangles - standard view icon */}
+        <rect x="2" y="2" width="12" height="12" fill="none" stroke="currentColor" strokeWidth="1.2" rx="0.5" opacity="0.8"/>
+        <rect x="4" y="4" width="12" height="12" fill="none" stroke="currentColor" strokeWidth="1.2" rx="0.5"/>
+    </Box>
+);
 
 export const handleDBDownload = async (sessionId: string) => {
     try {
@@ -119,116 +158,9 @@ interface ColumnStatistics {
     };
 }
 
-interface TableStatisticsViewProps {
-    tableName: string;
-    columnStats: ColumnStatistics[];
-}
-
-export class TableStatisticsView extends React.Component<TableStatisticsViewProps> {
-    render() {
-        const { tableName, columnStats } = this.props;
-
-        // Common styles for header cells
-        const headerCellStyle = {
-            backgroundColor: '#fff',
-            fontSize: 10,
-            color: "#333",
-            borderBottomColor: (theme: any) => theme.palette.primary.main,
-            borderBottomWidth: '1px',
-            borderBottomStyle: 'solid',
-            padding: '6px' 
-        };
-        
-        // Common styles for body cells
-        const bodyCellStyle = { 
-            fontSize: 10, 
-            padding: '6px' 
-        };
-        
-        return (
-            <Box sx={{ 
-                height: '310px',  // Match the table container height from CustomReactTable
-                display: 'flex', 
-                flexDirection: 'column' 
-            }}>
-                <TableContainer sx={{ 
-                    flex: 1, 
-                    maxHeight: '310px',  // Adjust to account for the header
-                    overflow: 'auto' 
-                }}>
-                    <Table size="small" stickyHeader>
-                        <TableHead>
-                            <TableRow>
-                                <TableCell sx={{...headerCellStyle, backgroundColor: "#f7f7f7", fontWeight: "bold"}}>Column</TableCell>
-                                <TableCell sx={headerCellStyle}>Type</TableCell>
-                                <TableCell align="right" sx={headerCellStyle}>Count</TableCell>
-                                <TableCell align="right" sx={headerCellStyle}>Unique</TableCell>
-                                <TableCell align="right" sx={headerCellStyle}>Null</TableCell>
-                                <TableCell align="right" sx={headerCellStyle}>Min</TableCell>
-                                <TableCell align="right" sx={headerCellStyle}>Max</TableCell>
-                                <TableCell align="right" sx={headerCellStyle}>Avg</TableCell>
-                            </TableRow>
-                        </TableHead>
-                        <TableBody>
-                            {columnStats.map((stat, idx) => (
-                                <TableRow 
-                                    key={stat.column} 
-                                    hover
-                                    sx={{ }}
-                                >
-                                    <TableCell 
-                                        component="th" 
-                                        scope="row" 
-                                        sx={{...bodyCellStyle, fontWeight: "bold", backgroundColor: "#f7f7f7"}}
-                                    >
-                                        {stat.column}
-                                    </TableCell>
-                                    <TableCell sx={bodyCellStyle}>
-                                        {stat.type}
-                                    </TableCell>
-                                    <TableCell align="right" sx={bodyCellStyle}>
-                                        {stat.statistics.count}
-                                    </TableCell>
-                                    <TableCell align="right" sx={bodyCellStyle}>
-                                        {stat.statistics.unique_count}
-                                    </TableCell>
-                                    <TableCell align="right" sx={bodyCellStyle}>
-                                        {stat.statistics.null_count}
-                                    </TableCell>
-                                    <TableCell align="right" sx={bodyCellStyle}>
-                                        {stat.statistics.min !== undefined ? stat.statistics.min : '-'}
-                                    </TableCell>
-                                    <TableCell align="right" sx={bodyCellStyle}>
-                                        {stat.statistics.max !== undefined ? stat.statistics.max : '-'}
-                                    </TableCell>
-                                    <TableCell align="right" sx={bodyCellStyle}>
-                                        {stat.statistics.avg !== undefined ? 
-                                            Number(stat.statistics.avg).toFixed(2) : '-'}
-                                    </TableCell>
-                                </TableRow>
-                            ))}
-                        </TableBody>
-                    </Table>
-                </TableContainer>
-            </Box>
-        );
-    }
-}
 
-export const DBTableSelectionDialog: React.FC<{ 
-    buttonElement?: any, 
-    sx?: SxProps,
-    onOpen?: () => void,
-    // Controlled mode props
-    open?: boolean,
-    onClose?: () => void
-}> = function DBTableSelectionDialog({ 
-    buttonElement,
-    sx,
-    onOpen,
-    open: controlledOpen,
-    onClose,
-}) {
+export const DBManagerPane: React.FC<{ 
+}> = function DBManagerPane({ }) {
     
     const theme = useTheme();
 
@@ -236,15 +168,10 @@ export const DBTableSelectionDialog: React.FC<{
     const sessionId = useSelector((state: DataFormulatorState) => state.sessionId);
     const tables = useSelector((state: DataFormulatorState) => state.tables);
     const serverConfig = useSelector((state: DataFormulatorState) => state.serverConfig);
+    const dataLoaderConnectParams = useSelector((state: DataFormulatorState) => state.dataLoaderConnectParams);
 
-    const [internalOpen, setInternalOpen] = useState<boolean>(false);
     
     // Support both controlled and uncontrolled modes
-    const isControlled = controlledOpen !== undefined;
-    const tableDialogOpen = isControlled ? controlledOpen : internalOpen;
-    const setTableDialogOpen = isControlled 
-        ? (open: boolean) => { if (!open && onClose) onClose(); }
-        : setInternalOpen;
     const [tableAnalysisMap, setTableAnalysisMap] = useState<Record<string, ColumnStatistics[] | null>>({});
     
     // maps data loader type to list of param defs
@@ -254,8 +181,15 @@ export const DBTableSelectionDialog: React.FC<{
 
     const [dbTables, setDbTables] = useState<DBTable[]>([]);
     const [selectedTabKey, setSelectedTabKey] = useState("");
+    const [selectedDataLoader, setSelectedDataLoader] = useState<string>("");
+    const [connectorMenuAnchorEl, setConnectorMenuAnchorEl] = useState<HTMLElement | null>(null);
 
     const [isUploading, setIsUploading] = useState<boolean>(false);
+    const [resetAnchorEl, setResetAnchorEl] = useState<HTMLElement | null>(null);
+    const [tableMenuAnchorEl, setTableMenuAnchorEl] = useState<HTMLElement | null>(null);
+    const [showViews, setShowViews] = useState<boolean>(false);
+    const dbFileInputRef = useRef<HTMLInputElement>(null);
+    const menuButtonRef = useRef<HTMLButtonElement>(null);
 
     let setSystemMessage = (content: string, severity: "error" | "warning" | "info" | "success") => {
         dispatch(dfActions.addMessages({
@@ -271,12 +205,14 @@ export const DBTableSelectionDialog: React.FC<{
     }, []);
 
     useEffect(() => {
-        if (!selectedTabKey.startsWith("dataLoader:") && dbTables.length == 0) {
-            setSelectedTabKey("");
-        } else if (!selectedTabKey.startsWith("dataLoader:") && dbTables.find(t => t.name === selectedTabKey) == undefined) {
-            setSelectedTabKey(dbTables[0].name);
+        if (selectedDataLoader === "") {
+            if (dbTables.length == 0) {
+                setSelectedTabKey("");
+            } else if (dbTables.find(t => t.name === selectedTabKey) == undefined) {
+                setSelectedTabKey(dbTables[0]?.name || "");
+            }
         }
-    }, [dbTables]);
+    }, [dbTables, selectedDataLoader]);
 
     // Fetch list of tables
     const fetchTables = async () => {
@@ -450,13 +386,11 @@ export const DBTableSelectionDialog: React.FC<{
         }
     };
 
-    // Handle data analysis
-    const handleAnalyzeData = async (tableName: string) => {
+    // Handle data analysis - auto-fetch when table is selected
+    const handleAnalyzeData = useCallback(async (tableName: string) => {
         if (!tableName) return;
         if (tableAnalysisMap[tableName]) return;
 
-        console.log('Analyzing table:', tableName);
-        
         try {
             const response = await fetch(getUrls().GET_COLUMN_STATS, {
                 method: 'POST',
@@ -467,7 +401,6 @@ export const DBTableSelectionDialog: React.FC<{
             });
             const data = await response.json();
             if (data.status === 'success') {
-                console.log('Analysis results:', data);
                 // Update the analysis map with the new results
                 setTableAnalysisMap(prevMap => ({
                     ...prevMap,
@@ -476,24 +409,16 @@ export const DBTableSelectionDialog: React.FC<{
             }
         } catch (error) {
             console.error('Failed to analyze table data:', error);
-            setSystemMessage('Failed to analyze table data, please check if the server is running', "error");
+            // Don't show error message for auto-fetch, just fail silently
         }
-    };
+    }, [tableAnalysisMap]);
 
-    // Toggle analysis view
-    const toggleAnalysisView = (tableName: string) => {
-        if (tableAnalysisMap[tableName]) {
-            // If we already have analysis, remove it to show table data again
-            setTableAnalysisMap(prevMap => {
-                const newMap = { ...prevMap };
-                delete newMap[tableName];
-                return newMap;
-            });
-        } else {
-            // If no analysis yet, fetch it
-            handleAnalyzeData(tableName);
+    // Auto-fetch stats when a table is selected
+    useEffect(() => {
+        if (selectedTabKey && selectedDataLoader === "") {
+            handleAnalyzeData(selectedTabKey);
         }
-    };
+    }, [selectedTabKey, selectedDataLoader, handleAnalyzeData]);
 
     const handleAddTableToDF = (dbTable: DBTable) => {
         const convertSqlTypeToAppType = (sqlType: string): Type => {
@@ -535,44 +460,12 @@ export const DBTableSelectionDialog: React.FC<{
         }
        dispatch(dfActions.loadTable(table));
        dispatch(fetchFieldSemanticType(table));
-       setTableDialogOpen(false);
     }
 
-    const handleTabChange = (event: React.SyntheticEvent, newValue: string) => {
-        setSelectedTabKey(newValue);
-    };
 
     useEffect(() => {
-        if (tableDialogOpen) {
-            fetchTables();
-        }
-    }, [tableDialogOpen]);
-
-    let importButton = (buttonElement: React.ReactNode) => {
-        return <Tooltip title="import a duckdb .db file to the local database">
-            <span>
-                <Button variant="text" sx={{fontSize: "inherit", minWidth: "auto"}} component="label" disabled={isUploading}>
-                    {buttonElement}
-                    <input type="file" hidden onChange={handleDBUpload} accept=".db" disabled={isUploading} />
-                </Button>
-            </span>
-        </Tooltip>
-    }
-
-    let exportButton = 
-        <Tooltip title="save the local database to a duckdb .db file">
-            <span>
-                <Button variant="text" size="small" onClick={() => {
-                    handleDBDownload(sessionId ?? '')
-                        .catch(error => {
-                            console.error('Failed to download database:', error);
-                            setSystemMessage('Failed to download database file', "error");
-                        });
-                }} disabled={isUploading || dbTables.length === 0}>
-                    export
-                </Button>
-            </span>
-        </Tooltip>
+        fetchTables();
+    }, []);
 
     function uploadFileButton(element: React.ReactNode, buttonSx?: SxProps) {
         return (
@@ -598,81 +491,192 @@ export const DBTableSelectionDialog: React.FC<{
         );
     }
 
-    let hasDerivedViews = dbTables.filter(t => t.view_source !== null).length > 0;
-
-    let dataLoaderPanel = <Box sx={{ p: 1, display: 'flex', flexDirection: 'column', backgroundColor: alpha(theme.palette.secondary.main, 0.02) }}>
-        <Box sx={{ display: 'flex', alignItems: 'center', px: 1, mb: 1 }}>
+    let tableSelectionPanel = <Box sx={{ 
+        px: 0.5, pt: 1, 
+        display: 'flex', 
+        flexDirection: 'column', 
+        backgroundColor: alpha(theme.palette.primary.main, 0.02),
+        width: '100%'
+    }}>
+        {/* Recent Data Loaders */}
+        <Box sx={{ px: 1, mb: 1 }}>
+                <Typography variant="caption" sx={{
+                    color: "text.disabled",
+                    fontSize: "0.75rem",
+                    mb: 1,
+                    display: 'block'
+                }}>
+                    External Data Loaders
+                </Typography>
+                <Box sx={{ 
+                    display: 'flex', 
+                    flexWrap: 'wrap', 
+                    gap: 0.5,
+                    alignItems: 'flex-start',
+                    width: '100%',
+                    minWidth: 0
+                }}>
+                    <Chip
+                        key="file upload"
+                        label="file"
+                        size="small"
+                        onClick={() => setSelectedDataLoader("file upload")}
+                        sx={{
+                            fontSize: '0.7rem',
+                            height: 20,
+                            maxWidth: '100%',
+                            backgroundColor: selectedDataLoader === "file upload" ? alpha(theme.palette.secondary.main, 0.2) : 'transparent',
+                            '& .MuiChip-label': {
+                                overflow: 'hidden',
+                                textOverflow: 'ellipsis',
+                                whiteSpace: 'nowrap'
+                            },
+                            '&:hover': {
+                                backgroundColor: alpha(theme.palette.secondary.main, 0.12),
+                                cursor: 'pointer'
+                            }
+                        }}
+                    />
+                    {Object.keys(dataLoaderMetadata ?? {})
+                        .map((dataLoaderType) => (
+                            <Chip
+                                key={dataLoaderType}
+                                label={dataLoaderType}
+                                size="small"
+                                onClick={() => setSelectedDataLoader(dataLoaderType)}
+                                sx={{
+                                    fontSize: '0.7rem',
+                                    height: 20,
+                                    maxWidth: '100%',
+                                    backgroundColor: selectedDataLoader === dataLoaderType ? alpha(theme.palette.secondary.main, 0.2) : 'transparent',
+                                    '& .MuiChip-label': {
+                                        overflow: 'hidden',
+                                        textOverflow: 'ellipsis',
+                                        whiteSpace: 'nowrap'
+                                    },
+                                    '&:hover': {
+                                        backgroundColor: alpha(theme.palette.secondary.main, 0.12),
+                                        cursor: 'pointer'
+                                    }
+                                }}
+                            />
+                        ))}
+                </Box>
+            </Box>
+        
+        <Box sx={{ display: 'flex', alignItems: 'center', justifyContent: 'space-between', px: 1, mb: 1 }}>
             <Typography variant="caption" sx={{
                 color: "text.disabled", 
                 fontWeight: "500", 
                 flexGrow: 1,
                 fontSize: "0.75rem",
             }}>
-                Data Connectors
+                Local DuckDB
             </Typography>
-        </Box>
-        
-        {["file upload", ...Object.keys(dataLoaderMetadata ?? {})].map((dataLoaderType, i) => (
-            <Button
-                key={`dataLoader:${dataLoaderType}`}
-                variant="text"
-                size="small"
-                onClick={() => {
-                    setSelectedTabKey('dataLoader:' + dataLoaderType);
+            <IconButton 
+                ref={menuButtonRef}
+                size="small" 
+                onClick={(e) => setTableMenuAnchorEl(e.currentTarget)}
+                sx={{ 
+                    padding: 0.5,
+                    '&:hover': {
+                        backgroundColor: alpha(theme.palette.primary.main, 0.08),
+                    }
+                }}
+            >
+                <MoreVertIcon sx={{ fontSize: 16 }} />
+            </IconButton>
+            <Menu
+                anchorEl={tableMenuAnchorEl}
+                open={Boolean(tableMenuAnchorEl)}
+                onClose={() => setTableMenuAnchorEl(null)}
+                anchorOrigin={{
+                    vertical: 'bottom',
+                    horizontal: 'right',
                 }}
-                color='secondary'
-                sx={{
-                    textTransform: "none",
-                    width: 120,
-                    justifyContent: 'flex-start',
-                    textAlign: 'left',
-                    borderRadius: 0,
-                    py: 0.5,
-                    px: 2,
-                    color: selectedTabKey === 'dataLoader:' + dataLoaderType ? 'secondary.main' : 'text.secondary',
-                    borderRight: selectedTabKey === 'dataLoader:' + dataLoaderType ? 2 : 0,
-                    borderColor: 'secondary.main',
+                transformOrigin={{
+                    vertical: 'top',
+                    horizontal: 'left',
                 }}
             >
-                <Typography 
-                    fontSize='inherit'
-                    sx={{
-                        textTransform: "none", 
-                        width: "calc(100% - 4px)", 
-                        textAlign: 'left', 
-                        textOverflow: 'ellipsis', 
-                        overflow: 'hidden', 
-                        whiteSpace: 'nowrap',
-                    }}>
-                    {dataLoaderType}
-                </Typography>
-            </Button>
-        ))}
-    </Box>;
-
-    let tableSelectionPanel = <Box sx={{ px: 0.5, pt: 1, display: 'flex', flexDirection: 'column', backgroundColor: alpha(theme.palette.primary.main, 0.02) }}>
-        <Box sx={{ display: 'flex', alignItems: 'center', px: 1, mb: 1 }}>
-            <Typography variant="caption" sx={{
-                color: "text.disabled", 
-                fontWeight: "500", 
-                flexGrow: 1,
-                fontSize: "0.75rem",
-            }}>
-                Data Tables
-            </Typography>
-            <Tooltip title="refresh the table list">
-                <IconButton size="small" color="primary" sx={{
-                    '&:hover': {
-                        transform: 'rotate(180deg)',
-                    },
-                    transition: 'transform 0.3s ease-in-out',
-                }} onClick={() => {
-                    fetchTables();
-                }}>
-                    <RefreshIcon sx={{fontSize: 14}} />
-                </IconButton>
-            </Tooltip>
+                <MenuItem 
+                    onClick={() => {
+                        fetchTables();
+                        setTableMenuAnchorEl(null);
+                    }}
+                    dense
+                >
+                    <RefreshIcon sx={{ fontSize: 16, mr: 1 }} />
+                    Refresh table list
+                </MenuItem>
+                <MenuItem 
+                    onClick={() => {
+                        handleCleanDerivedViews();
+                        setTableMenuAnchorEl(null);
+                    }}
+                    disabled={dbTables.filter(t => t.view_source !== null).length === 0}
+                    dense
+                >
+                    <CleaningServicesIcon sx={{ fontSize: 16, mr: 1 }} />
+                    Clean up derived views
+                </MenuItem>
+                <Divider />
+                <MenuItem 
+                    onClick={() => {
+                        dbFileInputRef.current?.click();
+                        setTableMenuAnchorEl(null);
+                    }}
+                    disabled={isUploading}
+                    dense
+                >
+                    <UploadFileIcon sx={{ fontSize: 16, mr: 1 }} />
+                    Import database file
+                </MenuItem>
+                <MenuItem 
+                    onClick={() => {
+                        if (!isUploading && dbTables.length > 0) {
+                            handleDBDownload(sessionId ?? '')
+                                .catch(error => {
+                                    console.error('Failed to download database:', error);
+                                    setSystemMessage('Failed to download database file', "error");
+                                });
+                        }
+                        setTableMenuAnchorEl(null);
+                    }}
+                    disabled={isUploading || dbTables.length === 0}
+                    dense
+                >
+                    <DownloadIcon sx={{ fontSize: 16, mr: 1 }} />
+                    Export database file
+                </MenuItem>
+                <MenuItem 
+                    onClick={() => {
+                        setTableMenuAnchorEl(null);
+                        if (!isUploading && menuButtonRef.current) {
+                            // Use setTimeout to ensure menu closes before popover opens
+                            setTimeout(() => {
+                                setResetAnchorEl(menuButtonRef.current);
+                            }, 100);
+                        }
+                    }}
+                    disabled={isUploading}
+                    dense
+                    sx={{ color: 'error.main' }}
+                >
+                    <RestartAltIcon sx={{ fontSize: 16, mr: 1 }} />
+                    Reset database
+                </MenuItem>
+            </Menu>
+            <input 
+                ref={dbFileInputRef}
+                type="file" 
+                hidden 
+                onChange={handleDBUpload} 
+                accept=".db" 
+                disabled={isUploading} 
+            />
         </Box>
+    
         
         {dbTables.length == 0 && 
             <Typography variant="caption" sx={{color: "lightgray", px: 2, py: 0.5, fontStyle: "italic"}}>
@@ -681,122 +685,147 @@ export const DBTableSelectionDialog: React.FC<{
         }
         
         {/* Regular Tables */}
-        {dbTables.filter(t => t.view_source === null).map((t, i) => (
-            <Button
-                key={t.name}
-                variant="text"
-                size="small"
-                color='primary'
-                onClick={() => {
-                    setSelectedTabKey(t.name);
-                }}
-                sx={{
-                    textTransform: "none",
-                    width: 160,
-                    justifyContent: 'flex-start',
-                    textAlign: 'left',
-                    borderRadius: 0,
-                    py: 0.5,
-                    px: 2,
-                    color: selectedTabKey === t.name ? 'primary.main' : 'text.secondary',
-                    borderRight: selectedTabKey === t.name ? 2 : 0,
-                }}
-            >
-                <Typography 
-                    fontSize='inherit'
+        {dbTables.filter(t => t.view_source === null).map((t, i) => {
+            const isLoaded = tables.some(loadedTable => loadedTable.id === t.name);
+            return (
+                <Button
+                    key={t.name}
+                    variant="text"
+                    size="small"
+                    color='primary'
+                    onClick={() => {
+                        setSelectedTabKey(t.name);
+                        // If in data loader view, go back to table view
+                        if (selectedDataLoader !== "") {
+                            setSelectedDataLoader("");
+                        }
+                    }}
                     sx={{
-                        width: "calc(100% - 4px)", 
-                        textAlign: 'left', 
-                        textOverflow: 'ellipsis', 
-                        overflow: 'hidden', 
-                        whiteSpace: 'nowrap',
-                    }}>
-                    {t.name}
-                </Typography>
-            </Button>
-        ))}
+                        textTransform: "none",
+                        width: '100%',
+                        maxWidth: '100%',
+                        justifyContent: 'flex-start',
+                        textAlign: 'left',
+                        borderRadius: 0,
+                        py: 0.5,
+                        px: 2,
+                        color: (selectedTabKey === t.name && selectedDataLoader === "") ? 'primary.main' : 'text.secondary',
+                        borderRight: (selectedTabKey === t.name && selectedDataLoader === "") ? 2 : 0,
+                        minWidth: 0,
+                    }}
+                    startIcon={<TableIcon />}
+                    endIcon={isLoaded ? <CheckIcon sx={{ fontSize: 14, color: 'success.main' }} /> : null}
+                >
+                    <Typography 
+                        fontSize='inherit'
+                        sx={{
+                            flex: 1,
+                            minWidth: 0,
+                            textAlign: 'left', 
+                            textOverflow: 'ellipsis', 
+                            overflow: 'hidden', 
+                            whiteSpace: 'nowrap',
+                        }}>
+                        {t.name}
+                    </Typography>
+                </Button>
+            );
+        })}
         
         {/* Derived Views Section */}
-        {hasDerivedViews && (
+        {dbTables.filter(t => t.view_source !== null).length > 0 && (
             <Box sx={{ mt: 2, display: 'flex', flexDirection: 'column' }}>
-                <Box sx={{ display: 'flex', alignItems: 'center', px: 1, mb: 1 }}>
-                    <Typography variant="caption" sx={{
-                        color: "text.disabled", 
-                        fontWeight: "500", 
-                        flexGrow: 1,
-                        fontSize: "0.75rem",
-                    }}>
-                        Derived Views
-                    </Typography>
-                    <Tooltip title="clean up unreferenced derived views">
-                        <IconButton size="small" color="primary" sx={{
-                            '&:hover': {
-                                transform: 'rotate(180deg)',
-                            },
-                            transition: 'transform 0.3s ease-in-out',
-                        }} 
-                        disabled={dbTables.filter(t => t.view_source !== null).length === 0}
-                        onClick={() => {
-                            handleCleanDerivedViews();
-                        }}>
-                            <CleaningServicesIcon sx={{fontSize: 14}} />
-                        </IconButton>
-                    </Tooltip>
-                </Box>
-                
-                {dbTables.filter(t => t.view_source !== null).map((t, i) => (
-                    <Button
-                        key={t.name}
-                        variant="text"
-                        size="small"
-                        onClick={() => {
-                            setSelectedTabKey(t.name);
-                        }}
+                <Button
+                    variant="text"
+                    size="small"
+                    onClick={() => setShowViews(!showViews)}
+                    sx={{
+                        textTransform: "none",
+                        width: '100%',
+                        justifyContent: 'flex-start',
+                        textAlign: 'left',
+                        borderRadius: 0,
+                        py: 0.5,
+                        px: 2,
+                        color: 'text.secondary',
+                        minWidth: 0,
+                        '&:hover': {
+                            backgroundColor: alpha(theme.palette.primary.main, 0.08)
+                        }
+                    }}
+                    startIcon={showViews ? <ExpandLessIcon sx={{ fontSize: 16 }} /> : <ExpandMoreIcon sx={{ fontSize: 16 }} />}
+                >
+                    <Typography 
+                        fontSize='0.75rem'
                         sx={{
-                            textTransform: "none",
-                            width: 160,
-                            justifyContent: 'flex-start',
+                            flex: 1,
+                            minWidth: 0,
                             textAlign: 'left',
-                            borderRadius: 0,
-                            py: 0.5,
-                            px: 2,
-                            color: selectedTabKey === t.name ? 'primary.main' : 'text.secondary',
-                            backgroundColor: 'transparent',
-                            borderRight: selectedTabKey === t.name ? 2 : 0,
-                            borderColor: 'primary.main',
-                            '&:hover': {
-                                backgroundColor: selectedTabKey === t.name ? 'primary.100' : 'primary.50'
-                            }
-                        }}
-                    >
-                        <Typography 
-                            fontSize='inherit'
-                            sx={{
-                                width: "calc(100% - 4px)", 
-                                textAlign: 'left', 
-                                textOverflow: 'ellipsis', 
-                                overflow: 'hidden', 
-                                whiteSpace: 'nowrap',
-                                
-                            }}>
-                            {t.name}
-                        </Typography>
-                    </Button>
-                ))}
+                        }}>
+                        Views ({dbTables.filter(t => t.view_source !== null).length})
+                    </Typography>
+                </Button>
+                <Collapse in={showViews}>
+                    <Box sx={{ display: 'flex', flexDirection: 'column' }}>
+                        {dbTables.filter(t => t.view_source !== null).map((t, i) => {
+                            return (
+                            <Button
+                                key={t.name}
+                                variant="text"
+                                size="small"
+                                onClick={() => {
+                                    setSelectedTabKey(t.name);
+                                    // If in data loader view, go back to table view
+                                    if (selectedDataLoader !== "") {
+                                        setSelectedDataLoader("");
+                                    }
+                                }}
+                                sx={{
+                                    textTransform: "none",
+                                    width: '100%',
+                                    maxWidth: '100%',
+                                    justifyContent: 'flex-start',
+                                    textAlign: 'left',
+                                    borderRadius: 0,
+                                    py: 0.5,
+                                    px: 2,
+                                    color: (selectedTabKey === t.name && selectedDataLoader === "") ? 'primary.main' : 'text.secondary',
+                                    backgroundColor: 'transparent',
+                                    borderRight: (selectedTabKey === t.name && selectedDataLoader === "") ? 2 : 0,
+                                    borderColor: 'primary.main',
+                                    minWidth: 0,
+                                    '&:hover': {
+                                        backgroundColor: (selectedTabKey === t.name && selectedDataLoader === "") ? 'primary.100' : 'primary.50'
+                                    }
+                                }}
+                                startIcon={<ViewIcon />}
+                            >
+                                <Typography 
+                                    fontSize='inherit'
+                                    sx={{
+                                        flex: 1,
+                                        minWidth: 0,
+                                        textAlign: 'left', 
+                                        textOverflow: 'ellipsis', 
+                                        overflow: 'hidden', 
+                                        whiteSpace: 'nowrap',
+                                    }}>
+                                    {t.name}
+                                </Typography>
+                            </Button>
+                            );
+                        })}
+                    </Box>
+                </Collapse>
             </Box>
         )}
     </Box>
 
-    let tableView = <Box sx={{ flex: 1, width: 880, overflow: 'auto', p: 2 }}>
-        {/* Empty state */}
-        {selectedTabKey === '' && (
-            <Typography variant="caption" sx={{color: "text.secondary", px: 1}}>
-                The database is empty, refresh the table list or import some data to get started.
-            </Typography>
-        )}
+    let dataConnectorView = <Box sx={{ height: '100%', overflowY: 'auto', overflowX: 'hidden', p: 2, display: 'flex', flexDirection: 'column', minWidth: 0, overscrollBehavior: 'contain' }}>
+
         
         {/* File upload */}
-        {selectedTabKey === 'dataLoader:file upload' && (
+        {selectedDataLoader === 'file upload' && (
             <Box>
                 {uploadFileButton(<Typography component="span" fontSize={18} textTransform="none">{isUploading ? 'uploading...' : 'upload a csv/tsv file to the local database'}</Typography>)} 
             </Box>
@@ -804,7 +833,7 @@ export const DBTableSelectionDialog: React.FC<{
         
         {/* Data loader forms */}
         {dataLoaderMetadata && Object.entries(dataLoaderMetadata).map(([dataLoaderType, metadata]) => (
-            selectedTabKey === 'dataLoader:' + dataLoaderType && (
+            selectedDataLoader === dataLoaderType && (
                 <Box key={`dataLoader:${dataLoaderType}`} sx={{ position: "relative", maxWidth: '100%' }}>
                     <DataLoaderForm 
                         key={`data-loader-form-${dataLoaderType}`}
@@ -817,6 +846,8 @@ export const DBTableSelectionDialog: React.FC<{
                         onFinish={(status, message, importedTables) => {
                             setIsUploading(false);
                             fetchTables().then(() => {
+                                // Switch back to tables view after import
+                                setSelectedDataLoader("");
                                 // Navigate to the first imported table after tables are fetched
                                 if (status === "success" && importedTables && importedTables.length > 0) {
                                     setSelectedTabKey(importedTables[0]);
@@ -830,196 +861,252 @@ export const DBTableSelectionDialog: React.FC<{
                 </Box>
             )
         ))}
+    </Box>;
+
+    let tableView = <Box sx={{ height: '100%', overflowY: 'auto', overflowX: 'hidden', p: 2, minWidth: 0, overscrollBehavior: 'contain' }}>
+        {/* Empty state */}
+        {selectedTabKey === '' && (
+            <Typography variant="caption" sx={{color: "text.secondary", px: 1}}>
+                The database is empty, refresh the table list or import some data to get started.
+            </Typography>
+        )}
         
         {/* Table content */}
         {dbTables.map((t, i) => {
             if (selectedTabKey !== t.name) return null;
             
             const currentTable = t;
-            const showingAnalysis = tableAnalysisMap[currentTable.name] !== undefined;
+            const columnStats = tableAnalysisMap[currentTable.name] ?? [];
+            const statsMap = new Map(columnStats.map((stat: ColumnStatistics) => [stat.column, stat]));
+            
             return (
                 <Box key={t.name} sx={{ maxWidth: '100%', overflowX: 'auto', display: 'flex', flexDirection: 'column', gap: 1 }}>
-                    <Paper variant="outlined">
-                        <Box sx={{ px: 1, display: 'flex', alignItems: 'center', borderBottom: '1px solid rgba(0,0,0,0.1)' }}>
-                            <Typography variant="caption" sx={{  }}>
-                                {showingAnalysis ? "column stats for " : "sample data from "} 
-                                <Typography component="span" sx={{fontSize: 12, fontWeight: "bold"}}>
-                                    {currentTable.name}
-                                </Typography>
-                                <Typography component="span" sx={{ml: 1, fontSize: 10, color: "text.secondary"}}>
-                                    ({currentTable.columns.length} columns × {currentTable.row_count} rows)
-                                </Typography>
+                    <Box sx={{ px: 1, display: 'flex', alignItems: 'center' }}>
+                        <Box sx={{ display: 'flex', alignItems: 'center', gap: 1 }}>
+                            {currentTable.view_source ? <ViewIcon /> : <TableIcon />}
+                            <Typography component="span" sx={{fontSize: 16, fontWeight: "bold"}}>
+                                {currentTable.name}
+                            </Typography>
+                        </Box>
+                        <Tooltip title="Drop Table">
+                            <IconButton 
+                                size="small" 
+                                color="error"
+                                sx={{ml: 'auto'}}
+                                onClick={() => handleDropTable(currentTable.name)}
+                                title="Drop Table"
+                            >
+                                <DeleteIcon fontSize="small" />
+                            </IconButton>
+                        </Tooltip>
+                    </Box>
+                    <Box sx={{ border: '1px solid', borderColor: 'divider', borderRadius: 1, p: 1 }}>
+                        <Box sx={{ position: 'relative' }}>
+                            <TableContainer sx={{ maxHeight: 340, overflow: 'auto' }}>
+                                <Table stickyHeader aria-label="sticky table" size="small">
+                                    <TableHead>
+                                        <TableRow>
+                                            {currentTable.columns.map((col) => {
+                                                const stat = statsMap.get(col.name);
+                                                return (
+                                                    <TableCell
+                                                        key={col.name}
+                                                        sx={{
+                                                            minWidth: 80,
+                                                            fontSize: 10,
+                                                            color: "#333",
+                                                            backgroundColor: '#fff',
+                                                            borderBottomColor: theme.palette.primary.main,
+                                                            borderBottomWidth: '1px',
+                                                            borderBottomStyle: 'solid',
+                                                            padding: '4px 6px',
+                                                            verticalAlign: 'top'
+                                                        }}
+                                                    >
+                                                        <Box sx={{ display: 'flex', flexDirection: 'column', gap: 0.5 }}>
+                                                            <Typography sx={{ fontSize: 11, fontWeight: 600, lineHeight: 1.2 }}>
+                                                                {col.name}
+                                                            </Typography>
+                                                            {stat ? (
+                                                                <Typography sx={{ fontSize: 9, color: 'text.secondary', lineHeight: 1.2 }}>
+                                                                    {stat.type}
+                                                                </Typography>
+                                                            ) : (
+                                                                <Typography sx={{ fontSize: 9, color: 'text.disabled', lineHeight: 1.2, fontStyle: 'italic' }}>
+                                                                    {col.type}
+                                                                </Typography>
+                                                            )}
+                                                        </Box>
+                                                    </TableCell>
+                                                );
+                                            })}
+                                        </TableRow>
+                                    </TableHead>
+                                    <TableBody>
+                                        {currentTable.sample_rows.slice(0, 9).map((row: any, rowIdx: number) => (
+                                            <TableRow 
+                                                hover 
+                                                tabIndex={-1} 
+                                                key={rowIdx} 
+                                                sx={{ background: rowIdx % 2 == 0 ? '#F0F0F0' : "none" }}
+                                            >
+                                                {currentTable.columns.map((col) => {
+                                                    const value = row[col.name];
+                                                    return (
+                                                        <TableCell
+                                                            key={col.name}
+                                                            sx={{
+                                                                fontSize: 10,
+                                                                maxWidth: "80px",
+                                                                padding: "6px",
+                                                                overflow: "clip",
+                                                                textOverflow: "ellipsis",
+                                                                whiteSpace: "nowrap"
+                                                            }}
+                                                        >
+                                                            {String(value ?? '')}
+                                                        </TableCell>
+                                                    );
+                                                })}
+                                            </TableRow>
+                                        ))}
+                                    </TableBody>
+                                </Table>
+                            </TableContainer>
+                            {currentTable.row_count > 10 && (
+                                <Box sx={{ px: 1, py: 0.5}}>
+                                    <Typography variant="caption" sx={{ fontSize: 9, color: 'text.secondary', fontStyle: 'italic' }}>
+                                        Showing first 9 rows of {currentTable.row_count} total rows
+                                    </Typography>
+                                </Box>
+                            )}
+                        </Box>
+                    </Box>
+                    {tables.some(t => t.id === currentTable.name) ? (
+                        <Box 
+                            sx={{
+                                ml: 'auto',
+                                display: 'flex',
+                                alignItems: 'center',
+                                gap: 0.5,
+                                color: 'success.main',
+                                fontSize: '12px',
+                                fontWeight: 500
+                            }}
+                        >
+                            <CheckIcon sx={{ fontSize: 16 }} />
+                            <Typography sx={{ fontSize: 'inherit', color: 'inherit', fontWeight: 'inherit' }}>
+                                Loaded
                             </Typography>
-                            <Box sx={{ marginLeft: 'auto', display: 'flex', gap: 1 }}>
-                                <Button 
+                        </Box>
+                    ) : (
+                        <Button 
+                            variant="contained"
+                            size="small"
+                            sx={{ml: 'auto', textTransform: 'none'}}
+                            disabled={isUploading || dbTables.length === 0 || dbTables.find(t => t.name === selectedTabKey) === undefined}
+                            onClick={() => {
+                                let t = dbTables.find(t => t.name === selectedTabKey);
+                                if (t) {
+                                    handleAddTableToDF(t);
+                                }
+                            }}>
+                            Load Table
+                        </Button>
+                    )}
+                </Box>
+            );
+        })}
+    </Box>;
+
+    let mainContent =  
+        <Box sx={{ display: 'flex', flexDirection: 'column', bgcolor: 'white', flex: 1, overflow: 'hidden', height: '100%' }}>
+            <Box sx={{ display: 'flex', flexDirection: 'row', flex: 1, overflow: 'hidden', minHeight: 0, height: '100%' }}>
+                {/* Button navigation - similar to TableSelectionView */}
+                <Box sx={{ display: 'flex', flexDirection: 'column', px: 1, width: 240, minWidth: 240, maxWidth: 240, overflow: 'hidden', height: '100%' }}>
+                    <Box sx={{ 
+                        display: 'flex',
+                        flexDirection: 'column',
+                        overflowY: 'auto',
+                        overflowX: 'hidden',
+                        flex: 1,
+                        minHeight: 0,
+                        height: '100%',
+                        position: 'relative',
+                        overscrollBehavior: 'contain'
+                    }}>
+                        {/* Available Tables Section - always visible */}
+                        {tableSelectionPanel}
+                    </Box>
+                    {/* Reset Confirmation Popover */}
+                    <Popover
+                        open={Boolean(resetAnchorEl)}
+                        anchorEl={resetAnchorEl}
+                        onClose={() => setResetAnchorEl(null)}
+                        anchorOrigin={{
+                            vertical: 'bottom',
+                            horizontal: 'left',
+                        }}
+                        transformOrigin={{
+                            vertical: 'top',
+                            horizontal: 'left',
+                        }}
+                    >
+                        <Box sx={{ p: 1.5, width: '240px' }}>
+                            <Typography variant="body2" sx={{ mb: 1.5, fontSize: '12px' }}>
+                                Reset backend database and delete all tables? This cannot be undone.
+                            </Typography>
+                            <Box sx={{ display: 'flex', gap: 1, justifyContent: 'flex-end' }}>
+                                <Button
                                     size="small"
-                                    color={showingAnalysis ? "secondary" : "primary"}
-                                    onClick={() => toggleAnalysisView(currentTable.name)}
-                                    startIcon={<AnalyticsIcon fontSize="small" />}
-                                    sx={{textTransform: "none"}}
+                                    onClick={() => setResetAnchorEl(null)}
+                                    sx={{ textTransform: 'none', fontSize: '12px', minWidth: 'auto', px: 0.75, py: 0.25, minHeight: '24px' }}
                                 >
-                                    {showingAnalysis ? "show data samples" : "show column stats"}
+                                    Cancel
                                 </Button>
-                                <IconButton 
-                                    size="small" 
+                                <Button
+                                    size="small"
                                     color="error"
-                                    onClick={() => handleDropTable(currentTable.name)}
-                                    title="Drop Table"
+                                    variant="contained"
+                                    onClick={async () => {
+                                        setResetAnchorEl(null);
+                                        await handleDBReset();
+                                    }}
+                                    sx={{ textTransform: 'none', fontSize: '12px', minWidth: 'auto', px: 0.75, py: 0.25, minHeight: '24px' }}
                                 >
-                                    <DeleteIcon fontSize="small" />
-                                </IconButton>
+                                    Reset
+                                </Button>
                             </Box>
                         </Box>
-                        {showingAnalysis ? (
-                            <TableStatisticsView 
-                                tableName={currentTable.name}
-                                columnStats={tableAnalysisMap[currentTable.name] ?? []}
-                            />
-                        ) : (
-                            <CustomReactTable 
-                                rows={currentTable.sample_rows.map((row: any) => {
-                                    return Object.fromEntries(Object.entries(row).map(([key, value]: [string, any]) => {
-                                        return [key, String(value)];
-                                    }));
-                                }).slice(0, 9)} 
-                                columnDefs={currentTable.columns.map(col => ({
-                                    id: col.name,
-                                    label: col.name,
-                                    minWidth: 60
-                                }))}
-                                rowsPerPageNum={-1}
-                                compact={false}
-                                isIncompleteTable={currentTable.row_count > 10}
-                            />
-                        )}
-                    </Paper>
-                    <Button 
-                        variant="contained"
-                        size="small"
-                        sx={{ml: 'auto'}}
-                        disabled={isUploading || dbTables.length === 0 || dbTables.find(t => t.name === selectedTabKey) === undefined}
-                        onClick={() => {
-                            let t = dbTables.find(t => t.name === selectedTabKey);
-                            if (t) {
-                                handleAddTableToDF(t);
-                                setTableDialogOpen(false);
-                            }
-                        }}>
-                        Load Table
-                    </Button>
+                    </Popover>
                 </Box>
-            );
-        })}
-    </Box>;
-
-    let mainContent =  
-        <Box sx={{ display: 'flex', flexDirection: 'row', minHeight: 400, borderRadius: 2, width: 'fit-content', bgcolor: 'white' }}>
-            {/* Button navigation - similar to TableSelectionView */}
-            <Box sx={{ display: 'flex', flexDirection: 'column', px: 1, borderRight: 1, borderColor: 'divider' }}>
-                <Box sx={{ 
-                    minWidth: 180, 
-                    display: 'flex',
-                    flexDirection: 'row',
-                    flexWrap: 'nowrap',
-                    overflowY: 'auto',
-                    flexGrow: 1
-                }}>
-                    {/* External Data Loaders Section */}
-                    {dataLoaderPanel}
-                    {/* Available Tables Section */}
-                    {tableSelectionPanel}
+                {/* Content area - show connector view if a connector is selected, otherwise show table view */}
+                <Box sx={{ flex: 1, overflow: 'hidden', minWidth: 0, minHeight: 0, height: '100%', position: 'relative' }}>
+                    {selectedDataLoader !== "" ? dataConnectorView : tableView}
                 </Box>
-                <Typography variant="caption" sx={{ mr: 'auto', mt: 'auto', mb: 1, textWrap: 'wrap', '& .MuiButton-root': { minWidth: 'auto',  textTransform: "none" } }}>
-                    {importButton(<Typography component="span" fontSize="inherit">Import</Typography>)}
-                    ,
-                    {exportButton}
-                    or
-                    <Button
-                        variant="text" size="small"
-                        color="warning"
-                        onClick={handleDBReset}
-                        disabled={isUploading}
-                        //endIcon={<RestartAltIcon />}
-                    >
-                        reset
-                    </Button>
-                    the backend database
-                </Typography>
             </Box>
-            {/* Content area - using conditional rendering instead of TabPanel */}
-            {tableView}
         </Box>  
 
     return (
-        <>
-            {buttonElement && (
-                <Tooltip 
-                    title={serverConfig.DISABLE_DATABASE ? (
-                        <Typography sx={{ fontSize: '11px' }}>
-                            Install Data Formulator locally to use database. <br />
-                            Link: <Link 
-                                href="https://github.com/microsoft/data-formulator" 
-                                target="_blank" 
-                                rel="noopener noreferrer"
-                                sx={{ color: 'inherit', textDecoration: 'underline' }}
-                                onClick={(e) => e.stopPropagation()}
-                            >
-                                https://github.com/microsoft/data-formulator
-                            </Link>
-                    </Typography>
-                ) : ""}
-                    placement="top"
-                >
-                    <span style={{cursor: serverConfig.DISABLE_DATABASE ? 'help' : 'pointer'}}>
-                        <Button variant="text" sx={{fontSize: "inherit", gap: 1}} disabled={serverConfig.DISABLE_DATABASE} onClick={() => {
-                            setTableDialogOpen(true);
-                            onOpen?.();
-                        }}>
-                            {buttonElement}
-                        </Button>
-                    </span>
-                </Tooltip>
+        <Box sx={{ position: 'relative', display: 'flex', flexDirection: 'column', height: '100%', width: '100%' }}>
+            {mainContent}
+            {isUploading && (
+                <Box sx={{ 
+                    position: 'absolute', 
+                    top: 0, 
+                    left: 0, 
+                    width: '100%', 
+                    height: '100%', 
+                    display: 'flex', 
+                    alignItems: 'center', 
+                    justifyContent: 'center',
+                    backgroundColor: 'rgba(255, 255, 255, 0.7)',
+                    zIndex: 1000
+                }}>
+                    <CircularProgress size={60} thickness={5} />
+                </Box>
             )}
-            <Dialog
-                key="db-table-selection-dialog" 
-                onClose={() => {setTableDialogOpen(false)}} 
-                open={tableDialogOpen}
-                sx={{ '& .MuiDialog-paper': { maxWidth: '100%', maxHeight: 800, minWidth: 800 } }}
-            >
-                <DialogTitle sx={{display: "flex" }} >
-                    Database
-                    <IconButton
-                        sx={{marginLeft: "auto"}}
-                        edge="start"
-                        size="small"
-                        color="inherit"
-                        aria-label="close"
-                        onClick={() => setTableDialogOpen(false)}
-                    >
-                        <CloseIcon fontSize="inherit"/>
-                    </IconButton>
-                </DialogTitle>
-                <DialogContent  sx={{p: 1, position: "relative"}}>
-                    {mainContent}
-                    {isUploading && (
-                        <Box sx={{ 
-                            position: 'absolute', 
-                            top: 0, 
-                            left: 0, 
-                            width: '100%', 
-                            height: '100%', 
-                            display: 'flex', 
-                            alignItems: 'center', 
-                            justifyContent: 'center',
-                            backgroundColor: 'rgba(255, 255, 255, 0.7)',
-                            zIndex: 1000
-                        }}>
-                            <CircularProgress size={60} thickness={5} />
-                        </Box>
-                    )}
-                </DialogContent>
-            </Dialog>
-        </>
+        </Box>
     );
   
 }
@@ -1040,8 +1127,6 @@ export const DataLoaderForm: React.FC<{
     let [tableFilter, setTableFilter] = useState<string>("");
     const [selectedTables, setSelectedTables] = useState<Set<string>>(new Set());
 
-    const [displayAuthInstructions, setDisplayAuthInstructions] = useState(false);
-
     let [isConnecting, setIsConnecting] = useState(false);
 
     const toggleDisplaySamples = (tableName: string) => {
@@ -1049,7 +1134,7 @@ export const DataLoaderForm: React.FC<{
     }
 
     let tableMetadataBox = [
-        <TableContainer component={Paper} sx={{maxHeight: 360, overflowY: "auto"}} >
+        <TableContainer component={Box} sx={{borderTop: '1px solid rgba(0, 0, 0, 0.1)', maxHeight: 340, overflowY: "auto"}} >
             <Table sx={{ minWidth: 650 }} size="small" aria-label="simple table">
             <TableBody>
                 {Object.entries(tableMetadata).map(([tableName, metadata]) => {
@@ -1058,17 +1143,32 @@ export const DataLoaderForm: React.FC<{
                         key={tableName}
                         sx={{ 
                             '&:last-child td, &:last-child th': { border: 0 }, 
-                            '& .MuiTableCell-root': { padding: 0.25, wordWrap: 'break-word', whiteSpace: 'normal' },
+                            '& .MuiTableCell-root': { 
+                                borderBottom: displaySamples[tableName] ? 'none' : '1px solid rgba(0, 0, 0, 0.1)',
+                                padding: 0.25, wordWrap: 'break-word', whiteSpace: 'normal'},
                             backgroundColor: selectedTables.has(tableName) ? 'action.selected' : 'inherit',
-                            '&:hover': { backgroundColor: selectedTables.has(tableName) ? 'action.selected' : 'action.hover' }
+                            '&:hover': { backgroundColor: selectedTables.has(tableName) ? 'action.selected' : 'action.hover' },
+                            cursor: 'pointer',
+                        }}
+                        onClick={() => {
+                            const newSelected = new Set(selectedTables);
+                            if (newSelected.has(tableName)) {
+                                newSelected.delete(tableName);
+                            } else {
+                                newSelected.add(tableName);
+                            }
+                            setSelectedTables(newSelected);
                         }}
                     >
-                        <TableCell sx={{borderBottom: displaySamples[tableName] ? 'none' : '1px solid rgba(0, 0, 0, 0.1)'}}>
-                            <IconButton size="small" onClick={() => toggleDisplaySamples(tableName)}>
+                        <TableCell>
+                            <IconButton size="small" onClick={(e) => {
+                                e.stopPropagation();
+                                toggleDisplaySamples(tableName);
+                            }}>
                                 {displaySamples[tableName] ? <ExpandLessIcon /> : <ExpandMoreIcon />}
                             </IconButton>
                         </TableCell>
-                        <TableCell sx={{maxWidth: 240, borderBottom: displaySamples[tableName] ? 'none' : '1px solid rgba(0, 0, 0, 0.1)'}} component="th" scope="row">
+                        <TableCell sx={{maxWidth: 240}} component="th" scope="row">
                             {tableName} <Typography variant="caption" sx={{color: "text.secondary"}} fontSize={10}>
                                 ({metadata.row_count > 0 ? `${metadata.row_count} rows × ` : ""}{metadata.columns.length} cols)
                             </Typography>
@@ -1078,19 +1178,10 @@ export const DataLoaderForm: React.FC<{
                                 <Chip key={column.name} label={column.name} sx={{fontSize: 11, margin: 0.25, height: 20}} size="small" />
                             ))}
                         </TableCell>
-                        <TableCell sx={{width: 40}} padding="checkbox">
+                        <TableCell sx={{width: 40}}>
                             <Checkbox
                                 size="small"
                                 checked={selectedTables.has(tableName)}
-                                onChange={(e) => {
-                                    const newSelected = new Set(selectedTables);
-                                    if (e.target.checked) {
-                                        newSelected.add(tableName);
-                                    } else {
-                                        newSelected.delete(tableName);
-                                    }
-                                    setSelectedTables(newSelected);
-                                }}
                             />
                         </TableCell>
                     </TableRow>,
@@ -1098,7 +1189,7 @@ export const DataLoaderForm: React.FC<{
                         <TableCell colSpan={4} sx={{ paddingBottom: 0, paddingTop: 0, px: 0, maxWidth: 800, overflowX: "auto", 
                                          borderBottom: displaySamples[tableName] ? '1px solid rgba(0, 0, 0, 0.1)' : 'none' }}>
                         <Collapse in={displaySamples[tableName]} timeout="auto" unmountOnExit>
-                            <Box sx={{ px: 1, py: 0.5}}>
+                            <Card variant="outlined" sx={{ ml: 5, my: 1}}>
                                 <CustomReactTable rows={metadata.sample_rows.slice(0, 9).map((row: any) => {
                                     return Object.fromEntries(Object.entries(row).map(([key, value]: [string, any]) => {
                                         return [key, String(value)];
@@ -1109,7 +1200,7 @@ export const DataLoaderForm: React.FC<{
                                 compact={false} 
                                 isIncompleteTable={metadata.row_count > 10}
                                 />
-                            </Box>
+                            </Card>
                         </Collapse>
                         </TableCell>
                     </TableRow>]
@@ -1117,11 +1208,13 @@ export const DataLoaderForm: React.FC<{
                 </TableBody>
                 </Table>
             </TableContainer>,
-        Object.keys(tableMetadata).length > 0 && <Box sx={{ display: 'flex', justifyContent: 'flex-end', mt: 1 }}>
+        Object.keys(tableMetadata).length > 0 && <Box sx={{ display: 'flex', justifyContent: 'center', mt: 1 }}>
             <Button 
-                variant="contained" 
+                variant="outlined" 
+                color="secondary"
                 size="small"
                 disabled={selectedTables.size === 0}
+                sx={{ textTransform: 'none' }}
                 onClick={() => {
                     const tablesToImport = Array.from(selectedTables);
                     onImport();
@@ -1146,7 +1239,13 @@ export const DataLoaderForm: React.FC<{
                             const errors = results.filter(r => r.status !== "success");
                             if (errors.length === 0) {
                                 setSelectedTables(new Set());
-                                onFinish("success", `Successfully imported ${tablesToImport.length} table(s)`, tablesToImport);
+                                // Get the actual table names that were created (may be sanitized)
+                                const actualTableNames = results
+                                    .filter(r => r.status === "success" && r.table_name)
+                                    .map(r => r.table_name);
+                                // Fallback to original names if actual names not provided
+                                const finalTableNames = actualTableNames.length > 0 ? actualTableNames : tablesToImport;
+                                onFinish("success", `Successfully imported ${tablesToImport.length} table(s)`, finalTableNames);
                             } else {
                                 onFinish("error", `Failed to import some tables: ${errors.map(e => e.error).join(", ")}`);
                             }
@@ -1157,13 +1256,18 @@ export const DataLoaderForm: React.FC<{
                         });
                 }}
             >
-                Import Selected ({selectedTables.size})
+                Import Selected Tables ({selectedTables.size})
             </Button>
         </Box>
     ]
 
+    const isConnected = Object.keys(tableMetadata).length > 0;
+
     return (
         <Box sx={{p: 0}}>
+            <Typography sx={{fontSize: 16, flex: 1}}>
+                Import tables from <Typography component="span" sx={{ fontSize: 'inherit', color: 'secondary.main', fontWeight: 'bold'}}>{dataLoaderType}</Typography>
+            </Typography>
             {isConnecting && <Box sx={{
                 position: "absolute", top: 0, left: 0, width: "100%", height: "100%", 
                 display: "flex", alignItems: "center", justifyContent: "center", zIndex: 1000,
@@ -1171,130 +1275,237 @@ export const DataLoaderForm: React.FC<{
             }}>
                 <CircularProgress size={20} />
             </Box>}
-            <Typography variant="body2" sx={{}}>
-                Data Connector (<Typography component="span" sx={{color: "secondary.main", fontWeight: "bold"}}>{dataLoaderType}</Typography>)
-            </Typography>
-            <Box sx={{display: "flex", flexDirection: "row", flexWrap: "wrap", gap: 1, ml: 4, mt: 2}}>
-                {paramDefs.map((paramDef) => (
-                    <Box key={paramDef.name}>
-                        <TextField
-                            disabled={Object.keys(tableMetadata).length > 0}
-                            sx={{width: "270px", 
-                                '& .MuiInputLabel-root': {fontSize: 14},
-                                '& .MuiInputBase-root': {fontSize: 14},
-                                '& .MuiInputBase-input::placeholder': {fontSize: 12, fontStyle: "italic"}
-                            }}
-                            variant="standard"
-                            size="small"
-                            required={paramDef.required}
-                            key={paramDef.name}
-                            label={paramDef.name}
-                            value={params[paramDef.name] ?? ''}
-                            placeholder={paramDef.default ? `e.g. ${paramDef.default}` : paramDef.description}
-                            onChange={(event: any) => { 
-                                dispatch(dfActions.updateDataLoaderConnectParam({
-                                    dataLoaderType, paramName: paramDef.name, 
-                                    paramValue: event.target.value}));
-                            }}
-                            slotProps={{
-                                inputLabel: {shrink: true}
-                            }}
-                        />
+            {isConnected ? (
+                // Connected state: show connection parameters and disconnect button
+                <Box sx={{mt: 2}}>
+                    <Box sx={{mb: 2}}>
+                        <Box sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 1, mb: 2, flexWrap: "wrap"}}>
+                            <Box sx={{flex: 1, minWidth: 200, display: "flex", flexDirection: "row", alignItems: "center", gap: 1.5, flexWrap: "wrap"}}>
+                                {paramDefs.filter((paramDef) => params[paramDef.name]).map((paramDef, index) => (
+                                    <Box key={paramDef.name} sx={{display: "flex", alignItems: "center", gap: 0.5}}>
+                                        <Typography variant="body2" component="span" sx={{fontSize: 13, color: 'text.secondary', fontWeight: 500}}>
+                                            {paramDef.name}:
+                                        </Typography>
+                                        <Typography variant="body2" component="span" sx={{fontSize: 13, color: 'text.primary'}}>
+                                            {params[paramDef.name] || '(empty)'}
+                                        </Typography>
+                                        {index < paramDefs.filter((paramDef) => params[paramDef.name]).length - 1 && (
+                                            <Typography variant="body2" component="span" sx={{fontSize: 13, color: 'text.secondary', mx: 0.5}}>
+                                                •
+                                            </Typography>
+                                        )}
+                                    </Box>
+                                ))}
+                            </Box>
+                        </Box>
+                        <Box sx={{display: "flex", flexDirection: "row", gap: 1}}>
+                            <Box sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 1, width: "calc(40% - 1rem)"}}>
+                                <Box sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 0.5, minWidth: "70px"}}>
+                                    <SearchIcon sx={{ fontSize: 12, color: theme.palette.secondary.main }} />
+                                    <Typography 
+                                        sx={{
+                                            fontSize: 12,
+                                            fontWeight: 400,
+                                            color: theme.palette.secondary.main
+                                        }}
+                                    >
+                                        table filter
+                                    </Typography>
+                                </Box>
+                                <TextField
+                                    sx={{
+                                        flex: 1,
+                                        '& .MuiInputBase-root': {fontSize: 12, height: '32px'},
+                                        '& .MuiInputBase-input': {fontSize: 12, py: 0.75},
+                                        '& .MuiInputBase-input::placeholder': {fontSize: 11, fontStyle: "italic"},
+                                        '& .MuiOutlinedInput-root': {
+                                            '& fieldset': {borderColor: theme.palette.secondary.main},
+                                            '&:hover fieldset': {borderColor: theme.palette.secondary.dark},
+                                        }
+                                    }}
+                                    variant="outlined"
+                                    size="small"
+                                    color="secondary"
+                                    autoComplete="off"
+                                    placeholder="load only tables containing keywords"
+                                    value={tableFilter}
+                                    onChange={(event) => setTableFilter(event.target.value)}
+                                />
+                            </Box>
+                            <Box sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 1}}>
+                                <Button
+                                    variant="outlined"
+                                    size="small"
+                                    sx={{textTransform: "none"}}
+                                    onClick={() => {
+                                        setIsConnecting(true);
+                                        fetch(getUrls().DATA_LOADER_LIST_TABLES, {
+                                            method: 'POST',
+                                            headers: {
+                                                'Content-Type': 'application/json',
+                                            },
+                                            body: JSON.stringify({
+                                                data_loader_type: dataLoaderType, 
+                                                data_loader_params: params,
+                                                table_filter: tableFilter.trim() || null
+                                            })
+                                    }).then(response => response.json())
+                                    .then(data => {
+                                        if (data.status === "success") {
+                                            console.log(data.tables);
+                                            setTableMetadata(Object.fromEntries(data.tables.map((table: any) => {
+                                                return [table.name, table.metadata];
+                                            })));
+                                        } else {
+                                            console.error('Failed to fetch data loader tables: {}', data.message);
+                                            onFinish("error", `Failed to fetch data loader tables: ${data.message}`);
+                                        }
+                                        setIsConnecting(false);
+                                    })
+                                    .catch(error => {
+                                        onFinish("error", `Failed to fetch data loader tables, please check the server is running`);
+                                        setIsConnecting(false);
+                                    });
+                                    }}
+                                >
+                                    Refresh
+                                </Button>
+                                <Button
+                                    variant="outlined"
+                                    size="small"
+                                    sx={{textTransform: "none"}}
+                                    onClick={() => {
+                                        setTableMetadata({});
+                                        setTableFilter("");
+                                    }}
+                                >
+                                    Disconnect
+                                </Button>
+                            </Box>
+                        </Box>
                     </Box>
-                ))}
-                <TextField
-                    size="small"
-                    color="secondary"
-                    sx={{width: "270px", 
-                        '& .MuiInputLabel-root': {fontSize: 14, color: theme.palette.secondary.main},
-                        '& .MuiInputBase-root': {fontSize: 14},
-                        '& .MuiInputBase-input::placeholder': {fontSize: 12, fontStyle: "italic"},
-                        '&:hover': {
-                            backgroundColor: alpha(theme.palette.secondary.main, 0.03),
-                        },
-                    }}
-                    key="table-filter"
-                    autoComplete="off"
-                    variant="standard"
-                    label={<Box sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 0.5}}>
-                        <SearchIcon sx={{ fontSize: 16, color: theme.palette.secondary.main }} />
-                        table filter
-                    </Box>}
-                    placeholder="load only tables containing keywords"
-                    value={tableFilter}
-                    onChange={(event) => setTableFilter(event.target.value)}
-                    slotProps={{
-                        inputLabel: {shrink: true},
-                    }}
-                />
-                {paramDefs.length > 0 && <ButtonGroup sx={{height: 32, mt: 'auto'}} size="small" 
-                 variant="contained" color="primary">
-                    <Button 
-                        sx={{textTransform: "none"}}
-                        onClick={() => {
-                            setIsConnecting(true);
-                            setDisplayAuthInstructions(false);
-                            fetch(getUrls().DATA_LOADER_LIST_TABLES, {
-                                method: 'POST',
-                                headers: {
-                                    'Content-Type': 'application/json',
-                                },
-                                body: JSON.stringify({
-                                    data_loader_type: dataLoaderType, 
-                                    data_loader_params: params,
-                                    table_filter: tableFilter.trim() || null
+                    
+                    {tableMetadataBox}
+                </Box>
+            ) : (
+                // Not connected: show connection forms
+                <>
+                    <Box sx={{display: "flex", flexDirection: "row", flexWrap: "wrap", gap: 1, mt: 2}}>
+                        {paramDefs.map((paramDef) => (
+                            <Box key={paramDef.name} 
+                                sx={{display: "flex", flexDirection: "row", mr: 1,alignItems: "center", gap: 1, width: "calc(50% - 1rem)"}}>
+                                <Typography 
+                                    sx={{
+                                        minWidth: "70px",
+                                        fontSize: 12,
+                                        fontWeight: paramDef.required ? 500 : 400,
+                                        color: paramDef.required ? 'text.primary' : 'text.secondary'
+                                    }}
+                                >
+                                    {paramDef.name}
+                                    {paramDef.required && <span style={{color: 'red'}}> *</span>}
+                                </Typography>
+                                <TextField
+                                    sx={{
+                                        flex: 1,
+                                        '& .MuiInputBase-root': {fontSize: 12, height: '32px'},
+                                        '& .MuiInputBase-input': {fontSize: 12, py: 0.75},
+                                        '& .MuiInputBase-input::placeholder': {fontSize: 11, fontStyle: "italic"}
+                                    }}
+                                    variant="outlined"
+                                    size="small"
+                                    required={paramDef.required}
+                                    value={params[paramDef.name] ?? ''}
+                                    placeholder={paramDef.default ? `e.g. ${paramDef.default}` : paramDef.description}
+                                    onChange={(event: any) => { 
+                                        dispatch(dfActions.updateDataLoaderConnectParam({
+                                            dataLoaderType, paramName: paramDef.name, 
+                                            paramValue: event.target.value}));
+                                    }}
+                                />
+                            </Box>
+                        ))}
+                        <Box sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 1, width: "calc(50% - 1rem)", mr: 1}}>
+                            <Box sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 0.5, minWidth: "70px"}}>
+                                <SearchIcon sx={{ fontSize: 12, color: theme.palette.secondary.main }} />
+                                <Typography 
+                                    sx={{
+                                        fontSize: 12,
+                                        fontWeight: 400,
+                                        color: theme.palette.secondary.main
+                                    }}
+                                >
+                                    table filter
+                                </Typography>
+                            </Box>
+                            <TextField
+                                sx={{
+                                    flex: 1,
+                                    '& .MuiInputBase-root': {fontSize: 12, height: '32px'},
+                                    '& .MuiInputBase-input': {fontSize: 12, py: 0.75},
+                                    '& .MuiInputBase-input::placeholder': {fontSize: 11, fontStyle: "italic"},
+                                    '& .MuiOutlinedInput-root': {
+                                        '& fieldset': {borderColor: theme.palette.secondary.main},
+                                        '&:hover fieldset': {borderColor: theme.palette.secondary.dark},
+                                    }
+                                }}
+                                variant="outlined"
+                                size="small"
+                                color="secondary"
+                                autoComplete="off"
+                                placeholder="load only tables containing keywords"
+                                value={tableFilter}
+                                onChange={(event) => setTableFilter(event.target.value)}
+                            />
+                        </Box>
+                        {paramDefs.length > 0 && <ButtonGroup sx={{height: 32, mt: 'auto'}} size="small" 
+                         variant="contained" color="primary">
+                            <Button 
+                                sx={{textTransform: "none"}}
+                                onClick={() => {
+                                    setIsConnecting(true);
+                                    fetch(getUrls().DATA_LOADER_LIST_TABLES, {
+                                        method: 'POST',
+                                        headers: {
+                                            'Content-Type': 'application/json',
+                                        },
+                                        body: JSON.stringify({
+                                            data_loader_type: dataLoaderType, 
+                                            data_loader_params: params,
+                                            table_filter: tableFilter.trim() || null
+                                        })
+                                }).then(response => response.json())
+                                .then(data => {
+                                    if (data.status === "success") {
+                                        console.log(data.tables);
+                                        setTableMetadata(Object.fromEntries(data.tables.map((table: any) => {
+                                            return [table.name, table.metadata];
+                                        })));
+                                    } else {
+                                        console.error('Failed to fetch data loader tables: {}', data.message);
+                                        onFinish("error", `Failed to fetch data loader tables: ${data.message}`);
+                                    }
+                                    setIsConnecting(false);
                                 })
-                        }).then(response => response.json())
-                        .then(data => {
-                            if (data.status === "success") {
-                                console.log(data.tables);
-                                setTableMetadata(Object.fromEntries(data.tables.map((table: any) => {
-                                    return [table.name, table.metadata];
-                                })));
-                            } else {
-                                console.error('Failed to fetch data loader tables: {}', data.message);
-                                onFinish("error", `Failed to fetch data loader tables: ${data.message}`);
-                            }
-                            setIsConnecting(false);
-                        })
-                        .catch(error => {
-                            onFinish("error", `Failed to fetch data loader tables, please check the server is running`);
-                            setIsConnecting(false);
-                        });
-                    }}>
-                        {Object.keys(tableMetadata).length > 0 ? "refresh" : "connect"} {tableFilter.trim() ? "with filter" : ""}
-                    </Button>
-                    <Button 
-                        disabled={Object.keys(tableMetadata).length === 0}
-                        sx={{textTransform: "none"}}                        onClick={() => {
-                            setTableMetadata({});
-                            setTableFilter("");
-                        }}>
-                        disconnect
-                    </Button>
-                </ButtonGroup>}
-
-            </Box>            
-            <Box  sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 1, ml: 4, mt: 4}}>
-                
-            </Box>
-            <Button
-                variant="text" 
-                size="small" 
-                sx={{textTransform: "none", height: 32, mt: 1}}
-                onClick={() => setDisplayAuthInstructions(!displayAuthInstructions)}>
-                {displayAuthInstructions ? "hide" : "show"} authentication instructions
-            </Button>
-            {<Collapse in={displayAuthInstructions} timeout="auto" unmountOnExit>
-                <Paper sx={{px: 1, py: 0.5, maxHeight: 300, overflowY: "auto"}}>
-                    <Typography variant="body2" sx={{fontSize: 12, whiteSpace: "pre-wrap", p: 1}}>
+                                .catch(error => {
+                                    onFinish("error", `Failed to fetch data loader tables, please check the server is running`);
+                                    setIsConnecting(false);
+                                });
+                            }}>
+                                connect {tableFilter.trim() ? "with filter" : ""}
+                            </Button>
+                        </ButtonGroup>}
+                    </Box>
+                    <Box  sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 1, ml: 4, mt: 4}}>
+                        
+                    </Box>
+                    <Typography variant="body2" sx={{
+                        color: "text.secondary",
+                        fontSize: 12, overflowY: "auto", whiteSpace: "pre-wrap", p: 1}}>
                         {authInstructions.trim()}
                     </Typography>
-                </Paper>
-                </Collapse>
-            }
-            
-            {Object.keys(tableMetadata).length > 0 && tableMetadataBox }
+                </>
+            )}
         </Box>
     );
 }
\ No newline at end of file
diff --git a/src/views/UnifiedDataUploadDialog.tsx b/src/views/UnifiedDataUploadDialog.tsx
index ab9e55d..17b8558 100644
--- a/src/views/UnifiedDataUploadDialog.tsx
+++ b/src/views/UnifiedDataUploadDialog.tsx
@@ -9,7 +9,6 @@ import {
     Dialog,
     DialogContent,
     DialogTitle,
-    DialogActions,
     IconButton,
     TextField,
     Typography,
@@ -19,6 +18,7 @@ import {
     Input,
     alpha,
     useTheme,
+    Divider,
 } from '@mui/material';
 
 import CloseIcon from '@mui/icons-material/Close';
@@ -29,14 +29,9 @@ import StorageIcon from '@mui/icons-material/Storage';
 import ImageSearchIcon from '@mui/icons-material/ImageSearch';
 import ExploreIcon from '@mui/icons-material/Explore';
 import RestartAltIcon from '@mui/icons-material/RestartAlt';
-import RefreshIcon from '@mui/icons-material/Refresh';
 import DeleteIcon from '@mui/icons-material/Delete';
-import AnalyticsIcon from '@mui/icons-material/Analytics';
-import CleaningServicesIcon from '@mui/icons-material/CleaningServices';
-import SearchIcon from '@mui/icons-material/Search';
 import ArrowBackIcon from '@mui/icons-material/ArrowBack';
 import Paper from '@mui/material/Paper';
-import CircularProgress from '@mui/material/CircularProgress';
 
 import { useDispatch, useSelector } from 'react-redux';
 import { DataFormulatorState, dfActions, fetchFieldSemanticType } from '../app/dfSlice';
@@ -47,8 +42,7 @@ import { DataLoadingChat } from './DataLoadingChat';
 import { DatasetSelectionView, DatasetMetadata } from './TableSelectionView';
 import { getUrls } from '../app/utils';
 import { CustomReactTable } from './ReactTable';
-import { Type } from '../data/types';
-import { TableStatisticsView, DataLoaderForm, handleDBDownload } from './DBTableManager';
+import { DBManagerPane } from './DBTableManager';
 
 export type UploadTabType = 'menu' | 'upload' | 'paste' | 'url' | 'database' | 'extract' | 'explore';
 
@@ -137,6 +131,17 @@ const PreviewPanel: React.FC<PreviewPanelProps> = ({
                 <Typography variant="body2" sx={{ fontWeight: 600 }}>
                     {title}
                 </Typography>
+                {onRemoveTable && previewTables && previewTables.length > 0 && (
+                    <IconButton
+                        size="small"
+                        color="error"
+                        onClick={() => onRemoveTable(activeIndex)}
+                        sx={{ ml: 'auto' }}
+                        aria-label="Remove table"
+                    >
+                        <DeleteIcon fontSize="small" />
+                    </IconButton>
+                )}
             </Box>
 
             {loading && <LinearProgress />}
@@ -231,16 +236,6 @@ const PreviewPanel: React.FC<PreviewPanelProps> = ({
                                         ? ` • ${activeTable.displayId || activeTable.id}`
                                         : ''}
                                 </Typography>
-                                {onRemoveTable && previewTables.length > 1 && (
-                                    <IconButton
-                                        size="small"
-                                        color="error"
-                                        onClick={() => onRemoveTable(activeIndex)}
-                                        sx={{ ml: 'auto' }}
-                                    >
-                                        <DeleteIcon fontSize="small" />
-                                    </IconButton>
-                                )}
                             </Box>
                             <CustomReactTable
                                 rows={activeTable.rows.slice(0, 12)}
@@ -384,14 +379,10 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
     const [showFullContent, setShowFullContent] = useState<boolean>(false);
     const [isOverSizeLimit, setIsOverSizeLimit] = useState<boolean>(false);
     
-    // URL tab state
+    // URL input state (merged into file upload)
     const [tableURL, setTableURL] = useState<string>("");
-    const [urlPreviewTable, setUrlPreviewTable] = useState<DictTable | null>(null);
-    const [urlPreviewLoading, setUrlPreviewLoading] = useState<boolean>(false);
-    const [urlPreviewError, setUrlPreviewError] = useState<string | null>(null);
-    const [urlPreviewUrl, setUrlPreviewUrl] = useState<string>("");
 
-    // File preview state
+    // File preview state (shared with URL)
     const [filePreviewTables, setFilePreviewTables] = useState<DictTable[] | null>(null);
     const [filePreviewLoading, setFilePreviewLoading] = useState<boolean>(false);
     const [filePreviewError, setFilePreviewError] = useState<string | null>(null);
@@ -412,12 +403,6 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         }
     }, [initialTab, open]);
 
-    useEffect(() => {
-        if (tableURL !== urlPreviewUrl) {
-            setUrlPreviewTable(null);
-            setUrlPreviewError(null);
-        }
-    }, [tableURL, urlPreviewUrl]);
 
     // Load sample datasets
     useEffect(() => {
@@ -483,10 +468,6 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         setIsOverSizeLimit(false);
         setShowFullContent(false);
         setTableURL("");
-        setUrlPreviewTable(null);
-        setUrlPreviewLoading(false);
-        setUrlPreviewError(null);
-        setUrlPreviewUrl("");
         setFilePreviewTables(null);
         setFilePreviewLoading(false);
         setFilePreviewError(null);
@@ -504,6 +485,8 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
             setFilePreviewError(null);
             setFilePreviewTables(null);
             setFilePreviewLoading(true);
+            // Clear URL input when file is uploaded
+            setTableURL("");
 
             const MAX_FILE_SIZE = 5 * 1024 * 1024;
             const previewTables: DictTable[] = [];
@@ -653,19 +636,13 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         }
     };
 
-    // URL submit handler
-    const handleURLSubmit = (): void => {
-        if (urlPreviewTable && urlPreviewUrl === tableURL) {
-            dispatch(dfActions.loadTable(urlPreviewTable));
-            dispatch(fetchFieldSemanticType(urlPreviewTable));
-            handleClose();
-        }
-    };
 
     const handleURLPreview = (): void => {
-        setUrlPreviewLoading(true);
-        setUrlPreviewError(null);
-        setUrlPreviewTable(null);
+        setFilePreviewLoading(true);
+        setFilePreviewError(null);
+        setFilePreviewTables(null);
+        // Clear file preview when URL is loaded
+        setFilePreviewFiles([]);
 
         let parts = tableURL.split('/');
         const baseName = parts[parts.length - 1] || 'dataset';
@@ -686,57 +663,61 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                 }
 
                 if (table) {
-                    setUrlPreviewTable(table);
-                    setUrlPreviewUrl(tableURL);
+                    setFilePreviewTables([table]);
                 } else {
-                    setUrlPreviewError('Unable to parse data from the provided URL.');
+                    setFilePreviewError('Unable to parse data from the provided URL.');
                 }
             })
             .catch(() => {
-                setUrlPreviewError('Failed to fetch data from the URL.');
+                setFilePreviewError('Failed to fetch data from the URL.');
             })
             .finally(() => {
-                setUrlPreviewLoading(false);
+                setFilePreviewLoading(false);
             });
     };
 
     const hasValidUrlSuffix = tableURL.endsWith('.csv') || tableURL.endsWith('.tsv') || tableURL.endsWith(".json");
     const hasMultipleFileTables = (filePreviewTables?.length || 0) > 1;
     const showFilePreview = filePreviewLoading || !!filePreviewError || (filePreviewTables && filePreviewTables.length > 0);
-    const showUrlPreview = urlPreviewLoading || !!urlPreviewError || (urlPreviewTable && urlPreviewUrl === tableURL);
     const hasPasteContent = pasteContent.trim() !== '';
 
     // Data source configurations for the menu
-    const dataSourceConfig = [
+    const regularDataSources = [
         { 
             value: 'explore' as UploadTabType, 
             title: 'Sample Datasets', 
             description: 'Explore and load curated example datasets',
             icon: <ExploreIcon />, 
-            disabled: false 
+            disabled: false,
+            disabledReason: undefined
         },
         { 
             value: 'upload' as UploadTabType, 
             title: 'Upload File', 
-            description: 'Upload CSV, TSV, JSON, or Excel files from your computer',
+            description: 'Upload structured data (CSV, TSV, JSON, Excel) from files or URLs',
             icon: <UploadFileIcon />, 
-            disabled: serverConfig.DISABLE_FILE_UPLOAD,
-            disabledReason: 'File upload is disabled in this environment'
+            disabled: false,
+            disabledReason: undefined
         },
         { 
             value: 'paste' as UploadTabType, 
             title: 'Paste Data', 
             description: 'Paste tabular data directly from clipboard',
             icon: <ContentPasteIcon />, 
-            disabled: false 
+            disabled: false,
+            disabledReason: undefined
         },
         { 
-            value: 'url' as UploadTabType, 
-            title: 'From URL', 
-            description: 'Load data from a web URL (CSV, TSV, or JSON)',
-            icon: <LinkIcon />, 
-            disabled: false 
+            value: 'extract' as UploadTabType, 
+            title: 'Extract from Documents', 
+            description: 'Extract tables from images, PDFs, or documents using AI',
+            icon: <ImageSearchIcon />, 
+            disabled: false,
+            disabledReason: undefined
         },
+    ];
+
+    const databaseDataSources = [
         { 
             value: 'database' as UploadTabType, 
             title: 'Database', 
@@ -745,15 +726,11 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
             disabled: serverConfig.DISABLE_DATABASE,
             disabledReason: 'Database connection is disabled in this environment'
         },
-        { 
-            value: 'extract' as UploadTabType, 
-            title: 'Extract from Documents', 
-            description: 'Extract tables from images, PDFs, or documents using AI',
-            icon: <ImageSearchIcon />, 
-            disabled: false 
-        },
     ];
 
+    // Combined config for finding tab titles
+    const dataSourceConfig = [...regularDataSources, ...databaseDataSources];
+
     // Get current tab title for header
     const getCurrentTabTitle = () => {
         const tab = dataSourceConfig.find(t => t.value === activeTab);
@@ -769,7 +746,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                 '& .MuiDialog-paper': { 
                     width: 1100,
                     maxWidth: '95vw',
-                    height: 700, 
+                    height: 600, 
                     maxHeight: '90vh',
                     display: 'flex',
                     flexDirection: 'column',
@@ -824,21 +801,50 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                         <Box sx={{ 
                             width: '100%',
                             maxWidth: 860,
-                            display: 'grid', 
-                            gridTemplateColumns: 'repeat(2, minmax(0, 1fr))',
-                            gap: 1.5,
+                            display: 'flex',
+                            flexDirection: 'column',
+                            gap: 2,
                         }}>
-                            {dataSourceConfig.map((source) => (
-                                <DataSourceCard
-                                    key={source.value}
-                                    icon={source.icon}
-                                    title={source.title}
-                                    description={source.description}
-                                    onClick={() => setActiveTab(source.value)}
-                                    disabled={source.disabled}
-                                    disabledReason={source.disabledReason}
-                                />
-                            ))}
+                            {/* Regular Data Sources Group */}
+                            <Box sx={{ 
+                                display: 'grid', 
+                                gridTemplateColumns: 'repeat(2, minmax(0, 1fr))',
+                                gap: 1.5,
+                            }}>
+                                {regularDataSources.map((source) => (
+                                    <DataSourceCard
+                                        key={source.value}
+                                        icon={source.icon}
+                                        title={source.title}
+                                        description={source.description}
+                                        onClick={() => setActiveTab(source.value)}
+                                        disabled={source.disabled}
+                                        disabledReason={source.disabledReason}
+                                    />
+                                ))}
+                            </Box>
+
+                            {/* Divider */}
+                            <Divider sx={{ my: 1 }} />
+
+                            {/* Database Data Sources Group */}
+                            <Box sx={{ 
+                                display: 'grid', 
+                                gridTemplateColumns: 'repeat(2, minmax(0, 1fr))',
+                                gap: 1.5,
+                            }}>
+                                {databaseDataSources.map((source) => (
+                                    <DataSourceCard
+                                        key={source.value}
+                                        icon={source.icon}
+                                        title={source.title}
+                                        description={source.description}
+                                        onClick={() => setActiveTab(source.value)}
+                                        disabled={source.disabled}
+                                        disabledReason={source.disabledReason}
+                                    />
+                                ))}
+                            </Box>
                         </Box>
                     </Box>
                 </TabPanel>
@@ -852,9 +858,9 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                         boxSizing: 'border-box',
                         gap: 2,
                         p: 2,
-                        justifyContent: 'center',
+                        justifyContent: showFilePreview ? 'flex-start' : 'center',
                     }}>
-                        <Box sx={{ width: '100%', maxWidth: 760, alignSelf: 'center', display: 'flex', flexDirection: 'column', gap: 2 }}>
+                        <Box sx={{ width: '100%', maxWidth: showFilePreview ? '100%' : 760, alignSelf: 'center', display: 'flex', flexDirection: 'column', gap: 2 }}>
                         <Input
                             inputProps={{ 
                                 accept: '.csv,.tsv,.json,.xlsx,.xls',
@@ -883,32 +889,79 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                 </Typography>
                             </Box>
                         ) : (
-                            <Box
-                                sx={{
-                                    border: '2px dashed',
-                                    borderColor: 'divider',
-                                    borderRadius: 2,
-                                    p: 3,
-                                    textAlign: 'center',
-                                    cursor: 'pointer',
-                                    transition: 'all 0.2s',
-                                    '&:hover': {
-                                        borderColor: 'primary.main',
-                                        backgroundColor: alpha(theme.palette.primary.main, 0.04),
-                                    }
-                                }}
-                                onClick={() => fileInputRef.current?.click()}
-                            >
-                                <UploadFileIcon sx={{ fontSize: 36, color: 'text.secondary', mb: 1 }} />
-                                <Typography variant="subtitle1" gutterBottom>
-                                    Click to upload or drag and drop
-                                </Typography>
-                                <Typography variant="body2" color="text.secondary">
-                                    Supported formats: CSV, TSV, JSON, Excel (xlsx, xls)
-                                </Typography>
-                                <Typography variant="caption" color="text.secondary" sx={{ mt: 1, display: 'block' }}>
-                                    Maximum file size: 5MB (use Database tab for larger files)
-                                </Typography>
+                            <Box sx={{ 
+                                display: 'flex', 
+                                flexDirection: showFilePreview ? 'row' : 'column',
+                                gap: 2,
+                                alignItems: showFilePreview ? 'flex-start' : 'stretch',
+                            }}>
+                                <Box
+                                    sx={{
+                                        border: '2px dashed',
+                                        borderColor: 'divider',
+                                        borderRadius: 2,
+                                        p: showFilePreview ? 2 : 3,
+                                        textAlign: 'center',
+                                        cursor: 'pointer',
+                                        transition: 'all 0.2s',
+                                        flex: showFilePreview ? '0 0 45%' : '1',
+                                        minWidth: showFilePreview ? 0 : 'auto',
+                                        '&:hover': {
+                                            borderColor: 'primary.main',
+                                            backgroundColor: alpha(theme.palette.primary.main, 0.04),
+                                        }
+                                    }}
+                                    onClick={() => fileInputRef.current?.click()}
+                                >
+                                    <UploadFileIcon sx={{ fontSize: showFilePreview ? 28 : 36, color: 'text.secondary', mb: 1 }} />
+                                    <Typography variant={showFilePreview ? "body2" : "subtitle1"} gutterBottom>
+                                        Drag & drop file here
+                                    </Typography>
+                                    <Typography variant="body2" color="text.secondary" sx={{ fontSize: showFilePreview ? '0.75rem' : '0.875rem' }}>
+                                        or <Link component="button" sx={{ textDecoration: 'underline', cursor: 'pointer' }}>Browse</Link>
+                                    </Typography>
+                                    {!showFilePreview && (
+                                        <Typography variant="caption" color="text.secondary" sx={{ mt: 1, display: 'block' }}>
+                                            Supported: CSV, TSV, JSON, Excel (xlsx, xls)
+                                        </Typography>
+                                    )}
+                                </Box>
+
+                                {/* URL Input Section */}
+                                <Box sx={{ 
+                                    display: 'flex', 
+                                    alignItems: 'center', 
+                                    gap: 1,
+                                    flex: showFilePreview ? '1' : '0 0 auto',
+                                    minWidth: showFilePreview ? 0 : 'auto',
+                                }}>
+                                    <TextField
+                                        fullWidth
+                                        placeholder="Load a CSV, TSV, or JSON file from a URL, e.g. https://example.com/data.json"
+                                        value={tableURL}
+                                        onChange={(e) => setTableURL(e.target.value.trim())}
+                                        error={tableURL !== "" && !hasValidUrlSuffix}
+                                        size="small"
+                                        sx={{ 
+                                            flex: 1,
+                                            '& .MuiInputBase-input': {
+                                                fontSize: '0.75rem',
+                                            },
+                                            '& .MuiInputBase-input::placeholder': {
+                                                fontSize: '0.75rem',
+                                            },
+                                        }}
+                                    />
+                                    <Button
+                                        variant="outlined"
+                                        size="small"
+                                        onClick={handleURLPreview}
+                                        disabled={!hasValidUrlSuffix || filePreviewLoading}
+                                        sx={{ textTransform: 'none', whiteSpace: 'nowrap' }}
+                                    >
+                                        Preview
+                                    </Button>
+                                </Box>
                             </Box>
                         )}
 
@@ -933,7 +986,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                     disabled={serverConfig.DISABLE_FILE_UPLOAD || filePreviewLoading}
                                     sx={{ textTransform: 'none' }}
                                 >
-                                    {hasMultipleFileTables ? 'Load Files' : 'Load File'}
+                                    {hasMultipleFileTables ? 'Load Tables' : 'Load Table'}
                                 </Button>
                             </Box>
                         )}
@@ -941,77 +994,6 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                     </Box>
                 </TabPanel>
 
-                {/* URL Tab */}
-                <TabPanel value={activeTab} index="url">
-                    <Box sx={{
-                        display: 'flex',
-                        flexDirection: 'column',
-                        height: '100%',
-                        boxSizing: 'border-box',
-                        gap: 2,
-                        p: 2,
-                        justifyContent: 'center',
-                    }}>
-                        <Box sx={{ width: '100%', maxWidth: 760, alignSelf: 'center', display: 'flex', flexDirection: 'column', gap: 2 }}>
-                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1 }}>
-                                <TextField
-                                    fullWidth
-                                    label="Data URL"
-                                    placeholder="https://example.com/data.csv"
-                                    value={tableURL}
-                                    onChange={(e) => setTableURL(e.target.value.trim())}
-                                    error={tableURL !== "" && !hasValidUrlSuffix}
-                                    size="small"
-                                />
-                                <Button
-                                    variant="outlined"
-                                    size="small"
-                                    onClick={handleURLPreview}
-                                    disabled={!hasValidUrlSuffix || urlPreviewLoading}
-                                    sx={{ textTransform: 'none', whiteSpace: 'nowrap' }}
-                                >
-                                    Preview
-                                </Button>
-                            </Box>
-
-                            {tableURL !== "" && !hasValidUrlSuffix && (
-                                <Typography variant="caption" color="error">
-                                    URL should link to a .csv, .tsv, or .json file.
-                                </Typography>
-                            )}
-
-                            <Typography variant="caption" color="text.secondary">
-                                Supported URLs: direct links to .csv, .tsv, or .json files.
-                            </Typography>
-
-                            {showUrlPreview && (
-                                <PreviewPanel
-                                    title="Preview"
-                                    loading={urlPreviewLoading}
-                                    error={urlPreviewError}
-                                    table={urlPreviewUrl === tableURL ? urlPreviewTable : null}
-                                    emptyLabel="Click Preview to fetch a sample."
-                                    meta={urlPreviewTable && urlPreviewUrl === tableURL ? `${urlPreviewTable.rows.length} rows × ${urlPreviewTable.names.length} columns` : undefined}
-                                />
-                            )}
-
-                            {urlPreviewTable && urlPreviewUrl === tableURL && (
-                                <Box sx={{ display: 'flex', justifyContent: 'center', gap: 1 }}>
-                                    <Button
-                                        variant="contained"
-                                        size="small"
-                                        onClick={handleURLSubmit}
-                                        disabled={!hasValidUrlSuffix}
-                                        sx={{ textTransform: 'none' }}
-                                    >
-                                        Load from URL
-                                    </Button>
-                                </Box>
-                            )}
-                        </Box>
-                    </Box>
-                </TabPanel>
-
                 {/* Paste Data Tab */}
                 <TabPanel value={activeTab} index="paste">
                     <Box sx={{
@@ -1121,7 +1103,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                             </Typography>
                         </Box>
                     ) : (
-                        <DatabaseTabContent onClose={handleClose} />
+                        <DBManagerPane />
                     )}
                 </TabPanel>
 
@@ -1164,559 +1146,4 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
     );
 };
 
-interface DBTable {
-    name: string;
-    columns: { name: string; type: string; }[];
-    row_count: number;
-    sample_rows: any[];
-    view_source: string | null;
-}
-
-interface ColumnStatistics {
-    column: string;
-    type: string;
-    statistics: {
-        count: number;
-        unique_count: number;
-        null_count: number;
-        min?: number;
-        max?: number;
-        avg?: number;
-    };
-}
-
-// Separate component for Database tab content
-const DatabaseTabContent: React.FC<{ onClose: () => void }> = ({ onClose }) => {
-    const theme = useTheme();
-    const dispatch = useDispatch<AppDispatch>();
-    const sessionId = useSelector((state: DataFormulatorState) => state.sessionId);
-    const tables = useSelector((state: DataFormulatorState) => state.tables);
-    const serverConfig = useSelector((state: DataFormulatorState) => state.serverConfig);
-
-    const [dbTables, setDbTables] = React.useState<DBTable[]>([]);
-    const [selectedTabKey, setSelectedTabKey] = React.useState("");
-    const [isUploading, setIsUploading] = React.useState<boolean>(false);
-    const [tableAnalysisMap, setTableAnalysisMap] = React.useState<Record<string, ColumnStatistics[] | null>>({});
-    const [dataLoaderMetadata, setDataLoaderMetadata] = React.useState<Record<string, {
-        params: {name: string, default: string, type: string, required: boolean, description: string}[], 
-        auth_instructions: string}>>({});
-
-    const setSystemMessage = (content: string, severity: "error" | "warning" | "info" | "success") => {
-        dispatch(dfActions.addMessages({
-            "timestamp": Date.now(),
-            "component": "DB manager",
-            "type": severity,
-            "value": content
-        }));
-    };
-
-    React.useEffect(() => {
-        fetchTables();
-        fetchDataLoaders();
-    }, []);
-
-    React.useEffect(() => {
-        if (!selectedTabKey.startsWith("dataLoader:") && dbTables.length == 0) {
-            setSelectedTabKey("");
-        } else if (!selectedTabKey.startsWith("dataLoader:") && dbTables.find(t => t.name === selectedTabKey) == undefined) {
-            if (dbTables.length > 0) {
-                setSelectedTabKey(dbTables[0].name);
-            }
-        }
-    }, [dbTables]);
-
-    const fetchTables = async () => {
-        if (serverConfig.DISABLE_DATABASE) return;
-        try {
-            const response = await fetch(getUrls().LIST_TABLES);
-            const data = await response.json();
-            if (data.status === 'success') {
-                setDbTables(data.tables);
-            }
-        } catch (error) {
-            setSystemMessage('Failed to fetch tables, please check if the server is running', "error");
-        }
-    };
-
-    const fetchDataLoaders = async () => {
-        fetch(getUrls().DATA_LOADER_LIST_DATA_LOADERS, {
-            method: 'GET',
-            headers: { 'Content-Type': 'application/json' },
-        })
-        .then(response => response.json())
-        .then(data => {
-            if (data.status === "success") {
-                setDataLoaderMetadata(data.data_loaders);
-            }
-        })
-        .catch(error => {
-            console.error('Failed to fetch data loader params:', error);
-        });
-    };
-
-    const handleDBFileUpload = async (event: React.ChangeEvent<HTMLInputElement>) => {
-        const file = event.target.files?.[0];
-        if (!file) return;
-    
-        const formData = new FormData();
-        formData.append('file', file);
-        formData.append('table_name', file.name.split('.')[0]);
-    
-        try {
-            setIsUploading(true);
-            const response = await fetch(getUrls().CREATE_TABLE, {
-                method: 'POST',
-                body: formData
-            });
-            const data = await response.json();
-            if (data.status === 'success') {
-                if (data.is_renamed) {
-                    setSystemMessage(`Table ${data.original_name} already exists. Renamed to ${data.table_name}`, "warning");
-                } 
-                fetchTables();
-            } else {
-                setSystemMessage(data.error || 'Failed to upload table', "error");
-            }
-        } catch (error) {
-            setSystemMessage('Failed to upload table, please check if the server is running', "error");
-        } finally {
-            setIsUploading(false);
-            if (event.target) {
-                event.target.value = '';
-            }
-        }
-    };
-
-    const handleDropTable = async (tableName: string) => {
-        if (tables.some(t => t.id === tableName)) {
-            if (!confirm(`Are you sure you want to delete ${tableName}? \n ${tableName} is currently loaded and will be removed from the database.`)) return;
-        }
-
-        try {
-            const response = await fetch(getUrls().DELETE_TABLE, {
-                method: 'POST',
-                headers: { 'Content-Type': 'application/json' },
-                body: JSON.stringify({ table_name: tableName })
-            });
-            const data = await response.json();
-            if (data.status === 'success') {
-                fetchTables();
-                setSelectedTabKey(dbTables.length > 0 ? dbTables[0].name : "");
-            } else {
-                setSystemMessage(data.error || 'Failed to delete table', "error");
-            }
-        } catch (error) {
-            setSystemMessage('Failed to delete table, please check if the server is running', "error");
-        }
-    };
-
-    const handleAnalyzeData = async (tableName: string) => {
-        if (!tableName) return;
-        if (tableAnalysisMap[tableName]) return;
-        
-        try {
-            const response = await fetch(getUrls().GET_COLUMN_STATS, {
-                method: 'POST',
-                headers: { 'Content-Type': 'application/json' },
-                body: JSON.stringify({ table_name: tableName })
-            });
-            const data = await response.json();
-            if (data.status === 'success') {
-                setTableAnalysisMap(prevMap => ({
-                    ...prevMap,
-                    [tableName]: data.statistics
-                }));
-            }
-        } catch (error) {
-            setSystemMessage('Failed to analyze table data', "error");
-        }
-    };
-
-    const toggleAnalysisView = (tableName: string) => {
-        if (tableAnalysisMap[tableName]) {
-            setTableAnalysisMap(prevMap => {
-                const newMap = { ...prevMap };
-                delete newMap[tableName];
-                return newMap;
-            });
-        } else {
-            handleAnalyzeData(tableName);
-        }
-    };
-
-    const handleAddTableToDF = (dbTable: DBTable) => {
-        const convertSqlTypeToAppType = (sqlType: string): Type => {
-            sqlType = sqlType.toUpperCase();
-            if (sqlType.includes('INT') || sqlType === 'BIGINT' || sqlType === 'SMALLINT' || sqlType === 'TINYINT') {
-                return Type.Integer;
-            } else if (sqlType.includes('FLOAT') || sqlType.includes('DOUBLE') || sqlType.includes('DECIMAL') || sqlType.includes('NUMERIC') || sqlType.includes('REAL')) {
-                return Type.Number;
-            } else if (sqlType.includes('BOOL')) {
-                return Type.Boolean;
-            } else if (sqlType.includes('DATE') || sqlType.includes('TIME') || sqlType.includes('TIMESTAMP')) {
-                return Type.Date;
-            } else {
-                return Type.String;
-            }
-        };
-
-        let table: DictTable = {
-            id: dbTable.name,
-            displayId: dbTable.name,
-            names: dbTable.columns.map((col: any) => col.name),
-            metadata: dbTable.columns.reduce((acc: Record<string, {type: Type, semanticType: string, levels: any[]}>, col: any) => ({
-                ...acc,
-                [col.name]: {
-                    type: convertSqlTypeToAppType(col.type),
-                    semanticType: "",
-                    levels: []
-                }
-            }), {}),
-            rows: dbTable.sample_rows,
-            virtual: {
-                tableId: dbTable.name,
-                rowCount: dbTable.row_count,
-            },
-            anchored: true,
-            createdBy: 'user',
-            attachedMetadata: ''
-        }
-        dispatch(dfActions.loadTable(table));
-        dispatch(fetchFieldSemanticType(table));
-        onClose();
-    };
-
-    const handleCleanDerivedViews = async () => {
-        let unreferencedViews = dbTables.filter(t => t.view_source !== null && t.view_source !== undefined && !tables.some(t2 => t2.id === t.name));
-
-        if (unreferencedViews.length > 0) {
-            if (confirm(`Are you sure you want to delete the following unreferenced derived views? \n${unreferencedViews.map(v => `- ${v.name}`).join("\n")}`)) {
-                let deletedViews = [];
-                for (let view of unreferencedViews) {
-                    try {
-                        const response = await fetch(getUrls().DELETE_TABLE, {
-                            method: 'POST',
-                            headers: { 'Content-Type': 'application/json' },
-                            body: JSON.stringify({ table_name: view.name })
-                        });
-                        const data = await response.json();
-                        if (data.status === 'success') {
-                            deletedViews.push(view.name);
-                        }
-                    } catch (error) {
-                        setSystemMessage('Failed to delete table', "error");
-                    }
-                }
-                if (deletedViews.length > 0) {
-                    setSystemMessage(`Deleted ${deletedViews.length} unreferenced derived views`, "success");
-                }
-                fetchTables();
-            }
-        }
-    };
-
-    const handleDBReset = async () => {
-        try {
-            const response = await fetch(getUrls().RESET_DB_FILE, { method: 'POST' });
-            const data = await response.json();
-            if (data.status === 'success') {
-                fetchTables();
-            } else {
-                setSystemMessage(data.error || 'Failed to reset database', "error");
-            }
-        } catch (error) {
-            setSystemMessage('Failed to reset database', "error");
-        }
-    };
-
-    const handleDBUpload = async (event: React.ChangeEvent<HTMLInputElement>) => {
-        const file = event.target.files?.[0];
-        if (!file) return;
-    
-        const formData = new FormData();
-        formData.append('file', file);
-    
-        try {
-            setIsUploading(true);
-            const response = await fetch(getUrls().UPLOAD_DB_FILE, {
-                method: 'POST',
-                body: formData
-            });
-            const data = await response.json();
-            if (data.status === 'success') {
-                fetchTables();
-            } else {
-                setSystemMessage(data.error || 'Failed to upload database', "error");
-            }
-        } catch (error) {
-            setSystemMessage('Failed to upload database', "error");
-        } finally {
-            setIsUploading(false);
-        }
-    };
-
-    const hasDerivedViews = dbTables.filter(t => t.view_source !== null).length > 0;
-
-    const dataLoaderPanel = (
-        <Box sx={{ p: 1, display: 'flex', flexDirection: 'column', backgroundColor: alpha(theme.palette.secondary.main, 0.02) }}>
-            <Box sx={{ display: 'flex', alignItems: 'center', px: 1, mb: 1 }}>
-                <Typography variant="caption" sx={{ color: "text.disabled", fontWeight: "500", flexGrow: 1, fontSize: "0.75rem" }}>
-                    Data Connectors
-                </Typography>
-            </Box>
-            
-            {["file upload", ...Object.keys(dataLoaderMetadata ?? {})].map((dataLoaderType) => (
-                <Button
-                    key={`dataLoader:${dataLoaderType}`}
-                    variant="text"
-                    size="small"
-                    onClick={() => setSelectedTabKey('dataLoader:' + dataLoaderType)}
-                    color='secondary'
-                    sx={{
-                        textTransform: "none",
-                        width: 120,
-                        justifyContent: 'flex-start',
-                        textAlign: 'left',
-                        borderRadius: 0,
-                        py: 0.5,
-                        px: 2,
-                        color: selectedTabKey === 'dataLoader:' + dataLoaderType ? 'secondary.main' : 'text.secondary',
-                        borderRight: selectedTabKey === 'dataLoader:' + dataLoaderType ? 2 : 0,
-                        borderColor: 'secondary.main',
-                    }}
-                >
-                    <Typography fontSize='inherit' sx={{ textTransform: "none", width: "calc(100% - 4px)", textAlign: 'left', textOverflow: 'ellipsis', overflow: 'hidden', whiteSpace: 'nowrap' }}>
-                        {dataLoaderType}
-                    </Typography>
-                </Button>
-            ))}
-        </Box>
-    );
-
-    const tableSelectionPanel = (
-        <Box sx={{ px: 0.5, pt: 1, display: 'flex', flexDirection: 'column', backgroundColor: alpha(theme.palette.primary.main, 0.02) }}>
-            <Box sx={{ display: 'flex', alignItems: 'center', px: 1, mb: 1 }}>
-                <Typography variant="caption" sx={{ color: "text.disabled", fontWeight: "500", flexGrow: 1, fontSize: "0.75rem" }}>
-                    Data Tables
-                </Typography>
-                <Tooltip title="refresh the table list">
-                    <IconButton size="small" color="primary" sx={{ '&:hover': { transform: 'rotate(180deg)' }, transition: 'transform 0.3s ease-in-out' }} onClick={fetchTables}>
-                        <RefreshIcon sx={{ fontSize: 14 }} />
-                    </IconButton>
-                </Tooltip>
-            </Box>
-            
-            {dbTables.length == 0 && 
-                <Typography variant="caption" sx={{ color: "lightgray", px: 2, py: 0.5, fontStyle: "italic" }}>
-                    no tables available
-                </Typography>
-            }
-            
-            {dbTables.filter(t => t.view_source === null).map((t) => (
-                <Button
-                    key={t.name}
-                    variant="text"
-                    size="small"
-                    color='primary'
-                    onClick={() => setSelectedTabKey(t.name)}
-                    sx={{
-                        textTransform: "none",
-                        width: 160,
-                        justifyContent: 'flex-start',
-                        textAlign: 'left',
-                        borderRadius: 0,
-                        py: 0.5,
-                        px: 2,
-                        color: selectedTabKey === t.name ? 'primary.main' : 'text.secondary',
-                        borderRight: selectedTabKey === t.name ? 2 : 0,
-                    }}
-                >
-                    <Typography fontSize='inherit' sx={{ width: "calc(100% - 4px)", textAlign: 'left', textOverflow: 'ellipsis', overflow: 'hidden', whiteSpace: 'nowrap' }}>
-                        {t.name}
-                    </Typography>
-                </Button>
-            ))}
-            
-            {hasDerivedViews && (
-                <Box sx={{ mt: 2, display: 'flex', flexDirection: 'column' }}>
-                    <Box sx={{ display: 'flex', alignItems: 'center', px: 1, mb: 1 }}>
-                        <Typography variant="caption" sx={{ color: "text.disabled", fontWeight: "500", flexGrow: 1, fontSize: "0.75rem" }}>
-                            Derived Views
-                        </Typography>
-                        <Tooltip title="clean up unreferenced derived views">
-                            <IconButton size="small" color="primary" disabled={dbTables.filter(t => t.view_source !== null).length === 0} onClick={handleCleanDerivedViews}>
-                                <CleaningServicesIcon sx={{ fontSize: 14 }} />
-                            </IconButton>
-                        </Tooltip>
-                    </Box>
-                    
-                    {dbTables.filter(t => t.view_source !== null).map((t) => (
-                        <Button
-                            key={t.name}
-                            variant="text"
-                            size="small"
-                            onClick={() => setSelectedTabKey(t.name)}
-                            sx={{
-                                textTransform: "none",
-                                width: 160,
-                                justifyContent: 'flex-start',
-                                textAlign: 'left',
-                                borderRadius: 0,
-                                py: 0.5,
-                                px: 2,
-                                color: selectedTabKey === t.name ? 'primary.main' : 'text.secondary',
-                                borderRight: selectedTabKey === t.name ? 2 : 0,
-                            }}
-                        >
-                            <Typography fontSize='inherit' sx={{ width: "calc(100% - 4px)", textAlign: 'left', textOverflow: 'ellipsis', overflow: 'hidden', whiteSpace: 'nowrap' }}>
-                                {t.name}
-                            </Typography>
-                        </Button>
-                    ))}
-                </Box>
-            )}
-        </Box>
-    );
-
-    const tableView = (
-        <Box sx={{ flex: 1, minWidth: 0, overflow: 'auto', p: 2 }}>
-            {selectedTabKey === '' && (
-                <Typography variant="caption" sx={{ color: "text.secondary", px: 1 }}>
-                    The database is empty, refresh the table list or import some data to get started.
-                </Typography>
-            )}
-            
-            {selectedTabKey === 'dataLoader:file upload' && (
-                <Box sx={{ display: 'flex', flexDirection: 'column', alignItems: 'center', gap: 2, py: 4 }}>
-                    <Tooltip title="upload a csv/xlsx file to the local database">
-                        <Button variant="outlined" component="label" disabled={isUploading}>
-                            <UploadFileIcon sx={{ mr: 1 }} />
-                            {isUploading ? 'Uploading...' : 'Upload CSV/XLSX to Database'}
-                            <input type="file" hidden onChange={handleDBFileUpload} accept=".csv,.xlsx,.json" disabled={isUploading} />
-                        </Button>
-                    </Tooltip>
-                    <Typography variant="caption" color="text.secondary">
-                        Files uploaded here are stored in the database and can handle larger datasets
-                    </Typography>
-                </Box>
-            )}
-            
-            {dataLoaderMetadata && Object.entries(dataLoaderMetadata).map(([dataLoaderType, metadata]) => (
-                selectedTabKey === 'dataLoader:' + dataLoaderType && (
-                    <Box key={`dataLoader:${dataLoaderType}`} sx={{ position: "relative", maxWidth: '100%' }}>
-                        <DataLoaderForm 
-                            key={`data-loader-form-${dataLoaderType}`}
-                            dataLoaderType={dataLoaderType} 
-                            paramDefs={metadata.params}
-                            authInstructions={metadata.auth_instructions}
-                            onImport={() => setIsUploading(true)} 
-                            onFinish={(status, message, importedTables) => {
-                                setIsUploading(false);
-                                fetchTables().then(() => {
-                                    if (status === "success" && importedTables && importedTables.length > 0) {
-                                        setSelectedTabKey(importedTables[0]);
-                                    }
-                                });
-                                if (status === "error") {
-                                    setSystemMessage(message, "error");
-                                }
-                            }} 
-                        />
-                    </Box>
-                )
-            ))}
-            
-            {dbTables.map((t) => {
-                if (selectedTabKey !== t.name) return null;
-                
-                const showingAnalysis = tableAnalysisMap[t.name] !== undefined;
-                return (
-                    <Box key={t.name} sx={{ maxWidth: '100%', overflowX: 'auto', display: 'flex', flexDirection: 'column', gap: 1 }}>
-                        <Paper variant="outlined">
-                            <Box sx={{ px: 1, display: 'flex', alignItems: 'center', borderBottom: '1px solid rgba(0,0,0,0.1)' }}>
-                                <Typography variant="caption">
-                                    {showingAnalysis ? "column stats for " : "sample data from "} 
-                                    <Typography component="span" sx={{ fontSize: 12, fontWeight: "bold" }}>{t.name}</Typography>
-                                    <Typography component="span" sx={{ ml: 1, fontSize: 10, color: "text.secondary" }}>
-                                        ({t.columns.length} columns × {t.row_count} rows)
-                                    </Typography>
-                                </Typography>
-                                <Box sx={{ marginLeft: 'auto', display: 'flex', gap: 1 }}>
-                                    <Button 
-                                        size="small"
-                                        color={showingAnalysis ? "secondary" : "primary"}
-                                        onClick={() => toggleAnalysisView(t.name)}
-                                        startIcon={<AnalyticsIcon fontSize="small" />}
-                                        sx={{ textTransform: "none" }}
-                                    >
-                                        {showingAnalysis ? "show data samples" : "show column stats"}
-                                    </Button>
-                                    <IconButton size="small" color="error" onClick={() => handleDropTable(t.name)} title="Drop Table">
-                                        <DeleteIcon fontSize="small" />
-                                    </IconButton>
-                                </Box>
-                            </Box>
-                            {showingAnalysis ? (
-                                <TableStatisticsView tableName={t.name} columnStats={tableAnalysisMap[t.name] ?? []} />
-                            ) : (
-                                <CustomReactTable 
-                                    rows={t.sample_rows.map((row: any) => Object.fromEntries(Object.entries(row).map(([key, value]: [string, any]) => [key, String(value)]))).slice(0, 9)} 
-                                    columnDefs={t.columns.map(col => ({ id: col.name, label: col.name, minWidth: 60 }))}
-                                    rowsPerPageNum={-1}
-                                    compact={false}
-                                    isIncompleteTable={t.row_count > 10}
-                                />
-                            )}
-                        </Paper>
-                        <Button 
-                            variant="contained"
-                            size="small"
-                            sx={{ ml: 'auto' }}
-                            disabled={isUploading}
-                            onClick={() => handleAddTableToDF(t)}
-                        >
-                            Load Table
-                        </Button>
-                    </Box>
-                );
-            })}
-        </Box>
-    );
-
-    return (
-        <Box sx={{ display: 'flex', flexDirection: 'row', height: '100%', position: 'relative' }}>
-            {isUploading && (
-                <Box sx={{ position: 'absolute', top: 0, left: 0, width: '100%', height: '100%', display: 'flex', alignItems: 'center', justifyContent: 'center', backgroundColor: 'rgba(255, 255, 255, 0.7)', zIndex: 1000 }}>
-                    <CircularProgress size={40} />
-                </Box>
-            )}
-            <Box sx={{ display: 'flex', flexDirection: 'column', borderRight: 1, borderColor: 'divider' }}>
-                <Box sx={{ minWidth: 180, display: 'flex', flexDirection: 'row', flexWrap: 'nowrap', overflowY: 'auto', flexGrow: 1 }}>
-                    {dataLoaderPanel}
-                    {tableSelectionPanel}
-                </Box>
-                <Typography variant="caption" sx={{ mr: 'auto', mt: 'auto', mb: 1, px: 1, textWrap: 'wrap', '& .MuiButton-root': { minWidth: 'auto', textTransform: "none" } }}>
-                    <Tooltip title="import a duckdb .db file">
-                        <Button variant="text" size="small" component="label" disabled={isUploading}>
-                            Import
-                            <input type="file" hidden onChange={handleDBUpload} accept=".db" disabled={isUploading} />
-                        </Button>
-                    </Tooltip>
-                    ,
-                    <Tooltip title="save database to .db file">
-                        <Button variant="text" size="small" onClick={() => handleDBDownload(sessionId ?? '')} disabled={isUploading || dbTables.length === 0}>
-                            Export
-                        </Button>
-                    </Tooltip>
-                    or
-                    <Button variant="text" size="small" color="warning" onClick={handleDBReset} disabled={isUploading}>
-                        Reset
-                    </Button>
-                </Typography>
-            </Box>
-            {tableView}
-        </Box>
-    );
-};
-
 export default UnifiedDataUploadDialog;

From e2bb8cc9e3d7d9cbc804233312ec16fdad96d063 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Sat, 17 Jan 2026 11:14:57 -0800
Subject: [PATCH 07/21] fixes and improvements

---
 src/app/App.tsx                       |  66 +----
 src/app/store.ts                      |   3 +
 src/app/utils.tsx                     | 113 +++++++++
 src/views/DBTableManager.tsx          | 176 +++++++------
 src/views/DataFormulator.tsx          |  11 +-
 src/views/DataLoadingChat.tsx         | 334 ++++++++++++++++---------
 src/views/TableSelectionView.tsx      | 167 +++++++------
 src/views/UnifiedDataUploadDialog.tsx | 346 ++++++++++++++++----------
 8 files changed, 745 insertions(+), 471 deletions(-)

diff --git a/src/app/App.tsx b/src/app/App.tsx
index 1a8707f..209f3ac 100644
--- a/src/app/App.tsx
+++ b/src/app/App.tsx
@@ -65,16 +65,11 @@ import { AppDispatch } from './store';
 import dfLogo from '../assets/df-logo.png';
 import { ModelSelectionButton } from '../views/ModelSelectionDialog';
 import KeyboardArrowDownIcon from '@mui/icons-material/KeyboardArrowDown';
-import ContentPasteIcon from '@mui/icons-material/ContentPaste';
 import UploadFileIcon from '@mui/icons-material/UploadFile';
 import DownloadIcon from '@mui/icons-material/Download';
 import { handleDBDownload } from '../views/DBTableManager';
-import CloudQueueIcon from '@mui/icons-material/CloudQueue';
 import { getUrls } from './utils';
-import { UnifiedDataUploadDialog, UploadTabType } from '../views/UnifiedDataUploadDialog';
-import LinkIcon from '@mui/icons-material/Link';
-import ImageSearchIcon from '@mui/icons-material/ImageSearch';
-import ExploreIcon from '@mui/icons-material/Explore';
+import { UnifiedDataUploadDialog } from '../views/UnifiedDataUploadDialog';
 import ChatIcon from '@mui/icons-material/Chat';
 import { AgentRulesDialog } from '../views/AgentRulesDialog';
 import ArticleIcon from '@mui/icons-material/Article';
@@ -221,78 +216,23 @@ export interface AppFCProps {
 
 // Extract menu components into separate components to prevent full app re-renders
 const TableMenu: React.FC = () => {
-    const [anchorEl, setAnchorEl] = useState<null | HTMLElement>(null);
     const [dialogOpen, setDialogOpen] = useState<boolean>(false);
-    const [initialTab, setInitialTab] = useState<UploadTabType>('menu');
-    const open = Boolean(anchorEl);
-
-    const handleOpenDialog = (tab: UploadTabType) => {
-        setAnchorEl(null);
-        setInitialTab(tab);
-        setDialogOpen(true);
-    };
     
     return (
         <>
             <Button
                 variant="text"
-                onClick={(e) => setAnchorEl(e.currentTarget)}
-                endIcon={<KeyboardArrowDownIcon />}
-                aria-controls={open ? 'add-table-menu' : undefined}
-                aria-haspopup="true"
-                aria-expanded={open ? 'true' : undefined}
+                onClick={() => setDialogOpen(true)}
                 sx={{ textTransform: 'none' }}
             >
                 Data
             </Button>
-            <Menu
-                id="add-table-menu"
-                anchorEl={anchorEl}
-                open={open}
-                onClose={() => setAnchorEl(null)}
-                slotProps={{
-                    paper: { sx: { py: '4px', px: '8px' } }
-                }}
-                aria-labelledby="add-table-button"
-                sx={{ 
-                    '& .MuiMenuItem-root': { padding: '4px 8px' },
-                    '& .MuiTypography-root': { fontSize: 14, display: 'flex', alignItems: 'center', textTransform: 'none', gap: 1 }
-                }}
-            >
-                <MenuItem onClick={() => handleOpenDialog('upload')}>
-                    <Typography fontSize="inherit">
-                        <UploadFileIcon fontSize="inherit" /> upload file <span style={{fontSize: '11px'}}>(csv/json/xlsx)</span>
-                    </Typography>
-                </MenuItem>
-                <MenuItem onClick={() => handleOpenDialog('paste')}>
-                    <Typography fontSize="inherit">
-                        <ContentPasteIcon fontSize="inherit" /> paste data <span style={{fontSize: '11px'}}>(csv/tsv/json)</span>
-                    </Typography>
-                </MenuItem>
-                <Divider />
-                <MenuItem onClick={() => handleOpenDialog('database')}>
-                    <Typography fontSize="inherit">
-                        <CloudQueueIcon fontSize="inherit" /> database
-                    </Typography>
-                </MenuItem>
-                <MenuItem onClick={() => handleOpenDialog('extract')}>
-                    <Typography fontSize="inherit">
-                        <ImageSearchIcon fontSize="inherit" /> extract data <span style={{fontSize: '11px'}}>(image/text)</span>
-                    </Typography>
-                </MenuItem>
-                <Divider />
-                <MenuItem onClick={() => handleOpenDialog('explore')}>
-                    <Typography fontSize="inherit">
-                        <ExploreIcon fontSize="inherit" /> explore samples
-                    </Typography>
-                </MenuItem>
-            </Menu>
             
             {/* Unified Data Upload Dialog */}
             <UnifiedDataUploadDialog 
                 open={dialogOpen}
                 onClose={() => setDialogOpen(false)}
-                initialTab={initialTab}
+                initialTab="menu"
             />
         </>
     );
diff --git a/src/app/store.ts b/src/app/store.ts
index 027f4ac..edc7c72 100644
--- a/src/app/store.ts
+++ b/src/app/store.ts
@@ -26,3 +26,6 @@ let store = configureStore({
 })
 
 export default store;
+
+// Export store instance for use in utilities
+export { store };
diff --git a/src/app/utils.tsx b/src/app/utils.tsx
index aeee817..8ed501c 100644
--- a/src/app/utils.tsx
+++ b/src/app/utils.tsx
@@ -62,6 +62,119 @@ export function getUrls() {
     };
 }
 
+/**
+ * List of API endpoints that require a session ID
+ * These endpoints will automatically fetch session ID if missing
+ */
+const SESSION_REQUIRED_ENDPOINTS = [
+    '/api/tables/upload-db-file',
+    '/api/tables/download-db-file',
+    '/api/tables/reset-db-file',
+    '/api/tables/list-tables',
+    '/api/tables/get-table',
+    '/api/tables/create-table',
+    '/api/tables/delete-table',
+    '/api/tables/analyze',
+    '/api/tables/sample-table',
+    '/api/tables/data-loader/list-tables',
+    '/api/tables/data-loader/ingest-data',
+    '/api/tables/data-loader/view-query-sample',
+    '/api/tables/data-loader/ingest-data-from-query',
+    '/api/tables/refresh-derived-data',
+];
+
+/**
+ * Enhanced fetch wrapper that automatically handles session ID at the app level
+ * If a request fails with "No session ID found" or similar errors,
+ * it will automatically fetch the session ID and retry the request
+ * 
+ * This function can be used as a drop-in replacement for fetch() in components
+ * that have access to Redux dispatch
+ * 
+ * @param url - The URL to fetch
+ * @param options - Fetch options (same as native fetch)
+ * @param dispatch - Redux dispatch function (optional, will try to get from store if not provided)
+ * @returns Promise<Response>
+ */
+export async function fetchWithSession(
+    url: string | URL,
+    options: RequestInit = {},
+    dispatch?: any
+): Promise<Response> {
+    const urlString = typeof url === 'string' ? url : url.toString();
+    
+    // Check if this endpoint requires session ID
+    const requiresSession = SESSION_REQUIRED_ENDPOINTS.some(endpoint => 
+        urlString.includes(endpoint)
+    );
+    
+    // Make the initial request
+    let response = await fetch(url, options);
+    
+    // If the response indicates a session ID issue, try to fetch it and retry
+    if (requiresSession && !response.ok) {
+        try {
+            const errorData = await response.clone().json().catch(() => null);
+            const errorMessage = errorData?.message || errorData?.error || '';
+            
+            // Check if error is related to missing session ID
+            if (errorMessage.toLowerCase().includes('session') && 
+                (errorMessage.toLowerCase().includes('not found') || 
+                 errorMessage.toLowerCase().includes('no session'))) {
+                
+                // Try to get dispatch from store if not provided
+                let dispatchFn = dispatch;
+                if (!dispatchFn) {
+                    try {
+                        const { store } = await import('./store');
+                        dispatchFn = store.dispatch;
+                    } catch (storeError) {
+                        console.error('Failed to access store:', storeError);
+                        // Return the original error response
+                        return response;
+                    }
+                }
+                
+                // Fetch session ID and retry
+                if (dispatchFn) {
+                    try {
+                        const { getSessionId } = await import('./dfSlice');
+                        // Dispatch the thunk and unwrap the result
+                        await dispatchFn(getSessionId()).unwrap();
+                        
+                        // Retry the original request
+                        response = await fetch(url, options);
+                    } catch (sessionError) {
+                        console.error('Failed to fetch session ID:', sessionError);
+                        // Return the original error response
+                    }
+                }
+            }
+        } catch (parseError) {
+            // If we can't parse the error, just return the original response
+        }
+    }
+    
+    return response;
+}
+
+/**
+ * React hook that provides a fetch function with automatic session ID handling
+ * Use this in components instead of native fetch for API calls that require session ID
+ * 
+ * @example
+ * const fetchWithSession = useFetchWithSession();
+ * const response = await fetchWithSession('/api/tables/list-tables');
+ */
+export function useFetchWithSession() {
+    // Dynamic import to avoid circular dependency
+    const { useDispatch } = require('react-redux');
+    const dispatch = useDispatch();
+    
+    return (url: string | URL, options: RequestInit = {}) => 
+        fetchWithSession(url, options, dispatch);
+}
+
 import * as vm from 'vm-browserify';
 import { generateFreshChart } from "./dfSlice";
 
diff --git a/src/views/DBTableManager.tsx b/src/views/DBTableManager.tsx
index 29b4a89..8d09016 100644
--- a/src/views/DBTableManager.tsx
+++ b/src/views/DBTableManager.tsx
@@ -42,7 +42,7 @@ import TableRowsIcon from '@mui/icons-material/TableRows';
 import RefreshIcon from '@mui/icons-material/Refresh';
 import SearchIcon from '@mui/icons-material/Search';
 
-import { getUrls } from '../app/utils';
+import { getUrls, fetchWithSession } from '../app/utils';
 import { CustomReactTable } from './ReactTable';
 import { DictTable } from '../components/ComponentType';
 import { Type } from '../data/types';
@@ -101,16 +101,19 @@ const ViewIcon: React.FC<{ sx?: SxProps }> = ({ sx }) => (
     </Box>
 );
 
-export const handleDBDownload = async (sessionId: string) => {
+export const handleDBDownload = async (sessionId: string, dispatch?: any) => {
     try {
-        const response = await fetch(getUrls().DOWNLOAD_DB_FILE, {
-            method: 'GET',
-        });
+        // Use fetchWithSession which automatically handles session ID if missing
+        const response = await fetchWithSession(
+            getUrls().DOWNLOAD_DB_FILE,
+            { method: 'GET' },
+            dispatch
+        );
         
         // Check if the response is ok
         if (!response.ok) {
             const errorData = await response.json();
-            throw new Error(errorData.error || 'Failed to download database file');
+            throw new Error(errorData.error || errorData.message || 'Failed to download database file');
         }
 
         // Get the blob directly from response
@@ -120,7 +123,7 @@ export const handleDBDownload = async (sessionId: string) => {
         // Create a temporary link element
         const link = document.createElement('a');
         link.href = url;
-        link.download = `df_${sessionId?.slice(0, 4)}.db`;
+        link.download = `df_${sessionId?.slice(0, 4) || 'db'}.db`;
         document.body.appendChild(link);    
         
         // Trigger download
@@ -218,7 +221,7 @@ export const DBManagerPane: React.FC<{
     const fetchTables = async () => {
         if (serverConfig.DISABLE_DATABASE) return;
         try {
-            const response = await fetch(getUrls().LIST_TABLES);
+            const response = await fetchWithSession(getUrls().LIST_TABLES, { method: 'GET' }, dispatch);
             const data = await response.json();
             if (data.status === 'success') {
                 setDbTables(data.tables);
@@ -258,10 +261,10 @@ export const DBManagerPane: React.FC<{
     
         try {
             setIsUploading(true);
-            const response = await fetch(getUrls().UPLOAD_DB_FILE, {
+            const response = await fetchWithSession(getUrls().UPLOAD_DB_FILE, {
                 method: 'POST',
                 body: formData
-            });
+            }, dispatch);
             const data = await response.json();
             if (data.status === 'success') {
                 fetchTables();  // Refresh table list
@@ -286,10 +289,10 @@ export const DBManagerPane: React.FC<{
     
         try {
             setIsUploading(true);
-            const response = await fetch(getUrls().CREATE_TABLE, {
+            const response = await fetchWithSession(getUrls().CREATE_TABLE, {
                 method: 'POST',
                 body: formData
-            });
+            }, dispatch);
             const data = await response.json();
             if (data.status === 'success') {
                 if (data.is_renamed) {
@@ -312,9 +315,9 @@ export const DBManagerPane: React.FC<{
 
     const handleDBReset = async () => {
         try {
-            const response = await fetch(getUrls().RESET_DB_FILE, {
+            const response = await fetchWithSession(getUrls().RESET_DB_FILE, {
                 method: 'POST',
-            });
+            }, dispatch);
             const data = await response.json();
             if (data.status === 'success') {
                 fetchTables();
@@ -334,13 +337,13 @@ export const DBManagerPane: React.FC<{
                 let deletedViews = [];
                 for (let view of unreferencedViews) {
                     try {
-                        const response = await fetch(getUrls().DELETE_TABLE, {
+                        const response = await fetchWithSession(getUrls().DELETE_TABLE, {
                             method: 'POST',
                             headers: {
                                 'Content-Type': 'application/json',
                             },
                             body: JSON.stringify({ table_name: view.name })
-                        });
+                        }, dispatch);
                         const data = await response.json();
                         if (data.status === 'success') {
                             deletedViews.push(view.name);
@@ -367,13 +370,13 @@ export const DBManagerPane: React.FC<{
         }
 
         try {
-            const response = await fetch(getUrls().DELETE_TABLE, {
+            const response = await fetchWithSession(getUrls().DELETE_TABLE, {
                 method: 'POST',
                 headers: {
                     'Content-Type': 'application/json',
                 },
                 body: JSON.stringify({ table_name: tableName })
-            });
+            }, dispatch);
             const data = await response.json();
             if (data.status === 'success') {
                 fetchTables();
@@ -392,13 +395,13 @@ export const DBManagerPane: React.FC<{
         if (tableAnalysisMap[tableName]) return;
 
         try {
-            const response = await fetch(getUrls().GET_COLUMN_STATS, {
+            const response = await fetchWithSession(getUrls().GET_COLUMN_STATS, {
                 method: 'POST',
                 headers: {
                     'Content-Type': 'application/json',
                 },
                 body: JSON.stringify({ table_name: tableName })
-            });
+            }, dispatch);
             const data = await response.json();
             if (data.status === 'success') {
                 // Update the analysis map with the new results
@@ -495,7 +498,6 @@ export const DBManagerPane: React.FC<{
         px: 0.5, pt: 1, 
         display: 'flex', 
         flexDirection: 'column', 
-        backgroundColor: alpha(theme.palette.primary.main, 0.02),
         width: '100%'
     }}>
         {/* Recent Data Loaders */}
@@ -503,7 +505,7 @@ export const DBManagerPane: React.FC<{
                 <Typography variant="caption" sx={{
                     color: "text.disabled",
                     fontSize: "0.75rem",
-                    mb: 1,
+                    my: 1,
                     display: 'block'
                 }}>
                     External Data Loaders
@@ -520,21 +522,20 @@ export const DBManagerPane: React.FC<{
                         key="file upload"
                         label="file"
                         size="small"
+                        variant="outlined"
                         onClick={() => setSelectedDataLoader("file upload")}
                         sx={{
                             fontSize: '0.7rem',
                             height: 20,
                             maxWidth: '100%',
-                            backgroundColor: selectedDataLoader === "file upload" ? alpha(theme.palette.secondary.main, 0.2) : 'transparent',
+                            borderColor: selectedDataLoader === "file upload"
+                                ? theme.palette.secondary.main
+                                : theme.palette.divider,
                             '& .MuiChip-label': {
                                 overflow: 'hidden',
                                 textOverflow: 'ellipsis',
                                 whiteSpace: 'nowrap'
                             },
-                            '&:hover': {
-                                backgroundColor: alpha(theme.palette.secondary.main, 0.12),
-                                cursor: 'pointer'
-                            }
                         }}
                     />
                     {Object.keys(dataLoaderMetadata ?? {})
@@ -543,28 +544,30 @@ export const DBManagerPane: React.FC<{
                                 key={dataLoaderType}
                                 label={dataLoaderType}
                                 size="small"
+                                variant="outlined"
                                 onClick={() => setSelectedDataLoader(dataLoaderType)}
                                 sx={{
                                     fontSize: '0.7rem',
                                     height: 20,
                                     maxWidth: '100%',
-                                    backgroundColor: selectedDataLoader === dataLoaderType ? alpha(theme.palette.secondary.main, 0.2) : 'transparent',
+                                    backgroundColor: selectedDataLoader === dataLoaderType 
+                                        ? alpha(theme.palette.secondary.main, 0.2) 
+                                        : 'transparent',
+                                    borderColor: selectedDataLoader === dataLoaderType
+                                        ? theme.palette.secondary.main
+                                        : theme.palette.divider,
                                     '& .MuiChip-label': {
                                         overflow: 'hidden',
                                         textOverflow: 'ellipsis',
                                         whiteSpace: 'nowrap'
                                     },
-                                    '&:hover': {
-                                        backgroundColor: alpha(theme.palette.secondary.main, 0.12),
-                                        cursor: 'pointer'
-                                    }
                                 }}
                             />
                         ))}
                 </Box>
             </Box>
         
-        <Box sx={{ display: 'flex', alignItems: 'center', justifyContent: 'space-between', px: 1, mb: 1 }}>
+        <Box sx={{ display: 'flex', alignItems: 'center', justifyContent: 'space-between', px: 1, my: 1 }}>
             <Typography variant="caption" sx={{
                 color: "text.disabled", 
                 fontWeight: "500", 
@@ -609,17 +612,6 @@ export const DBManagerPane: React.FC<{
                     <RefreshIcon sx={{ fontSize: 16, mr: 1 }} />
                     Refresh table list
                 </MenuItem>
-                <MenuItem 
-                    onClick={() => {
-                        handleCleanDerivedViews();
-                        setTableMenuAnchorEl(null);
-                    }}
-                    disabled={dbTables.filter(t => t.view_source !== null).length === 0}
-                    dense
-                >
-                    <CleaningServicesIcon sx={{ fontSize: 16, mr: 1 }} />
-                    Clean up derived views
-                </MenuItem>
                 <Divider />
                 <MenuItem 
                     onClick={() => {
@@ -635,7 +627,8 @@ export const DBManagerPane: React.FC<{
                 <MenuItem 
                     onClick={() => {
                         if (!isUploading && dbTables.length > 0) {
-                            handleDBDownload(sessionId ?? '')
+                            // fetchWithSession will automatically handle session ID if missing
+                            handleDBDownload(sessionId ?? '', dispatch)
                                 .catch(error => {
                                     console.error('Failed to download database:', error);
                                     setSystemMessage('Failed to download database file', "error");
@@ -735,36 +728,54 @@ export const DBManagerPane: React.FC<{
         {/* Derived Views Section */}
         {dbTables.filter(t => t.view_source !== null).length > 0 && (
             <Box sx={{ mt: 2, display: 'flex', flexDirection: 'column' }}>
-                <Button
-                    variant="text"
-                    size="small"
-                    onClick={() => setShowViews(!showViews)}
-                    sx={{
-                        textTransform: "none",
-                        width: '100%',
-                        justifyContent: 'flex-start',
-                        textAlign: 'left',
-                        borderRadius: 0,
-                        py: 0.5,
-                        px: 2,
-                        color: 'text.secondary',
-                        minWidth: 0,
-                        '&:hover': {
-                            backgroundColor: alpha(theme.palette.primary.main, 0.08)
-                        }
-                    }}
-                    startIcon={showViews ? <ExpandLessIcon sx={{ fontSize: 16 }} /> : <ExpandMoreIcon sx={{ fontSize: 16 }} />}
-                >
-                    <Typography 
-                        fontSize='0.75rem'
+                <Box sx={{ display: 'flex', alignItems: 'center', width: '100%' }}>
+                    <Button
+                        variant="text"
+                        size="small"
+                        onClick={() => setShowViews(!showViews)}
                         sx={{
+                            textTransform: "none",
                             flex: 1,
-                            minWidth: 0,
+                            justifyContent: 'flex-start',
                             textAlign: 'left',
-                        }}>
-                        Views ({dbTables.filter(t => t.view_source !== null).length})
-                    </Typography>
-                </Button>
+                            borderRadius: 0,
+                            py: 0.5,
+                            px: 2,
+                            color: 'text.secondary',
+                            minWidth: 0,
+                            '&:hover': {
+                                backgroundColor: alpha(theme.palette.primary.main, 0.08)
+                            }
+                        }}
+                        startIcon={showViews ? <ExpandLessIcon sx={{ fontSize: 16 }} /> : <ExpandMoreIcon sx={{ fontSize: 16 }} />}
+                    >
+                        <Typography 
+                            fontSize='0.75rem'
+                            sx={{
+                                flex: 1,
+                                minWidth: 0,
+                                textAlign: 'left',
+                            }}>
+                            Views ({dbTables.filter(t => t.view_source !== null).length})
+                        </Typography>
+                    </Button>
+                    <Tooltip title="Clean up unused views">
+                        <IconButton
+                            size="small"
+                            onClick={handleCleanDerivedViews}
+                            disabled={dbTables.filter(t => t.view_source !== null && t.view_source !== undefined && !tables.some(t2 => t2.id === t.name)).length === 0}
+                            sx={{
+                                padding: 0.5,
+                                mr: 0.5,
+                                '&:hover': {
+                                    backgroundColor: alpha(theme.palette.primary.main, 0.08),
+                                }
+                            }}
+                        >
+                            <CleaningServicesIcon sx={{ fontSize: 16 }} />
+                        </IconButton>
+                    </Tooltip>
+                </Box>
                 <Collapse in={showViews}>
                     <Box sx={{ display: 'flex', flexDirection: 'column' }}>
                         {dbTables.filter(t => t.view_source !== null).map((t, i) => {
@@ -1033,6 +1044,7 @@ export const DBManagerPane: React.FC<{
                         minHeight: 0,
                         height: '100%',
                         position: 'relative',
+                        borderRight: `1px solid ${theme.palette.divider}`,
                         overscrollBehavior: 'contain'
                     }}>
                         {/* Available Tables Section - always visible */}
@@ -1221,7 +1233,7 @@ export const DataLoaderForm: React.FC<{
                     
                     // Import all selected tables sequentially
                     const importPromises = tablesToImport.map(tableName => 
-                        fetch(getUrls().DATA_LOADER_INGEST_DATA, {
+                        fetchWithSession(getUrls().DATA_LOADER_INGEST_DATA, {
                             method: 'POST',
                             headers: {
                                 'Content-Type': 'application/json',
@@ -1231,7 +1243,7 @@ export const DataLoaderForm: React.FC<{
                                 data_loader_params: params, 
                                 table_name: tableName
                             })
-                        }).then(response => response.json())
+                        }, dispatch).then((response: Response) => response.json())
                     );
                     
                     Promise.all(importPromises)
@@ -1339,7 +1351,7 @@ export const DataLoaderForm: React.FC<{
                                     sx={{textTransform: "none"}}
                                     onClick={() => {
                                         setIsConnecting(true);
-                                        fetch(getUrls().DATA_LOADER_LIST_TABLES, {
+                                        fetchWithSession(getUrls().DATA_LOADER_LIST_TABLES, {
                                             method: 'POST',
                                             headers: {
                                                 'Content-Type': 'application/json',
@@ -1349,8 +1361,8 @@ export const DataLoaderForm: React.FC<{
                                                 data_loader_params: params,
                                                 table_filter: tableFilter.trim() || null
                                             })
-                                    }).then(response => response.json())
-                                    .then(data => {
+                                        }, dispatch).then((response: Response) => response.json())
+                                    .then((data: any) => {
                                         if (data.status === "success") {
                                             console.log(data.tables);
                                             setTableMetadata(Object.fromEntries(data.tables.map((table: any) => {
@@ -1362,7 +1374,7 @@ export const DataLoaderForm: React.FC<{
                                         }
                                         setIsConnecting(false);
                                     })
-                                    .catch(error => {
+                                    .catch((error: any) => {
                                         onFinish("error", `Failed to fetch data loader tables, please check the server is running`);
                                         setIsConnecting(false);
                                     });
@@ -1464,7 +1476,7 @@ export const DataLoaderForm: React.FC<{
                                 sx={{textTransform: "none"}}
                                 onClick={() => {
                                     setIsConnecting(true);
-                                    fetch(getUrls().DATA_LOADER_LIST_TABLES, {
+                                    fetchWithSession(getUrls().DATA_LOADER_LIST_TABLES, {
                                         method: 'POST',
                                         headers: {
                                             'Content-Type': 'application/json',
@@ -1474,8 +1486,8 @@ export const DataLoaderForm: React.FC<{
                                             data_loader_params: params,
                                             table_filter: tableFilter.trim() || null
                                         })
-                                }).then(response => response.json())
-                                .then(data => {
+                                    }, dispatch).then((response: Response) => response.json())
+                                .then((data: any) => {
                                     if (data.status === "success") {
                                         console.log(data.tables);
                                         setTableMetadata(Object.fromEntries(data.tables.map((table: any) => {
@@ -1487,7 +1499,7 @@ export const DataLoaderForm: React.FC<{
                                     }
                                     setIsConnecting(false);
                                 })
-                                .catch(error => {
+                                .catch((error: any) => {
                                     onFinish("error", `Failed to fetch data loader tables, please check the server is running`);
                                     setIsConnecting(false);
                                 });
diff --git a/src/views/DataFormulator.tsx b/src/views/DataFormulator.tsx
index 20aa40e..c71aaea 100644
--- a/src/views/DataFormulator.tsx
+++ b/src/views/DataFormulator.tsx
@@ -281,7 +281,16 @@ export const DataFormulatorFC = ({ }) => {
             <Box sx={{my: 4}}>
                 <Typography sx={{ 
                     maxWidth: 1100, fontSize: 32, color: alpha(theme.palette.text.primary, 0.8), 
-                    '& span': { textDecoration: 'underline', textUnderlineOffset: '0.2em', cursor: 'pointer', color: theme.palette.primary.main }}}>
+                    lineHeight: 2,
+                    '& span': { 
+                        textTransform: 'uppercase',
+                        letterSpacing: '0.02em',
+                        textDecoration: 'underline', textUnderlineOffset: '0.2em', 
+                        cursor: 'pointer', color: theme.palette.primary.main,
+                        '&:hover': {
+                            color: theme.palette.primary.dark,
+                        }
+                    }}}>
                     To begin, 
                     {' '}<span onClick={() => openUploadDialog('extract')}>extract</span>{' '}
                     data from images or text documents, load {' '}
diff --git a/src/views/DataLoadingChat.tsx b/src/views/DataLoadingChat.tsx
index 1a014ba..6602149 100644
--- a/src/views/DataLoadingChat.tsx
+++ b/src/views/DataLoadingChat.tsx
@@ -4,7 +4,7 @@
 import * as React from 'react';
 import { useEffect, useRef, useState } from 'react';
 
-import { Box, Button, Divider, IconButton, Typography, Tooltip, CircularProgress } from '@mui/material';
+import { Box, Button, Divider, IconButton, Typography, Tooltip, CircularProgress, alpha, useTheme } from '@mui/material';
 
 
 import { useDispatch, useSelector } from 'react-redux';
@@ -30,7 +30,7 @@ const getUniqueTableName = (baseName: string, existingNames: Set<string>): strin
 };
 
 export const DataLoadingChat: React.FC = () => {
-
+    const theme = useTheme();
     const dispatch = useDispatch<AppDispatch>();
     const inputBoxRef = useRef<(() => void) | null>(null);
     const abortControllerRef = useRef<AbortController | null>(null);
@@ -87,12 +87,6 @@ export const DataLoadingChat: React.FC = () => {
         }
     };
 
-    if (!existOutputBlocks && !streamingContent) {
-        return <Box sx={{ width: 'calc(100% - 32px)', borderRadius: 2, px: 2 }}>
-            <DataLoadingInputBox maxLines={24} onStreamingContentUpdate={setStreamingContent} abortControllerRef={abortControllerRef} />
-        </Box>
-    }
-
     const thinkingBanner = (
         <Box sx={{ 
             py: 0.5, 
@@ -138,129 +132,241 @@ export const DataLoadingChat: React.FC = () => {
         </Box>
     );
 
-    
-    let chatCard = (
-        <Box sx={{ width: (existOutputBlocks || streamingContent) ? '960px' : '640px', minHeight: 400,
-                display: 'flex', flexDirection: 'row', borderRadius: 2 }}>
-            
-            {/* Left: Chat panel */}
-            <Box
-                sx={{
-                    width: 240,
+    // Empty state - centered layout similar to upload dialog
+    if (!existOutputBlocks && !streamingContent) {
+        return (
+            <Box sx={{ 
+                width: '100%', 
+                height: '100%', 
+                display: 'flex', 
+                justifyContent: 'center', 
+                alignItems: 'center',
+                p: 2,
+                boxSizing: 'border-box'
+            }}>
+                <Box sx={{ 
+                    width: '100%',
+                    maxWidth: 720,
                     display: 'flex',
                     flexDirection: 'column',
-                    padding: 1,
-                    position: 'relative'
-                }}
-            >
-                <Box sx={{ flex: 1,  display: 'flex', flexDirection: 'column', minHeight: '480px', 
-                    overflowY: 'auto', overflowX: 'hidden' }}>
-                    {threadsComponent}
+                    gap: 2,
+                }}>
+                    <DataLoadingInputBox 
+                        maxLines={24} 
+                        onStreamingContentUpdate={setStreamingContent} 
+                        abortControllerRef={abortControllerRef} 
+                    />
                 </Box>
-                <DataLoadingInputBox ref={inputBoxRef} maxLines={4} onStreamingContentUpdate={setStreamingContent} abortControllerRef={abortControllerRef} />
             </Box>
+        );
+    }
 
-            <Divider orientation="vertical" flexItem sx={{m: 2, color: 'divider'}} />
-
-            {streamingContent && (
-                <Box
-                    sx={{
-                        flex: 1.4,
-                        minWidth: 480,
-                        maxWidth: 640,
-                        display: 'flex',
-                        flexDirection: 'column',
-                        padding: 1
-                    }}
-                >
-                    {thinkingBanner}
-                    <Typography variant="body2" color="text.secondary" 
-                        sx={{ mt: 4, fontSize: '11px', whiteSpace: 'pre-wrap', overflow: 'clip', maxHeight: '600px', overflowY: 'auto' }}>
-                        {streamingContent.trim()}
-                    </Typography>
-                </Box>
-            )}
-
-            {/* Right: Data preview panel */}
-            {(existOutputBlocks && !streamingContent) && (
-                <Box
-                    sx={{
-                        flex: 1.4,
-                        minWidth: 480,
+    // Main layout with sidebar (similar to DBTablePane)
+    return (
+        <Box sx={{ 
+            display: 'flex', 
+            flexDirection: 'column', 
+            bgcolor: 'white', 
+            flex: 1, 
+            overflow: 'hidden', 
+            height: '100%',
+            width: '100%'
+        }}>
+            <Box sx={{ 
+                display: 'flex', 
+                flexDirection: 'row', 
+                flex: 1, 
+                overflow: 'hidden', 
+                minHeight: 0, 
+                height: '100%' 
+            }}>
+                {/* Left sidebar - Thread list (similar to DBTablePane) */}
+                <Box sx={{ 
+                    display: 'flex', 
+                    flexDirection: 'column', 
+                    width: 240, 
+                    minWidth: 240, 
+                    maxWidth: 240, 
+                    overflow: 'hidden', 
+                    height: '100%',
+                    borderRight: '1px solid',
+                    borderColor: 'divider'
+                }}>
+                    <Box sx={{ 
                         display: 'flex',
                         flexDirection: 'column',
-                        padding: 1
-                    }}
-                >
-                    
-                    <Typography 
-                        sx={{ 
-                            fontSize: 14, 
-                            marginBottom: 1,
-                            fontWeight: 500,
-                            color: 'text.primary',
-                            display: 'flex',
-                            alignItems: 'center',
-                            gap: 0.5
-                        }}
-                        gutterBottom
-                    >
-                        {selectedTable && (
-                            <Typography variant="caption" sx={{ color: 'text.secondary' }}>
-                                {selectedTable?.name}
-                            </Typography>
-                        )}
-                    </Typography>
-                    
-                    <Box 
-                        sx={{
-                            display: 'flex',
-                            flexDirection: 'column',
-                            flex: 1,
-                            gap: 1,
-                            overflow: 'hidden'
-                        }}
-                    >
-                        {selectedTable ? (
-                            <DataPreviewBox />
+                        overflowY: 'auto',
+                        overflowX: 'hidden',
+                        flex: 1,
+                        minHeight: 0,
+                        height: '100%',
+                        position: 'relative',
+                        overscrollBehavior: 'contain',
+                        px: 0.5,
+                        pt: 1
+                    }}>
+                        {threadsComponent.length > 0 ? (
+                            threadsComponent
                         ) : (
-                            <Typography variant="body2" color="text.secondary" sx={{ textAlign: 'center', mt: 4, fontSize: '11px' }}>
-                                No data available
+                            <Typography variant="caption" sx={{ 
+                                color: "text.disabled", 
+                                px: 2, 
+                                py: 0.5, 
+                                fontStyle: "italic",
+                                textAlign: 'center'
+                            }}>
+                                No extraction threads yet
                             </Typography>
                         )}
+                    </Box>
+                    <Box sx={{ 
+                        borderTop: '1px solid',
+                        borderColor: 'divider',
+                        p: 1
+                    }}>
+                        <DataLoadingInputBox 
+                            ref={inputBoxRef} 
+                            maxLines={4} 
+                            onStreamingContentUpdate={setStreamingContent} 
+                            abortControllerRef={abortControllerRef} 
+                        />
+                    </Box>
+                </Box>
 
-                        {/* Bottom submit bar */}
-                        <Box sx={{ mt: 'auto', pt: 1, display: 'flex', flexDirection: 'row', alignItems: 'center', gap: 1, 
-                            '& .MuiButton-root': { textTransform: 'none' } }}>
-                            <Button
-                                variant="contained"
-                                sx={{  }}
-                                onClick={() => {
-                                    if (inputBoxRef.current) {
-                                        inputBoxRef.current();
-                                    }
+                {/* Right content area */}
+                <Box sx={{ 
+                    flex: 1, 
+                    overflow: 'hidden', 
+                    minWidth: 0, 
+                    minHeight: 0, 
+                    height: '100%', 
+                    position: 'relative',
+                    display: 'flex',
+                    flexDirection: 'column'
+                }}>
+                    {streamingContent ? (
+                        <Box
+                            sx={{
+                                display: 'flex',
+                                flexDirection: 'column',
+                                padding: 2,
+                                height: '100%',
+                                overflow: 'auto'
+                            }}
+                        >
+                            {thinkingBanner}
+                            <Typography 
+                                variant="body2" 
+                                color="text.secondary" 
+                                sx={{ 
+                                    mt: 2, 
+                                    fontSize: '11px', 
+                                    whiteSpace: 'pre-wrap', 
+                                    overflow: 'clip', 
+                                    maxHeight: '100%', 
+                                    overflowY: 'auto' 
                                 }}
-                                disabled={!selectedTable || selectedTable.content.type !== 'image_url' || cleanInProgress}
-                                size="small"
                             >
-                                Extract data from image
-                            </Button>
-                            <Button
-                                variant="contained"
-                                sx={{ ml: 'auto' }}
-                                onClick={handleUpload}
-                                disabled={!selectedTable || selectedTable.content.type !== 'csv'}
-                                size="small"
+                                {streamingContent.trim()}
+                            </Typography>
+                        </Box>
+                    ) : existOutputBlocks ? (
+                        <Box
+                            sx={{
+                                display: 'flex',
+                                flexDirection: 'column',
+                                padding: 2,
+                                height: '100%',
+                                overflow: 'hidden'
+                            }}
+                        >
+                            {selectedTable && (
+                                <Typography 
+                                    sx={{ 
+                                        fontSize: 14, 
+                                        marginBottom: 1,
+                                        fontWeight: 500,
+                                        color: 'text.primary',
+                                        display: 'flex',
+                                        alignItems: 'center',
+                                        gap: 0.5
+                                    }}
+                                    gutterBottom
+                                >
+                                    {selectedTable?.name}
+                                </Typography>
+                            )}
+                            
+                            <Box 
+                                sx={{
+                                    display: 'flex',
+                                    flexDirection: 'column',
+                                    flex: 1,
+                                    gap: 1,
+                                    overflow: 'hidden',
+                                    minHeight: 0
+                                }}
                             >
-                                Load table
-                            </Button>
+                                {selectedTable ? (
+                                    <Box sx={{ flex: 1, overflow: 'auto', minHeight: 0 }}>
+                                        <DataPreviewBox />
+                                    </Box>
+                                ) : (
+                                    <Box sx={{ 
+                                        display: 'flex', 
+                                        alignItems: 'center', 
+                                        justifyContent: 'center',
+                                        flex: 1,
+                                        minHeight: 0
+                                    }}>
+                                        <Typography variant="body2" color="text.secondary" sx={{ textAlign: 'center', fontSize: '11px' }}>
+                                            Select a table from the left to preview
+                                        </Typography>
+                                    </Box>
+                                )}
+
+                                {/* Bottom submit bar */}
+                                {selectedTable && (
+                                    <Box sx={{ 
+                                        mt: 'auto', 
+                                        pt: 1, 
+                                        display: 'flex', 
+                                        flexDirection: 'row', 
+                                        alignItems: 'center', 
+                                        gap: 1, 
+                                        borderTop: '1px solid',
+                                        borderColor: 'divider',
+                                        '& .MuiButton-root': { textTransform: 'none' } 
+                                    }}>
+                                        <Button
+                                            variant="contained"
+                                            onClick={() => {
+                                                if (inputBoxRef.current) {
+                                                    inputBoxRef.current();
+                                                }
+                                            }}
+                                            disabled={!selectedTable || selectedTable.content.type !== 'image_url' || cleanInProgress}
+                                            size="small"
+                                        >
+                                            Extract data from image
+                                        </Button>
+                                        <Button
+                                            variant="contained"
+                                            sx={{ ml: 'auto' }}
+                                            onClick={handleUpload}
+                                            disabled={!selectedTable || selectedTable.content.type !== 'csv'}
+                                            size="small"
+                                        >
+                                            Load table
+                                        </Button>
+                                    </Box>
+                                )}
+                            </Box>
                         </Box>
-                    </Box>
+                    ) : null}
                 </Box>
-            )}
+            </Box>
         </Box>
     );
-
-    return chatCard;
 };
 
diff --git a/src/views/TableSelectionView.tsx b/src/views/TableSelectionView.tsx
index 79a127f..ba3cbba 100644
--- a/src/views/TableSelectionView.tsx
+++ b/src/views/TableSelectionView.tsx
@@ -6,7 +6,7 @@ import { useEffect } from 'react';
 
 import Typography from '@mui/material/Typography';
 import Box from '@mui/material/Box';
-import { Button, Paper } from '@mui/material';
+import { Button, Card, Paper } from '@mui/material';
 import { CustomReactTable } from './ReactTable';
 import { createTableFromFromObjectArray } from '../data/utils';
 
@@ -56,93 +56,112 @@ export const DatasetSelectionView: React.FC<DatasetSelectionViewProps> = functio
     }
 
     return (
-        <Box sx={{ flexGrow: 1, bgcolor: 'background.paper', display: 'flex', height: 600, borderRadius: 2 }} >
+        <Box sx={{ bgcolor: 'background.paper', display: 'flex', height: '100%', borderRadius: 2, overflow: 'hidden' }} >
             {/* Button navigation */}
             <Box sx={{ 
-                minWidth: 180, 
+                minWidth: 180,
+                maxWidth: 180,
+                width: 180,
                 display: 'flex',
                 flexDirection: 'column',
                 borderRight: 1,
-                borderColor: 'divider'
+                borderColor: 'divider',
+                overflow: 'hidden',
+                height: '100%'
             }}>
-                {datasetTitles.map((title, i) => (
-                    <Button
-                        key={i}
-                        variant="text"
-                        size="small"
-                        color='primary'
-                        onClick={() => handleDatasetSelect(i)}
-                        sx={{
-                            fontSize: 12,
-                            textTransform: "none",
-                            width: 180,
-                            justifyContent: 'flex-start',
-                            textAlign: 'left',
-                            borderRadius: 0,
-                            py: 1,
-                            px: 2,
-                            color: selectedDatasetName === title ? 'primary.main' : 'text.secondary',
-                            borderRight: selectedDatasetName === title ? 2 : 0,
-                            borderColor: 'primary.main',
-                        }}
-                    >
-                        {title}
-                    </Button>
-                ))}
+                <Box sx={{ 
+                    display: 'flex',
+                    flexDirection: 'column',
+                    overflowY: 'auto',
+                    overflowX: 'hidden',
+                    flex: 1,
+                    minHeight: 0,
+                    height: '100%',
+                    position: 'relative',
+                    overscrollBehavior: 'contain'
+                }}>
+                    {datasetTitles.map((title, i) => (
+                        <Button
+                            key={i}
+                            variant="text"
+                            size="small"
+                            color='primary'
+                            onClick={() => handleDatasetSelect(i)}
+                            sx={{
+                                fontSize: 12,
+                                textTransform: "none",
+                                width: 180,
+                                justifyContent: 'flex-start',
+                                textAlign: 'left',
+                                borderRadius: 0,
+                                py: 1,
+                                px: 2,
+                                color: selectedDatasetName === title ? 'primary.main' : 'text.secondary',
+                                borderRight: selectedDatasetName === title ? 2 : 0,
+                                borderColor: 'primary.main',
+                            }}
+                        >
+                            {title}
+                        </Button>
+                    ))}
+                </Box>
             </Box>
 
             {/* Content area */}
-            <Box sx={{ flex: 1, overflow: 'auto', p: 2 }}>
-                {datasets.map((dataset, i) => {
-                    if (dataset.name !== selectedDatasetName) return null;
+            <Box sx={{ flex: 1, overflow: 'hidden', minWidth: 0, minHeight: 0, height: '100%', position: 'relative' }}>
+                <Box sx={{ height: '100%', overflowY: 'auto', overflowX: 'hidden', p: 2, minWidth: 0, overscrollBehavior: 'contain' }}>
+                    {datasets.map((dataset, i) => {
+                        if (dataset.name !== selectedDatasetName) return null;
 
-                    let tableComponents = dataset.tables.map((table, j) => {
-                        let t = createTableFromFromObjectArray(table.table_name, table.sample, true);
-                        let maxDisplayRows = dataset.tables.length > 1 ? 5 : 9;
-                        if (t.rows.length < maxDisplayRows) {
-                            maxDisplayRows = t.rows.length - 1;
-                        }
-                        let sampleRows = [
-                            ...t.rows.slice(0,maxDisplayRows), 
-                            Object.fromEntries(t.names.map(n => [n, "..."]))
-                        ];
-                        let colDefs = t.names.map(name => { return {
-                            id: name, label: name, minWidth: 60, align: undefined, format: (v: any) => v,
-                        }})
-
-                        let content = <Paper variant="outlined" key={t.names.join("-")} sx={{width: 800, maxWidth: '100%', padding: "0px", marginBottom: "8px"}}>
-                            <CustomReactTable rows={sampleRows} columnDefs={colDefs} rowsPerPageNum={-1} compact={false} />
-                        </Paper>
+                        let tableComponents = dataset.tables.map((table, j) => {
+                            let t = createTableFromFromObjectArray(table.table_name, table.sample, true);
+                            let maxDisplayRows = dataset.tables.length > 1 ? 5 : 9;
+                            if (t.rows.length < maxDisplayRows) {
+                                maxDisplayRows = t.rows.length - 1;
+                            }
+                            let sampleRows = [
+                                ...t.rows.slice(0,maxDisplayRows), 
+                                Object.fromEntries(t.names.map(n => [n, "..."]))
+                            ];
+                            let colDefs = t.names.map(name => { return {
+                                id: name, label: name, minWidth: 60, align: undefined, format: (v: any) => v,
+                            }})
 
+                            return (
+                                <Box key={j}>
+                                    <Typography variant="subtitle2" sx={{ mb: 1, fontSize: 12}} color="text.secondary">
+                                        {table.url.split("/").pop()?.split(".")[0]}  ({Object.keys(t.rows[0]).length} columns{hideRowNum ? "" : ` ⨉ ${t.rows.length} rows`})
+                                    </Typography>
+                                    <Box sx={{ maxWidth: '100%', overflowX: 'auto', display: 'flex', flexDirection: 'column', mb: 1 }}>
+                                        <Card variant="outlined" sx={{
+                                            width: 800, minWidth: 'fit-content', padding: "0px"}}>
+                                            <CustomReactTable rows={sampleRows} columnDefs={colDefs} rowsPerPageNum={-1} compact={false} />
+                                        </Card>
+                                    </Box>
+                                </Box>
+                            )
+                        });
+                        
                         return (
-                            <Box key={j}>
-                                <Typography variant="subtitle2" sx={{ mb: 1, fontSize: 12}} color="text.secondary">
-                                    {table.url.split("/").pop()?.split(".")[0]}  ({Object.keys(t.rows[0]).length} columns{hideRowNum ? "" : ` ⨉ ${t.rows.length} rows`})
-                                </Typography>
-                                {content}
-                            </Box>
-                        )
-                    });
-                    
-                    return (
-                        <Box key={i}>
-                            <Box sx={{mb: 1, gap: 1, maxWidth: 800, display: "flex", alignItems: "center"}}>
-                                <Typography sx={{fontSize: 12}}>
-                                    {dataset.description} <Typography variant="caption" sx={{color: "primary.light", fontSize: 10, mx: 0.5}}>[from {dataset.source}]</Typography> 
-                                </Typography>
-                                <Box sx={{marginLeft: "auto", flexShrink: 0}} >
-                                    <Button size="small" variant="contained" 
-                                            onClick={(event: React.MouseEvent<HTMLElement>) => {
-                                                handleSelectDataset(dataset);
-                                            }}>
-                                        load dataset
-                                    </Button>
+                            <Box key={i}>
+                                <Box sx={{mb: 1, gap: 1, maxWidth: 800, display: "flex", alignItems: "center"}}>
+                                    <Typography sx={{fontSize: 12}}>
+                                        {dataset.description} <Typography variant="caption" sx={{color: "primary.light", fontSize: 10, mx: 0.5}}>[from {dataset.source}]</Typography> 
+                                    </Typography>
+                                    <Box sx={{marginLeft: "auto", flexShrink: 0}} >
+                                        <Button size="small" variant="contained" 
+                                                onClick={(event: React.MouseEvent<HTMLElement>) => {
+                                                    handleSelectDataset(dataset);
+                                                }}>
+                                            load dataset
+                                        </Button>
+                                    </Box>
                                 </Box>
+                                {tableComponents}
                             </Box>
-                            {tableComponents}
-                        </Box>
-                    );
-                })}
+                        );
+                    })}
+                </Box>
             </Box>
         </Box>
     );
diff --git a/src/views/UnifiedDataUploadDialog.tsx b/src/views/UnifiedDataUploadDialog.tsx
index 17b8558..dfe5adf 100644
--- a/src/views/UnifiedDataUploadDialog.tsx
+++ b/src/views/UnifiedDataUploadDialog.tsx
@@ -6,6 +6,7 @@ import { useState, useCallback, useEffect, useRef } from 'react';
 import {
     Box,
     Button,
+    Chip,
     Dialog,
     DialogContent,
     DialogTitle,
@@ -18,7 +19,7 @@ import {
     Input,
     alpha,
     useTheme,
-    Divider,
+    Card,
 } from '@mui/material';
 
 import CloseIcon from '@mui/icons-material/Close';
@@ -88,6 +89,8 @@ interface PreviewPanelProps {
     emptyLabel: string;
     meta?: string;
     onRemoveTable?: (index: number) => void;
+    activeIndex?: number;
+    onActiveIndexChange?: (index: number) => void;
 }
 
 const PreviewPanel: React.FC<PreviewPanelProps> = ({
@@ -99,27 +102,37 @@ const PreviewPanel: React.FC<PreviewPanelProps> = ({
     emptyLabel,
     meta,
     onRemoveTable,
+    activeIndex: controlledActiveIndex,
+    onActiveIndexChange,
 }) => {
     const previewTables = tables ?? (table ? [table] : null);
-    const [activeIndex, setActiveIndex] = useState(0);
+    const [internalActiveIndex, setInternalActiveIndex] = useState(0);
+    const activeIndex = controlledActiveIndex !== undefined ? controlledActiveIndex : internalActiveIndex;
+    const setActiveIndex = onActiveIndexChange || setInternalActiveIndex;
 
     useEffect(() => {
         if (!previewTables || previewTables.length === 0) {
-            setActiveIndex(0);
+            if (onActiveIndexChange) {
+                onActiveIndexChange(0);
+            } else {
+                setInternalActiveIndex(0);
+            }
             return;
         }
         if (activeIndex > previewTables.length - 1) {
-            setActiveIndex(previewTables.length - 1);
+            const newIndex = previewTables.length - 1;
+            if (onActiveIndexChange) {
+                onActiveIndexChange(newIndex);
+            } else {
+                setInternalActiveIndex(newIndex);
+            }
         }
-    }, [previewTables, activeIndex]);
+    }, [previewTables, activeIndex, onActiveIndexChange]);
 
     const activeTable = previewTables && previewTables.length > 0 ? previewTables[activeIndex] : null;
     return (
         <Box
             sx={{
-                border: '1px solid',
-                borderColor: 'divider',
-                borderRadius: 1,
                 p: 1,
                 display: 'flex',
                 flexDirection: 'column',
@@ -127,23 +140,6 @@ const PreviewPanel: React.FC<PreviewPanelProps> = ({
                 minHeight: 120,
             }}
         >
-            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1 }}>
-                <Typography variant="body2" sx={{ fontWeight: 600 }}>
-                    {title}
-                </Typography>
-                {onRemoveTable && previewTables && previewTables.length > 0 && (
-                    <IconButton
-                        size="small"
-                        color="error"
-                        onClick={() => onRemoveTable(activeIndex)}
-                        sx={{ ml: 'auto' }}
-                        aria-label="Remove table"
-                    >
-                        <DeleteIcon fontSize="small" />
-                    </IconButton>
-                )}
-            </Box>
-
             {loading && <LinearProgress />}
 
             {error && (
@@ -160,96 +156,107 @@ const PreviewPanel: React.FC<PreviewPanelProps> = ({
 
             {previewTables && previewTables.length > 0 && (
                 <Box>
-                    {previewTables.length > 1 && (
-                        <Box
-                            sx={{
-                                display: 'flex',
-                                flexWrap: 'nowrap',
-                                gap: 0.25,
-                                mb: 0.5,
-                                pb: 0.25,
-                                overflowX: 'auto',
-                                overflowY: 'hidden',
-                                '&::-webkit-scrollbar': { height: 4 },
-                                '&::-webkit-scrollbar-thumb': {
-                                    backgroundColor: 'action.disabled',
-                                    borderRadius: 4,
-                                },
-                            }}
-                        >
-                            {previewTables.map((t, idx) => {
-                                const label = t.displayId || t.id;
-                                return (
-                                    <Tooltip key={`${t.id}-${idx}`} title={label} placement="top" arrow>
-                                        <Button
-                                            size="small"
-                                            variant="text"
-                                            onClick={() => setActiveIndex(idx)}
-                                            sx={{
-                                                textTransform: 'none',
-                                                minWidth: 'auto',
-                                                px: 1,
-                                                py: 0.5,
-                                                borderRadius: 1,
-                                                borderBottom: '2px solid',
-                                                borderBottomColor: idx === activeIndex ? (theme) => alpha(theme.palette.primary.main, 0.6) : 'transparent',
-                                                backgroundColor: idx === activeIndex ? (theme) => alpha(theme.palette.primary.main, 0.08) : 'transparent',
-                                                color: idx === activeIndex ? 'text.primary' : 'text.secondary',
-                                                fontWeight: idx === activeIndex ? 600 : 500,
-                                                fontSize: 12,
-                                                lineHeight: 1.2,
-                                                maxWidth: 160,
+                    <Box
+                        sx={{
+                            display: 'flex',
+                            alignItems: 'center',
+                            flexWrap: 'nowrap',
+                            gap: 0.25,
+                            mb: 0.5,
+                            pb: 0.25,
+                            overflowX: 'auto',
+                            overflowY: 'hidden',
+                            '&::-webkit-scrollbar': { height: 4 },
+                            '&::-webkit-scrollbar-thumb': {
+                                backgroundColor: 'action.disabled',
+                                borderRadius: 4,
+                            },
+                        }}
+                    >
+                        <Typography variant="caption" sx={{ fontSize: '0.625rem', fontWeight: 'bold' }}>Preview</Typography>
+                        {previewTables.map((t, idx) => {
+                            const label = t.displayId || t.id;
+                            const isSelected = idx === activeIndex;
+                            return (
+                                <Tooltip key={`${t.id}-${idx}`} title={label} placement="top" arrow>
+                                    <Chip
+                                        label={label}
+                                        size="small"
+                                        onClick={() => {
+                                            if (onActiveIndexChange) {
+                                                onActiveIndexChange(idx);
+                                            } else {
+                                                setInternalActiveIndex(idx);
+                                            }
+                                        }}
+                                        sx={{
+                                            borderRadius: 1,
+                                            cursor: 'pointer',
+                                            maxWidth: 160,
+                                            backgroundColor: (theme) => 
+                                                isSelected 
+                                                    ? alpha(theme.palette.primary.main, 0.12)
+                                                    : 'transparent',
+                                            borderColor: (theme) => 
+                                                isSelected 
+                                                    ? alpha(theme.palette.primary.main, 0.5)
+                                                    : undefined,
+                                            color: (theme) => 
+                                                isSelected 
+                                                    ? theme.palette.primary.main
+                                                    : theme.palette.text.secondary,
+                                            '& .MuiChip-label': {
+                                                fontSize: '0.625rem',
                                                 overflow: 'hidden',
-                                                '&:hover': {
-                                                    backgroundColor: (theme) => alpha(theme.palette.primary.main, 0.06),
-                                                },
-                                                '& .MuiButton-label': {
-                                                    overflow: 'hidden',
-                                                },
-                                            }}
-                                        >
-                                            <Box
-                                                component="span"
-                                                sx={{
-                                                    display: 'inline-block',
-                                                    maxWidth: 140,
-                                                    overflow: 'hidden',
-                                                    textOverflow: 'ellipsis',
-                                                    whiteSpace: 'nowrap',
-                                                }}
-                                            >
-                                                {label}
-                                            </Box>
-                                        </Button>
-                                    </Tooltip>
-                                );
-                            })}
-                        </Box>
-                    )}
+                                                textOverflow: 'ellipsis',
+                                                whiteSpace: 'nowrap',
+                                                maxWidth: 140,
+                                            },
+                                            '&:hover': {
+                                                backgroundColor: (theme) => 
+                                                    isSelected 
+                                                        ? alpha(theme.palette.primary.main, 0.16)
+                                                        : alpha(theme.palette.primary.main, 0.08),
+                                            },
+                                        }}
+                                    />
+                                </Tooltip>
+                            );
+                        })}
+                        {onRemoveTable && (
+                            <IconButton
+                                size="small"
+                                color="error"
+                                onClick={() => onRemoveTable(activeIndex)}
+                                sx={{ ml: 'auto', flexShrink: 0 }}
+                                aria-label="Remove table"
+                            >
+                                <DeleteIcon fontSize="small" />
+                            </IconButton>
+                        )}
+                    </Box>
 
                     {activeTable && (
-                        <Box sx={{ pb: 1 }}>
-                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, mb: 0.5 }}>
-                                <Typography variant="caption" color="text.secondary">
-                                    {activeTable.rows.length} rows × {activeTable.names.length} columns
-                                    {previewTables && previewTables.length === 1
-                                        ? ` • ${activeTable.displayId || activeTable.id}`
-                                        : ''}
-                                </Typography>
-                            </Box>
-                            <CustomReactTable
-                                rows={activeTable.rows.slice(0, 12)}
-                                columnDefs={activeTable.names.map(name => ({
-                                    id: name,
-                                    label: name,
-                                    minWidth: 60,
-                                }))}
-                                rowsPerPageNum={-1}
-                                compact={true}
-                                isIncompleteTable={activeTable.rows.length > 12}
-                                maxHeight={200}
-                            />
-                        </Box>
+                        <Box>
+                            <Card variant="outlined" sx={{ pb: 0.5 }}>
+                                <CustomReactTable
+                                    rows={activeTable.rows.slice(0, 12)}
+                                    columnDefs={activeTable.names.map(name => ({
+                                        id: name,
+                                        label: name,
+                                        minWidth: 60,
+                                    }))}
+                                    rowsPerPageNum={-1}
+                                    compact={true}
+                                    isIncompleteTable={activeTable.rows.length > 12}
+                                    maxHeight={200}
+                                />
+                            
+                            </Card>
+                            <Typography variant="caption" color="text.secondary">
+                            {activeTable.rows.length} rows × {activeTable.names.length} columns
+                        </Typography>
+                      </Box>
                     )}
                 </Box>
             )}
@@ -387,6 +394,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
     const [filePreviewLoading, setFilePreviewLoading] = useState<boolean>(false);
     const [filePreviewError, setFilePreviewError] = useState<string | null>(null);
     const [filePreviewFiles, setFilePreviewFiles] = useState<File[]>([]);
+    const [filePreviewActiveIndex, setFilePreviewActiveIndex] = useState<number>(0);
 
     // Sample datasets state
     const [datasetPreviews, setDatasetPreviews] = useState<DatasetMetadata[]>([]);
@@ -556,7 +564,30 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         }
     };
 
-    const handleFileLoadSubmit = (): void => {
+    // Reset activeIndex when tables change
+    useEffect(() => {
+        if (filePreviewTables && filePreviewTables.length > 0) {
+            if (filePreviewActiveIndex >= filePreviewTables.length) {
+                setFilePreviewActiveIndex(filePreviewTables.length - 1);
+            }
+        } else {
+            setFilePreviewActiveIndex(0);
+        }
+    }, [filePreviewTables, filePreviewActiveIndex]);
+
+    const handleFileLoadSingleTable = (): void => {
+        if (!filePreviewTables || filePreviewTables.length === 0) {
+            return;
+        }
+        const table = filePreviewTables[filePreviewActiveIndex];
+        if (table) {
+            dispatch(dfActions.loadTable(table));
+            dispatch(fetchFieldSemanticType(table));
+            handleClose();
+        }
+    };
+
+    const handleFileLoadAllTables = (): void => {
         if (!filePreviewTables || filePreviewTables.length === 0) {
             return;
         }
@@ -694,7 +725,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         { 
             value: 'upload' as UploadTabType, 
             title: 'Upload File', 
-            description: 'Upload structured data (CSV, TSV, JSON, Excel) from files or URLs',
+            description: 'Structured data (CSV, TSV, JSON, Excel) from files or URLs',
             icon: <UploadFileIcon />, 
             disabled: false,
             disabledReason: undefined
@@ -805,6 +836,21 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                             flexDirection: 'column',
                             gap: 2,
                         }}>
+                            {/* Section hint */}
+                            <Typography 
+                                variant="body2" 
+                                color="text.secondary" 
+                                sx={{ 
+                                    textAlign: 'left',
+                                    my: 1,
+                                    opacity: 0.6,
+                                    fontSize: '0.75rem',
+                                    letterSpacing: '0.02em'
+                                }}
+                            >
+                                Local data
+                            </Typography>
+
                             {/* Regular Data Sources Group */}
                             <Box sx={{ 
                                 display: 'grid', 
@@ -824,8 +870,20 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                 ))}
                             </Box>
 
-                            {/* Divider */}
-                            <Divider sx={{ my: 1 }} />
+                            {/* Section hint */}
+                            <Typography 
+                                variant="body2" 
+                                color="text.secondary" 
+                                sx={{ 
+                                    textAlign: 'left',
+                                    my: 1,
+                                    opacity: 0.6,
+                                    fontSize: '0.75rem',
+                                    letterSpacing: '0.02em'
+                                }}
+                            >
+                                Or connect to a database
+                            </Typography>
 
                             {/* Database Data Sources Group */}
                             <Box sx={{ 
@@ -860,7 +918,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                         p: 2,
                         justifyContent: showFilePreview ? 'flex-start' : 'center',
                     }}>
-                        <Box sx={{ width: '100%', maxWidth: showFilePreview ? '100%' : 760, alignSelf: 'center', display: 'flex', flexDirection: 'column', gap: 2 }}>
+                        <Box sx={{ width: '100%', maxWidth: showFilePreview ? '60%' : 760, alignSelf: 'center', display: 'flex', flexDirection: 'column', gap: 2 }}>
                         <Input
                             inputProps={{ 
                                 accept: '.csv,.tsv,.json,.xlsx,.xls',
@@ -891,9 +949,9 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                         ) : (
                             <Box sx={{ 
                                 display: 'flex', 
-                                flexDirection: showFilePreview ? 'row' : 'column',
+                                flexDirection: 'column',
                                 gap: 2,
-                                alignItems: showFilePreview ? 'flex-start' : 'stretch',
+                                alignItems: 'stretch',
                             }}>
                                 <Box
                                     sx={{
@@ -904,7 +962,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                         textAlign: 'center',
                                         cursor: 'pointer',
                                         transition: 'all 0.2s',
-                                        flex: showFilePreview ? '0 0 45%' : '1',
+                                        flex: '1',
                                         minWidth: showFilePreview ? 0 : 'auto',
                                         '&:hover': {
                                             borderColor: 'primary.main',
@@ -932,8 +990,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                     display: 'flex', 
                                     alignItems: 'center', 
                                     gap: 1,
-                                    flex: showFilePreview ? '1' : '0 0 auto',
-                                    minWidth: showFilePreview ? 0 : 'auto',
+                                    flex: '0 0 auto',
                                 }}>
                                     <TextField
                                         fullWidth
@@ -964,33 +1021,48 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                 </Box>
                             </Box>
                         )}
+                        </Box>
 
                         {showFilePreview && (
-                            <PreviewPanel
-                                title="Preview"
-                                loading={filePreviewLoading}
-                                error={filePreviewError}
-                                tables={filePreviewTables}
-                                emptyLabel={serverConfig.DISABLE_FILE_UPLOAD ? 'File upload is disabled.' : 'Select a file to preview.'}
-                                meta={filePreviewTables && filePreviewTables.length > 0 ? `${filePreviewTables.length} table${filePreviewTables.length > 1 ? 's' : ''} previewed${hasMultipleFileTables ? ' • Multiple sheets detected' : ''}` : undefined}
-                                onRemoveTable={handleRemoveFilePreviewTable}
-                            />
+                            <Box sx={{ width: '90%', alignSelf: 'center' }}>
+                                <PreviewPanel
+                                    title="Preview"
+                                    loading={filePreviewLoading}
+                                    error={filePreviewError}
+                                    tables={filePreviewTables}
+                                    emptyLabel={serverConfig.DISABLE_FILE_UPLOAD ? 'File upload is disabled.' : 'Select a file to preview.'}
+                                    meta={filePreviewTables && filePreviewTables.length > 0 ? `${filePreviewTables.length} table${filePreviewTables.length > 1 ? 's' : ''} previewed${hasMultipleFileTables ? ' • Multiple sheets detected' : ''}` : undefined}
+                                    onRemoveTable={handleRemoveFilePreviewTable}
+                                    activeIndex={filePreviewActiveIndex}
+                                    onActiveIndexChange={setFilePreviewActiveIndex}
+                                />
+                            </Box>
                         )}
 
                         {filePreviewTables && filePreviewTables.length > 0 && (
                             <Box sx={{ display: 'flex', justifyContent: 'flex-end', gap: 1 }}>
                                 <Button
-                                    variant="contained"
+                                    variant="outlined"
                                     size="small"
-                                    onClick={handleFileLoadSubmit}
+                                    onClick={handleFileLoadSingleTable}
                                     disabled={serverConfig.DISABLE_FILE_UPLOAD || filePreviewLoading}
                                     sx={{ textTransform: 'none' }}
                                 >
-                                    {hasMultipleFileTables ? 'Load Tables' : 'Load Table'}
+                                    Load Table
                                 </Button>
+                                {hasMultipleFileTables && (
+                                    <Button
+                                        variant="contained"
+                                        size="small"
+                                        onClick={handleFileLoadAllTables}
+                                        disabled={serverConfig.DISABLE_FILE_UPLOAD || filePreviewLoading}
+                                        sx={{ textTransform: 'none' }}
+                                    >
+                                        Load All Tables
+                                    </Button>
+                                )}
                             </Box>
                         )}
-                        </Box>
                     </Box>
                 </TabPanel>
 
@@ -1114,7 +1186,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
 
                 {/* Explore Sample Datasets Tab */}
                 <TabPanel value={activeTab} index="explore">
-                    <Box sx={{ p: 2 }}>
+                    <Box sx={{ p: 2, height: '100%', boxSizing: 'border-box', display: 'flex', flexDirection: 'column' }}>
                         <DatasetSelectionView 
                         datasets={datasetPreviews} 
                         hideRowNum
@@ -1138,7 +1210,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                             }
                             handleClose();
                         }}
-                    />
+                        />
                     </Box>
                 </TabPanel>
             </DialogContent>

From cb925eef6ea882519460790fd7133c2cc7d9dc45 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Sat, 17 Jan 2026 12:17:26 -0800
Subject: [PATCH 08/21] ok

---
 src/views/DataThread.tsx        | 288 ++++++++++++++++++++++++++++----
 src/views/RefreshDataDialog.tsx | 269 ++++++++++++++++++++---------
 2 files changed, 444 insertions(+), 113 deletions(-)

diff --git a/src/views/DataThread.tsx b/src/views/DataThread.tsx
index df772a5..d210fee 100644
--- a/src/views/DataThread.tsx
+++ b/src/views/DataThread.tsx
@@ -465,12 +465,62 @@ const EditableTableName: FC<{
     );
 };
 
+// Compact view for thread0 - displays table cards with charts in a simple grid
+// Reuses SingleThreadGroupView with compact mode
+let CompactThread0View: FC<{
+    scrollRef: any,
+    leafTables: DictTable[];
+    chartElements: { tableId: string, chartId: string, element: any }[];
+    sx?: SxProps
+}> = function ({
+    scrollRef,
+    leafTables,
+    chartElements,
+    sx
+}) {
+    const theme = useTheme();
+    
+    return (
+        <Box sx={{ ...sx, 
+            '& .selected-card': { 
+                border: `2px solid ${theme.palette.primary.light}`,
+            },
+            transition: "box-shadow 0.1s linear",
+        }}
+        data-thread-index={-1}>
+            <Box sx={{ display: 'flex', direction: 'ltr', margin: '2px 2px 8px 2px' }}>
+                <Divider flexItem sx={{
+                    margin: 'auto',
+                    "& .MuiDivider-wrapper": { display: 'flex', flexDirection: 'row' },
+                    "&::before, &::after": { borderColor: alpha(theme.palette.custom.main, 0.2), borderWidth: '2px', width: 60 },
+                }}>
+                    <Typography sx={{ fontSize: "10px",  color: 'text.secondary', textTransform: 'none' }}>
+                        workspace
+                    </Typography>
+                </Divider>
+            </Box>
+            <Box sx={{ padding: '2px 4px 2px 4px', marginTop: 0, direction: 'ltr' }}>
+                <SingleThreadGroupView
+                    scrollRef={scrollRef}
+                    threadIdx={-1}
+                    leafTables={leafTables}
+                    chartElements={chartElements}
+                    usedIntermediateTableIds={[]}
+                    compact={true}
+                    sx={{ display: 'flex', flexDirection: 'column', gap: 0.5 }}
+                />
+            </Box>
+        </Box>
+    );
+}
+
 let SingleThreadGroupView: FC<{
     scrollRef: any,
     threadIdx: number,
     leafTables: DictTable[];
     chartElements: { tableId: string, chartId: string, element: any }[];
     usedIntermediateTableIds: string[],
+    compact?: boolean, // When true, only show table cards in a simple column (for thread0)
     sx?: SxProps
 }> = function ({
     scrollRef,
@@ -478,6 +528,7 @@ let SingleThreadGroupView: FC<{
     leafTables,
     chartElements,
     usedIntermediateTableIds, // tables that have been used
+    compact = false,
     sx
 }) {
 
@@ -506,8 +557,6 @@ let SingleThreadGroupView: FC<{
     const [selectedTableForRefresh, setSelectedTableForRefresh] = useState<DictTable | null>(null);
     const [isRefreshing, setIsRefreshing] = useState(false);
 
-    const activeModel = useSelector(dfSelectors.getActiveModel);
-
     let handleUpdateTableDisplayId = (tableId: string, displayId: string) => {
         dispatch(dfActions.updateTableDisplayId({
             tableId: tableId,
@@ -681,7 +730,7 @@ let SingleThreadGroupView: FC<{
         </Box>;
     }
 
-    let buildTableCard = (tableId: string) => {
+    let buildTableCard = (tableId: string, compact = false) => {
 
         if (parentTable && tableId == parentTable.id && parentTable.anchored && tableIdList.length > 1) {
             let table = tables.find(t => t.id == tableId);
@@ -901,7 +950,7 @@ let SingleThreadGroupView: FC<{
                         backgroundSize: '1px 6px, 3px 100%'
                     }}></Box>
                 </Box>}
-                <Box sx={{ flex: 1, padding: '8px 0px', minHeight: '8px', ...chartElementProps }}>
+                <Box sx={{ flex: 1, padding: '4px 0px', minHeight: '0px', ...chartElementProps }}>
                     {releventChartElements}
                     {agentActionBox}
                 </Box>
@@ -974,6 +1023,94 @@ let SingleThreadGroupView: FC<{
         </Stack>;
     });
 
+    // Compact mode: just show leaf table cards in a simple column
+    if (compact) {
+        // For compact mode, ensure highlightedTableIds includes focused table if it's a leaf
+        if (focusedTableId && leafTableIds.includes(focusedTableId)) {
+            highlightedTableIds = [focusedTableId];
+        }
+        
+        return (
+            <Box sx={{ ...sx, display: 'flex', flexDirection: 'column', gap: 0.25 }}>
+                {leafTables.map((table) => {
+                    const tableCardResult = buildTableCard(table.id, compact);
+                    // buildTableCard returns an array [regularTableBox, chartBox]
+                    // In compact mode, we want to show them stacked
+                    return (
+                        <React.Fragment key={`compact-table-${table.id}`}>
+                            {tableCardResult}
+                        </React.Fragment>
+                    );
+                })}
+                <MetadataPopup
+                    open={metadataPopupOpen}
+                    anchorEl={metadataAnchorEl}
+                    onClose={handleCloseMetadataPopup}
+                    onSave={handleSaveMetadata}
+                    initialValue={selectedTableForMetadata?.attachedMetadata || ''}
+                    tableName={selectedTableForMetadata?.displayId || selectedTableForMetadata?.id || ''}
+                />
+                <Menu
+                    anchorEl={tableMenuAnchorEl}
+                    open={Boolean(tableMenuAnchorEl)}
+                    onClose={handleCloseTableMenu}
+                    onClick={(e) => e.stopPropagation()}
+                >
+                    <MenuItem 
+                        onClick={(e) => {
+                            e.stopPropagation();
+                            if (selectedTableForMenu) {
+                                handleOpenMetadataPopup(selectedTableForMenu, tableMenuAnchorEl!);
+                            }
+                            handleCloseTableMenu();
+                        }}
+                        sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
+                    >
+                        <AttachFileIcon sx={{ 
+                            fontSize: 16,
+                            color: selectedTableForMenu?.attachedMetadata ? 'secondary.main' : 'text.secondary',
+                        }}/>
+                        {selectedTableForMenu?.attachedMetadata ? "Edit metadata" : "Attach metadata"}
+                    </MenuItem>
+                    <MenuItem 
+                        onClick={(e) => {
+                            e.stopPropagation();
+                            if (selectedTableForMenu) {
+                                handleOpenRefreshDialog(selectedTableForMenu);
+                            }
+                        }}
+                        sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
+                    >
+                        <RefreshIcon sx={{ fontSize: 16, color: 'primary.main' }}/>
+                        Refresh data
+                    </MenuItem>
+                    <MenuItem 
+                        onClick={(e) => {
+                            e.stopPropagation();
+                            if (selectedTableForMenu) {
+                                dispatch(dfActions.deleteTable(selectedTableForMenu.id));
+                            }
+                            handleCloseTableMenu();
+                        }}
+                        disabled={selectedTableForMenu ? tables.some(t => t.derive?.trigger.tableId === selectedTableForMenu.id) : true}
+                        sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1, color: 'warning.main' }}
+                    >
+                        <DeleteIcon sx={{ fontSize: 16 }} color='warning'/>
+                        Delete table
+                    </MenuItem>
+                </Menu>
+                {selectedTableForRefresh && (
+                    <RefreshDataDialog
+                        open={refreshDialogOpen}
+                        onClose={handleCloseRefreshDialog}
+                        table={selectedTableForRefresh}
+                        onRefreshComplete={handleRefreshComplete}
+                    />
+                )}
+            </Box>
+        );
+    }
+
     return <Box sx={{ ...sx, 
             '& .selected-card': { 
                 border: `2px solid ${theme.palette.primary.light}`,
@@ -988,7 +1125,7 @@ let SingleThreadGroupView: FC<{
                 "&::before, &::after": { borderColor: alpha(theme.palette.custom.main, 0.2), borderWidth: '2px', width: 60 },
             }}>
                 <Typography sx={{ fontSize: "10px",  color: 'text.secondary', textTransform: 'none' }}>
-                    {`thread - ${threadIdx + 1}`}
+                    {threadIdx === -1 ? 'thread0' : `thread - ${threadIdx + 1}`}
                 </Typography>
             </Divider>
         </Box>
@@ -1385,7 +1522,22 @@ export const DataThread: FC<{sx?: SxProps}> = function ({ sx }) {
         return aOrders.length - bOrders.length;
     });
 
-    let leafTableGroups = leafTables.reduce((groups: { [groupId: string]: DictTable[] }, leafTable) => {
+    // Identify hanging tables (tables with no descendants or parents)
+    let isHangingTable = (table: DictTable) => {
+        // A table is hanging if:
+        // 1. It has no derive.source (no parent)
+        // 2. No other table derives from it (no descendants)
+        const hasNoParent = table.derive == undefined;
+        const hasNoDescendants = !tables.some(t => t.derive?.trigger.tableId == table.id);
+        return hasNoParent && hasNoDescendants;
+    };
+
+    // Separate hanging tables from regular leaf tables
+    let hangingTables = leafTables.filter(t => isHangingTable(t));
+    let regularLeafTables = leafTables.filter(t => !isHangingTable(t));
+
+    // Build groups for regular leaf tables (excluding hanging tables)
+    let leafTableGroups = regularLeafTables.reduce((groups: { [groupId: string]: DictTable[] }, leafTable) => {
         // Get the immediate parent table ID (first trigger in the chain)
         const triggers = getTriggers(leafTable, tables);
         const immediateParentTableId = triggers.length > 0 ? triggers[triggers.length - 1].tableId : 'root';
@@ -1409,8 +1561,38 @@ export const DataThread: FC<{sx?: SxProps}> = function ({ sx }) {
         return groups;
     }, {});
 
-    let drawerOpen = threadDrawerOpen && leafTables.length > 1;
-    let collaposedViewWidth = Math.max(...Object.values(leafTableGroups).map(x => x.length)) > 1 ? 248 : 232
+    // Filter threads to only include those with length > 1
+    let filteredLeafTableGroups: { [groupId: string]: DictTable[] } = {};
+    Object.entries(leafTableGroups).forEach(([groupId, groupTables]) => {
+        // Calculate thread length: count all tables in the thread chain
+        const threadLength = groupTables.reduce((maxLength, leafTable) => {
+            const triggers = getTriggers(leafTable, tables);
+            // Thread length = number of triggers + 1 (the leaf table itself)
+            return Math.max(maxLength, triggers.length + 1);
+        }, 0);
+        
+        // Only include threads with length > 1
+        if (threadLength > 1) {
+            filteredLeafTableGroups[groupId] = groupTables;
+        } else {
+            // Add single-table threads to hanging tables (they go to thread0)
+            groupTables.forEach(table => {
+                if (!hangingTables.includes(table)) {
+                    hangingTables.push(table);
+                }
+            });
+        }
+    });
+
+    // Create thread0 group for hanging tables
+    let thread0Group: { [groupId: string]: DictTable[] } = {};
+    if (hangingTables.length > 0) {
+        thread0Group['thread0'] = hangingTables;
+    }
+
+    let drawerOpen = threadDrawerOpen && (Object.keys(filteredLeafTableGroups).length > 0 || hangingTables.length > 0);
+    let allGroupsForWidth = { ...filteredLeafTableGroups, ...thread0Group };
+    let collaposedViewWidth = Math.max(...Object.values(allGroupsForWidth).map(x => x.length)) > 1 ? 248 : 232
 
     let view = <Box maxWidth={drawerOpen ? 720 : collaposedViewWidth} sx={{ 
         overflow: 'auto', // Add horizontal scroll when drawer is open
@@ -1424,11 +1606,38 @@ export const DataThread: FC<{sx?: SxProps}> = function ({ sx }) {
         p: 1,
         transition: 'max-width 0.1s linear', // Smooth width transition
     }}>
-        {Object.entries(leafTableGroups).map(([groupId, leafTables], i) => {
-
-            let usedIntermediateTableIds = Object.values(leafTableGroups).slice(0, i).flat()
+        {/* Render thread0 (hanging tables) first if it exists - using compact view */}
+        {Object.entries(thread0Group).map(([groupId, leafTables], i) => {
+            return <CompactThread0View
+                key={`thread-${groupId}-${i}`}
+                scrollRef={scrollRef}
+                leafTables={leafTables} 
+                chartElements={chartElements} 
+                sx={{
+                    backgroundColor: 'white', 
+                    borderRadius: 2,
+                    padding: 1,
+                    my: 0.5,
+                    flex:  'none',
+                    display: 'flex',
+                    flexDirection: 'column',
+                    height: 'fit-content',
+                    width: leafTables.length > 1 ? '216px' : '200px', 
+                    transition: 'all 0.3s ease',
+                }} />
+        })}
+        {/* Render regular threads (length > 1) */}
+        {Object.entries(filteredLeafTableGroups).map(([groupId, leafTables], i) => {
+            // Calculate used tables from thread0 and previous threads
+            let usedIntermediateTableIds = Object.values(thread0Group).flat()
                 .map(x => [ ...getTriggers(x, tables).map(y => y.tableId) || []]).flat();
-            let usedLeafTableIds = Object.values(leafTableGroups).slice(0, i).flat().map(x => x.id);
+            let usedLeafTableIds = Object.values(thread0Group).flat().map(x => x.id);
+            
+            // Add tables from previous regular threads
+            const previousThreadGroups = Object.values(filteredLeafTableGroups).slice(0, i);
+            usedIntermediateTableIds = [...usedIntermediateTableIds, ...previousThreadGroups.flat()
+                .map(x => [ ...getTriggers(x, tables).map(y => y.tableId) || []]).flat()];
+            usedLeafTableIds = [...usedLeafTableIds, ...previousThreadGroups.flat().map(x => x.id)];
                 
             return <SingleThreadGroupView
                 key={`thread-${groupId}-${i}`}
@@ -1452,11 +1661,20 @@ export const DataThread: FC<{sx?: SxProps}> = function ({ sx }) {
         })}
     </Box>
 
+    // Calculate total thread count (thread0 + regular threads)
+    let totalThreadCount = Object.keys(filteredLeafTableGroups).length + (Object.keys(thread0Group).length > 0 ? 1 : 0);
+    let threadIndices: number[] = [];
+    if (Object.keys(thread0Group).length > 0) {
+        threadIndices.push(-1); // thread0
+    }
+    threadIndices.push(...Array.from({length: Object.keys(filteredLeafTableGroups).length}, (_, i) => i));
+
     let jumpButtonsDrawerOpen = <ButtonGroup size="small" color="primary">
-        {_.chunk(Array.from({length: Object.keys(leafTableGroups).length}, (_, i) => i), 3).map((group, groupIdx) => {
-            const startNum = group[0] + 1;
-            const endNum = group[group.length - 1] + 1;
-            const label = startNum === endNum ? `${startNum}` : `${startNum}-${endNum}`;
+        {_.chunk(threadIndices, 3).map((group, groupIdx) => {
+            const getLabel = (idx: number) => idx === -1 ? '0' : String(idx + 1);
+            const startNum = getLabel(group[0]);
+            const endNum = getLabel(group[group.length - 1]);
+            const label = startNum === endNum ? startNum : `${startNum}-${endNum}`;
             
             return (
                 <Tooltip key={`thread-nav-group-${groupIdx}`} title={`Jump to thread${startNum === endNum ? '' : 's'} ${label}`}>
@@ -1471,8 +1689,9 @@ export const DataThread: FC<{sx?: SxProps}> = function ({ sx }) {
                                 const currentIndex = Array.from(document.querySelectorAll('[data-thread-index]')).reduce((closest, element) => {
                                     const rect = element.getBoundingClientRect();
                                     const distance = Math.abs(rect.left + rect.width/2 - viewportCenter);
+                                    const idx = parseInt(element.getAttribute('data-thread-index') || '0');
                                     if (!closest || distance < closest.distance) {
-                                        return { index: parseInt(element.getAttribute('data-thread-index') || '0'), distance };
+                                        return { index: idx, distance };
                                     }
                                     return closest;
                                 }, null as { index: number, distance: number } | null)?.index || 0;
@@ -1500,21 +1719,24 @@ export const DataThread: FC<{sx?: SxProps}> = function ({ sx }) {
     </ButtonGroup>
 
     let jumpButtonDrawerClosed = <ButtonGroup size="small" color="primary" sx={{ gap: 0 }}>
-        {Object.keys(leafTableGroups).map((groupId, idx) => (
-            <Tooltip key={`thread-nav-${idx}`} title={`Jump to thread ${idx + 1}`}>
-                <IconButton 
-                    size="small" 
-                    color="primary"
-                    sx={{ fontSize: '12px', padding: '4px' }} 
-                    onClick={() => {
-                        const threadElement = document.querySelector(`[data-thread-index="${idx}"]`);
-                        threadElement?.scrollIntoView({ behavior: 'smooth' });
-                    }}
-                > 
-                    {idx + 1}
-                </IconButton>
-            </Tooltip>
-        ))}
+        {threadIndices.map((threadIdx) => {
+            const label = threadIdx === -1 ? '0' : String(threadIdx + 1);
+            return (
+                <Tooltip key={`thread-nav-${threadIdx}`} title={`Jump to thread${threadIdx === -1 ? '0' : ` ${threadIdx + 1}`}`}>
+                    <IconButton 
+                        size="small" 
+                        color="primary"
+                        sx={{ fontSize: '12px', padding: '4px' }} 
+                        onClick={() => {
+                            const threadElement = document.querySelector(`[data-thread-index="${threadIdx}"]`);
+                            threadElement?.scrollIntoView({ behavior: 'smooth' });
+                        }}
+                    > 
+                        {label}
+                    </IconButton>
+                </Tooltip>
+            );
+        })}
     </ButtonGroup>
 
     let jumpButtons = drawerOpen ? jumpButtonsDrawerOpen : jumpButtonDrawerClosed;
@@ -1544,7 +1766,7 @@ export const DataThread: FC<{sx?: SxProps}> = function ({ sx }) {
                     <Tooltip title={"expand"}>
                         <span>
                             <IconButton size={'small'} color="primary" 
-                                disabled={leafTables.length <= 1} onClick={() => { 
+                                disabled={totalThreadCount <= 1} onClick={() => { 
                                     setThreadDrawerOpen(true); 
                                 }}>
                                 <ChevronRightIcon />
diff --git a/src/views/RefreshDataDialog.tsx b/src/views/RefreshDataDialog.tsx
index 92fb32b..a650cc8 100644
--- a/src/views/RefreshDataDialog.tsx
+++ b/src/views/RefreshDataDialog.tsx
@@ -19,8 +19,11 @@ import {
     Alert,
     Tooltip,
     Link,
+    alpha,
+    useTheme,
 } from '@mui/material';
 import CloseIcon from '@mui/icons-material/Close';
+import UploadFileIcon from '@mui/icons-material/UploadFile';
 import { useDispatch, useSelector } from 'react-redux';
 import { AppDispatch } from '../app/store';
 import { DataFormulatorState, dfActions, dfSelectors, fetchFieldSemanticType } from '../app/dfSlice';
@@ -44,7 +47,7 @@ function TabPanel(props: TabPanelProps) {
             aria-labelledby={`refresh-tab-${index}`}
             {...other}
         >
-            {value === index && <Box sx={{ p: 2 }}>{children}</Box>}
+            {value === index && <Box sx={{ p: 2.5, pt: 3 }}>{children}</Box>}
         </div>
     );
 }
@@ -62,6 +65,7 @@ export const RefreshDataDialog: React.FC<RefreshDataDialogProps> = ({
     table,
     onRefreshComplete,
 }) => {
+    const theme = useTheme();
     const dispatch = useDispatch<AppDispatch>();
     const [tabValue, setTabValue] = useState(0);
     const [pasteContent, setPasteContent] = useState('');
@@ -352,115 +356,218 @@ export const RefreshDataDialog: React.FC<RefreshDataDialogProps> = ({
             onClose={handleClose}
             maxWidth="md"
             fullWidth
-            sx={{ '& .MuiDialog-paper': { minHeight: 400 } }}
+            sx={{ '& .MuiDialog-paper': { minHeight: 500 } }}
         >
-            <DialogTitle sx={{ display: 'flex', alignItems: 'center' }}>
-                Refresh Data for "{table.displayId || table.id}"
+            <DialogTitle sx={{ display: 'flex', alignItems: 'center', pb: 1 }}>
+                <Typography variant="h6" component="span">
+                    Refresh Data for "{table.displayId || table.id}"
+                </Typography>
                 <IconButton
                     sx={{ marginLeft: 'auto' }}
                     size="small"
                     onClick={handleClose}
                 >
-                    <CloseIcon fontSize="inherit" />
+                    <CloseIcon fontSize="small" />
                 </IconButton>
             </DialogTitle>
-            <DialogContent dividers>
-                <Alert severity="info" sx={{ mb: 2, fontSize: 12 }}>
-                    Upload new data to replace the current table content. The new data must have the same columns: <strong>{table.names.join(', ')}</strong>
-                </Alert>
-
-                {error && (
-                    <Alert severity="error" sx={{ mb: 2, fontSize: 12 }}>
-                        {error}
-                    </Alert>
-                )}
+            <DialogContent sx={{ p: 0 }}>
+                <Box sx={{ px: 3, pt: 2.5, pb: 1.5 }}>
+                    <Typography 
+                        variant="caption" 
+                        sx={{ 
+                            display: 'block',
+                            color: 'text.secondary',
+                            fontSize: '0.75rem',
+                            mb: 2,
+                            lineHeight: 1.5
+                        }}
+                    >
+                        Upload new data to replace the current table content. Required columns: <strong style={{ color: 'inherit' }}>{table.names.join(', ')}</strong>
+                    </Typography>
+
+                    {error && (
+                        <Box 
+                            sx={{ 
+                                mb: 1.5,
+                                p: 1,
+                                backgroundColor: alpha(theme.palette.error.main, 0.08),
+                                borderLeft: `3px solid ${theme.palette.error.main}`,
+                                borderRadius: '4px',
+                            }}
+                        >
+                            <Typography variant="caption" sx={{ color: 'error.main', fontSize: '0.75rem', lineHeight: 1.5 }}>
+                                {error}
+                            </Typography>
+                        </Box>
+                    )}
 
-                {isLoading && <LinearProgress sx={{ mb: 2 }} />}
+                    {isLoading && <LinearProgress sx={{ mb: 2, height: 2 }} />}
+                </Box>
 
-                <Tabs value={tabValue} onChange={handleTabChange} sx={{ borderBottom: 1, borderColor: 'divider' }}>
-                    <Tab label="Paste Data" sx={{ textTransform: 'none', fontSize: 12 }} />
-                    <Tab label="Upload File" sx={{ textTransform: 'none', fontSize: 12 }} />
-                    <Tab label="From URL" sx={{ textTransform: 'none', fontSize: 12 }} />
+                <Tabs value={tabValue} onChange={handleTabChange} sx={{ borderBottom: 1, borderColor: 'divider', px: 3 }}>
+                    <Tab label="Paste Data" sx={{ textTransform: 'none', fontSize: '0.875rem', minHeight: 48 }} />
+                    <Tab label="Upload File" sx={{ textTransform: 'none', fontSize: '0.875rem', minHeight: 48 }} />
+                    <Tab label="From URL" sx={{ textTransform: 'none', fontSize: '0.875rem', minHeight: 48 }} />
                 </Tabs>
 
                 <TabPanel value={tabValue} index={0}>
-                    {isOverSizeLimit && (
-                        <Box sx={{ display: 'flex', alignItems: 'center', mb: 1, p: 1, backgroundColor: 'rgba(244, 67, 54, 0.1)', borderRadius: 1 }}>
-                            <Typography variant="caption" sx={{ color: 'error.main' }}>
-                                ⚠️ Content exceeds 2MB size limit.
-                            </Typography>
-                        </Box>
-                    )}
-                    {isLargeContent && !isOverSizeLimit && (
-                        <Box sx={{ display: 'flex', alignItems: 'center', mb: 1, p: 1, backgroundColor: 'rgba(255, 193, 7, 0.1)', borderRadius: 1 }}>
-                            <Typography variant="caption" sx={{ flex: 1 }}>
-                                Large content detected. {showFullContent ? 'Showing full content' : 'Showing preview'}
-                            </Typography>
-                            <Button size="small" variant="outlined" onClick={toggleFullContent} sx={{ textTransform: 'none' }}>
-                                {showFullContent ? 'Show Preview' : 'Show Full'}
-                            </Button>
-                        </Box>
-                    )}
-                    <TextField
-                        fullWidth
-                        multiline
-                        minRows={8}
-                        maxRows={15}
-                        placeholder="Paste CSV, TSV, or JSON data here..."
-                        value={displayContent}
-                        onChange={handlePasteContentChange}
-                        disabled={isLoading}
-                        sx={{ '& .MuiInputBase-input': { fontSize: 12, fontFamily: 'monospace' } }}
-                    />
-                </TabPanel>
-
-                <TabPanel value={tabValue} index={1}>
-                    <Box sx={{ display: 'flex', flexDirection: 'column', alignItems: 'center', gap: 2, py: 4 }}>
-                        <Typography variant="body2" color="text.secondary">
-                            Upload a CSV, TSV, JSON, or Excel file
-                        </Typography>
-                        <Input
-                            inputProps={{ accept: '.csv,.tsv,.json,.xlsx,.xls' }}
-                            type="file"
-                            sx={{ display: 'none' }}
-                            inputRef={fileInputRef}
-                            onChange={handleFileUpload}
-                        />
-                        <Tooltip
-                            title={serverConfig.DISABLE_FILE_UPLOAD ? (
-                                <Typography sx={{ fontSize: '11px' }}>
-                                    Install Data Formulator locally to enable file upload.
+                    <Box sx={{ display: 'flex', flexDirection: 'column', gap: 1.5 }}>
+                        {isOverSizeLimit && (
+                            <Box 
+                                sx={{ 
+                                    p: 1,
+                                    backgroundColor: alpha(theme.palette.error.main, 0.06),
+                                    borderLeft: `3px solid ${theme.palette.error.main}`,
+                                    borderRadius: '4px',
+                                }}
+                            >
+                                <Typography variant="caption" sx={{ color: 'error.main', fontSize: '0.75rem', lineHeight: 1.5 }}>
+                                    Content exceeds {(MAX_CONTENT_SIZE / (1024 * 1024)).toFixed(0)}MB limit ({(new Blob([pasteContent]).size / (1024 * 1024)).toFixed(2)}MB)
                                 </Typography>
-                            ) : ""}
-                        >
-                            <span>
-                                <Button
-                                    variant="contained"
-                                    disabled={isLoading || serverConfig.DISABLE_FILE_UPLOAD}
-                                    onClick={() => fileInputRef.current?.click()}
+                            </Box>
+                        )}
+                        {isLargeContent && !isOverSizeLimit && (
+                            <Box sx={{ 
+                                display: 'flex', 
+                                alignItems: 'center', 
+                                gap: 1.5,
+                                p: 1, 
+                                backgroundColor: alpha(theme.palette.text.secondary, 0.04), 
+                                borderRadius: 1,
+                                border: `1px solid ${alpha(theme.palette.divider, 0.5)}`
+                            }}>
+                                <Typography variant="caption" sx={{ flex: 1, fontSize: '0.75rem', color: 'text.secondary' }}>
+                                    Large content ({Math.round(pasteContent.length / 1000)}KB) • {showFullContent ? 'Full view' : 'Preview'}
+                                </Typography>
+                                <Button 
+                                    size="small" 
+                                    variant="text" 
+                                    onClick={toggleFullContent}
+                                    sx={{ 
+                                        textTransform: 'none', 
+                                        minWidth: 'auto', 
+                                        fontSize: '0.75rem',
+                                        color: 'text.secondary',
+                                        '&:hover': {
+                                            backgroundColor: alpha(theme.palette.text.secondary, 0.08),
+                                        }
+                                    }}
                                 >
-                                    Choose File
+                                    {showFullContent ? 'Preview' : 'Full'}
                                 </Button>
-                            </span>
-                        </Tooltip>
+                            </Box>
+                        )}
+                        <TextField
+                            autoFocus
+                            multiline
+                            fullWidth
+                            value={displayContent}
+                            onChange={handlePasteContentChange}
+                            placeholder="Paste your data here (CSV, TSV, or JSON format)"
+                            disabled={isLoading}
+                            sx={{
+                                '& .MuiInputBase-root': {
+                                    minHeight: 240,
+                                    alignItems: 'flex-start',
+                                },
+                                '& .MuiInputBase-input': {
+                                    fontSize: 12,
+                                    fontFamily: 'monospace',
+                                    lineHeight: 1.5,
+                                }
+                            }}
+                        />
                     </Box>
                 </TabPanel>
 
+                <TabPanel value={tabValue} index={1}>
+                    {serverConfig.DISABLE_FILE_UPLOAD ? (
+                        <Box sx={{ textAlign: 'center', py: 6 }}>
+                            <Typography color="text.secondary" sx={{ mb: 1.5, fontSize: '0.875rem' }}>
+                                File upload is disabled in this environment.
+                            </Typography>
+                            <Typography variant="body2" color="text.secondary" sx={{ fontSize: '0.75rem' }}>
+                                Install Data Formulator locally to enable file upload. <br />
+                                <Link 
+                                    href="https://github.com/microsoft/data-formulator" 
+                                    target="_blank" 
+                                    rel="noopener noreferrer"
+                                    sx={{ fontSize: '0.75rem' }}
+                                >
+                                    https://github.com/microsoft/data-formulator
+                                </Link>
+                            </Typography>
+                        </Box>
+                    ) : (
+                        <Box sx={{ display: 'flex', flexDirection: 'column', gap: 2 }}>
+                            <Input
+                                inputProps={{ accept: '.csv,.tsv,.json,.xlsx,.xls' }}
+                                type="file"
+                                sx={{ display: 'none' }}
+                                inputRef={fileInputRef}
+                                onChange={handleFileUpload}
+                            />
+                            <Box
+                                sx={{
+                                    border: '2px dashed',
+                                    borderColor: 'divider',
+                                    borderRadius: 2,
+                                    p: 4,
+                                    textAlign: 'center',
+                                    cursor: 'pointer',
+                                    transition: 'all 0.2s',
+                                    '&:hover': {
+                                        borderColor: 'primary.main',
+                                        backgroundColor: alpha(theme.palette.primary.main, 0.04),
+                                    }
+                                }}
+                                onClick={() => fileInputRef.current?.click()}
+                            >
+                                <UploadFileIcon sx={{ fontSize: 40, color: 'text.secondary', mb: 1.5 }} />
+                                <Typography variant="subtitle1" gutterBottom sx={{ fontSize: '0.9375rem', fontWeight: 500 }}>
+                                    Drag & drop file here
+                                </Typography>
+                                <Typography variant="body2" color="text.secondary" sx={{ fontSize: '0.8125rem', mb: 0.5 }}>
+                                    or <Link component="button" sx={{ textDecoration: 'underline', cursor: 'pointer' }}>Browse</Link>
+                                </Typography>
+                                <Typography variant="caption" color="text.secondary" sx={{ fontSize: '0.75rem' }}>
+                                    Supported: CSV, TSV, JSON, Excel (xlsx, xls)
+                                </Typography>
+                            </Box>
+                        </Box>
+                    )}
+                </TabPanel>
+
                 <TabPanel value={tabValue} index={2}>
                     <TextField
                         fullWidth
-                        placeholder="Enter URL to CSV, TSV, or JSON file"
+                        placeholder="Load a CSV, TSV, or JSON file from a URL, e.g. https://example.com/data.json"
                         value={urlContent}
                         onChange={(e) => setUrlContent(e.target.value.trim())}
                         disabled={isLoading}
                         error={urlContent !== '' && !hasValidUrlSuffix}
                         helperText={urlContent !== '' && !hasValidUrlSuffix ? 'URL should link to a .csv, .tsv, or .json file' : ''}
-                        sx={{ '& .MuiInputBase-input': { fontSize: 12 } }}
+                        size="small"
+                        sx={{ 
+                            '& .MuiInputBase-input': {
+                                fontSize: '0.875rem',
+                            },
+                            '& .MuiInputBase-input::placeholder': {
+                                fontSize: '0.875rem',
+                            },
+                            '& .MuiFormHelperText-root': {
+                                fontSize: '0.75rem',
+                            },
+                        }}
                     />
                 </TabPanel>
             </DialogContent>
-            <DialogActions>
-                <Button onClick={handleClose} disabled={isLoading}>
+            <DialogActions sx={{ px: 3, py: 2, gap: 1 }}>
+                <Button 
+                    onClick={handleClose} 
+                    disabled={isLoading}
+                    sx={{ textTransform: 'none' }}
+                >
                     Cancel
                 </Button>
                 {tabValue === 0 && (
@@ -468,6 +575,7 @@ export const RefreshDataDialog: React.FC<RefreshDataDialogProps> = ({
                         variant="contained"
                         onClick={handlePasteSubmit}
                         disabled={isLoading || !pasteContent.trim() || isOverSizeLimit}
+                        sx={{ textTransform: 'none' }}
                     >
                         Refresh Data
                     </Button>
@@ -477,6 +585,7 @@ export const RefreshDataDialog: React.FC<RefreshDataDialogProps> = ({
                         variant="contained"
                         onClick={handleUrlSubmit}
                         disabled={isLoading || !urlContent.trim() || !hasValidUrlSuffix}
+                        sx={{ textTransform: 'none' }}
                     >
                         Refresh Data
                     </Button>

From 6932f787a344353896afd329dc9db9c975a99107 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Sat, 17 Jan 2026 12:40:30 -0800
Subject: [PATCH 09/21] TODO add agentic data selection

---
 src/views/ChartRecBox.tsx       | 130 +-------------------------------
 src/views/EncodingShelfCard.tsx | 125 +-----------------------------
 2 files changed, 7 insertions(+), 248 deletions(-)

diff --git a/src/views/ChartRecBox.tsx b/src/views/ChartRecBox.tsx
index 943f833..4e403f6 100644
--- a/src/views/ChartRecBox.tsx
+++ b/src/views/ChartRecBox.tsx
@@ -69,111 +69,6 @@ export interface ChartRecBoxProps {
     sx?: SxProps;
 }
 
-// Table selector component for ChartRecBox
-const NLTableSelector: FC<{
-    selectedTableIds: string[],
-    tables: DictTable[],
-    updateSelectedTableIds: (tableIds: string[]) => void,
-    requiredTableIds?: string[]
-}> = ({ selectedTableIds, tables, updateSelectedTableIds, requiredTableIds = [] }) => {
-    const [anchorEl, setAnchorEl] = useState<null | HTMLElement>(null);
-    const open = Boolean(anchorEl);
-
-    const handleClick = (event: React.MouseEvent<HTMLElement>) => {
-        setAnchorEl(event.currentTarget);
-    };
-
-    const handleClose = () => {
-        setAnchorEl(null);
-    };
-
-    const handleTableSelect = (table: DictTable) => {
-        if (!selectedTableIds.includes(table.id)) {
-            updateSelectedTableIds([...selectedTableIds, table.id]);
-        }
-        handleClose();
-    };
-
-    return (
-        <Box sx={{ 
-            display: 'flex',
-            flexWrap: 'wrap',
-            gap: '2px',
-            padding: '4px',
-            marginBottom: 0.5,
-        }}>
-            {selectedTableIds.map((tableId) => {
-                const isRequired = requiredTableIds.includes(tableId);
-                return (
-                    <Chip
-                        key={tableId}
-                        label={tables.find(t => t.id == tableId)?.displayId}
-                        size="small"
-                        sx={{
-                            height: 16,
-                            fontSize: '10px',
-                            borderRadius: '2px',
-                            bgcolor: isRequired ? 'rgba(25, 118, 210, 0.2)' : 'rgba(25, 118, 210, 0.1)',
-                            color: 'rgba(0, 0, 0, 0.7)',
-                            '& .MuiChip-label': {
-                                pl: '4px',
-                                pr: '6px'
-                            }
-                        }}
-                        deleteIcon={isRequired ? undefined : <CloseIcon sx={{ fontSize: '8px', width: '12px', height: '12px' }} />}
-                        onDelete={isRequired ? undefined : () => updateSelectedTableIds(selectedTableIds.filter(id => id !== tableId))}
-                    />
-                );
-            })}
-            <Tooltip title="select tables for data formulation">
-                <IconButton
-                    size="small"
-                    onClick={handleClick}
-                    sx={{ 
-                        width: 16,
-                        height: 16,
-                        fontSize: '10px',
-                        padding: 0
-                    }}
-                >
-                    <AddIcon fontSize="inherit" />
-                </IconButton>
-            </Tooltip>
-            <Menu
-                anchorEl={anchorEl}
-                open={open}
-                onClose={handleClose}
-            >
-                {tables
-                    .filter(t => t.derive === undefined || t.anchored)
-                    .map((table) => {
-                        const isSelected = selectedTableIds.includes(table.id);
-                        const isRequired = requiredTableIds.includes(table.id);
-                        return (
-                            <MenuItem 
-                                disabled={isSelected}
-                                key={table.id}
-                                onClick={() => handleTableSelect(table)}
-                                sx={{ 
-                                    fontSize: '12px',
-                                    display: 'flex',
-                                    justifyContent: 'space-between',
-                                    alignItems: 'center'
-                                }}
-                            >
-                                {table.displayId}
-                                {isRequired && <Typography sx={{ fontSize: '10px', color: 'text.secondary' }}>(required)</Typography>}
-                            </MenuItem>
-                        );
-                    })
-                }
-            </Menu>
-        </Box>
-    );
-};
-
-
-
 export const IdeaChip: FC<{
     mini?: boolean,
     idea: {text?: string, questions?: string[], goal: string, difficulty: 'easy' | 'medium' | 'hard', type?: 'branch' | 'deep_dive'} 
@@ -357,17 +252,11 @@ export const ChartRecBox: FC<ChartRecBoxProps> = function ({ tableId, placeHolde
     const currentTable = tables.find(t => t.id === tableId);
 
     const availableTables = tables.filter(t => t.derive === undefined || t.anchored);
-    const [additionalTableIds, setAdditionalTableIds] = useState<string[]>([]);
-
+  
     // Combine the main tableId with additional selected tables
-    const selectedTableIds = currentTable?.derive ? [...currentTable.derive.source, ...additionalTableIds] : [tableId, ...additionalTableIds];
-
-    const handleTableSelectionChange = (newTableIds: string[]) => {
-        // Filter out the main tableId since it's always included
-        const additionalIds = newTableIds.filter(id => id !== tableId);
-        setAdditionalTableIds(additionalIds);
-    };
-
+    let selectedTableIds = currentTable?.derive ? [...currentTable.derive.source] : [tableId];
+    selectedTableIds = [...selectedTableIds, ...availableTables.map(t => t.id).filter(id => !selectedTableIds.includes(id))];
+    
     // Function to get a question from the list with cycling
     const getQuestion = (): string => {
         return mode === "agent" ? "let's explore something interesting about the data" : "show something interesting about the data";
@@ -1238,17 +1127,6 @@ export const ChartRecBox: FC<ChartRecBoxProps> = function ({ tableId, placeHolde
                         }} 
                     />
                 )}
-                {showTableSelector && (
-                    <Box>
-                        <NLTableSelector
-                            selectedTableIds={selectedTableIds}
-                            tables={availableTables}
-                            updateSelectedTableIds={handleTableSelectionChange}
-                            requiredTableIds={[tableId]}
-                        />
-                    </Box>
-                )}
-
                 <Box sx={{ display: 'flex', flexDirection: 'row', gap: 1, alignItems: 'flex-end' }}>
                     <TextField
                         variant="standard"
diff --git a/src/views/EncodingShelfCard.tsx b/src/views/EncodingShelfCard.tsx
index d66e357..bb230df 100644
--- a/src/views/EncodingShelfCard.tsx
+++ b/src/views/EncodingShelfCard.tsx
@@ -250,111 +250,6 @@ export const TriggerCard: FC<{
     </Card>
 }
 
-// Add this component before EncodingShelfCard
-const UserActionTableSelector: FC<{
-    requiredActionTableIds: string[],
-    userSelectedActionTableIds: string[],
-    tables: DictTable[],
-    updateUserSelectedActionTableIds: (tableIds: string[]) => void,
-    requiredTableIds?: string[]
-}> = ({ requiredActionTableIds, userSelectedActionTableIds, tables, updateUserSelectedActionTableIds, requiredTableIds = [] }) => {
-    const [anchorEl, setAnchorEl] = useState<null | HTMLElement>(null);
-    const open = Boolean(anchorEl);
-
-    let actionTableIds = [...requiredActionTableIds, ...userSelectedActionTableIds.filter(id => !requiredActionTableIds.includes(id))];
-
-    const handleClick = (event: React.MouseEvent<HTMLElement>) => {
-        setAnchorEl(event.currentTarget);
-    };
-
-    const handleClose = () => {
-        setAnchorEl(null);
-    };
-
-    const handleTableSelect = (table: DictTable) => {
-        if (!actionTableIds.includes(table.id)) {
-            updateUserSelectedActionTableIds([...userSelectedActionTableIds, table.id]);
-        }
-        handleClose();
-    };
-
-    return (
-        <Box sx={{ 
-            display: 'flex',
-            flexWrap: 'wrap',
-            gap: '2px',
-            padding: '4px',
-            marginBottom: 0.5,
-        }}>
-            {actionTableIds.map((tableId) => {
-                const isRequired = requiredTableIds.includes(tableId);
-                return (
-                    <Chip
-                        key={tableId}
-                        label={tables.find(t => t.id == tableId)?.displayId}
-                        size="small"
-                        sx={{
-                            height: 16,
-                            fontSize: '10px',
-                            borderRadius: '0px',
-                            bgcolor: isRequired ? 'rgba(25, 118, 210, 0.2)' : 'rgba(25, 118, 210, 0.1)', // darker blue for required
-                            color: 'rgba(0, 0, 0, 0.7)',
-                            '& .MuiChip-label': {
-                                pl: '4px',
-                                pr: '6px'
-                            }
-                        }}
-                        deleteIcon={<CloseIcon sx={{ fontSize: '8px', width: '12px', height: '12px' }} />}
-                        onDelete={isRequired ? undefined : () => updateUserSelectedActionTableIds(actionTableIds.filter(id => id !== tableId))}
-                    />
-                );
-            })}
-            <Tooltip title="add more base tables for data formulation">
-                <span>
-                    <IconButton
-                        size="small"
-                        onClick={handleClick}
-                        sx={{ 
-                            width: 16,
-                            height: 16,
-                            fontSize: '10px',
-                            padding: 0
-                        }}
-                    >
-                        <AddIcon fontSize="inherit" />
-                    </IconButton>
-                </span>
-            </Tooltip>
-            <Menu
-                anchorEl={anchorEl}
-                open={open}
-                onClose={handleClose}
-            >
-                {tables
-                    .map((table) => {
-                        const isSelected = !!actionTableIds.find(t => t === table.id);
-                        return (
-                            <MenuItem 
-                                disabled={isSelected}
-                                key={table.id}
-                                onClick={() => handleTableSelect(table)}
-                                sx={{ 
-                                    fontSize: '12px',
-                                    display: 'flex',
-                                    justifyContent: 'space-between',
-                                    alignItems: 'center'
-                                }}
-                            >
-                                {table.displayId}
-                            </MenuItem>
-                        );
-                    })
-                }
-            </Menu>
-        </Box>
-    );
-};
-
 
 export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId }) {
     const theme = useTheme();
@@ -363,7 +258,6 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
     const tables = useSelector((state: DataFormulatorState) => state.tables);
     const config = useSelector((state: DataFormulatorState) => state.config);
     const agentRules = useSelector((state: DataFormulatorState) => state.agentRules);
-    let existMultiplePossibleBaseTables = tables.filter(t => t.derive == undefined || t.anchored).length > 1;
 
     let activeModel = useSelector(dfSelectors.getActiveModel);
     let allCharts = useSelector(dfSelectors.getAllCharts);
@@ -401,9 +295,7 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
     // Check if chart is available
     let isChartAvailable = checkChartAvailability(chart, conceptShelfItems, currentTable.rows);
 
-    // Add this state
-    const [userSelectedActionTableIds, setUserSelectedActionTableIds] = useState<string[]>([]);
-    
+
     // Consolidated chart state - maps chartId to its ideas, thinkingBuffer, and loading state
     const [chartState, setChartState] = useState<Record<string, {
         ideas: {text: string, goal: string, difficulty: 'easy' | 'medium' | 'hard'}[],
@@ -441,11 +333,7 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
     
     // Add state for developer message dialog
     const [devMessageOpen, setDevMessageOpen] = useState<boolean>(false);
-    
-    // Update the handler to use state
-    const handleUserSelectedActionTableChange = (newTableIds: string[]) => {
-        setUserSelectedActionTableIds(newTableIds);
-    };
+
 
     let encodingBoxGroups = Object.entries(ChannelGroups)
         .filter(([group, channelList]) => channelList.some(ch => Object.keys(encodingMap).includes(ch)))
@@ -479,7 +367,7 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
     let requiredActionTables = selectBaseTables(activeFields, currentTable, tables);
     let actionTableIds = [
         ...requiredActionTables.map(t => t.id),
-        ...userSelectedActionTableIds.filter(id => !requiredActionTables.map(t => t.id).includes(id))
+        ...tables.filter(t => t.derive === undefined || t.anchored).map(t => t.id).filter(id => !requiredActionTables.map(t => t.id).includes(id))
     ];
 
     let getIdeasForVisualization = async () => {
@@ -1155,13 +1043,6 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
 
     let channelComponent = (
         <Box sx={{ width: "100%", minWidth: "210px", height: '100%', display: "flex", flexDirection: "column" }}>
-            {existMultiplePossibleBaseTables && <UserActionTableSelector 
-                requiredActionTableIds={requiredActionTables.map(t => t.id)}
-                userSelectedActionTableIds={userSelectedActionTableIds}
-                tables={tables.filter(t => t.derive === undefined || t.anchored)}
-                updateUserSelectedActionTableIds={handleUserSelectedActionTableChange}
-                requiredTableIds={requiredActionTables.map(t => t.id)}
-            />}
             <Box key='mark-selector-box' sx={{ flex: '0 0 auto' }}>
                 <FormControl sx={{ m: 1, minWidth: 120, width: "100%", margin: "0px 0"}} size="small">
                     <Select

From 12b123e5b9d7523e5a748dc06520c29201db1fb9 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Sat, 17 Jan 2026 12:48:21 -0800
Subject: [PATCH 10/21] fixes

---
 src/views/ChartRecBox.tsx             | 5 ++++-
 src/views/UnifiedDataUploadDialog.tsx | 2 +-
 2 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/src/views/ChartRecBox.tsx b/src/views/ChartRecBox.tsx
index 4e403f6..850631b 100644
--- a/src/views/ChartRecBox.tsx
+++ b/src/views/ChartRecBox.tsx
@@ -1146,7 +1146,10 @@ export const ChartRecBox: FC<ChartRecBoxProps> = function ({ tableId, placeHolde
                             "& .MuiInput-underline:not(.Mui-disabled):before": {
                                 borderBottom: 'none',
                             },
-                            "& .MuiInput-underline:(.Mui-disabled):before": {
+                            "& .MuiInput-underline.Mui-disabled:before": {
+                                borderBottom: 'none',
+                            },
+                            "& .MuiInput-underline.Mui-disabled:after": {
                                 borderBottom: 'none',
                             },
                             "& .MuiInput-underline:after": {
diff --git a/src/views/UnifiedDataUploadDialog.tsx b/src/views/UnifiedDataUploadDialog.tsx
index dfe5adf..82be5f0 100644
--- a/src/views/UnifiedDataUploadDialog.tsx
+++ b/src/views/UnifiedDataUploadDialog.tsx
@@ -796,7 +796,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                     </IconButton>
                 )}
                 <Typography variant="h6" component="span">
-                    {activeTab === 'menu' ? 'Add Data' : getCurrentTabTitle()}
+                    {activeTab === 'menu' ? 'Load Data' : getCurrentTabTitle()}
                 </Typography>
                 {activeTab === 'extract' && dataCleanBlocks.length > 0 && (
                     <Tooltip title="Reset extraction">

From 34b40bc483d611d06238435d84d200c4b4ff73d9 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 23 Jan 2026 04:42:58 +0000
Subject: [PATCH 11/21] Bump lodash from 4.17.21 to 4.17.23

Bumps [lodash](https://github.com/lodash/lodash) from 4.17.21 to 4.17.23.
- [Release notes](https://github.com/lodash/lodash/releases)
- [Commits](https://github.com/lodash/lodash/compare/4.17.21...4.17.23)

---
updated-dependencies:
- dependency-name: lodash
  dependency-version: 4.17.23
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 package.json |  2 +-
 yarn.lock    | 16 ++++++++--------
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/package.json b/package.json
index 66bfcfd..fdb706d 100644
--- a/package.json
+++ b/package.json
@@ -20,7 +20,7 @@
         "html2canvas": "^1.4.1",
         "katex": "^0.16.22",
         "localforage": "^1.10.0",
-        "lodash": "^4.17.21",
+        "lodash": "^4.17.23",
         "markdown-to-jsx": "^7.4.0",
         "mui-markdown": "^2.0.3",
         "prettier": "^2.8.3",
diff --git a/yarn.lock b/yarn.lock
index f1d9bfb..c5f41b6 100644
--- a/yarn.lock
+++ b/yarn.lock
@@ -3552,10 +3552,10 @@ lodash.uniq@^4.5.0:
   resolved "https://registry.npmjs.org/lodash.uniq/-/lodash.uniq-4.5.0.tgz"
   integrity sha512-xfBaXQd9ryd9dlSDvnvI0lvxfLJlYAZzXomUYzLKtUeOQvOP5piqAWuGtrhWeqaXK9hhoM/iyJc5AV+XfsX3HQ==
 
-lodash@^4.17.21:
-  version "4.17.21"
-  resolved "https://registry.npmjs.org/lodash/-/lodash-4.17.21.tgz"
-  integrity sha512-v2kDEe57lecTulaDIuNTPy3Ry4gLGJ6Z1O3vE1krgXZNrsQ+LFTGHVxVjcXPs17LhbZVGedAJv8XZ1tvj5FvSg==
+lodash@^4.17.23:
+  version "4.17.23"
+  resolved "https://registry.yarnpkg.com/lodash/-/lodash-4.17.23.tgz#f113b0378386103be4f6893388c73d0bde7f2c5a"
+  integrity sha512-LgVTMpQtIopCi79SJeDiP0TfWi5CNEc/L/aRdTh3yIvmZXTnheWpKjSZhnvMl8iXbC1tFg9gdHHDMLoV7CnG+w==
 
 loose-envify@^1.1.0, loose-envify@^1.4.0:
   version "1.4.0"
@@ -4801,10 +4801,10 @@ uuid@^8.3.0:
   resolved "https://registry.npmjs.org/uuid/-/uuid-8.3.2.tgz"
   integrity sha512-+NYs2QeMWy+GWFOEm9xnn6HCDp0l7QBD7ml8zLUmJ+93Q5NF0NocErnwkTkXVFNiX3/fpC6afS8Dhb/gz7R7eg==
 
-validator@^13.15.22:
-  version "13.15.22"
-  resolved "https://registry.yarnpkg.com/validator/-/validator-13.15.22.tgz#5f847cf4a799107e5716fc87e5cf2a337a71eb14"
-  integrity sha512-uT/YQjiyLJP7HSrv/dPZqK9L28xf8hsNca01HSz1dfmI0DgMfjopp1rO/z13NeGF1tVystF0Ejx3y4rUKPw+bQ==
+validator@^13.15.20:
+  version "13.15.26"
+  resolved "https://registry.yarnpkg.com/validator/-/validator-13.15.26.tgz#36c3deeab30e97806a658728a155c66fcaa5b944"
+  integrity sha512-spH26xU080ydGggxRyR1Yhcbgx+j3y5jbNXk/8L+iRvdIEQ4uTRH2Sgf2dokud6Q4oAtsbNvJ1Ft+9xmm6IZcA==
 
 vega-canvas@^2.0.0:
   version "2.0.0"

From 816dc5a72509b94df5cd8d66779bd47aa54b3ebf Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Sat, 24 Jan 2026 00:03:07 -0800
Subject: [PATCH 12/21] refresh data design v1

---
 .gitignore                                    |   5 +
 .../agents/agent_py_data_rec.py               |  41 +-
 .../agents/agent_py_data_transform.py         |  49 +-
 py-src/data_formulator/agents/agent_utils.py  |  61 +-
 py-src/data_formulator/app.py                 |   6 +
 .../data_loader/external_data_loader.py       |  17 +-
 py-src/data_formulator/demo_stream_routes.py  | 925 ++++++++++++++++++
 .../example_datasets_config.py                |  88 ++
 py-src/data_formulator/tables_routes.py       | 333 ++++++-
 requirements.txt                              |   2 +
 src/app/dfSlice.tsx                           |  43 +-
 src/app/useDataRefresh.tsx                    | 649 ++++++++++++
 src/app/utils.tsx                             | 107 +-
 src/components/ChartTemplates.tsx             |  60 +-
 src/components/ComponentType.tsx              |  45 +-
 src/scss/DataView.scss                        |  33 +-
 src/views/DBTableManager.tsx                  | 144 ++-
 src/views/DataFormulator.tsx                  |   9 +-
 src/views/DataThread.tsx                      | 453 +++++++--
 src/views/DataView.tsx                        |   2 +-
 src/views/EncodingShelfCard.tsx               |  88 +-
 src/views/ReportView.tsx                      |  64 ++
 src/views/SelectableDataGrid.tsx              | 254 ++++-
 src/views/TableSelectionView.tsx              |  38 +-
 src/views/UnifiedDataUploadDialog.tsx         | 514 +++++++---
 25 files changed, 3552 insertions(+), 478 deletions(-)
 create mode 100644 py-src/data_formulator/demo_stream_routes.py
 create mode 100644 src/app/useDataRefresh.tsx

diff --git a/.gitignore b/.gitignore
index df0ef7c..f3420ac 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,6 +5,7 @@
 .DS_Store
 build/
 dist/
+experiment_data/
 
 ## Ignore Visual Studio temporary files, build results, and
 ## files generated by popular Visual Studio add-ons.
@@ -405,3 +406,7 @@ FodyWeavers.xsd
 # JetBrains Rider
 *.sln.iml
 venv
+
+
+\.\NUL
+NUL
\ No newline at end of file
diff --git a/py-src/data_formulator/agents/agent_py_data_rec.py b/py-src/data_formulator/agents/agent_py_data_rec.py
index 2fce791..1ff67b0 100644
--- a/py-src/data_formulator/agents/agent_py_data_rec.py
+++ b/py-src/data_formulator/agents/agent_py_data_rec.py
@@ -32,6 +32,7 @@
     "recap": "..." // string, a short summary of the user's goal.
     "display_instruction": "..." // string, the even shorter verb phrase describing the users' goal.
     "recommendation": "..." // string, explain why this recommendation is made
+    "input_tables": [...] // string[], describe names of the input tables that will be used in the transformation.
     "output_fields": [...] // string[], describe the desired output fields that the output data should have (i.e., the goal of transformed data), it's a good idea to preseve intermediate fields here
     "chart_type": "" // string, one of "point", "bar", "line", "area", "heatmap", "group_bar", 'boxplot'. "chart_type" should either be inferred from user instruction, or recommend if the user didn't specify any.
     "chart_encodings": {
@@ -65,6 +66,7 @@
         - if you mention column names from the input or the output data, highlight the text in **bold**.
             * the column can either be a column in the input data, or a new column that will be computed in the output data.
             * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned "average score" in the text while the column to be computed is "Avg_Score", you should still highlight "**average score**" in the text.
+    - determine "input_tables", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.
     - "chart_type" must be one of "point", "bar", "line", "area", "heatmap", "group_bar", "boxplot"
     - "chart_encodings" should specify which fields should be used to create the visualization
         - decide which visual channels should be used to create the visualization appropriate for the chart type.
@@ -157,9 +159,11 @@ def transform_data(df1, df2, ...):
 ```
 
 note: 
-- if the user provided one table, then it should be `def transform_data(df1)`, if the user provided multiple tables, then it should be `def transform_data(df1, df2, ...)` and you should consider the join between tables to derive the output.
-- **VERY IMPORTANT** the number of arguments in the function must match the number of tables provided, and the order of arguments must match the order of tables provided.
-- you can use intuitive table names to refer to the input dataframes, for example, if the user provided two tables city and weather, you can use `transform_data(df_city, df_weather)` to refer to the two dataframes, as long as the number and order of the arguments match the number and order of the tables provided.
+- decide the function signature based on the number of tables you decided in the previous step "input_tables":
+    - if you decide there will only be one input table, then function signature should be `def transform_data(df1)`
+    - if you decided there will be k input tables, then function signature should be `def transform_data(df_1, df_2, ..., df_k)`.
+    - instead of using generic names like df1, df2, ..., try to use intuitive table names for function arguments, for example, if you have input_tables: ["City", "Weather"]`, you can use `transform_data(df_city, df_weather)` to refer to the two dataframes.
+    - **VERY IMPORTANT** the number of arguments in the function signature must be the same as the number of tables provided in "input_tables", and the order of arguments must match the order of tables provided in "input_tables".
 - datetime objects handling:
     - if the output field is year, convert it to number, if it is year-month / year-month-day, convert it to string object (e.g., "2020-01" / "2020-01-01").
     - if the output is time only: convert hour to number if it's just the hour (e.g., 10), but convert hour:min or h:m:s to string object (e.g., "10:30", "10:30:45")
@@ -205,6 +209,7 @@ def transform_data(df1, df2, ...):
     "display_instruction": "Rank students by average scores",
     "mode": "infer",
     "recommendation": "To rank students based on their average scores, we need to calculate the average score for each student, then sort the data, and finally assign a rank to each student based on their average score.",  
+    "input_tables": ["student_exam"],
     "output_fields": ["student", "major", "average_score", "rank"],  
     "chart_type": "bar",  
     "chart_encodings": {"x": "student", "y": "average_score"},  
@@ -260,7 +265,7 @@ def process_gpt_response(self, input_tables, messages, response):
             if len(json_blocks) > 0:
                 refined_goal = json_blocks[0]
             else:
-                refined_goal = { 'mode': "", 'recommendation': "", 'output_fields': [], 'chart_encodings': {}, 'chart_type': "" }
+                refined_goal = { 'mode': "", 'recommendation': "", 'input_tables': [], 'output_fields': [], 'chart_encodings': {}, 'chart_type': "" }
 
             code_blocks = extract_code_from_gpt_response(choice.message.content + "\n", "python")
 
@@ -268,7 +273,33 @@ def process_gpt_response(self, input_tables, messages, response):
                 code_str = code_blocks[-1]
 
                 try:
-                    result = py_sandbox.run_transform_in_sandbox2020(code_str, [pd.DataFrame.from_records(t['rows']) for t in input_tables], self.exec_python_in_subprocess)
+                    # Check if input_tables is available
+                    if not input_tables:
+                        result = {'status': 'error', 'code': code_str, 'content': "No input tables available."}
+                    else:
+                        # Determine which tables to use based on refined_goal
+                        if 'input_tables' in refined_goal and isinstance(refined_goal['input_tables'], list) and len(refined_goal['input_tables']) > 0:
+                            # Use only specified tables - validate all exist
+                            table_name_map = {t['name']: t for t in input_tables}
+                            tables_to_use = []
+                            missing_tables = []
+                            
+                            for table_name in refined_goal['input_tables']:
+                                if table_name in table_name_map:
+                                    tables_to_use.append(table_name_map[table_name])
+                                else:
+                                    missing_tables.append(table_name)
+                            
+                            # Error if any specified table is missing
+                            if missing_tables:
+                                available_table_names = [t['name'] for t in input_tables]
+                                result = {'status': 'error', 'code': code_str, 'content': f"Table(s) '{', '.join(missing_tables)}' specified in 'input_tables' not found. Available tables: {', '.join(available_table_names)}"}
+                            else:
+                                result = py_sandbox.run_transform_in_sandbox2020(code_str, [pd.DataFrame.from_records(t['rows']) for t in tables_to_use], self.exec_python_in_subprocess)
+                        else:
+                            # No input_tables specified in refined_goal, use all input_tables
+                            result = py_sandbox.run_transform_in_sandbox2020(code_str, [pd.DataFrame.from_records(t['rows']) for t in input_tables], self.exec_python_in_subprocess)
+                    
                     result['code'] = code_str
 
                     if result['status'] == 'ok':
diff --git a/py-src/data_formulator/agents/agent_py_data_transform.py b/py-src/data_formulator/agents/agent_py_data_transform.py
index b492857..5b86b9e 100644
--- a/py-src/data_formulator/agents/agent_py_data_transform.py
+++ b/py-src/data_formulator/agents/agent_py_data_transform.py
@@ -34,6 +34,7 @@
             - if you mention column names from the input or the output data, highlight the text in **bold**.
                 * the column can either be a column in the input data, or a new column that will be computed in the output data.
                 * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned "average score" in the text while the column to be computed is "Avg_Score", you should still highlight "**average score**" in the text.
+        - determine "input_tables", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.
         - determine "output_fields", the desired fields that the output data should have to achieve the user's goal, it's a good idea to include intermediate fields here.
         - then decide "chart_encodings", which maps visualization channels (x, y, color, size, opacity, facet, etc.) to a subset of "output_fields" that will be visualized, 
             - the "chart_encodings" should be created to support the user's "chart_type".
@@ -48,7 +49,7 @@
                 - e.g., they may mention "use B metric instead" while A metric is in provided fields, in this case, you should update "chart_encodings" to update A metric with B metric.
         - guide on statistical analysis:
             - when the user asks for forecasting or regression analysis, you should consider the following:
-                - the output should be a long format table where actual x, y pairs and predicted x, y pairs are included in the X, Y columns, they are differentiated with a third column "is_predicted" that is a boolean field.
+                - the output should be a long format table where actual x, y pairs and predicted x, y pairs are included in the X, Y columns, they are differentiated with a third column "is_predicted".
                 - i.e., if the user ask for forecasting based on two columns T and Y, the output should be three columns: T, Y, is_predicted, where
                     - T, Y columns contain BOTH original values from the data and predicted values from the data.
                     - is_predicted is a boolean field to indicate whether the x, y pairs are original values from the data or predicted / regression values from the data.
@@ -65,6 +66,7 @@
 {
     "detailed_instruction": "..." // string, elaborate user instruction with details if the user
     "display_instruction": "..." // string, the short verb phrase describing the users' goal.
+    "input_tables": [...] // string[], describe names of the input tables that will be used in the transformation.
     "output_fields": [...] // string[], describe the desired output fields that the output data should have based on the user's goal, it's a good idea to preserve intermediate fields here (i.e., the goal of transformed data)
     "chart_encodings": {
         "x": "",
@@ -79,8 +81,8 @@
 }
 ```
 
-    2. Then, write a python function based on the refined goal, the function input is a dataframe "df" (or multiple dataframes based on tables presented in the [CONTEXT] section) and the output is the transformed dataframe "transformed_df". "transformed_df" should contain all "output_fields" from the refined goal.
-The python function must follow the template provided in [TEMPLATE], do not import any other libraries or modify function name. The function should be as simple as possible and easily readable.
+    2. Then, write a python function based on the refined goal, the function input is a dataframe "df" (or multiple dataframes based on tables described in "input_tables") and the output is the transformed dataframe "transformed_df". "transformed_df" should contain all "output_fields" from the refined goal.
+The python function must follow the template provided in [TEMPLATE], only import libraries allowed in the template, do not modify function name. The function should be as simple as possible and easily readable.
 If there is no data transformation needed based on "output_fields", the transformation function can simply "return df".
 
 [TEMPLATE]
@@ -97,9 +99,11 @@ def transform_data(df1, df2, ...):
 ```
 
 note: 
-- if the user provided one table, then it should be `def transform_data(df1)`, if the user provided multiple tables, then it should be `def transform_data(df1, df2, ...)` and you should consider the join between tables to derive the output.
-- **VERY IMPORTANT** the number of arguments in the function must match the number of tables provided, and the order of arguments must match the order of tables provided.
-- try to use intuitive table names to refer to the input dataframes, for example, if the user provided two tables city and weather, you can use `transform_data(df_city, df_weather)` to refer to the two dataframes, as long as the number and order of the arguments match the number and order of the tables provided.
+- decide the function signature based on the number of tables you decided in the previous step "input_tables":
+    - if you decide there will only be one input table, then function signature should be `def transform_data(df1)`
+    - if you decided there will be k input tables, then function signature should be `def transform_data(df_1, df_2, ..., df_k)`.
+    - instead of using generic names like df1, df2, ..., try to use intuitive table names for function arguments, for example, if you have input_tables: ["City", "Weather"]`, you can use `transform_data(df_city, df_weather)` to refer to the two dataframes.
+    - **VERY IMPORTANT** the number of arguments in the function signature must be the same as the number of tables provided in "input_tables", and the order of arguments must match the order of tables provided in "input_tables".
 - datetime objects handling:
     - if the output field is year, convert it to number, if it is year-month / year-month-day, convert it to string object (e.g., "2020-01" / "2020-01-01").
     - if the output is time only: convert hour to number if it's just the hour (e.g., 10), but convert hour:min or h:m:s to string object (e.g., "10:30", "10:30:45")
@@ -202,6 +206,7 @@ def transform_data(df):
 
 {  
     "detailed_instruction": "Create a scatter plot to compare Seattle and Atlanta temperatures with Seattle temperatures on the x-axis and Atlanta temperatures on the y-axis. Color the points by which city is warmer.",  
+    "input_tables": ["weather_seattle_atlanta"],
     "output_fields": ["Date", "Seattle Temperature", "Atlanta Temperature", "Warmer City"],  
     "chart_encodings": {"x": "Seattle Temperature", "y": "Atlanta Temperature", "color": "Warmer City"},  
     "reason": "To compare Seattle and Atlanta temperatures with Seattle temperatures on the x-axis and Atlanta temperatures on the y-axis, and color points by which city is warmer, separate temperature fields for Seattle and Atlanta are required. Additionally, a new field 'Warmer City' is needed to indicate which city is warmer."  
@@ -212,7 +217,7 @@ def transform_data(df):
 import collections  
 import numpy as np  
   
-def transform_data(df):  
+def transform_data(df_weather_seattle_atlanta):  
     # Pivot the dataframe to have separate columns for Seattle and Atlanta temperatures  
     df_pivot = df.pivot(index='Date', columns='City', values='Temperature').reset_index()  
     df_pivot.columns = ['Date', 'Atlanta Temperature', 'Seattle Temperature']  
@@ -260,7 +265,7 @@ def process_gpt_response(self, input_tables, messages, response):
             if len(json_blocks) > 0:
                 refined_goal = json_blocks[0]
             else:
-                refined_goal = {'chart_encodings': {}, 'instruction': '', 'reason': ''}
+                refined_goal = {'chart_encodings': {}, 'instruction': '', 'reason': '', 'input_tables': []}
 
             code_blocks = extract_code_from_gpt_response(choice.message.content + "\n", "python")
 
@@ -268,7 +273,33 @@ def process_gpt_response(self, input_tables, messages, response):
                 code_str = code_blocks[-1]
 
                 try:
-                    result = py_sandbox.run_transform_in_sandbox2020(code_str, [pd.DataFrame.from_records(t['rows']) for t in input_tables], self.exec_python_in_subprocess)
+                    # Check if input_tables is available
+                    if not input_tables:
+                        result = {'status': 'error', 'code': code_str, 'content': "No input tables available."}
+                    else:
+                        # Determine which tables to use based on refined_goal
+                        if 'input_tables' in refined_goal and isinstance(refined_goal['input_tables'], list) and len(refined_goal['input_tables']) > 0:
+                            # Use only specified tables - validate all exist
+                            table_name_map = {t['name']: t for t in input_tables}
+                            tables_to_use = []
+                            missing_tables = []
+                            
+                            for table_name in refined_goal['input_tables']:
+                                if table_name in table_name_map:
+                                    tables_to_use.append(table_name_map[table_name])
+                                else:
+                                    missing_tables.append(table_name)
+                            
+                            # Error if any specified table is missing
+                            if missing_tables:
+                                available_table_names = [t['name'] for t in input_tables]
+                                result = {'status': 'error', 'code': code_str, 'content': f"Table(s) '{', '.join(missing_tables)}' specified in 'input_tables' not found. Available tables: {', '.join(available_table_names)}"}
+                            else:
+                                result = py_sandbox.run_transform_in_sandbox2020(code_str, [pd.DataFrame.from_records(t['rows']) for t in tables_to_use], self.exec_python_in_subprocess)
+                        else:
+                            # No input_tables specified in refined_goal, use all input_tables
+                            result = py_sandbox.run_transform_in_sandbox2020(code_str, [pd.DataFrame.from_records(t['rows']) for t in input_tables], self.exec_python_in_subprocess)
+                    
                     result['code'] = code_str
 
                     if result['status'] == 'ok':
diff --git a/py-src/data_formulator/agents/agent_utils.py b/py-src/data_formulator/agents/agent_utils.py
index 0bd4d18..87a3a14 100644
--- a/py-src/data_formulator/agents/agent_utils.py
+++ b/py-src/data_formulator/agents/agent_utils.py
@@ -216,32 +216,61 @@ def sample_val_cap(val):
     return f"{field_name} -- type: {df[field_name].dtype}, values: {val_str}"
 
 def generate_data_summary(input_tables, include_data_samples=True, field_sample_size=7, max_val_chars=140):
+    """
+    Generate a natural, well-organized summary of input tables.
+    
+    Organization approach:
+    - Each table is clearly separated with a header
+    - Information flows logically: Overview → Schema → Examples
+    - Consistent section ordering for better readability
+    """
     
     def assemble_table_summary(input_table, idx):
-        table_id = f'table{idx+1}'
         name = string_to_py_varname(input_table["name"])
         rows = input_table["rows"]
         description = input_table.get("attached_metadata", "")
         
         df = pd.DataFrame(rows)
-        fields_summary = '\n'.join(['\t*' + get_field_summary(fname, df, field_sample_size, max_val_chars)  for fname in list(df.columns.values)])
-
-        fields_section = f'## fields\n{fields_summary}\n\n'
-        sample_section = f'## sample\n{pd.DataFrame(rows[:5]).to_string()}\n......\n\n' if include_data_samples else ''
-        description_section = f'## description\n{description}\n\n' if description else ''
-
-        summary_str = f'''# {table_id} ({name})\n\n{description_section}{fields_section}{sample_section}'''
-        return summary_str
+        num_rows = len(df)
+        num_cols = len(df.columns)
+        
+        # Build sections in logical order: Overview → Schema → Examples
+        sections = []
+        
+        # 1. Table Header with basic stats
+        header = f"## Table {idx + 1}: {name}"
+        if num_rows > 0:
+            header += f" ({num_rows:,} rows × {num_cols} columns)"
+        sections.append(header)
+        sections.append("")  # Empty line for spacing
+        
+        # 2. Description (if available) - provides context first
+        if description:
+            sections.append(f"### Description\n{description}\n")
+        
+        # 3. Schema/Fields - core structure information
+        fields_summary = '\n'.join(['  - ' + get_field_summary(fname, df, field_sample_size, max_val_chars) 
+                                    for fname in list(df.columns.values)])
+        sections.append(f"### Schema ({num_cols} fields)\n{fields_summary}\n")
+        
+        # 4. Sample data (if requested) - concrete examples last
+        if include_data_samples and num_rows > 0:
+            sample_df = pd.DataFrame(rows[:5])
+            sections.append(f"### Sample Data (first 5 rows)\n```\n{sample_df.to_string()}\n```\n")
+        
+        return '\n'.join(sections)
 
+    # Join tables with clear separators
     table_summaries = [assemble_table_summary(input_table, i) for i, input_table in enumerate(input_tables)]
     
-    # Join with newline (extracted from f-string for Python 3.9/3.10 compatibility)
-    joined_summaries = '\n'.join(table_summaries)
+    # Add visual separator between tables (except for the last one)
+    separator = "\n" + "─" * 60 + "\n\n"
+    joined_summaries = separator.join(table_summaries)
     
-    full_summary = f'''Here are our datasets, here are their summaries and samples:
-
-{joined_summaries}
-'''
-
+    # Natural introduction
+    num_tables = len(input_tables)
+    intro = f"Here are {num_tables} dataset{'s' if num_tables != 1 else ''} with their summaries:\n\n"
+    
+    full_summary = intro + joined_summaries
     return full_summary
 
diff --git a/py-src/data_formulator/app.py b/py-src/data_formulator/app.py
index ceb8d32..a767d27 100644
--- a/py-src/data_formulator/app.py
+++ b/py-src/data_formulator/app.py
@@ -35,6 +35,7 @@
 # blueprints
 from data_formulator.tables_routes import tables_bp
 from data_formulator.agent_routes import agent_bp
+from data_formulator.demo_stream_routes import demo_stream_bp, limiter as demo_stream_limiter
 from data_formulator.db_manager import db_manager
 from data_formulator.example_datasets_config import EXAMPLE_DATASETS
 
@@ -45,6 +46,10 @@
 app.secret_key = secrets.token_hex(16)  # Generate a random secret key for sessions
 app.json.sort_keys = False
 
+# Initialize rate limiter for demo stream routes that call external APIs
+# The limiter is defined in demo_stream_routes.py to avoid circular imports
+demo_stream_limiter.init_app(app)
+
 class CustomJSONEncoder(json.JSONEncoder):
     def default(self, obj):
         if isinstance(obj, np.int64):
@@ -74,6 +79,7 @@ def default(self, obj):
 if not app.config['CLI_ARGS']['disable_database']:
     app.register_blueprint(tables_bp)
 app.register_blueprint(agent_bp)
+app.register_blueprint(demo_stream_bp)
 
 # Get logger for this module (logging config moved to run_app function)
 logger = logging.getLogger(__name__)
diff --git a/py-src/data_formulator/data_loader/external_data_loader.py b/py-src/data_formulator/data_loader/external_data_loader.py
index 6bc4425..8048085 100644
--- a/py-src/data_formulator/data_loader/external_data_loader.py
+++ b/py-src/data_formulator/data_loader/external_data_loader.py
@@ -56,19 +56,8 @@ def ingest_df_to_duckdb(self, df: pd.DataFrame, table_name: str):
             if pd.api.types.is_datetime64_any_dtype(df[col]):
                 sample_values = df[col].dropna().head(3)
                 logger.info(f"Datetime column '{col}' sample values: {list(sample_values)}")
-
-        base_name = table_name
-        counter = 1
-        while True:
-            # Check if table exists
-            exists = self.duck_db_conn.execute(f"SELECT COUNT(*) FROM duckdb_tables() WHERE table_name = '{table_name}'").fetchone()[0] > 0
-            if not exists:
-                break
-            # If exists, append counter to base name
-            table_name = f"{base_name}_{counter}"
-            counter += 1
     
-        # Create table
+        # Create or replace table (replaces existing table with same name)
         random_suffix = ''.join(random.choices(string.ascii_letters + string.digits, k=6))
         self.duck_db_conn.register(f'df_temp_{random_suffix}', df)
         
@@ -79,10 +68,10 @@ def ingest_df_to_duckdb(self, df: pd.DataFrame, table_name: str):
         except Exception as e:
             logger.warning(f"Could not get schema info: {e}")
         
-        self.duck_db_conn.execute(f"CREATE TABLE {table_name} AS SELECT * FROM df_temp_{random_suffix}")
+        self.duck_db_conn.execute(f"CREATE OR REPLACE TABLE {table_name} AS SELECT * FROM df_temp_{random_suffix}")
         self.duck_db_conn.execute(f"DROP VIEW df_temp_{random_suffix}")  # Drop the temporary view after creating the table
         
-        logger.info(f"Successfully created DuckDB table '{table_name}'")
+        logger.info(f"Successfully created/replaced DuckDB table '{table_name}'")
     
     
     @staticmethod
diff --git a/py-src/data_formulator/demo_stream_routes.py b/py-src/data_formulator/demo_stream_routes.py
new file mode 100644
index 0000000..e8b5829
--- /dev/null
+++ b/py-src/data_formulator/demo_stream_routes.py
@@ -0,0 +1,925 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+"""
+Demo data REST APIs for streaming/refresh demos.
+
+Design Philosophy:
+- Each endpoint returns a COMPLETE dataset (not just a single row)
+- Datasets are meaningful on their own for analysis/visualization
+- When refreshed, datasets change over time:
+  * New rows may be added (accumulating data)
+  * Existing values may update (latest readings)
+- This allows tracking trends, changes, and patterns over time
+
+Example Use Cases:
+- Stock prices: "Last 30 days" grows daily with new data
+- ISS position: Track trajectory over last N minutes
+- Earthquakes: All quakes since a start date accumulates
+
+Rate Limiting:
+- External API routes are rate-limited to prevent abuse
+- Limits are set per IP address using Flask-Limiter
+"""
+
+import random
+import logging
+import requests
+import io
+import csv
+import math
+from datetime import datetime, timedelta
+from flask import Blueprint, Response, request, jsonify
+from typing import List, Dict, Any, Optional
+from collections import deque
+import threading
+
+logger = logging.getLogger(__name__)
+
+demo_stream_bp = Blueprint('demo_stream', __name__, url_prefix='/api/demo-stream')
+
+# ============================================================================
+# Rate Limiting Configuration
+# ============================================================================
+# Uses Flask-Limiter with deferred app initialization to avoid circular imports.
+# The limiter is created here and init_app() is called from app.py.
+
+from flask_limiter import Limiter
+from flask_limiter.util import get_remote_address
+
+# Create limiter without app - will be initialized via init_app() in app.py
+limiter = Limiter(
+    key_func=get_remote_address,
+    default_limits=[],  # No default limits - only apply to specific routes
+    storage_uri="memory://",
+    strategy="fixed-window",
+)
+
+# Rate limit strings for different endpoint types
+# These are applied to routes that call external APIs
+
+# ISS API (open-notify.org) - generous limits
+ISS_RATE_LIMIT = "30 per minute"
+
+# USGS Earthquake API - allow reasonable queries
+EARTHQUAKE_RATE_LIMIT = "20 per minute"
+
+# Weather APIs (Open-Meteo, NWS) - moderate limits
+WEATHER_RATE_LIMIT = "20 per minute"
+
+# yfinance API - more restrictive due to Yahoo's limits
+YFINANCE_RATE_LIMIT = "10 per minute"
+
+# Simulated/mock data - no external calls, more generous
+MOCK_RATE_LIMIT = "60 per minute"
+
+# Try to import yfinance
+import yfinance as yf
+
+
+# ============================================================================
+# Helper Functions
+# ============================================================================
+
+def make_csv_response(rows: list, filename: str = "data.csv") -> Response:
+    """Convert list of dicts to CSV text response"""
+    if not rows:
+        return Response("", mimetype='text/csv')
+    
+    output = io.StringIO()
+    writer = csv.DictWriter(output, fieldnames=rows[0].keys())
+    writer.writeheader()
+    writer.writerows(rows)
+    
+    return Response(
+        output.getvalue(),
+        mimetype='text/csv',
+        headers={'Access-Control-Allow-Origin': '*'}
+    )
+
+
+# ============================================================================
+# ISS Location Tracking - Real-time trajectory
+# Returns accumulated position history that grows over time
+# Recommended refresh: 5-10 seconds
+# ============================================================================
+
+# Thread-safe storage for ISS position history
+_iss_track_lock = threading.Lock()
+_iss_track_history: deque = deque(maxlen=500)  # Keep last 500 positions (~40 min at 5s intervals)
+_iss_last_fetch: Optional[datetime] = None
+
+def _fetch_iss_position() -> Optional[Dict[str, Any]]:
+    """Fetch current ISS position from API"""
+    try:
+        response = requests.get("http://api.open-notify.org/iss-now.json", timeout=10)
+        response.raise_for_status()
+        data = response.json()
+        position = data.get("iss_position", {})
+        return {
+            "timestamp": datetime.utcfromtimestamp(data.get("timestamp", 0)).isoformat() + "Z",
+            "latitude": float(position.get("latitude", 0)),
+            "longitude": float(position.get("longitude", 0)),
+        }
+    except Exception as e:
+        logger.warning(f"Failed to fetch ISS position: {e}")
+        return None
+
+
+@demo_stream_bp.route('/iss', methods=['GET'])
+@limiter.limit(ISS_RATE_LIMIT)
+def get_iss():
+    """
+    ISS position trajectory over time. Each refresh adds new position(s).
+    
+    Query params:
+        - minutes: How many minutes of history to return (default: 30, max: 60)
+        - limit: Max number of points to return (default: 100, max: 500)
+    
+    Data accumulates over time - each refresh may add new positions.
+    The ISS completes one orbit in ~90 minutes, so 30 min shows ~1/3 of orbit.
+    
+    Recommended refresh: 5-10 seconds
+    """
+    global _iss_last_fetch
+    
+    minutes = min(60, max(1, int(request.args.get('minutes', 30))))
+    limit = min(500, max(10, int(request.args.get('limit', 100))))
+    
+    now = datetime.utcnow()
+    cutoff = now - timedelta(minutes=minutes)
+    
+    # Fetch new position if enough time has passed (at least 3 seconds)
+    with _iss_track_lock:
+        should_fetch = _iss_last_fetch is None or (now - _iss_last_fetch).total_seconds() >= 3
+        
+        if should_fetch:
+            position = _fetch_iss_position()
+            if position:
+                position["fetched_at"] = now.isoformat() + "Z"
+                _iss_track_history.append(position)
+                _iss_last_fetch = now
+        
+        # Filter to requested time window and limit
+        rows = []
+        for pos in _iss_track_history:
+            try:
+                pos_time = datetime.fromisoformat(pos["timestamp"].replace("Z", "+00:00")).replace(tzinfo=None)
+                if pos_time >= cutoff:
+                    rows.append(pos)
+            except:
+                continue
+        
+        # Limit and sort by time
+        rows = sorted(rows, key=lambda x: x["timestamp"])[-limit:]
+    
+    # If we have no data yet, fetch once and return
+    if not rows:
+        position = _fetch_iss_position()
+        if position:
+            position["fetched_at"] = now.isoformat() + "Z"
+            rows = [position]
+    
+    return make_csv_response(rows)
+
+
+@demo_stream_bp.route('/iss/current', methods=['GET'])
+@limiter.limit(ISS_RATE_LIMIT)
+def get_iss_current():
+    """
+    Current ISS position only (single row).
+    Use /iss for trajectory tracking over time.
+    Recommended refresh: 5 seconds
+    """
+    try:
+        response = requests.get("http://api.open-notify.org/iss-now.json", timeout=10)
+        response.raise_for_status()
+        data = response.json()
+        
+        position = data.get("iss_position", {})
+        rows = [{
+            "timestamp": datetime.utcfromtimestamp(data.get("timestamp", 0)).isoformat() + "Z",
+            "latitude": float(position.get("latitude", 0)),
+            "longitude": float(position.get("longitude", 0)),
+            "fetched_at": datetime.utcnow().isoformat() + "Z"
+        }]
+        return make_csv_response(rows)
+    except Exception as e:
+        return Response(f"error,{str(e)}", mimetype='text/csv'), 500
+
+
+# ============================================================================
+# USGS Earthquakes - Accumulating dataset of seismic events
+# Data naturally grows over time as new earthquakes occur
+# Recommended refresh: 60 seconds
+# ============================================================================
+
+@demo_stream_bp.route('/earthquakes', methods=['GET'])
+@limiter.limit(EARTHQUAKE_RATE_LIMIT)
+def get_earthquakes():
+    """
+    Earthquakes from USGS. Dataset grows as new quakes occur.
+    
+    Query params:
+        - timeframe: 'hour', 'day', 'week', 'month' (default: 'day')
+        - min_magnitude: Minimum magnitude filter (default: 0)
+        - max_magnitude: Maximum magnitude filter (optional)
+        - since: ISO date string - only return quakes after this time
+        - limit: Maximum number of results (default: 20000, max: 20000)
+        - use_query_api: 'true' to use query API for more data (default: 'false' for quick summary)
+    
+    Use case:
+        - Set timeframe='week' to see a week of earthquake data
+        - Each refresh may show new earthquakes that occurred
+        - Use min_magnitude to filter for significant quakes (e.g., 4.0+)
+        - Set use_query_api=true and limit=10000 to get large datasets
+    
+    Recommended refresh: 60 seconds
+    """
+    timeframe = request.args.get('timeframe', 'day')
+    min_magnitude = float(request.args.get('min_magnitude', 0))
+    max_magnitude = request.args.get('max_magnitude')
+    since_str = request.args.get('since')
+    limit = min(20000, max(1, int(request.args.get('limit', 20000))))
+    use_query_api = request.args.get('use_query_api', 'false').lower() == 'true'
+    
+    fetched_at = datetime.utcnow().isoformat() + "Z"
+    rows = []
+    
+    # Parse 'since' filter if provided
+    since_timestamp = None
+    if since_str:
+        try:
+            since_dt = datetime.fromisoformat(since_str.replace("Z", "+00:00")).replace(tzinfo=None)
+            since_timestamp = since_dt.timestamp() * 1000  # USGS uses milliseconds
+        except:
+            pass
+    
+    try:
+        if use_query_api or limit > 1000:
+            # Use USGS Query API for larger datasets
+            now = datetime.utcnow()
+            timeframe_deltas = {
+                "hour": timedelta(hours=1),
+                "day": timedelta(days=1),
+                "week": timedelta(weeks=1),
+                "month": timedelta(days=30)
+            }
+            start_time = now - timeframe_deltas.get(timeframe, timedelta(days=1))
+            
+            params = {
+                "format": "geojson",
+                "starttime": start_time.strftime("%Y-%m-%dT%H:%M:%S"),
+                "endtime": now.strftime("%Y-%m-%dT%H:%M:%S"),
+                "minmagnitude": min_magnitude,
+                "limit": limit,
+                "orderby": "time"  # Most recent first
+            }
+            
+            if max_magnitude:
+                params["maxmagnitude"] = float(max_magnitude)
+            
+            url = "https://earthquake.usgs.gov/fdsnws/event/1/query"
+            response = requests.get(url, params=params, timeout=60)
+            response.raise_for_status()
+            data = response.json()
+        else:
+            # Use summary feeds for quick queries
+            feeds = {"hour": "all_hour", "day": "all_day", "week": "all_week", "month": "all_month"}
+            feed = feeds.get(timeframe, "all_day")
+            url = f"https://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/{feed}.geojson"
+            response = requests.get(url, timeout=30)
+            response.raise_for_status()
+            data = response.json()
+        
+        for feature in data.get("features", []):
+            props = feature.get("properties", {})
+            coords = feature.get("geometry", {}).get("coordinates", [0, 0, 0])
+            
+            # Filter by magnitude (additional client-side filter for summary feeds)
+            mag = props.get("mag")
+            if mag is not None:
+                if mag < min_magnitude:
+                    continue
+                if max_magnitude and mag > float(max_magnitude):
+                    continue
+            
+            # Filter by 'since' time
+            quake_time = props.get("time", 0)
+            if since_timestamp and quake_time <= since_timestamp:
+                continue
+            
+            rows.append({
+                "id": feature.get("id"),
+                "time": datetime.utcfromtimestamp(quake_time / 1000).isoformat() + "Z",
+                "latitude": coords[1] if len(coords) > 1 else None,
+                "longitude": coords[0] if len(coords) > 0 else None,
+                "depth_km": coords[2] if len(coords) > 2 else None,
+                "magnitude": mag,
+                "place": props.get("place"),
+                "type": props.get("type", "earthquake"),
+                "status": props.get("status"),
+                "felt": props.get("felt"),  # Number of people who reported feeling it
+                "cdi": props.get("cdi"),  # Maximum reported intensity
+                "mmi": props.get("mmi"),  # Maximum estimated instrumental intensity
+                "tsunami": props.get("tsunami", 0),  # Tsunami warning (0 or 1)
+                "sig": props.get("sig"),  # Significance (0-1000)
+                "net": props.get("net"),  # Network that reported the event
+                "code": props.get("code"),  # Event code
+                "url": props.get("url"),  # USGS detail page URL
+                "fetched_at": fetched_at
+            })
+            
+            # Limit results if using summary feed
+            if not use_query_api and len(rows) >= limit:
+                break
+        
+        # Sort by time, most recent first
+        rows.sort(key=lambda x: x["time"], reverse=True)
+        
+        # Apply limit (in case summary feed returned more than requested)
+        if len(rows) > limit:
+            rows = rows[:limit]
+        
+        return make_csv_response(rows)
+    except Exception as e:
+        logger.warning(f"Failed to fetch earthquakes: {e}")
+        return Response(f"error,{str(e)}", mimetype='text/csv'), 500
+
+
+# ============================================================================
+# Current Weather (Open-Meteo) - Updates every 15 minutes
+# Recommended refresh: 300 seconds
+# ============================================================================
+
+WEATHER_CITIES = [
+    {"name": "Seattle", "lat": 47.6062, "lon": -122.3321},
+    {"name": "New York", "lat": 40.7128, "lon": -74.0060},
+    {"name": "Los Angeles", "lat": 34.0522, "lon": -118.2437},
+    {"name": "Chicago", "lat": 41.8781, "lon": -87.6298},
+    {"name": "Miami", "lat": 25.7617, "lon": -80.1918},
+    {"name": "Denver", "lat": 39.7392, "lon": -104.9903},
+    {"name": "Boston", "lat": 42.3601, "lon": -71.0589},
+    {"name": "Phoenix", "lat": 33.4484, "lon": -112.0740},
+]
+
+@demo_stream_bp.route('/weather', methods=['GET'])
+@limiter.limit(WEATHER_RATE_LIMIT)
+def get_weather():
+    """
+    Current weather for major US cities. Updates every 15 minutes.
+    Recommended refresh: 300 seconds
+    """
+    fetched_at = datetime.utcnow().isoformat() + "Z"
+    rows = []
+    
+    for city in WEATHER_CITIES:
+        try:
+            params = {
+                "latitude": city["lat"],
+                "longitude": city["lon"],
+                "current": "temperature_2m,relative_humidity_2m,wind_speed_10m,precipitation",
+                "timezone": "auto"
+            }
+            response = requests.get("https://api.open-meteo.com/v1/forecast", params=params, timeout=10)
+            response.raise_for_status()
+            data = response.json()
+            current = data.get("current", {})
+            
+            rows.append({
+                "city": city["name"],
+                "latitude": city["lat"],
+                "longitude": city["lon"],
+                "temperature_c": current.get("temperature_2m"),
+                "humidity_percent": current.get("relative_humidity_2m"),
+                "wind_speed_kmh": current.get("wind_speed_10m"),
+                "precipitation_mm": current.get("precipitation"),
+                "fetched_at": fetched_at
+            })
+        except Exception as e:
+            logger.warning(f"Failed to fetch weather for {city['name']}: {e}")
+    
+    return make_csv_response(rows)
+
+
+# ============================================================================
+# Weather History (Open-Meteo) - Past days of hourly data
+# Dataset grows as new hours pass
+# ============================================================================
+
+@demo_stream_bp.route('/weather/history', methods=['GET'])
+@limiter.limit(WEATHER_RATE_LIMIT)
+def get_weather_history():
+    """
+    Hourly weather history for a location. Dataset grows with each hour.
+    
+    Query params:
+        - city: City name (default: Seattle) - one of the WEATHER_CITIES
+        - days: Number of past days to include (default: 7, max: 14)
+    
+    Use case:
+        - Track temperature/weather trends over the past week
+        - Each hour, a new row appears in the dataset
+        - Great for visualizing weather patterns
+    
+    Recommended refresh: 3600 seconds (hourly)
+    """
+    city_name = request.args.get('city', 'Seattle')
+    days = min(14, max(1, int(request.args.get('days', 7))))
+    
+    # Find city coordinates
+    city = next((c for c in WEATHER_CITIES if c["name"].lower() == city_name.lower()), WEATHER_CITIES[0])
+    
+    fetched_at = datetime.utcnow().isoformat() + "Z"
+    
+    try:
+        # Open-Meteo historical/archive API
+        end_date = datetime.utcnow()
+        start_date = end_date - timedelta(days=days)
+        
+        params = {
+            "latitude": city["lat"],
+            "longitude": city["lon"],
+            "hourly": "temperature_2m,relative_humidity_2m,wind_speed_10m,precipitation,weather_code",
+            "timezone": "auto",
+            "start_date": start_date.strftime("%Y-%m-%d"),
+            "end_date": end_date.strftime("%Y-%m-%d")
+        }
+        
+        response = requests.get("https://api.open-meteo.com/v1/forecast", params=params, timeout=30)
+        response.raise_for_status()
+        data = response.json()
+        
+        hourly = data.get("hourly", {})
+        times = hourly.get("time", [])
+        temps = hourly.get("temperature_2m", [])
+        humidity = hourly.get("relative_humidity_2m", [])
+        wind = hourly.get("wind_speed_10m", [])
+        precip = hourly.get("precipitation", [])
+        weather_codes = hourly.get("weather_code", [])
+        
+        # Weather code descriptions
+        weather_desc = {
+            0: "Clear", 1: "Mainly Clear", 2: "Partly Cloudy", 3: "Overcast",
+            45: "Foggy", 48: "Depositing Rime Fog",
+            51: "Light Drizzle", 53: "Moderate Drizzle", 55: "Dense Drizzle",
+            61: "Slight Rain", 63: "Moderate Rain", 65: "Heavy Rain",
+            71: "Slight Snow", 73: "Moderate Snow", 75: "Heavy Snow",
+            80: "Slight Showers", 81: "Moderate Showers", 82: "Violent Showers",
+            95: "Thunderstorm", 96: "Thunderstorm with Hail", 99: "Thunderstorm with Heavy Hail"
+        }
+        
+        rows = []
+        for i, time_str in enumerate(times):
+            code = weather_codes[i] if i < len(weather_codes) else 0
+            rows.append({
+                "city": city["name"],
+                "timestamp": time_str + ":00Z" if ":" in time_str else time_str,
+                "temperature_c": temps[i] if i < len(temps) else None,
+                "humidity_percent": humidity[i] if i < len(humidity) else None,
+                "wind_speed_kmh": wind[i] if i < len(wind) else None,
+                "precipitation_mm": precip[i] if i < len(precip) else None,
+                "weather_code": code,
+                "weather": weather_desc.get(code, "Unknown"),
+                "fetched_at": fetched_at
+            })
+        
+        return make_csv_response(rows)
+    except Exception as e:
+        logger.warning(f"Failed to fetch weather history: {e}")
+        return Response(f"error,{str(e)}", mimetype='text/csv'), 500
+
+
+# ============================================================================
+# NWS Weather Forecast - Updates every few hours
+# Recommended refresh: 3600 seconds (1 hour)
+# ============================================================================
+
+NWS_LOCATIONS = {
+    "seattle": {"name": "Seattle, WA", "office": "SEW", "gridX": 124, "gridY": 67},
+    "new_york": {"name": "New York, NY", "office": "OKX", "gridX": 33, "gridY": 37},
+    "los_angeles": {"name": "Los Angeles, CA", "office": "LOX", "gridX": 154, "gridY": 44},
+    "chicago": {"name": "Chicago, IL", "office": "LOT", "gridX": 65, "gridY": 76},
+}
+
+@demo_stream_bp.route('/forecast/<location>', methods=['GET'])
+@limiter.limit(WEATHER_RATE_LIMIT)
+def get_forecast(location: str):
+    """
+    7-day forecast from NWS. Updates every few hours.
+    Locations: seattle, new_york, los_angeles, chicago
+    Recommended refresh: 3600 seconds
+    """
+    loc_key = location.lower().replace("-", "_")
+    if loc_key not in NWS_LOCATIONS:
+        return Response(f"error,Unknown location. Use: {','.join(NWS_LOCATIONS.keys())}", mimetype='text/csv'), 400
+    
+    loc = NWS_LOCATIONS[loc_key]
+    
+    try:
+        url = f"https://api.weather.gov/gridpoints/{loc['office']}/{loc['gridX']},{loc['gridY']}/forecast"
+        headers = {"User-Agent": "(DataFormulator, demo@example.com)"}
+        response = requests.get(url, headers=headers, timeout=30)
+        response.raise_for_status()
+        data = response.json()
+        
+        fetched_at = datetime.utcnow().isoformat() + "Z"
+        rows = []
+        
+        for period in data.get("properties", {}).get("periods", []):
+            rows.append({
+                "location": loc["name"],
+                "period": period.get("name"),
+                "temperature": period.get("temperature"),
+                "temperature_unit": period.get("temperatureUnit"),
+                "wind_speed": period.get("windSpeed"),
+                "wind_direction": period.get("windDirection"),
+                "forecast": period.get("shortForecast"),
+                "fetched_at": fetched_at
+            })
+        
+        return make_csv_response(rows)
+    except Exception as e:
+        return Response(f"error,{str(e)}", mimetype='text/csv'), 500
+
+
+# ============================================================================
+# yfinance - Stock/Financial Data via Yahoo Finance
+# Single unified API with historical daily data + recent 15min intraday data
+# Recommended refresh: 300 seconds (5 minutes) during market hours
+# ============================================================================
+
+DEFAULT_SYMBOLS = ["AAPL", "MSFT", "GOOGL", "AMZN", "META", "NVDA", "TSLA"]
+
+
+@demo_stream_bp.route('/yfinance', methods=['GET'])
+@limiter.limit(YFINANCE_RATE_LIMIT)
+def get_yfinance():
+    """
+    Stock prices via yfinance with historical daily data + recent intraday data (15min intervals).
+    
+    Returns a complete dataset combining:
+    - Historical daily data from start_date (default: 6 months ago)
+    - Recent intraday data at 15-minute intervals (last ~5-7 days)
+    - Today's live intraday data points
+    
+    Query params:
+        - symbols: comma-separated stock symbols (default: AAPL,MSFT,GOOGL,AMZN,META,NVDA,TSLA)
+        - start_date: YYYY-MM-DD format (default: 6 months ago)
+    
+    Example use case:
+        - /api/demo-stream/yfinance?symbols=AAPL,MSFT&start_date=2025-07-01
+        - Returns daily data from July 2025, plus recent 15min intraday data
+        - New data appears each trading day
+    
+    Recommended refresh: 300 seconds (5 minutes) during market hours
+    """
+    symbols_param = request.args.get('symbols', ','.join(DEFAULT_SYMBOLS))
+    symbols = [s.strip().upper() for s in symbols_param.split(',') if s.strip()][:10]
+    
+    now = datetime.utcnow()
+    today = now.date()
+    
+    # Parse start_date, default to 6 months ago
+    start_date_str = request.args.get('start_date')
+    if start_date_str:
+        try:
+            start_date = datetime.strptime(start_date_str, "%Y-%m-%d")
+        except:
+            start_date = now - timedelta(days=180)
+    else:
+        start_date = now - timedelta(days=180)
+    
+    # Calculate number of days
+    days = (now - start_date).days
+    
+    # yfinance typically provides intraday data for last 5-7 days
+    intraday_days_limit = 7
+    intraday_interval = '15m'
+    
+    fetched_at = now.isoformat() + "Z"
+    rows = []
+    
+    # Helper to check if value is valid (not NaN/None)
+    def is_valid(val):
+        try:
+            return val is not None and not (isinstance(val, float) and math.isnan(val))
+        except:
+            return False
+    
+    # Helper to format timestamp
+    def format_timestamp(date_obj):
+        """Convert pandas Timestamp or datetime to string"""
+        try:
+            if hasattr(date_obj, 'tz_convert'):
+                date_utc = date_obj.tz_convert('UTC')
+            elif hasattr(date_obj, 'tz_localize') and date_obj.tz is not None:
+                date_utc = date_obj.tz_convert('UTC')
+            else:
+                date_utc = date_obj
+            
+            if hasattr(date_utc, 'to_pydatetime'):
+                date_utc = date_utc.to_pydatetime()
+            elif hasattr(date_utc, 'timestamp'):
+                date_utc = datetime.fromtimestamp(date_utc.timestamp())
+            
+            if isinstance(date_utc, datetime):
+                return date_utc.strftime("%Y-%m-%d %H:%M:%S")
+            else:
+                return str(date_utc)
+        except:
+            return str(date_obj)
+    
+    for symbol in symbols:
+        try:
+            ticker = yf.Ticker(symbol)
+            
+            # Get historical daily data for older period (before intraday range)
+            daily_days = max(0, days - intraday_days_limit)
+            
+            if daily_days > 0:
+                daily_end = now - timedelta(days=intraday_days_limit)
+                hist_daily = ticker.history(start=start_date.strftime("%Y-%m-%d"), end=daily_end.strftime("%Y-%m-%d"))
+                
+                for date, row in hist_daily.iterrows():
+                    try:
+                        if hasattr(date, 'strftime'):
+                            date_str = date.strftime("%Y-%m-%d")
+                        else:
+                            date_str = str(date)
+                    except:
+                        date_str = str(date)
+                    
+                    rows.append({
+                        "symbol": symbol,
+                        "timestamp": date_str + " 00:00:00",
+                        "date": date_str,
+                        "open": round(row["Open"], 2) if is_valid(row["Open"]) else None,
+                        "high": round(row["High"], 2) if is_valid(row["High"]) else None,
+                        "low": round(row["Low"], 2) if is_valid(row["Low"]) else None,
+                        "close": round(row["Close"], 2) if is_valid(row["Close"]) else None,
+                        "volume": int(row["Volume"]) if is_valid(row["Volume"]) else None,
+                        "data_type": "daily",
+                        "fetched_at": fetched_at
+                    })
+            
+            # Get recent intraday data at 15min intervals (last 5-7 days excluding today)
+            try:
+                hist_intraday = ticker.history(interval=intraday_interval, period='7d')
+                
+                if not hist_intraday.empty:
+                    for date, row in hist_intraday.iterrows():
+                        # Skip today (we'll get it separately to ensure latest)
+                        try:
+                            if hasattr(date, 'date'):
+                                date_only = date.date()
+                            elif hasattr(date, 'to_pydatetime'):
+                                date_only = date.to_pydatetime().date()
+                            else:
+                                date_only = date
+                            
+                            if isinstance(date_only, str):
+                                date_only = datetime.strptime(date_only, "%Y-%m-%d").date()
+                            
+                            if date_only == today:
+                                continue  # Skip today, will get it below
+                        except:
+                            pass
+                        
+                        timestamp_str = format_timestamp(date)
+                        
+                        rows.append({
+                            "symbol": symbol,
+                            "timestamp": timestamp_str,
+                            "date": timestamp_str.split()[0] if ' ' in timestamp_str else str(date),
+                            "open": round(row["Open"], 2) if is_valid(row["Open"]) else None,
+                            "high": round(row["High"], 2) if is_valid(row["High"]) else None,
+                            "low": round(row["Low"], 2) if is_valid(row["Low"]) else None,
+                            "close": round(row["Close"], 2) if is_valid(row["Close"]) else None,
+                            "volume": int(row["Volume"]) if is_valid(row["Volume"]) else None,
+                            "data_type": "intraday",
+                            "fetched_at": fetched_at
+                        })
+            except Exception as e:
+                logger.warning(f"Failed to fetch intraday historical for {symbol}: {e}")
+            
+            # Get today's intraday data (always fetch to ensure latest)
+            hist_intraday_today = ticker.history(interval=intraday_interval, period='1d')
+            
+            if not hist_intraday_today.empty:
+                for date, row in hist_intraday_today.iterrows():
+                    timestamp_str = format_timestamp(date)
+                    
+                    rows.append({
+                        "symbol": symbol,
+                        "timestamp": timestamp_str,
+                        "date": today.strftime("%Y-%m-%d"),
+                        "open": round(row["Open"], 2) if is_valid(row["Open"]) else None,
+                        "high": round(row["High"], 2) if is_valid(row["High"]) else None,
+                        "low": round(row["Low"], 2) if is_valid(row["Low"]) else None,
+                        "close": round(row["Close"], 2) if is_valid(row["Close"]) else None,
+                        "volume": int(row["Volume"]) if is_valid(row["Volume"]) else None,
+                        "data_type": "intraday",
+                        "fetched_at": fetched_at
+                    })
+            else:
+                # If no intraday data, try to get today's price
+                try:
+                    info = ticker.info
+                    price = info.get('currentPrice') or info.get('regularMarketPrice') or info.get('previousClose')
+                    if price:
+                        rows.append({
+                            "symbol": symbol,
+                            "timestamp": today.strftime("%Y-%m-%d") + " 00:00:00",
+                            "date": today.strftime("%Y-%m-%d"),
+                            "open": price,
+                            "high": price,
+                            "low": price,
+                            "close": price,
+                            "volume": info.get('volume', 0),
+                            "data_type": "daily",
+                            "fetched_at": fetched_at
+                        })
+                except:
+                    pass
+                    
+        except Exception as e:
+            logger.warning(f"Failed to fetch data for {symbol}: {e}")
+    
+    # Sort by symbol, then timestamp
+    rows.sort(key=lambda x: (x["symbol"], x["timestamp"]))
+    
+    return make_csv_response(rows)
+
+
+# ============================================================================
+# Mock Live Sales Feed - Updates every second (for demo)
+# Rich schema with programmatically correlated data
+# ============================================================================
+
+
+@demo_stream_bp.route('/live-sales', methods=['GET'])
+@limiter.limit(MOCK_RATE_LIMIT)
+def get_live_sales():
+    """
+    Simulated live sales feed. Updates every second.
+    Each refresh shows recent "transactions" with product details.
+    Recommended refresh: 1 second
+    """
+    now = datetime.utcnow()
+    hour_of_day = now.hour + now.minute / 60
+    
+    # Products with realistic pricing and popularity
+    products = [
+        {"name": "Wireless Headphones", "category": "Electronics", "base_price": 79.99, "popularity": 0.15},
+        {"name": "Smart Watch", "category": "Electronics", "base_price": 199.99, "popularity": 0.10},
+        {"name": "Running Shoes", "category": "Sports", "base_price": 129.99, "popularity": 0.12},
+        {"name": "Yoga Mat", "category": "Sports", "base_price": 34.99, "popularity": 0.08},
+        {"name": "Coffee Maker", "category": "Home", "base_price": 89.99, "popularity": 0.09},
+        {"name": "Desk Lamp", "category": "Home", "base_price": 45.99, "popularity": 0.07},
+        {"name": "Backpack", "category": "Accessories", "base_price": 59.99, "popularity": 0.11},
+        {"name": "Water Bottle", "category": "Accessories", "base_price": 24.99, "popularity": 0.13},
+        {"name": "Bluetooth Speaker", "category": "Electronics", "base_price": 49.99, "popularity": 0.08},
+        {"name": "Fitness Tracker", "category": "Electronics", "base_price": 69.99, "popularity": 0.07},
+    ]
+    
+    regions = ["North America", "Europe", "Asia Pacific", "Latin America"]
+    region_weights = [0.45, 0.30, 0.18, 0.07]
+    
+    channels = ["Web", "Mobile App", "In-Store", "Partner"]
+    channel_weights = [0.40, 0.35, 0.15, 0.10]
+    
+    # Generate 5-10 recent transactions
+    num_transactions = random.randint(5, 10)
+    rows = []
+    
+    for i in range(num_transactions):
+        product = random.choices(products, weights=[p["popularity"] for p in products])[0]
+        region = random.choices(regions, weights=region_weights)[0]
+        channel = random.choices(channels, weights=channel_weights)[0]
+        
+        quantity = random.choices([1, 2, 3, 4, 5], weights=[0.5, 0.25, 0.15, 0.07, 0.03])[0]
+        discount = random.choices([0, 5, 10, 15, 20], weights=[0.6, 0.15, 0.12, 0.08, 0.05])[0]
+        
+        unit_price = round(product["base_price"] * (1 - discount / 100), 2)
+        total = round(unit_price * quantity, 2)
+        
+        # Transaction time within the last minute
+        tx_time = now - timedelta(seconds=random.randint(0, 60))
+        
+        rows.append({
+            "transaction_id": f"TX{int(tx_time.timestamp() * 1000) % 1000000:06d}",
+            "timestamp": tx_time.isoformat() + "Z",
+            "product": product["name"],
+            "category": product["category"],
+            "quantity": quantity,
+            "unit_price": unit_price,
+            "discount_pct": discount,
+            "total": total,
+            "region": region,
+            "channel": channel,
+        })
+    
+    # Sort by timestamp descending
+    rows.sort(key=lambda x: x["timestamp"], reverse=True)
+    
+    return make_csv_response(rows)
+
+
+# ============================================================================
+# API Info Endpoint
+# ============================================================================
+
+@demo_stream_bp.route('/info', methods=['GET'])
+def get_info():
+    """List all available demo data endpoints with their parameters"""
+    return jsonify({
+        "name": "Demo Data REST APIs",
+        "description": "Each endpoint returns CSV text with complete datasets that change over time. "
+                       "Import URL in frontend, set auto-refresh to watch data evolve.",
+        "design_philosophy": [
+            "Each endpoint returns a COMPLETE dataset (not just one row)",
+            "Datasets are meaningful for analysis and visualization", 
+            "When refreshed, new data may appear (accumulating) or values may update",
+            "Use date parameters to track data from a specific point in time"
+        ],
+        "demo_examples": [
+            {
+                "id": "yfinance",
+                "url": "/api/demo-stream/yfinance?symbols=AAPL,MSFT,GOOGL",
+                "name": "Stock Data (6 months + Intraday)",
+                "refresh_seconds": 300,
+                "description": "Historical daily data (6 months default) + recent 15min intraday data + today's live prices (via yfinance)",
+                "params": {
+                    "symbols": "Comma-separated stock symbols (max 10)",
+                    "start_date": "YYYY-MM-DD start date (default: 6 months ago)"
+                }
+            },
+            {
+                "id": "yfinance-ytd",
+                "url": f"/api/demo-stream/yfinance?symbols=AAPL,NVDA,TSLA&start_date={datetime.utcnow().strftime('%Y')}-01-01",
+                "name": "Stock Data (Year to Date)",
+                "refresh_seconds": 300,
+                "description": "Year-to-date stock data with daily history + recent intraday (via yfinance)"
+            },
+            {
+                "id": "iss-trajectory",
+                "url": "/api/demo-stream/iss?minutes=30",
+                "name": "ISS Trajectory",
+                "refresh_seconds": 5,
+                "description": "ISS orbital path - positions accumulate over time",
+                "params": {
+                    "minutes": "Minutes of history (1-60, default 30)",
+                    "limit": "Max points to return (10-500)"
+                }
+            },
+            {
+                "id": "earthquakes-week",
+                "url": "/api/demo-stream/earthquakes?timeframe=week&min_magnitude=4",
+                "name": "Earthquakes (Week, M4+)",
+                "refresh_seconds": 60,
+                "description": "Significant earthquakes - new quakes appear over time",
+                "params": {
+                    "timeframe": "hour, day, week, month",
+                    "min_magnitude": "Minimum magnitude filter",
+                    "max_magnitude": "Maximum magnitude filter (optional)",
+                    "since": "ISO datetime - only quakes after this time",
+                    "limit": "Max results (1-20000, default 20000)",
+                    "use_query_api": "true to use query API for large datasets (default false)"
+                }
+            },
+            {
+                "id": "earthquakes-large",
+                "url": "/api/demo-stream/earthquakes?timeframe=month&min_magnitude=2&use_query_api=true&limit=10000",
+                "name": "Earthquakes (Month, Large Dataset)",
+                "refresh_seconds": 300,
+                "description": "Large dataset with up to 10,000 earthquakes from the past month"
+            },
+            {
+                "id": "weather-history",
+                "url": "/api/demo-stream/weather/history?city=Seattle&days=7",
+                "name": "Weather History (7 days)",
+                "refresh_seconds": 3600,
+                "description": "Hourly weather data - new hours appear over time",
+                "params": {
+                    "city": "City name (Seattle, New York, etc.)",
+                    "days": "Past days to include (1-14)"
+                }
+            },
+            {
+                "id": "live-sales",
+                "url": "/api/demo-stream/live-sales",
+                "name": "Live Sales Feed",
+                "refresh_seconds": 1,
+                "description": "Simulated e-commerce transactions"
+            },
+            {
+                "id": "weather-current",
+                "url": "/api/demo-stream/weather",
+                "name": "Weather (Current)",
+                "refresh_seconds": 300,
+                "description": "Current conditions for 8 US cities"
+            }
+        ],
+        "usage": "Click any example to load it, or enter a custom URL. Set auto-refresh to watch data change over time."
+    })
diff --git a/py-src/data_formulator/example_datasets_config.py b/py-src/data_formulator/example_datasets_config.py
index d63fe8d..7991603 100644
--- a/py-src/data_formulator/example_datasets_config.py
+++ b/py-src/data_formulator/example_datasets_config.py
@@ -413,6 +413,94 @@
 1974-063,2442268.64,1974-08-09,1974,Thor Burner 2A,,DMSP Block 5C F-1,US,US,O,state'''
             }
         ]
+    },
+    # ==========================================================================
+    # LIVE DATA EXAMPLES - Auto-refresh streaming datasets
+    # ==========================================================================
+    {
+        'source': 'demo',
+        'name': 'Live Sales Feed (Live)',
+        'description': 'Simulated e-commerce transactions with product details, regions, and channels. Updates every 1 second.',
+        'live': True,
+        'refreshIntervalSeconds': 1,
+        'tables': [
+            {
+                "format": 'csv',
+                "url": '/api/demo-stream/live-sales',
+                "sample": '''transaction_id,timestamp,product,category,quantity,unit_price,discount_pct,total,region,channel
+TX123456,2024-01-15T10:30:00Z,Wireless Headphones,Electronics,2,71.99,10,143.98,North America,Web
+TX123457,2024-01-15T10:29:45Z,Running Shoes,Sports,1,129.99,0,129.99,Europe,Mobile App
+TX123458,2024-01-15T10:29:30Z,Coffee Maker,Home,1,80.99,10,80.99,Asia Pacific,Web'''
+            }
+        ]
+    },
+    {
+        'source': 'open-notify.org',
+        'name': 'ISS Location (Live)',
+        'description': 'Real-time International Space Station position trajectory. Updates every 5 seconds.',
+        'live': True,
+        'refreshIntervalSeconds': 5,
+        'tables': [
+            {
+                "format": 'csv',
+                "url": '/api/demo-stream/iss',
+                "sample": '''timestamp,latitude,longitude,fetched_at
+2024-01-15T10:30:00Z,45.234,-122.456,2024-01-15T10:30:00Z
+2024-01-15T10:29:55Z,45.123,-122.345,2024-01-15T10:29:55Z
+2024-01-15T10:29:50Z,45.012,-122.234,2024-01-15T10:29:50Z'''
+            }
+        ]
+    },
+    {
+        'source': 'USGS',
+        'name': 'Earthquakes (Live)',
+        'description': 'Real-time earthquake data from USGS. New quakes appear over time. Updates every 60 seconds.',
+        'live': True,
+        'refreshIntervalSeconds': 60,
+        'tables': [
+            {
+                "format": 'csv',
+                "url": '/api/demo-stream/earthquakes?timeframe=hour',
+                "sample": '''id,time,latitude,longitude,depth_km,magnitude,place,type,status,felt,cdi,mmi,tsunami,sig,net,code,url,fetched_at
+us7000abc1,2024-01-15T10:25:00Z,36.234,-117.456,5.2,2.5,"10km N of Ridgecrest, CA",earthquake,reviewed,,,0,0,125,us,abc1,https://earthquake.usgs.gov/earthquakes/eventpage/us7000abc1,2024-01-15T10:30:00Z
+us7000abc2,2024-01-15T10:15:00Z,61.123,-150.345,45.8,3.1,"50km S of Anchorage, AK",earthquake,automatic,5,,0,0,180,us,abc2,https://earthquake.usgs.gov/earthquakes/eventpage/us7000abc2,2024-01-15T10:30:00Z'''
+            }
+        ]
+    },
+    {
+        'source': 'Open-Meteo',
+        'name': 'Weather (Live)',
+        'description': 'Current weather conditions for major US cities. Updates every 5 minutes.',
+        'live': True,
+        'refreshIntervalSeconds': 300,
+        'tables': [
+            {
+                "format": 'csv',
+                "url": '/api/demo-stream/weather',
+                "sample": '''city,latitude,longitude,temperature_c,humidity_percent,wind_speed_kmh,precipitation_mm,fetched_at
+Seattle,47.6062,-122.3321,8.5,72,12.5,0.2,2024-01-15T10:30:00Z
+New York,40.7128,-74.006,2.3,65,18.2,0.0,2024-01-15T10:30:00Z
+Los Angeles,34.0522,-118.2437,15.8,55,8.3,0.0,2024-01-15T10:30:00Z'''
+            }
+        ]
+    },
+    {
+        'source': 'yfinance',
+        'name': 'Stock Prices (Live)',
+        'description': 'Stock prices with 6 months of daily history + recent 15-minute intraday data. Updates every 5 minutes during market hours.',
+        'live': True,
+        'refreshIntervalSeconds': 300,
+        'tables': [
+            {
+                "format": 'csv',
+                "url": '/api/demo-stream/yfinance?symbols=AAPL,MSFT,GOOGL,NVDA',
+                "sample": '''symbol,timestamp,date,open,high,low,close,volume,data_type,fetched_at
+AAPL,2024-01-15 14:30:00,2024-01-15,185.50,186.20,185.30,185.95,1234567,intraday,2024-01-15T19:35:00Z
+MSFT,2024-01-15 14:30:00,2024-01-15,388.75,389.50,388.25,389.10,987654,intraday,2024-01-15T19:35:00Z
+GOOGL,2024-01-15 14:30:00,2024-01-15,141.20,141.80,141.00,141.55,654321,intraday,2024-01-15T19:35:00Z
+NVDA,2024-01-15 14:30:00,2024-01-15,545.20,548.80,544.50,547.35,2345678,intraday,2024-01-15T19:35:00Z'''
+            }
+        ]
     }
 ]
 
diff --git a/py-src/data_formulator/tables_routes.py b/py-src/data_formulator/tables_routes.py
index b065e04..66a32ce 100644
--- a/py-src/data_formulator/tables_routes.py
+++ b/py-src/data_formulator/tables_routes.py
@@ -50,8 +50,12 @@ def list_tables():
             for table_metadata in table_metadata_list:
                 [database_name, schema_name, table_name, is_current_schema, object_type] = table_metadata
                 table_name = table_name if is_current_schema else '.'.join([database_name, schema_name, table_name])
+                
+                # Skip system databases and internal metadata tables
                 if database_name in ['system', 'temp']:
                     continue
+                if table_name.startswith('_df_'):  # Internal Data Formulator metadata tables
+                    continue
                 
                 try:
                     # Get column information
@@ -69,12 +73,20 @@ def list_tables():
                         # If the query fails, assume it's a regular table
                         view_source = None
                     
+                    # Get source metadata if available (for refreshable tables)
+                    source_metadata = None
+                    try:
+                        source_metadata = get_table_metadata(db, table_name)
+                    except Exception:
+                        pass  # Metadata table may not exist yet
+                    
                     result.append({
                         "name": table_name,
                         "columns": [{"name": col[0], "type": col[1]} for col in columns],
                         "row_count": row_count,
                         "sample_rows": json.loads(sample_rows.to_json(orient='records', date_format='iso')),
-                        "view_source": view_source
+                        "view_source": view_source,
+                        "source_metadata": source_metadata
                     })
                     
                 except Exception as e:
@@ -749,6 +761,158 @@ def data_loader_list_tables():
         }), status_code
 
 
+def ensure_table_metadata_table(db_conn):
+    """
+    Ensure the _df_table_source_metadata table exists for storing table source information.
+    This stores connection info so backend can refresh tables - frontend manages timing/toggle.
+    """
+    db_conn.execute("""
+        CREATE TABLE IF NOT EXISTS _df_table_source_metadata (
+            table_name VARCHAR PRIMARY KEY,
+            data_loader_type VARCHAR,
+            data_loader_params JSON,
+            source_table_name VARCHAR,
+            source_query VARCHAR,
+            last_refreshed TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+            content_hash VARCHAR
+        )
+    """)
+    
+    # Add content_hash column if it doesn't exist (for existing databases)
+    try:
+        db_conn.execute("""
+            ALTER TABLE _df_table_source_metadata ADD COLUMN content_hash VARCHAR
+        """)
+    except Exception:
+        # Column already exists
+        pass
+
+
+def compute_table_content_hash(db_conn, table_name: str) -> str:
+    """
+    Compute a content hash for a table using DuckDB's built-in hash function.
+    Uses a sampling strategy for efficiency with large tables:
+    - Row count
+    - Column names
+    - First 50 rows, last 50 rows, and 50 sampled rows from middle
+    """
+    import hashlib
+    
+    # Get row count
+    row_count = db_conn.execute(f"SELECT COUNT(*) FROM {table_name}").fetchone()[0]
+    
+    # Get column names
+    columns = db_conn.execute(f"DESCRIBE {table_name}").fetchall()
+    column_names = [col[0] for col in columns]
+    
+    # Build hash components
+    hash_parts = [
+        f"count:{row_count}",
+        f"cols:{','.join(column_names)}"
+    ]
+    
+    if row_count > 0:
+        # Sample rows for hashing
+        # First 50 rows
+        first_rows = db_conn.execute(f"""
+            SELECT * FROM {table_name} LIMIT 50
+        """).fetchall()
+        
+        # Last 50 rows (using row number)
+        last_rows = db_conn.execute(f"""
+            SELECT * FROM (
+                SELECT *, ROW_NUMBER() OVER () as _rn FROM {table_name}
+            ) WHERE _rn > {max(0, row_count - 50)}
+        """).fetchall()
+        
+        # Middle sample (every Nth row to get ~50 rows)
+        if row_count > 100:
+            step = max(1, (row_count - 100) // 50)
+            middle_rows = db_conn.execute(f"""
+                SELECT * FROM (
+                    SELECT *, ROW_NUMBER() OVER () as _rn FROM {table_name}
+                ) WHERE _rn > 50 AND _rn <= {row_count - 50} AND (_rn - 50) % {step} = 0
+                LIMIT 50
+            """).fetchall()
+        else:
+            middle_rows = []
+        
+        # Convert rows to strings for hashing
+        all_sample_rows = first_rows + middle_rows + last_rows
+        row_strs = [str(row) for row in all_sample_rows]
+        hash_parts.append(f"rows:{';'.join(row_strs)}")
+    
+    # Compute hash
+    content_str = '|'.join(hash_parts)
+    return hashlib.md5(content_str.encode()).hexdigest()
+
+
+def save_table_metadata(db_conn, table_name: str, data_loader_type: str, data_loader_params: dict, 
+                        source_table_name: str = None, source_query: str = None, content_hash: str = None):
+    """Save or update table source metadata"""
+    ensure_table_metadata_table(db_conn)
+    
+    # Remove sensitive fields from params before storing
+    safe_params = {k: v for k, v in data_loader_params.items() if k not in ['password', 'api_key', 'secret']}
+    
+    # Compute content hash if not provided
+    if content_hash is None:
+        try:
+            content_hash = compute_table_content_hash(db_conn, table_name)
+        except Exception as e:
+            logger.warning(f"Failed to compute content hash for {table_name}: {e}")
+            content_hash = None
+    
+    db_conn.execute("""
+        INSERT OR REPLACE INTO _df_table_source_metadata 
+        (table_name, data_loader_type, data_loader_params, source_table_name, source_query, last_refreshed, content_hash)
+        VALUES (?, ?, ?, ?, ?, CURRENT_TIMESTAMP, ?)
+    """, [table_name, data_loader_type, json.dumps(safe_params), source_table_name, source_query, content_hash])
+
+
+def get_table_metadata(db_conn, table_name: str) -> dict:
+    """Get metadata for a specific table (connection info for refresh)"""
+    ensure_table_metadata_table(db_conn)
+    
+    result = db_conn.execute("""
+        SELECT table_name, data_loader_type, data_loader_params, source_table_name, source_query, last_refreshed, content_hash
+        FROM _df_table_source_metadata 
+        WHERE table_name = ?
+    """, [table_name]).fetchone()
+    
+    if result:
+        return {
+            "table_name": result[0],
+            "data_loader_type": result[1],
+            "data_loader_params": json.loads(result[2]) if result[2] else {},
+            "source_table_name": result[3],
+            "source_query": result[4],
+            "last_refreshed": str(result[5]) if result[5] else None,
+            "content_hash": result[6]
+        }
+    return None
+
+
+def get_all_table_metadata(db_conn) -> list:
+    """Get metadata for all tables"""
+    ensure_table_metadata_table(db_conn)
+    
+    results = db_conn.execute("""
+        SELECT table_name, data_loader_type, data_loader_params, source_table_name, source_query, last_refreshed, content_hash
+        FROM _df_table_source_metadata
+    """).fetchall()
+    
+    return [{
+        "table_name": r[0],
+        "data_loader_type": r[1],
+        "data_loader_params": json.loads(r[2]) if r[2] else {},
+        "source_table_name": r[3],
+        "source_query": r[4],
+        "last_refreshed": str(r[5]) if r[5] else None,
+        "content_hash": r[6]
+    } for r in results]
+
+
 @tables_bp.route('/data-loader/ingest-data', methods=['POST'])
 def data_loader_ingest_data():
     """Ingest data from a data loader"""
@@ -765,10 +929,23 @@ def data_loader_ingest_data():
         with db_manager.connection(session['session_id']) as duck_db_conn:
             data_loader = DATA_LOADERS[data_loader_type](data_loader_params, duck_db_conn)
             data_loader.ingest_data(table_name)
+            
+            # Get the actual table name that was created (may be sanitized)
+            sanitized_name = table_name.split('.')[-1]  # Base name
+            
+            # Store metadata for refresh capability
+            save_table_metadata(
+                duck_db_conn, 
+                sanitized_name, 
+                data_loader_type, 
+                data_loader_params, 
+                source_table_name=table_name
+            )
 
             return jsonify({
                 "status": "success",
-                "message": "Successfully ingested data from data loader"
+                "message": "Successfully ingested data from data loader",
+                "table_name": sanitized_name
             })
 
     except Exception as e:
@@ -829,10 +1006,20 @@ def data_loader_ingest_data_from_query():
         with db_manager.connection(session['session_id']) as duck_db_conn:
             data_loader = DATA_LOADERS[data_loader_type](data_loader_params, duck_db_conn)
             data_loader.ingest_data_from_query(query, name_as)
+            
+            # Store metadata for refresh capability
+            save_table_metadata(
+                duck_db_conn, 
+                name_as, 
+                data_loader_type, 
+                data_loader_params, 
+                source_query=query
+            )
 
             return jsonify({
                 "status": "success",
-                "message": "Successfully ingested data from data loader"
+                "message": "Successfully ingested data from data loader",
+                "table_name": name_as
             })
 
     except Exception as e:
@@ -844,6 +1031,146 @@ def data_loader_ingest_data_from_query():
         }), status_code
 
 
+@tables_bp.route('/data-loader/refresh-table', methods=['POST'])
+def data_loader_refresh_table():
+    """
+    Refresh a table by re-importing data from its original source.
+    Requires the table to have been imported via a data loader with stored metadata.
+    Returns content_hash and data_changed flag so frontend can skip resampling if data unchanged.
+    """
+    try:
+        data = request.get_json()
+        table_name = data.get('table_name')
+        # Allow passing updated connection params (e.g., for password that wasn't stored)
+        updated_params = data.get('data_loader_params', {})
+
+        if not table_name:
+            return jsonify({"status": "error", "message": "table_name is required"}), 400
+
+        with db_manager.connection(session['session_id']) as duck_db_conn:
+            # Get stored metadata
+            metadata = get_table_metadata(duck_db_conn, table_name)
+            
+            if not metadata:
+                return jsonify({
+                    "status": "error", 
+                    "message": f"No source metadata found for table '{table_name}'. Cannot refresh."
+                }), 400
+            
+            # Get old content hash before refresh
+            old_content_hash = metadata.get('content_hash')
+            
+            data_loader_type = metadata['data_loader_type']
+            data_loader_params = {**metadata['data_loader_params'], **updated_params}
+            
+            if data_loader_type not in DATA_LOADERS:
+                return jsonify({
+                    "status": "error", 
+                    "message": f"Unknown data loader type: {data_loader_type}"
+                }), 400
+            
+            # Create data loader and refresh
+            data_loader = DATA_LOADERS[data_loader_type](data_loader_params, duck_db_conn)
+            
+            if metadata['source_query']:
+                # Refresh from query
+                data_loader.ingest_data_from_query(metadata['source_query'], table_name)
+            elif metadata['source_table_name']:
+                # Refresh from table
+                data_loader.ingest_data(metadata['source_table_name'], name_as=table_name)
+            else:
+                return jsonify({
+                    "status": "error", 
+                    "message": "No source table or query found in metadata"
+                }), 400
+            
+            # Compute new content hash after refresh
+            new_content_hash = compute_table_content_hash(duck_db_conn, table_name)
+            data_changed = old_content_hash != new_content_hash
+            
+            # Update last_refreshed timestamp and content_hash
+            duck_db_conn.execute("""
+                UPDATE _df_table_source_metadata 
+                SET last_refreshed = CURRENT_TIMESTAMP, content_hash = ?
+                WHERE table_name = ?
+            """, [new_content_hash, table_name])
+            
+            # Get updated row count
+            row_count = duck_db_conn.execute(f"SELECT COUNT(*) FROM {table_name}").fetchone()[0]
+
+            return jsonify({
+                "status": "success",
+                "message": f"Successfully refreshed table '{table_name}'",
+                "row_count": row_count,
+                "content_hash": new_content_hash,
+                "data_changed": data_changed
+            })
+
+    except Exception as e:
+        logger.error(f"Error refreshing table: {str(e)}")
+        logger.error(traceback.format_exc())
+        safe_msg, status_code = sanitize_db_error_message(e)
+        return jsonify({
+            "status": "error", 
+            "message": safe_msg
+        }), status_code
+
+
+@tables_bp.route('/data-loader/get-table-metadata', methods=['POST'])
+def data_loader_get_table_metadata():
+    """Get source metadata for a specific table"""
+    try:
+        data = request.get_json()
+        table_name = data.get('table_name')
+
+        if not table_name:
+            return jsonify({"status": "error", "message": "table_name is required"}), 400
+
+        with db_manager.connection(session['session_id']) as duck_db_conn:
+            metadata = get_table_metadata(duck_db_conn, table_name)
+            
+            if metadata:
+                return jsonify({
+                    "status": "success",
+                    "metadata": metadata
+                })
+            else:
+                return jsonify({
+                    "status": "success",
+                    "metadata": None,
+                    "message": f"No metadata found for table '{table_name}'"
+                })
+
+    except Exception as e:
+        logger.error(f"Error getting table metadata: {str(e)}")
+        safe_msg, status_code = sanitize_db_error_message(e)
+        return jsonify({
+            "status": "error", 
+            "message": safe_msg
+        }), status_code
+
+
+@tables_bp.route('/data-loader/list-table-metadata', methods=['GET'])
+def data_loader_list_table_metadata():
+    """Get source metadata for all tables"""
+    try:
+        with db_manager.connection(session['session_id']) as duck_db_conn:
+            metadata_list = get_all_table_metadata(duck_db_conn)
+            
+            return jsonify({
+                "status": "success",
+                "metadata": metadata_list
+            })
+
+    except Exception as e:
+        logger.error(f"Error listing table metadata: {str(e)}")
+        safe_msg, status_code = sanitize_db_error_message(e)
+        return jsonify({
+            "status": "error", 
+            "message": safe_msg
+        }), status_code
+
+
 @tables_bp.route('/refresh-derived-data', methods=['POST'])
 def refresh_derived_data():
     """
diff --git a/requirements.txt b/requirements.txt
index 45ad17e..0fe4db1 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,6 +4,7 @@ pandas
 numpy
 flask
 flask-cors
+flask-limiter
 openai
 python-dotenv
 vega_datasets
@@ -13,6 +14,7 @@ vl-convert-python
 backoff
 beautifulsoup4
 scikit-learn
+yfinance # for demo stream routes
 
 # External data loaders (Azure, BigQuery, AWS S3, MySQL, MSSQL)
 azure-identity
diff --git a/src/app/dfSlice.tsx b/src/app/dfSlice.tsx
index 7664b0f..e1a17e3 100644
--- a/src/app/dfSlice.tsx
+++ b/src/app/dfSlice.tsx
@@ -2,13 +2,13 @@
 // Licensed under the MIT License.
 
 import { createAsyncThunk, createSlice, PayloadAction, createSelector } from '@reduxjs/toolkit'
-import { Channel, Chart, ChartTemplate, DataCleanBlock, EncodingItem, EncodingMap, FieldItem, Trigger } from '../components/ComponentType'
+import { Channel, Chart, ChartTemplate, DataCleanBlock, DataSourceConfig, EncodingItem, EncodingMap, FieldItem, Trigger } from '../components/ComponentType'
 import { enableMapSet } from 'immer';
 import { DictTable } from "../components/ComponentType";
 import { Message } from '../views/MessageSnackbar';
 import { getChartTemplate, getChartChannels } from "../components/ChartTemplates"
 import { getDataTable } from '../views/VisualizationView';
-import { adaptChart, getTriggers, getUrls } from './utils';
+import { adaptChart, getTriggers, getUrls, computeContentHash } from './utils';
 import { Type } from '../data/types';
 import { createTableFromFromObjectArray, inferTypeFromValueArray } from '../data/utils';
 
@@ -442,6 +442,10 @@ export const dataFormulatorSlice = createSlice({
         },
         loadTable: (state, action: PayloadAction<DictTable>) => {
             let table = action.payload;
+            // Compute content hash if not already set
+            if (!table.contentHash) {
+                table = { ...table, contentHash: computeContentHash(table.rows, table.names) };
+            }
             state.tables = [...state.tables, table];
             state.charts = [...state.charts];
             state.conceptShelfItems = [...state.conceptShelfItems, ...getDataFieldItems(table)];
@@ -475,11 +479,12 @@ export const dataFormulatorSlice = createSlice({
             let attachedMetadata = action.payload.attachedMetadata;
             state.tables = state.tables.map(t => t.id == tableId ? {...t, attachedMetadata} : t);
         },
-        updateTableRows: (state, action: PayloadAction<{tableId: string, rows: any[]}>) => {
+        updateTableRows: (state, action: PayloadAction<{tableId: string, rows: any[], contentHash?: string}>) => {
             // Update the rows of a table while preserving all other table properties
             // This is used for refreshing data in original (non-derived) tables
             let tableId = action.payload.tableId;
             let newRows = action.payload.rows;
+            let providedContentHash = action.payload.contentHash;
             
             state.tables = state.tables.map(t => {
                 if (t.id == tableId) {
@@ -493,7 +498,37 @@ export const dataFormulatorSlice = createSlice({
                             };
                         }
                     }
-                    return { ...t, rows: newRows, metadata: newMetadata };
+                    // Update lastRefreshed timestamp if source exists
+                    const updatedSource = t.source ? { ...t.source, lastRefreshed: Date.now() } : undefined;
+                    // Use provided content hash (from backend for virtual/DB tables) or compute locally
+                    // For virtual tables, backend hash reflects full table; for stream tables, compute from actual rows
+                    const newContentHash = providedContentHash || computeContentHash(newRows, t.names);
+                    return { ...t, rows: newRows, metadata: newMetadata, source: updatedSource, contentHash: newContentHash };
+                }
+                return t;
+            });
+        },
+        updateTableSource: (state, action: PayloadAction<{tableId: string, source: DataSourceConfig}>) => {
+            // Update the source configuration of a table
+            let tableId = action.payload.tableId;
+            let source = action.payload.source;
+            state.tables = state.tables.map(t => t.id == tableId ? {...t, source} : t);
+        },
+        updateTableSourceRefreshSettings: (state, action: PayloadAction<{tableId: string, autoRefresh: boolean, refreshIntervalSeconds?: number}>) => {
+            // Update just the refresh settings of a table's source
+            let tableId = action.payload.tableId;
+            let autoRefresh = action.payload.autoRefresh;
+            let refreshIntervalSeconds = action.payload.refreshIntervalSeconds;
+            state.tables = state.tables.map(t => {
+                if (t.id == tableId && t.source) {
+                    return {
+                        ...t,
+                        source: {
+                            ...t.source,
+                            autoRefresh,
+                            ...(refreshIntervalSeconds !== undefined ? { refreshIntervalSeconds } : {})
+                        }
+                    };
                 }
                 return t;
             });
diff --git a/src/app/useDataRefresh.tsx b/src/app/useDataRefresh.tsx
new file mode 100644
index 0000000..d5b8f43
--- /dev/null
+++ b/src/app/useDataRefresh.tsx
@@ -0,0 +1,649 @@
+// Copyright (c) Microsoft Corporation.
+// Licensed under the MIT License.
+
+import { useEffect, useRef, useCallback } from 'react';
+import { useDispatch, useSelector } from 'react-redux';
+import { DataFormulatorState, dfActions } from './dfSlice';
+import { AppDispatch } from './store';
+import { DictTable, DataSourceConfig } from '../components/ComponentType';
+import { createTableFromFromObjectArray, createTableFromText } from '../data/utils';
+import { fetchWithSession, getUrls, computeContentHash } from './utils';
+
+interface RefreshResult {
+    tableId: string;
+    success: boolean;
+    message: string;
+    newRows?: any[];
+    contentHash?: string; // Hash from backend for database sources
+}
+
+/**
+ * Custom hook that manages automatic data refresh for tables with streaming or database sources.
+ * It sets up intervals for each table that has auto-refresh enabled.
+ */
+export function useDataRefresh() {
+    const dispatch = useDispatch<AppDispatch>();
+    const tables = useSelector((state: DataFormulatorState) => state.tables);
+    const timeoutRefs = useRef<Map<string, NodeJS.Timeout>>(new Map());
+    const refreshInProgressRef = useRef<Map<string, boolean>>(new Map());
+    const isActiveRef = useRef<Map<string, boolean>>(new Map());
+    const lastMessageTimeRef = useRef<number>(0);
+    const MESSAGE_THROTTLE_MS = 10000; // 10 seconds
+
+    /**
+     * Throttled message dispatcher - only sends messages if at least 10 seconds have passed since last message
+     */
+    const dispatchThrottledMessage = useCallback((message: Parameters<typeof dfActions.addMessages>[0]) => {
+        const now = Date.now();
+        const timeSinceLastMessage = now - lastMessageTimeRef.current;
+        
+        if (timeSinceLastMessage >= MESSAGE_THROTTLE_MS) {
+            lastMessageTimeRef.current = now;
+            dispatch(dfActions.addMessages(message));
+        } else {
+            console.log(`[DataRefresh] Throttling message (${Math.round((MESSAGE_THROTTLE_MS - timeSinceLastMessage) / 1000)}s remaining): ${message.value}`);
+        }
+    }, [dispatch]);
+
+    /**
+     * Fetches fresh data from a streaming URL
+     */
+    const fetchStreamData = useCallback(async (table: DictTable): Promise<RefreshResult> => {
+        const source = table.source;
+        if (!source?.url) {
+            return { tableId: table.id, success: false, message: 'No URL configured' };
+        }
+
+        try {
+            const response = await fetch(source.url);
+            if (!response.ok) {
+                throw new Error(`HTTP ${response.status}: ${response.statusText}`);
+            }
+
+            const content = await response.text();
+            let newRows: any[] = [];
+
+            try {
+                const jsonContent = JSON.parse(content);
+                if (Array.isArray(jsonContent)) {
+                    newRows = jsonContent;
+                } else {
+                    throw new Error('JSON content must be an array');
+                }
+            } catch {
+                // Try parsing as CSV/TSV
+                const tempTable = createTableFromText('temp', content);
+                if (tempTable) {
+                    newRows = tempTable.rows;
+                } else {
+                    throw new Error('Unable to parse response as JSON or CSV/TSV');
+                }
+            }
+
+            return {
+                tableId: table.id,
+                success: true,
+                message: 'Data refreshed successfully',
+                newRows
+            };
+        } catch (error) {
+            return {
+                tableId: table.id,
+                success: false,
+                message: error instanceof Error ? error.message : 'Unknown error'
+            };
+        }
+    }, []);
+
+    /**
+     * Refreshes a virtual table from its original database source.
+     * Backend stores connection info and knows how to refresh - frontend just triggers it.
+     * Backend returns data_changed flag - if false, skip resampling to avoid unnecessary work.
+     * DuckDB views that depend on this table will auto-recalculate only if data changed.
+     */
+    const refreshDatabaseTable = useCallback(async (table: DictTable): Promise<RefreshResult> => {
+        if (!table.virtual?.tableId) {
+            return { tableId: table.id, success: false, message: 'Not a virtual table' };
+        }
+
+        const tableName = table.virtual.tableId;
+
+        try {
+            // Tell backend to refresh the table - it has the connection info stored
+            console.log(`[DataRefresh] Requesting backend to refresh "${tableName}" from external source...`);
+            
+            const refreshResponse = await fetchWithSession(getUrls().DATA_LOADER_REFRESH_TABLE, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ table_name: tableName })
+            }, dispatch);
+
+            const refreshData = await refreshResponse.json();
+            
+            if (refreshData.status !== 'success') {
+                // Backend doesn't have connection info for this table
+                console.log(`[DataRefresh] Cannot refresh "${tableName}": ${refreshData.message}`);
+                return {
+                    tableId: table.id,
+                    success: false,
+                    message: refreshData.message || 'No connection info stored for this table'
+                };
+            }
+            
+            console.log(`[DataRefresh] Backend refreshed "${tableName}" (${refreshData.row_count} rows, data_changed=${refreshData.data_changed}, hash=${refreshData.content_hash?.slice(0, 8)})`);
+
+            // If data hasn't changed, skip resampling - no need to update frontend
+            if (!refreshData.data_changed) {
+                console.log(`[DataRefresh] Data unchanged for "${tableName}", skipping resample`);
+                return {
+                    tableId: table.id,
+                    success: true,
+                    message: `Data unchanged (${refreshData.row_count} rows)`,
+                    // Don't include newRows - signals no update needed
+                };
+            }
+
+            // Data changed - get a fresh sample for the frontend
+            const sampleResponse = await fetchWithSession(getUrls().SAMPLE_TABLE, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ 
+                    table: tableName,
+                    size: Math.min(table.rows.length, 10000)
+                })
+            }, dispatch);
+
+            const sampleData = await sampleResponse.json();
+            if (sampleData.status === 'success') {
+                return {
+                    tableId: table.id,
+                    success: true,
+                    message: `Refreshed from source (${refreshData.row_count} rows)`,
+                    newRows: sampleData.rows,
+                    contentHash: refreshData.content_hash
+                };
+            } else {
+                return {
+                    tableId: table.id,
+                    success: false,
+                    message: sampleData.error || 'Failed to sample refreshed table'
+                };
+            }
+        } catch (error) {
+            return {
+                tableId: table.id,
+                success: false,
+                message: error instanceof Error ? error.message : 'Unknown error'
+            };
+        }
+    }, [dispatch]);
+
+    /**
+     * Refresh a single table's data
+     */
+    const refreshTable = useCallback(async (table: DictTable): Promise<RefreshResult> => {
+        const source = table.source;
+
+        // Stream source - frontend has URL
+        if (source?.type === 'stream' && source.url) {
+            return fetchStreamData(table);
+        }
+
+        // Database source - backend has connection info
+        if (table.virtual && source?.type === 'database' && source.canRefresh) {
+            return refreshDatabaseTable(table);
+        }
+
+        return { tableId: table.id, success: false, message: 'Table does not support refresh' };
+    }, [fetchStreamData, refreshDatabaseTable]);
+
+    /**
+     * Refresh table and update state, then refresh derived tables
+     */
+    const performRefresh = useCallback(async (table: DictTable) => {
+        // Prevent overlapping refreshes for the same table
+        if (refreshInProgressRef.current.get(table.id)) {
+            console.log(`[DataRefresh] Refresh already in progress for "${table.id}", skipping...`);
+            return;
+        }
+
+        refreshInProgressRef.current.set(table.id, true);
+
+        try {
+            const result = await refreshTable(table);
+
+            if (result.success) {
+                // Check if we have new rows to process
+                if (result.newRows) {
+                    // For stream sources: compute hash locally and compare
+                    // For database sources: backend already determined data changed
+                    const newContentHash = result.contentHash || computeContentHash(result.newRows, table.names);
+                    const oldContentHash = table.contentHash;
+                    
+                    const dataChanged = oldContentHash !== newContentHash;
+                    
+                    if (dataChanged) {
+                        console.log(`[DataRefresh] Table "${table.id}" data changed (hash: ${oldContentHash?.slice(0, 8) || 'none'} -> ${newContentHash.slice(0, 8)}), updating...`);
+                        
+                        // Update the table rows - this will trigger useDerivedTableRefresh
+                        // Pass contentHash from backend for virtual/DB tables so it reflects full table state
+                        dispatch(dfActions.updateTableRows({
+                            tableId: table.id,
+                            rows: result.newRows,
+                            contentHash: result.contentHash  // Use backend hash for DB tables
+                        }));
+
+                        // Notify about the refresh
+                        dispatchThrottledMessage({
+                            timestamp: Date.now(),
+                            component: 'Data Refresh',
+                            type: 'info',
+                            value: `Table "${table.displayId || table.id}" data refreshed (${result.newRows.length} rows)`
+                        });
+                    } else {
+                        console.log(`[DataRefresh] Table "${table.id}" data unchanged (hash: ${newContentHash.slice(0, 8)})`);
+                    }
+                } else {
+                    // Success but no newRows means database refresh detected no data change
+                    // No need to update frontend state or trigger derived table refresh
+                    console.log(`[DataRefresh] Table "${table.id}" refresh complete - data unchanged (backend check)`);
+                }
+            } else {
+                console.warn(`[DataRefresh] Failed to refresh "${table.id}": ${result.message}`);
+                dispatchThrottledMessage({
+                    timestamp: Date.now(),
+                    component: 'Data Refresh',
+                    type: 'warning',
+                    value: `Failed to refresh "${table.displayId || table.id}": ${result.message}`
+                });
+            }
+        } finally {
+            refreshInProgressRef.current.set(table.id, false);
+        }
+    }, [dispatch, refreshTable, dispatchThrottledMessage]);
+
+    /**
+     * Schedule the next refresh for a table after the current one completes.
+     * Uses recursive setTimeout pattern to ensure updates wait until complete.
+     */
+    const scheduleNextRefresh = useCallback((tableId: string) => {
+        // Look up the current table state to get latest source config
+        const table = tables.find(t => t.id === tableId);
+        if (!table) {
+            // Table no longer exists, stop scheduling
+            isActiveRef.current.set(tableId, false);
+            return;
+        }
+
+        const source = table.source;
+        if (!source?.autoRefresh || !source.refreshIntervalSeconds || source.refreshIntervalSeconds <= 0) {
+            // Auto-refresh disabled or invalid interval, stop scheduling
+            isActiveRef.current.set(tableId, false);
+            return;
+        }
+
+        // Check if this table is still active (hasn't been removed or disabled)
+        if (!isActiveRef.current.get(tableId)) {
+            return;
+        }
+
+        const intervalMs = source.refreshIntervalSeconds * 1000;
+        
+        // Schedule the next refresh
+        const timeout = setTimeout(async () => {
+            // Check again if still active before performing refresh
+            if (!isActiveRef.current.get(tableId)) {
+                return;
+            }
+
+            // Look up table again to get latest state
+            const currentTable = tables.find(t => t.id === tableId);
+            if (!currentTable) {
+                isActiveRef.current.set(tableId, false);
+                return;
+            }
+
+            // Perform refresh and wait for it to complete
+            await performRefresh(currentTable);
+            
+            // Schedule the next refresh after this one completes
+            scheduleNextRefresh(tableId);
+        }, intervalMs);
+
+        timeoutRefs.current.set(tableId, timeout);
+    }, [tables, performRefresh]);
+
+    /**
+     * Set up refresh intervals for tables with auto-refresh enabled.
+     * Uses recursive setTimeout pattern to ensure updates wait until complete.
+     */
+    useEffect(() => {
+        // Clear all existing timeouts
+        timeoutRefs.current.forEach((timeout) => clearTimeout(timeout));
+        timeoutRefs.current.clear();
+        isActiveRef.current.clear();
+
+        // Set up new refresh schedules for tables with auto-refresh
+        tables.forEach((table) => {
+            const source = table.source;
+            
+            // Check if auto-refresh is enabled
+            const shouldAutoRefresh = source?.autoRefresh && 
+                source.refreshIntervalSeconds && 
+                source.refreshIntervalSeconds > 0;
+
+            if (shouldAutoRefresh) {
+                const intervalMs = source.refreshIntervalSeconds! * 1000;
+                
+                console.log(`[DataRefresh] Setting up auto-refresh for "${table.id}" every ${source.refreshIntervalSeconds}s (waiting for completion)`);
+                
+                // Mark as active
+                isActiveRef.current.set(table.id, true);
+                
+                // Start the refresh cycle - first refresh happens after interval, then schedules next after completion
+                const initialTimeout = setTimeout(async () => {
+                    if (!isActiveRef.current.get(table.id)) {
+                        return;
+                    }
+                    await performRefresh(table);
+                    scheduleNextRefresh(table.id);
+                }, intervalMs);
+
+                timeoutRefs.current.set(table.id, initialTimeout);
+            }
+        });
+
+        // Cleanup on unmount or when tables change
+        return () => {
+            timeoutRefs.current.forEach((timeout) => clearTimeout(timeout));
+            timeoutRefs.current.clear();
+            isActiveRef.current.clear();
+        };
+    }, [tables, performRefresh, scheduleNextRefresh]);
+
+    /**
+     * Manual refresh function that can be called from components
+     */
+    const manualRefresh = useCallback(async (tableId: string) => {
+        const table = tables.find(t => t.id === tableId);
+        if (table) {
+            await performRefresh(table);
+        }
+    }, [tables, performRefresh]);
+
+    /**
+     * Get refresh info for a table
+     */
+    const getRefreshInfo = useCallback((tableId: string) => {
+        const table = tables.find(t => t.id === tableId);
+        if (!table) return null;
+
+        const source = table.source;
+        // Can refresh if: stream with URL, or database table with backend connection info
+        const canRefresh = (source?.type === 'stream' && !!source.url) || 
+                          (source?.type === 'database' && source.canRefresh === true);
+        return {
+            canRefresh,
+            autoRefreshEnabled: source?.autoRefresh ?? false,
+            refreshIntervalSeconds: source?.refreshIntervalSeconds,
+            lastRefreshed: source?.lastRefreshed,
+            sourceType: source?.type
+        };
+    }, [tables]);
+
+    return {
+        manualRefresh,
+        getRefreshInfo
+    };
+}
+
+/**
+ * Hook to handle refreshing derived tables when their source tables change.
+ * This should be used in conjunction with useDataRefresh.
+ */
+export function useDerivedTableRefresh() {
+    const dispatch = useDispatch<AppDispatch>();
+    const tables = useSelector((state: DataFormulatorState) => state.tables);
+    const prevTableRowsRef = useRef<Map<string, string>>(new Map());
+    const refreshInProgressRef = useRef<Set<string>>(new Set());
+    const lastMessageTimeRef = useRef<number>(0);
+    const MESSAGE_THROTTLE_MS = 10000; // 10 seconds
+
+    /**
+     * Throttled message dispatcher - only sends messages if at least 10 seconds have passed since last message
+     */
+    const dispatchThrottledMessage = useCallback((message: Parameters<typeof dfActions.addMessages>[0]) => {
+        const now = Date.now();
+        const timeSinceLastMessage = now - lastMessageTimeRef.current;
+        
+        if (timeSinceLastMessage >= MESSAGE_THROTTLE_MS) {
+            lastMessageTimeRef.current = now;
+            dispatch(dfActions.addMessages(message));
+        } else {
+            console.log(`[DerivedRefresh] Throttling message (${Math.round((MESSAGE_THROTTLE_MS - timeSinceLastMessage) / 1000)}s remaining): ${message.value}`);
+        }
+    }, [dispatch]);
+
+    /**
+     * Refresh a SQL view (virtual table) by re-sampling from DuckDB.
+     * DuckDB views auto-update when base tables change, so we just need fresh data.
+     */
+    const refreshSqlView = useCallback(async (derivedTable: DictTable): Promise<boolean> => {
+        if (!derivedTable.virtual?.tableId) return false;
+
+        const tableName = derivedTable.virtual.tableId;
+        console.log(`[DerivedRefresh] Re-sampling SQL view "${tableName}" (DuckDB auto-updated)...`);
+
+        try {
+            const response = await fetchWithSession(getUrls().SAMPLE_TABLE, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ 
+                    table: tableName,
+                    size: Math.max(derivedTable.rows.length, 1000)
+                })
+            }, dispatch);
+
+            const data = await response.json();
+            if (data.status === 'success' && data.rows) {
+                console.log(`[DerivedRefresh] Successfully re-sampled SQL view "${tableName}" (${data.rows.length} rows)`);
+                
+                dispatch(dfActions.updateTableRows({
+                    tableId: derivedTable.id,
+                    rows: data.rows
+                }));
+
+                dispatchThrottledMessage({
+                    timestamp: Date.now(),
+                    component: 'Data Refresh',
+                    type: 'info',
+                    value: `View "${derivedTable.displayId || derivedTable.id}" refreshed (${data.rows.length} rows)`
+                });
+                return true;
+            }
+            return false;
+        } catch (error) {
+            console.error(`[DerivedRefresh] Error re-sampling SQL view ${tableName}:`, error);
+            return false;
+        }
+    }, [dispatch, dispatchThrottledMessage]);
+
+    /**
+     * Refresh a derived table by re-running its derivation code (Python)
+     * or re-sampling if it's an SQL view.
+     */
+    const refreshDerivedTable = useCallback(async (derivedTable: DictTable, allTables: DictTable[]) => {
+        if (!derivedTable.derive) return;
+        
+        // Prevent concurrent refreshes of the same table
+        if (refreshInProgressRef.current.has(derivedTable.id)) {
+            console.log(`[DerivedRefresh] Refresh already in progress for: ${derivedTable.id}`);
+            return;
+        }
+        
+        refreshInProgressRef.current.add(derivedTable.id);
+
+        try {
+            // For SQL views (virtual tables), DuckDB auto-updates the view
+            // We just need to re-sample to get the updated data
+            if (derivedTable.virtual?.tableId) {
+                console.log(`[DerivedRefresh] Table "${derivedTable.id}" is an SQL view - DuckDB auto-updates it`);
+                await refreshSqlView(derivedTable);
+                return;
+            }
+
+            // For Python-derived tables, we need to re-run the transformation code
+            const { source: sourceTableIds, code } = derivedTable.derive;
+
+            console.log(`[DerivedRefresh] Looking for source tables: ${sourceTableIds.join(', ')}`);
+            console.log(`[DerivedRefresh] Available tables: ${allTables.map(t => t.id).join(', ')}`);
+            
+            // Get the actual source table data
+            const inputTables: {name: string, rows: any[]}[] = [];
+            for (const sourceId of sourceTableIds) {
+                const sourceTable = allTables.find(t => t.id === sourceId);
+                if (!sourceTable) {
+                    console.warn(`[DerivedRefresh] Source table not found: ${sourceId}`);
+                    continue;
+                }
+                const tableName = sourceTable.virtual?.tableId || sourceTable.id.replace(/\.[^/.]+$/, "");
+                console.log(`[DerivedRefresh] Found source table "${sourceId}" -> "${tableName}" with ${sourceTable.rows.length} rows`);
+                inputTables.push({
+                    name: tableName,
+                    rows: sourceTable.rows
+                });
+            }
+
+            if (inputTables.length !== sourceTableIds.length) {
+                console.error(`[DerivedRefresh] Missing source tables for: ${derivedTable.id} (got ${inputTables.length}/${sourceTableIds.length})`);
+                return;
+            }
+
+            console.log(`[DerivedRefresh] Calling server to refresh "${derivedTable.id}" with ${inputTables.length} input tables, code length: ${code.length}`);
+
+            // Call the server to re-run the derivation
+            const response = await fetchWithSession(getUrls().REFRESH_DERIVED_DATA, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({
+                    input_tables: inputTables,
+                    code: code
+                })
+            }, dispatch);
+
+            const data = await response.json();
+            
+            if (data.status === 'ok' && data.rows) {
+                console.log(`[DerivedRefresh] Successfully refreshed "${derivedTable.id}" with ${data.rows.length} rows`);
+                
+                dispatch(dfActions.updateTableRows({
+                    tableId: derivedTable.id,
+                    rows: data.rows
+                }));
+
+                dispatchThrottledMessage({
+                    timestamp: Date.now(),
+                    component: 'Data Refresh',
+                    type: 'info',
+                    value: `Derived table "${derivedTable.displayId || derivedTable.id}" refreshed (${data.rows.length} rows)`
+                });
+            } else {
+                console.error(`[DerivedRefresh] Failed to refresh "${derivedTable.id}": ${data.message}`);
+                dispatchThrottledMessage({
+                    timestamp: Date.now(),
+                    component: 'Data Refresh',
+                    type: 'warning',
+                    value: `Failed to refresh "${derivedTable.displayId || derivedTable.id}": ${data.message}`
+                });
+            }
+        } catch (error) {
+            console.error(`[DerivedRefresh] Error refreshing derived table ${derivedTable.id}:`, error);
+            dispatchThrottledMessage({
+                timestamp: Date.now(),
+                component: 'Data Refresh',
+                type: 'error',
+                value: `Error refreshing "${derivedTable.displayId || derivedTable.id}": ${error instanceof Error ? error.message : 'Unknown error'}`
+            });
+        } finally {
+            refreshInProgressRef.current.delete(derivedTable.id);
+        }
+    }, [dispatch, refreshSqlView, dispatchThrottledMessage]);
+
+    /**
+     * Check for table changes and refresh dependent derived tables.
+     * Uses content hashes for source tables only - derived tables don't need hashing
+     * since their changes are driven by source table changes.
+     */
+    useEffect(() => {
+        console.log(`[DerivedRefresh] useEffect triggered, ${tables.length} tables in state`);
+        
+        // Build a map of content hashes for source tables only (non-derived tables)
+        const currentHashMap = new Map<string, string>();
+        tables.forEach(table => {
+            // Only track hashes for source tables (non-derived)
+            if (!table.derive) {
+                // Use stored contentHash if available, otherwise compute it
+                const hash = table.contentHash || computeContentHash(table.rows, table.names);
+                currentHashMap.set(table.id, hash);
+            }
+        });
+
+        // Check which source tables have changed
+        const changedTableIds: string[] = [];
+        currentHashMap.forEach((hash, tableId) => {
+            const prevHash = prevTableRowsRef.current.get(tableId);
+            if (prevHash && prevHash !== hash) {
+                changedTableIds.push(tableId);
+                console.log(`[DerivedRefresh] Detected change in source table "${tableId}" (hash: ${prevHash.slice(0, 8)} -> ${hash.slice(0, 8)})`);
+            }
+        });
+
+        // Log if no previous hashes (first run)
+        if (prevTableRowsRef.current.size === 0 && tables.length > 0) {
+            const sourceTableCount = tables.filter(t => !t.derive).length;
+            console.log(`[DerivedRefresh] First run, initializing content hashes for ${sourceTableCount} source tables`);
+        }
+
+        // If any source tables changed, find and refresh derived tables that depend on them
+        if (changedTableIds.length > 0) {
+            console.log(`[DerivedRefresh] Source tables changed: ${changedTableIds.join(', ')}`);
+            
+            // Find derived tables that DIRECTLY depend on the changed tables
+            const directlyDependentTables: DictTable[] = [];
+            
+            tables.forEach(table => {
+                if (table.derive) {
+                    // Check if this table directly depends on any changed table
+                    const dependsOnChanged = table.derive.source.some(
+                        sourceId => changedTableIds.includes(sourceId)
+                    );
+                    
+                    const inProgress = refreshInProgressRef.current.has(table.id);
+                    
+                    console.log(`[DerivedRefresh] Checking derived table "${table.id}": dependsOnChanged=${dependsOnChanged}, inProgress=${inProgress}, sources=[${table.derive.source.join(', ')}]`);
+                    
+                    // Only refresh if:
+                    // 1. It depends on a changed source table
+                    // 2. It's not already being refreshed
+                    if (dependsOnChanged && !inProgress) {
+                        directlyDependentTables.push(table);
+                    }
+                }
+            });
+
+            if (directlyDependentTables.length > 0) {
+                console.log(`[DerivedRefresh] Will refresh ${directlyDependentTables.length} directly dependent tables: ${directlyDependentTables.map(t => t.id).join(', ')}`);
+                
+                // Refresh each directly dependent table
+                directlyDependentTables.forEach(derivedTable => {
+                    refreshDerivedTable(derivedTable, tables);
+                });
+            } else {
+                console.log(`[DerivedRefresh] No derived tables need refreshing`);
+            }
+        }
+
+        // Update the previous hashes reference (only source tables)
+        prevTableRowsRef.current = currentHashMap;
+    }, [tables, refreshDerivedTable]);
+}
diff --git a/src/app/utils.tsx b/src/app/utils.tsx
index 8ed501c..8eb2148 100644
--- a/src/app/utils.tsx
+++ b/src/app/utils.tsx
@@ -52,6 +52,9 @@ export function getUrls() {
         DATA_LOADER_INGEST_DATA: `/api/tables/data-loader/ingest-data`,
         DATA_LOADER_VIEW_QUERY_SAMPLE: `/api/tables/data-loader/view-query-sample`,
         DATA_LOADER_INGEST_DATA_FROM_QUERY: `/api/tables/data-loader/ingest-data-from-query`,
+        DATA_LOADER_REFRESH_TABLE: `/api/tables/data-loader/refresh-table`,
+        DATA_LOADER_GET_TABLE_METADATA: `/api/tables/data-loader/get-table-metadata`,
+        DATA_LOADER_LIST_TABLE_METADATA: `/api/tables/data-loader/list-table-metadata`,
 
         QUERY_COMPLETION: `/api/agent/query-completion`,
         GET_RECOMMENDATION_QUESTIONS: `/api/agent/get-recommendation-questions`,
@@ -80,6 +83,9 @@ const SESSION_REQUIRED_ENDPOINTS = [
     '/api/tables/data-loader/ingest-data',
     '/api/tables/data-loader/view-query-sample',
     '/api/tables/data-loader/ingest-data-from-query',
+    '/api/tables/data-loader/refresh-table',
+    '/api/tables/data-loader/get-table-metadata',
+    '/api/tables/data-loader/list-table-metadata',
     '/api/tables/refresh-derived-data',
 ];
 
@@ -186,6 +192,104 @@ export function usePrevious<T>(value: T): T | undefined {
     return ref.current;
 }
 
+/**
+ * Simple hash function (djb2 algorithm) for creating content fingerprints
+ * @param str - The string to hash
+ * @returns A hexadecimal hash string
+ */
+function djb2Hash(str: string): string {
+    let hash = 5381;
+    for (let i = 0; i < str.length; i++) {
+        hash = ((hash << 5) + hash) + str.charCodeAt(i);
+        hash = hash & hash; // Convert to 32-bit integer
+    }
+    return (hash >>> 0).toString(16); // Convert to unsigned and then to hex
+}
+
+/**
+ * Computes a content hash for table data to detect changes.
+ * Uses a sampling strategy for efficiency with large datasets:
+ * - Always includes column names and row count
+ * - Samples first 50, last 50, and 50 evenly distributed rows from the middle
+ * - This catches most data changes while remaining efficient
+ * 
+ * @param rows - The table rows to hash
+ * @param names - Optional column names (for additional fingerprinting)
+ * @returns A hash string representing the content
+ */
+export function computeContentHash(rows: any[], names?: string[]): string {
+    const parts: string[] = [];
+    
+    // Include column names if provided
+    if (names && names.length > 0) {
+        parts.push(`cols:${names.join(',')}`);
+    }
+    
+    // Include row count
+    const rowCount = rows.length;
+    parts.push(`count:${rowCount}`);
+    
+    if (rowCount === 0) {
+        return djb2Hash(parts.join('|'));
+    }
+    
+    // Get column names from first row if not provided
+    const columnNames = names || Object.keys(rows[0] || {});
+    parts.push(`fields:${columnNames.join(',')}`);
+    
+    // Sampling strategy for efficiency
+    const sampleSize = 50;
+    const samplesToInclude: number[] = [];
+    
+    // Always include first N rows
+    for (let i = 0; i < Math.min(sampleSize, rowCount); i++) {
+        samplesToInclude.push(i);
+    }
+    
+    // Include evenly distributed rows from the middle
+    if (rowCount > sampleSize * 2) {
+        const step = Math.floor((rowCount - sampleSize * 2) / sampleSize);
+        if (step > 0) {
+            for (let i = sampleSize; i < rowCount - sampleSize; i += step) {
+                if (samplesToInclude.length < sampleSize * 2) {
+                    samplesToInclude.push(i);
+                }
+            }
+        }
+    }
+    
+    // Always include last N rows
+    for (let i = Math.max(rowCount - sampleSize, sampleSize); i < rowCount; i++) {
+        if (!samplesToInclude.includes(i)) {
+            samplesToInclude.push(i);
+        }
+    }
+    
+    // Sort indices for consistent ordering
+    samplesToInclude.sort((a, b) => a - b);
+    
+    // Build content string from sampled rows
+    const rowStrings: string[] = [];
+    for (const idx of samplesToInclude) {
+        const row = rows[idx];
+        if (row) {
+            // Create a deterministic string representation of the row
+            const rowValues = columnNames.map(col => {
+                const val = row[col];
+                if (val === null) return 'null';
+                if (val === undefined) return 'undefined';
+                if (typeof val === 'object') return JSON.stringify(val);
+                return String(val);
+            });
+            rowStrings.push(`${idx}:${rowValues.join(',')}`);
+        }
+    }
+    
+    parts.push(`rows:${rowStrings.join(';')}`);
+    
+    return djb2Hash(parts.join('|'));
+}
+
 export function runCodeOnInputListsInVM(
             code: string, 
             inputTupleList: any[][], 
@@ -390,9 +494,6 @@ export const assembleVegaChart = (
             } else if (channel == 'column' || channel == 'row') {
                 // if the column or row channel and no dtype is specified, use nominal
                 encodingObj["type"] = 'nominal';
-            } else if (chartType == 'Grouped Bar Chart' && (channel == 'color' || channel == 'x')) {
-                // if the chart type is grouped bar chart and the channel is color or x, use nominal
-                encodingObj["type"] = 'nominal';
             }
             
             if (aggrPreprocessed) {
diff --git a/src/components/ChartTemplates.tsx b/src/components/ChartTemplates.tsx
index 347d125..980770b 100644
--- a/src/components/ChartTemplates.tsx
+++ b/src/components/ChartTemplates.tsx
@@ -205,7 +205,6 @@ const barCharts: ChartTemplate[] = [
         "icon": <ChartIcon src={chartIconPyramid} />,
         "template": {
             "spacing": 0,
-            
             "resolve": {"scale": {"y": "shared"}},
             "hconcat": [{
                 "mark": "bar",
@@ -268,9 +267,66 @@ const barCharts: ChartTemplate[] = [
         "paths": {
             "x": ["encoding", "x"],
             "y": ["encoding", "y"],
-            "color": [["encoding", "xOffset"], ["encoding", "color"]],
+            "color": [["encoding", "color"]],
             "column": ["encoding", "column"],
             "row": ["encoding", "row"]
+        },
+        "postProcessor": (vgSpec: any, table: any[]) => {
+            if (!vgSpec.encoding.color?.field) return vgSpec;
+            
+            let nominalChannel: "x" | "y" | null = null;
+            let offsetChannel: "xOffset" | "yOffset" | null = null;
+            
+            if (vgSpec.encoding.x?.type === "nominal") {
+                nominalChannel = "x";
+                offsetChannel = "xOffset";
+            } else if (vgSpec.encoding.y?.type === "nominal") {
+                nominalChannel = "y";
+                offsetChannel = "yOffset";
+            } else if (vgSpec.encoding.x && vgSpec.encoding.y) {
+                // Neither are nominal, convert the one with lower cardinality to nominal
+                if (table && table.length > 0) {
+                    const xField = vgSpec.encoding.x?.field;
+                    const yField = vgSpec.encoding.y?.field;
+                    
+                    let xCardinality = Infinity;
+                    let yCardinality = Infinity;
+                    
+                    if (xField) {
+                        const xValues = [...new Set(table.map(r => r[xField]))];
+                        xCardinality = xValues.length;
+                    }
+                    
+                    if (yField) {
+                        const yValues = [...new Set(table.map(r => r[yField]))];
+                        yCardinality = yValues.length;
+                    }
+                    
+                    if (xCardinality <= yCardinality) {
+                        nominalChannel = "x";
+                        offsetChannel = "xOffset";
+                        vgSpec.encoding.x.type = "nominal";
+                    } else {
+                        nominalChannel = "y";
+                        offsetChannel = "yOffset";
+                        vgSpec.encoding.y.type = "nominal";
+                    }
+                } else {
+                    // Default: convert x to nominal and use xOffset if no table data
+                    nominalChannel = "x";
+                    offsetChannel = "xOffset";
+                    vgSpec.encoding.x.type = "nominal";
+                }
+            }
+            
+            if (nominalChannel && offsetChannel) {
+                if (!vgSpec.encoding[offsetChannel]) {
+                    vgSpec.encoding[offsetChannel] = {};
+                }
+                vgSpec.encoding[offsetChannel].field = vgSpec.encoding.color.field;
+                vgSpec.encoding[offsetChannel].type = "nominal";
+            }
+            return vgSpec;
         }
     },
     {
diff --git a/src/components/ComponentType.tsx b/src/components/ComponentType.tsx
index abb85af..04d7d5c 100644
--- a/src/components/ComponentType.tsx
+++ b/src/components/ComponentType.tsx
@@ -40,7 +40,6 @@ export interface Trigger {
     instruction: string,
     displayInstruction: string, // the short instruction that will be displayed to the user
 
-
     resultTableId: string,
 }
 
@@ -70,6 +69,37 @@ export interface DataCleanBlock {
     dialogItem?: any; // Store the dialog item from the model response
 }
 
+// Data source types for tracking where data originated
+export type DataSourceType = 'paste' | 'file' | 'url' | 'stream' | 'database' | 'example' | 'extract';
+
+// Configuration for data source refresh behavior
+// Note: For database sources, connection details are stored in DuckDB backend,
+// not in the frontend. Frontend only manages refresh timing/toggle.
+export interface DataSourceConfig {
+    type: DataSourceType;
+    
+    // For URL/stream sources - the URL to fetch data from
+    url?: string;
+    
+    // Refresh interval in seconds (used for streams and database auto-refresh)
+    refreshIntervalSeconds?: number;
+    
+    // For database sources - the DuckDB table name (backend knows how to refresh it)
+    databaseTable?: string;
+    
+    // Whether auto-refresh is enabled (frontend controls this for all source types)
+    autoRefresh?: boolean;
+    
+    // Last refresh timestamp
+    lastRefreshed?: number;
+    
+    // Original file name (for file uploads)
+    fileName?: string;
+    
+    // Whether this table can be refreshed (backend has connection info)
+    canRefresh?: boolean;
+}
+
 export interface DictTable {
     id: string; // name/id of the table
     displayId: string; // display id of the table 
@@ -106,6 +136,13 @@ export interface DictTable {
     anchored: boolean; // whether this table is anchored as a persistent table used to derive other tables
     createdBy: 'user' | 'agent'; // whether this table is created by the user or the agent
     attachedMetadata: string; // a string of attached metadata explaining what the table is about (used for prompt)
+    
+    // New field: tracks the source of the data and refresh configuration
+    source?: DataSourceConfig;
+    
+    // Content hash for detecting data changes during refresh
+    // Used to avoid unnecessary derived table recalculations when data hasn't changed
+    contentHash?: string;
 }
 
 export function createDictTable(
@@ -115,7 +152,8 @@ export function createDictTable(
     virtual: {tableId: string, rowCount: number} | undefined = undefined,
     anchored: boolean = false,
     createdBy: 'user' | 'agent' = 'user', // by default, all tables are created by the user
-    attachedMetadata: string = ''
+    attachedMetadata: string = '',
+    source: DataSourceConfig | undefined = undefined
 ) : DictTable {
     
     let names = Object.keys(rows[0])
@@ -137,7 +175,8 @@ export function createDictTable(
         virtual,
         anchored,
         createdBy,
-        attachedMetadata
+        attachedMetadata,
+        source
     }
 }
 
diff --git a/src/scss/DataView.scss b/src/scss/DataView.scss
index 6fdcf81..aa8b8de 100644
--- a/src/scss/DataView.scss
+++ b/src/scss/DataView.scss
@@ -114,37 +114,6 @@ span.bold {
         display: flex;
         flex-direction: row;
         margin: 0 2px 0 0;
-        padding: 4px 6px;
-        height: 36px;
-
-        .data-view-header-title {
-            flex: 1 1 auto;
-            display: flex;
-            overflow: clip;
-            text-overflow: ellipsis;
-            white-space: nowrap;
-            color: #333;
-            font-size: 14px;
-            text-align: left;
-            margin-left: 0px;
-
-            .data-view-header-name {
-                font-size: inherit;
-                margin-left: 2px;
-                font-size: 12px;
-                font-weight: 700;
-                overflow-wrap: normal;
-                white-space: normal;
-                overflow: hidden;
-                text-overflow: ellipsis;
-                display: -webkit-box;
-                -webkit-line-clamp: 2;
-                line-clamp: 2;
-                -webkit-box-orient: vertical;
-                max-height: 36px;
-                flex-shrink: 1;
-                color: #333;
-            }
-        }
+        padding: 4px 4px;
     }
 }
\ No newline at end of file
diff --git a/src/views/DBTableManager.tsx b/src/views/DBTableManager.tsx
index 8d09016..449700f 100644
--- a/src/views/DBTableManager.tsx
+++ b/src/views/DBTableManager.tsx
@@ -31,7 +31,10 @@ import {
   useTheme,
   Link,
   Checkbox,
-  Popover
+  Popover,
+  Switch,
+  Slider,
+  FormControlLabel
 } from '@mui/material';
 
 import DeleteIcon from '@mui/icons-material/Delete';
@@ -44,7 +47,7 @@ import SearchIcon from '@mui/icons-material/Search';
 
 import { getUrls, fetchWithSession } from '../app/utils';
 import { CustomReactTable } from './ReactTable';
-import { DictTable } from '../components/ComponentType';
+import { DataSourceConfig, DictTable } from '../components/ComponentType';
 import { Type } from '../data/types';
 import { useDispatch, useSelector } from 'react-redux';
 import { dfActions, dfSelectors, getSessionId } from '../app/dfSlice';
@@ -146,6 +149,16 @@ interface DBTable {
     row_count: number;
     sample_rows: any[];
     view_source: string | null;
+    // Source metadata for refreshable tables (from data loaders)
+    // Backend stores connection info; frontend manages refresh timing
+    source_metadata?: {
+        table_name: string;
+        data_loader_type: string;
+        data_loader_params: Record<string, any>;
+        source_table_name?: string;
+        source_query?: string;
+        last_refreshed?: string;
+    } | null;
 }
 
 interface ColumnStatistics {
@@ -193,6 +206,23 @@ export const DBManagerPane: React.FC<{
     const [showViews, setShowViews] = useState<boolean>(false);
     const dbFileInputRef = useRef<HTMLInputElement>(null);
     const menuButtonRef = useRef<HTMLButtonElement>(null);
+    
+    // Watch/auto-refresh settings for the currently selected table
+    const [watchEnabled, setWatchEnabled] = useState<boolean>(false);
+    const [watchInterval, setWatchInterval] = useState<number>(60);
+    
+    // Reset watch settings when selected table changes
+    useEffect(() => {
+        setWatchEnabled(false);
+        setWatchInterval(60);
+    }, [selectedTabKey]);
+    
+    // Helper to format interval for display
+    const formatInterval = (seconds: number) => {
+        if (seconds < 60) return `${seconds}s`;
+        if (seconds < 3600) return `${Math.floor(seconds / 60)}m`;
+        return `${Math.floor(seconds / 3600)}h`;
+    };
 
     let setSystemMessage = (content: string, severity: "error" | "warning" | "info" | "success") => {
         dispatch(dfActions.addMessages({
@@ -218,17 +248,19 @@ export const DBManagerPane: React.FC<{
     }, [dbTables, selectedDataLoader]);
 
     // Fetch list of tables
-    const fetchTables = async () => {
-        if (serverConfig.DISABLE_DATABASE) return;
+    const fetchTables = async (): Promise<DBTable[] | undefined> => {
+        if (serverConfig.DISABLE_DATABASE) return undefined;
         try {
             const response = await fetchWithSession(getUrls().LIST_TABLES, { method: 'GET' }, dispatch);
             const data = await response.json();
             if (data.status === 'success') {
                 setDbTables(data.tables);
+                return data.tables;
             }
         } catch (error) {
             setSystemMessage('Failed to fetch tables, please check if the server is running', "error");
         }
+        return undefined;
     };
 
     const fetchDataLoaders = async () => {
@@ -423,7 +455,7 @@ export const DBManagerPane: React.FC<{
         }
     }, [selectedTabKey, selectedDataLoader, handleAnalyzeData]);
 
-    const handleAddTableToDF = (dbTable: DBTable) => {
+    const handleAddTableToDF = (dbTable: DBTable, refreshSettings?: {autoRefresh: boolean, refreshIntervalSeconds: number}) => {
         const convertSqlTypeToAppType = (sqlType: string): Type => {
             // Convert SQL types to application types
             sqlType = sqlType.toUpperCase();
@@ -440,6 +472,19 @@ export const DBManagerPane: React.FC<{
             }
         };
 
+        // Build source config - backend stores connection details, frontend just manages refresh timing
+        const sourceMeta = dbTable.source_metadata;
+        const sourceConfig: DataSourceConfig = {
+            type: 'database',
+            databaseTable: dbTable.name,
+            // Frontend manages these refresh settings (from user selection)
+            autoRefresh: refreshSettings?.autoRefresh ?? false,
+            refreshIntervalSeconds: refreshSettings?.refreshIntervalSeconds ?? 60,
+            // Backend has connection info if source_metadata exists
+            canRefresh: sourceMeta != null,
+            lastRefreshed: Date.now()
+        };
+
         let table: DictTable = {
             id: dbTable.name,
             displayId: dbTable.name,
@@ -459,7 +504,8 @@ export const DBManagerPane: React.FC<{
             },
             anchored: true, // by default, db tables are anchored
             createdBy: 'user',
-            attachedMetadata: ''
+            attachedMetadata: '',
+            source: sourceConfig
         }
        dispatch(dfActions.loadTable(table));
        dispatch(fetchFieldSemanticType(table));
@@ -1011,19 +1057,71 @@ export const DBManagerPane: React.FC<{
                             </Typography>
                         </Box>
                     ) : (
-                        <Button 
-                            variant="contained"
-                            size="small"
-                            sx={{ml: 'auto', textTransform: 'none'}}
-                            disabled={isUploading || dbTables.length === 0 || dbTables.find(t => t.name === selectedTabKey) === undefined}
-                            onClick={() => {
-                                let t = dbTables.find(t => t.name === selectedTabKey);
-                                if (t) {
-                                    handleAddTableToDF(t);
-                                }
-                            }}>
-                            Load Table
-                        </Button>
+                        <Box sx={{ ml: 2, display: 'flex', flexDirection: 'row', gap: 1 }}>
+                            {/* Watch settings - only show for tables that can be refreshed */}
+                            {currentTable.source_metadata && (
+                                <Box sx={{ display: 'flex', gap: 1 }}>
+                                    <FormControlLabel
+                                        control={
+                                            <Switch
+                                                checked={watchEnabled}
+                                                onChange={(e) => setWatchEnabled(e.target.checked)}
+                                                size="small"
+                                            />
+                                        }
+                                        label={
+                                            <Typography variant="body2" sx={{ fontSize: 12 }}>
+                                                Watch for updates
+                                            </Typography>
+                                        }
+                                        sx={{ mr: 0 }}
+                                    />
+                                    {watchEnabled && (
+                                        <Box sx={{ display: 'flex', alignItems: 'center', gap: 0.5, minWidth: 100 }}>
+                                            <Typography variant="body2" sx={{ fontSize: 11, color: 'text.secondary' }}>
+                                                every
+                                            </Typography>
+                                            <TextField
+                                                select
+                                                size="small"
+                                                value={watchInterval}
+                                                onChange={(e) => setWatchInterval(Number(e.target.value))}
+                                                sx={{ 
+                                                    minWidth: 70,
+                                                    '& .MuiInputBase-root': { fontSize: 11, height: 28 },
+                                                    '& .MuiSelect-select': { py: 0.5 }
+                                                }}
+                                            >
+                                                <MenuItem value={1}>1s</MenuItem>
+                                                <MenuItem value={10}>10s</MenuItem>
+                                                <MenuItem value={30}>30s</MenuItem>
+                                                <MenuItem value={60}>1m</MenuItem>
+                                                <MenuItem value={300}>5m</MenuItem>
+                                                <MenuItem value={600}>10m</MenuItem>
+                                                <MenuItem value={1800}>30m</MenuItem>
+                                                <MenuItem value={3600}>1h</MenuItem>
+                                            </TextField>
+                                        </Box>
+                                    )}
+                                </Box>
+                            )}
+                            <Button 
+                                variant="contained"
+                                size="small"
+                                sx={{ textTransform: 'none', ml: 'auto' }}
+                                disabled={isUploading || dbTables.length === 0 || dbTables.find(t => t.name === selectedTabKey) === undefined}
+                                onClick={() => {
+                                    let t = dbTables.find(t => t.name === selectedTabKey);
+                                    if (t) {
+                                        handleAddTableToDF(t, currentTable.source_metadata ? {
+                                            autoRefresh: watchEnabled,
+                                            refreshIntervalSeconds: watchInterval
+                                        } : undefined);
+                                    }
+                                }}>
+                                Load {watchEnabled? 'Streaming' : ''} Table {watchEnabled && currentTable.source_metadata ? `(watching every ${formatInterval(watchInterval)})` : ''}
+                            </Button>
+                        </Box>
                     )}
                 </Box>
             );
@@ -1118,6 +1216,7 @@ export const DBManagerPane: React.FC<{
                     <CircularProgress size={60} thickness={5} />
                 </Box>
             )}
+            
         </Box>
     );
   
@@ -1135,7 +1234,8 @@ export const DataLoaderForm: React.FC<{
     const theme = useTheme();
     const params = useSelector((state: DataFormulatorState) => state.dataLoaderConnectParams[dataLoaderType] ?? {});
 
-    const [tableMetadata, setTableMetadata] = useState<Record<string, any>>({});    let [displaySamples, setDisplaySamples] = useState<Record<string, boolean>>({});
+    const [tableMetadata, setTableMetadata] = useState<Record<string, any>>({});
+    let [displaySamples, setDisplaySamples] = useState<Record<string, boolean>>({});
     let [tableFilter, setTableFilter] = useState<string>("");
     const [selectedTables, setSelectedTables] = useState<Set<string>>(new Set());
 
@@ -1259,7 +1359,9 @@ export const DataLoaderForm: React.FC<{
                                 const finalTableNames = actualTableNames.length > 0 ? actualTableNames : tablesToImport;
                                 onFinish("success", `Successfully imported ${tablesToImport.length} table(s)`, finalTableNames);
                             } else {
-                                onFinish("error", `Failed to import some tables: ${errors.map(e => e.error).join(", ")}`);
+                                // Backend returns 'message' field for errors
+                                const errorMessages = errors.map(e => e.message || e.error || 'Unknown error').filter(Boolean);
+                                onFinish("error", `Failed to import some tables: ${errorMessages.join(", ")}`);
                             }
                         })
                         .catch(error => {
diff --git a/src/views/DataFormulator.tsx b/src/views/DataFormulator.tsx
index c71aaea..a4441ad 100644
--- a/src/views/DataFormulator.tsx
+++ b/src/views/DataFormulator.tsx
@@ -51,6 +51,7 @@ import { getUrls } from '../app/utils';
 import { UnifiedDataUploadDialog, UploadTabType } from './UnifiedDataUploadDialog';
 import { ReportView } from './ReportView';
 import { ExampleSession, exampleSessions, ExampleSessionCard } from './ExampleSessions';
+import { useDataRefresh, useDerivedTableRefresh } from '../app/useDataRefresh';
 
 export const DataFormulatorFC = ({ }) => {
 
@@ -62,6 +63,12 @@ export const DataFormulatorFC = ({ }) => {
 
     const dispatch = useDispatch();
 
+    // Set up auto-refresh for streaming and database tables
+    const { manualRefresh, getRefreshInfo } = useDataRefresh();
+    
+    // Set up automatic refresh of derived tables when source data changes
+    useDerivedTableRefresh();
+
     // State for unified data upload dialog
     const [uploadDialogOpen, setUploadDialogOpen] = useState(false);
     const [uploadDialogInitialTab, setUploadDialogInitialTab] = useState<UploadTabType>('menu');
@@ -230,7 +237,7 @@ export const DataFormulatorFC = ({ }) => {
                 {viewMode === 'editor' ? (
                     <>
                         {visPane}
-                        <ConceptShelf />
+                        {/* <ConceptShelf /> */}
                     </>
                 ) : (
                     <ReportView />
diff --git a/src/views/DataThread.tsx b/src/views/DataThread.tsx
index d210fee..5a2077b 100644
--- a/src/views/DataThread.tsx
+++ b/src/views/DataThread.tsx
@@ -25,6 +25,8 @@ import {
     Badge,
     Menu,
     MenuItem,
+    Switch,
+    FormControlLabel,
 } from '@mui/material';
 
 import { VegaLite } from 'react-vega'
@@ -65,6 +67,7 @@ import CloudQueueIcon from '@mui/icons-material/CloudQueue';
 import AttachFileIcon from '@mui/icons-material/AttachFile';
 import MoreVertIcon from '@mui/icons-material/MoreVert';
 import RefreshIcon from '@mui/icons-material/Refresh';
+import StreamIcon from '@mui/icons-material/Stream';
 
 import { alpha } from '@mui/material/styles';
 
@@ -72,6 +75,7 @@ import { dfSelectors } from '../app/dfSlice';
 import { RefreshDataDialog } from './RefreshDataDialog';
 import { getUrls } from '../app/utils';
 import { AppDispatch } from '../app/store';
+import StopIcon from '@mui/icons-material/Stop';
 
 export const ThinkingBanner = (message: string, sx?: SxProps) => (
     <Box sx={{ 
@@ -118,6 +122,137 @@ export const ThinkingBanner = (message: string, sx?: SxProps) => (
 );
 
 
+// Streaming Settings Popup Component
+const StreamingSettingsPopup = memo<{
+    open: boolean;
+    anchorEl: HTMLElement | null;
+    onClose: () => void;
+    table: DictTable;
+    onUpdateSettings: (autoRefresh: boolean, refreshIntervalSeconds?: number) => void;
+}>(({ open, anchorEl, onClose, table, onUpdateSettings }) => {
+    const [refreshInterval, setRefreshInterval] = useState<number>(
+        table.source?.refreshIntervalSeconds || 60
+    );
+    const [autoRefresh, setAutoRefresh] = useState<boolean>(
+        table.source?.autoRefresh || false
+    );
+    const [selectMenuOpen, setSelectMenuOpen] = useState<boolean>(false);
+
+    useEffect(() => {
+        if (open) {
+            setRefreshInterval(table.source?.refreshIntervalSeconds || 60);
+            setAutoRefresh(table.source?.autoRefresh || false);
+        }
+    }, [open, table.source]);
+
+    const handleAutoRefreshChange = (enabled: boolean) => {
+        setAutoRefresh(enabled);
+        onUpdateSettings(enabled, enabled ? refreshInterval : undefined);
+        if (!enabled) {
+            onClose();
+        }
+    };
+
+    const handleIntervalChange = (interval: number) => {
+        setRefreshInterval(interval);
+        if (autoRefresh) {
+            onUpdateSettings(true, interval);
+        }
+    };
+
+    const handleClickAway = (event: MouseEvent | TouchEvent) => {
+        // Don't close if the select menu is open
+        if (selectMenuOpen) {
+            return;
+        }
+        // Don't close if clicking on the select menu or menu items
+        const target = event.target as HTMLElement;
+        if (
+            target.closest('.MuiMenu-root') ||
+            target.closest('.MuiPaper-root')?.classList.contains('MuiMenu-paper') ||
+            target.closest('[role="menuitem"]') ||
+            target.closest('[role="listbox"]')
+        ) {
+            return;
+        }
+        onClose();
+    };
+
+    return (
+        <Popper
+            open={open}
+            anchorEl={anchorEl}
+            placement="bottom-start"
+            style={{ zIndex: 1300 }}
+        >
+            <ClickAwayListener onClickAway={handleClickAway} mouseEvent="onMouseDown">
+                <Paper
+                    elevation={8}
+                    sx={{
+                        fontSize: 12,
+                        p: 1.5,
+                        mt: 1,
+                        border: '1px solid',
+                        borderColor: 'divider'
+                    }}
+                >
+                    <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, flexWrap: 'nowrap' }}>
+                        <FormControlLabel
+                            control={
+                                <Switch
+                                    checked={autoRefresh}
+                                    onChange={(e) => handleAutoRefreshChange(e.target.checked)}
+                                    size="small"
+                                />
+                            }
+                            label={
+                                <Typography variant="body2" sx={{ fontSize: 11 }}>
+                                    Watch for updates
+                                </Typography>
+                            }
+                            sx={{ mr: 0 }}
+                        />
+                        {autoRefresh && (
+                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 0.5, minWidth: 100 }}>
+                                <Typography variant="body2" sx={{ fontSize: 11, color: 'text.secondary' }}>
+                                    every
+                                </Typography>
+                                <TextField
+                                    select
+                                    size="small"
+                                    value={refreshInterval}
+                                    onChange={(e) => handleIntervalChange(Number(e.target.value))}
+                                    slotProps={{
+                                        select: {
+                                            open: selectMenuOpen,
+                                            onOpen: () => setSelectMenuOpen(true),
+                                            onClose: () => setSelectMenuOpen(false)
+                                        }
+                                    }}
+                                    sx={{ 
+                                        minWidth: 70,
+                                        '& .MuiInputBase-root': { fontSize: 11, height: 28 },
+                                        '& .MuiSelect-select': { py: 0.5 }
+                                    }}
+                                >
+                                    <MenuItem value={1}>1s</MenuItem>
+                                    <MenuItem value={10}>10s</MenuItem>
+                                    <MenuItem value={30}>30s</MenuItem>
+                                    <MenuItem value={60}>1m</MenuItem>
+                                    <MenuItem value={300}>5m</MenuItem>
+                                    <MenuItem value={600}>10m</MenuItem>
+                                    <MenuItem value={1800}>30m</MenuItem>
+                                    <MenuItem value={3600}>1h</MenuItem>
+                                </TextField>
+                            </Box>
+                        )}
+                    </Box>
+                </Paper>
+            </ClickAwayListener>
+        </Popper>
+    );
+});
+
 // Metadata Popup Component
 const MetadataPopup = memo<{
     open: boolean;
@@ -557,6 +692,11 @@ let SingleThreadGroupView: FC<{
     const [selectedTableForRefresh, setSelectedTableForRefresh] = useState<DictTable | null>(null);
     const [isRefreshing, setIsRefreshing] = useState(false);
 
+    // Streaming settings popup state
+    const [streamingSettingsPopupOpen, setStreamingSettingsPopupOpen] = useState(false);
+    const [selectedTableForStreamingSettings, setSelectedTableForStreamingSettings] = useState<DictTable | null>(null);
+    const [streamingSettingsAnchorEl, setStreamingSettingsAnchorEl] = useState<HTMLElement | null>(null);
+
     let handleUpdateTableDisplayId = (tableId: string, displayId: string) => {
         dispatch(dfActions.updateTableDisplayId({
             tableId: tableId,
@@ -608,6 +748,29 @@ let SingleThreadGroupView: FC<{
         setSelectedTableForRefresh(null);
     };
 
+    // Streaming settings handlers
+    const handleOpenStreamingSettingsPopup = (table: DictTable, anchorEl: HTMLElement) => {
+        setSelectedTableForStreamingSettings(table);
+        setStreamingSettingsAnchorEl(anchorEl);
+        setStreamingSettingsPopupOpen(true);
+    };
+
+    const handleCloseStreamingSettingsPopup = () => {
+        setStreamingSettingsPopupOpen(false);
+        setSelectedTableForStreamingSettings(null);
+        setStreamingSettingsAnchorEl(null);
+    };
+
+    const handleUpdateStreamingSettings = (autoRefresh: boolean, refreshIntervalSeconds?: number) => {
+        if (selectedTableForStreamingSettings) {
+            dispatch(dfActions.updateTableSourceRefreshSettings({
+                tableId: selectedTableForStreamingSettings.id,
+                autoRefresh,
+                refreshIntervalSeconds
+            }));
+        }
+    };
+
     // Function to refresh derived tables
     const refreshDerivedTables = async (sourceTableId: string, newRows: any[]) => {
         // Find all tables that are derived from this source table
@@ -796,13 +959,22 @@ let SingleThreadGroupView: FC<{
         // only charts without dependency can be deleted
         let tableDeleteEnabled = !tables.some(t => t.derive?.trigger.tableId == tableId);
 
-        let tableCardIcon =  ( table?.anchored ? 
-            <AnchorIcon sx={{ 
+        const iconColor = tableId === focusedTableId ? theme.palette.primary.main : 'rgba(0,0,0,0.6)';
+        const iconOpacity = table?.anchored ? 1 : 0.5;
+        
+        let tableCardIcon = table?.virtual ? (
+            <CloudQueueIcon sx={{ 
                 fontSize: 16,
-                color: tableId === focusedTableId ? theme.palette.primary.main : 'rgba(0,0,0,0.5)',
-                fontWeight: tableId === focusedTableId ? 'bold' : 'normal',
-            }} /> : 
-            <TableRowsIcon sx={{ fontSize: 16 }} /> )
+                color: iconColor,
+                opacity: iconOpacity,
+            }} />
+        ) : (
+            <TableRowsIcon sx={{ 
+                fontSize: 16,
+                color: iconColor,
+                opacity: iconOpacity,
+            }} />
+        )
 
         let regularTableBox = <Box key={`regular-table-box-${tableId}`} ref={relevantCharts.some(c => c.chartId == focusedChartId) ? scrollRef : null} 
             sx={{ padding: '0px' }}>
@@ -824,27 +996,83 @@ let SingleThreadGroupView: FC<{
                 }}>
                 <Box sx={{ margin: '0px', display: 'flex' }}>
                     <Stack direction="row" sx={{ marginLeft: 0.5, marginRight: 'auto', fontSize: 12 }} alignItems="center" gap={"2px"}>
-                        <IconButton color="primary" sx={{
-                            minWidth: 0, 
-                            padding: 0.25,
-                            '&:hover': {
-                                transform: 'scale(1.3)',
-                                transition: 'all 0.1s linear'
-                            },
-                            '&.Mui-disabled': {
-                                color: 'rgba(0, 0, 0, 0.5)'
-                            }
-                        }} 
-                        size="small" 
-                        disabled={table?.derive == undefined || tables.some(t => t.derive?.trigger.tableId == tableId)}
-                        onClick={(event) => {
-                            event.stopPropagation();
-                            dispatch(dfActions.updateTableAnchored({tableId: tableId, anchored: !table?.anchored}));
-                        }}>
-                            {tableCardIcon}
-                        </IconButton>
+                        {/* For non-derived tables: icon opens menu; for derived tables: icon toggles anchored */}
+                        {table?.derive == undefined ? (
+                            <Tooltip title="more options">
+                                <IconButton color="primary" sx={{
+                                    minWidth: 0, 
+                                    padding: 0.25,
+                                    '&:hover': {
+                                        transform: 'scale(1.3)',
+                                        transition: 'all 0.1s linear'
+                                    },
+                                }} 
+                                size="small" 
+                                onClick={(event) => {
+                                    event.stopPropagation();
+                                    handleOpenTableMenu(table!, event.currentTarget);
+                                }}>
+                                    {tableCardIcon}
+                                </IconButton>
+                            </Tooltip>
+                        ) : (
+                            <IconButton color="primary" sx={{
+                                minWidth: 0, 
+                                padding: 0.25,
+                                '&:hover': {
+                                    transform: 'scale(1.3)',
+                                    transition: 'all 0.1s linear'
+                                },
+                                '&.Mui-disabled': {
+                                    color: 'rgba(0, 0, 0, 0.5)'
+                                }
+                            }} 
+                            size="small" 
+                            disabled={tables.some(t => t.derive?.trigger.tableId == tableId)}
+                            onClick={(event) => {
+                                event.stopPropagation();
+                                dispatch(dfActions.updateTableAnchored({tableId: tableId, anchored: !table?.anchored}));
+                            }}>
+                                {tableCardIcon}
+                            </IconButton>
+                        )}
                         <Box sx={{ margin: '4px 8px 4px 2px', display: 'flex', alignItems: 'center' }}>
-                            {table?.virtual? <CloudQueueIcon sx={{ fontSize: 10, }} /> : ""}
+                            {/* Only show streaming icon when actively watching for updates */}
+                            {(table?.source?.type === 'stream' || table?.source?.type === 'database') && table?.source?.autoRefresh ? (
+                                <Tooltip title={`Auto-refresh every ${
+                                    (table.source?.refreshIntervalSeconds || 60) < 60 
+                                        ? `${table.source?.refreshIntervalSeconds}s` 
+                                        : (table.source?.refreshIntervalSeconds || 60) < 3600 
+                                            ? `${Math.floor((table.source?.refreshIntervalSeconds || 60) / 60)}m`
+                                            : `${Math.floor((table.source?.refreshIntervalSeconds || 60) / 3600)}h`
+                                } - Click to change interval or stop watching`}>
+                                    <IconButton
+                                        size="small"
+                                        onClick={(event) => {
+                                            event.stopPropagation();
+                                            handleOpenStreamingSettingsPopup(table!, event.currentTarget);
+                                        }}
+                                        sx={{
+                                            padding: 0.25,
+                                            '&:hover': {
+                                                transform: 'scale(1.2)',
+                                                transition: 'all 0.1s linear'
+                                            }
+                                        }}
+                                    >
+                                        <StreamIcon sx={{ 
+                                            fontSize: 12, 
+                                            color: theme.palette.success.main,
+                                            animation: 'pulse 2s infinite',
+                                            '@keyframes pulse': {
+                                                '0%': { opacity: 1 },
+                                                '50%': { opacity: 0.5 },
+                                                '100%': { opacity: 1 },
+                                            },
+                                        }} />
+                                    </IconButton>
+                                </Tooltip>
+                            ) : ""}
                             {focusedTableId == tableId ? <EditableTableName
                                 initialValue={table?.displayId || tableId}
                                 tableId={tableId}
@@ -853,7 +1081,7 @@ let SingleThreadGroupView: FC<{
                                 textAlign: 'center',
                                 color:  'rgba(0,0,0,0.7)', 
                                 maxWidth: '90px',
-                                ml: table?.virtual ? 0.5 : 0,
+                                ml: table?.virtual || ((table?.source?.type === 'stream' || table?.source?.type === 'database') && table?.source?.autoRefresh) ? 0.5 : 0,
                                 wordWrap: 'break-word',
                                 whiteSpace: 'normal'
                             }}>{table?.displayId || tableId}</Typography>}
@@ -875,47 +1103,22 @@ let SingleThreadGroupView: FC<{
                             </IconButton>
                         </Tooltip>
                         
-                        {/* For non-derived, non-virtual tables: show dropdown menu with metadata, refresh, delete */}
-                        {table?.derive == undefined && !table?.virtual && (
-                            <Tooltip key="table-menu-btn-tooltip" title="more options">
-                                <IconButton 
-                                    aria-label="more options" 
-                                    size="small" 
-                                    sx={{ 
-                                        padding: 0.25, 
-                                        '&:hover': {
-                                            transform: 'scale(1.2)',
-                                            transition: 'all 0.1s linear'
-                                        } 
-                                    }}
+                        {/* Delete button - shown for all deletable tables */}
+                        {tableDeleteEnabled && (
+                            <Tooltip key="delete-table-btn-tooltip" title="delete table">
+                                <IconButton aria-label="delete" size="small" sx={{ padding: 0.25, '&:hover': {
+                                    transform: 'scale(1.2)',
+                                    transition: 'all 0.1s linear'
+                                    } }}
                                     onClick={(event) => {
                                         event.stopPropagation();
-                                        handleOpenTableMenu(table!, event.currentTarget);
+                                        dispatch(dfActions.deleteTable(tableId));
                                     }}
                                 >
-                                    <MoreVertIcon fontSize="small" sx={{ fontSize: 18, color: 'text.secondary' }}/>
+                                    <DeleteIcon fontSize="small" sx={{ fontSize: 18 }} color='warning'/>
                                 </IconButton>
                             </Tooltip>
                         )}
-
-                        {/* For derived tables or virtual tables: show individual buttons */}
-                        {(table?.derive != undefined || table?.virtual) && (
-                            <>
-                                {tableDeleteEnabled && <Tooltip key="delete-table-btn-tooltip" title="delete table">
-                                    <IconButton aria-label="delete" size="small" sx={{ padding: 0.25, '&:hover': {
-                                        transform: 'scale(1.2)',
-                                        transition: 'all 0.1s linear'
-                                        } }}
-                                        onClick={(event) => {
-                                            event.stopPropagation();
-                                            dispatch(dfActions.deleteTable(tableId));
-                                        }}
-                                    >
-                                        <DeleteIcon fontSize="small" sx={{ fontSize: 18 }} color='warning'/>
-                                    </IconButton>
-                                </Tooltip>}
-                            </>
-                        )}
                     </ButtonGroup>
                 </Box>
             </Card>
@@ -1072,32 +1275,39 @@ let SingleThreadGroupView: FC<{
                         }}/>
                         {selectedTableForMenu?.attachedMetadata ? "Edit metadata" : "Attach metadata"}
                     </MenuItem>
-                    <MenuItem 
-                        onClick={(e) => {
-                            e.stopPropagation();
-                            if (selectedTableForMenu) {
-                                handleOpenRefreshDialog(selectedTableForMenu);
-                            }
-                        }}
-                        sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
-                    >
-                        <RefreshIcon sx={{ fontSize: 16, color: 'primary.main' }}/>
-                        Refresh data
-                    </MenuItem>
-                    <MenuItem 
-                        onClick={(e) => {
-                            e.stopPropagation();
-                            if (selectedTableForMenu) {
-                                dispatch(dfActions.deleteTable(selectedTableForMenu.id));
-                            }
-                            handleCloseTableMenu();
-                        }}
-                        disabled={selectedTableForMenu ? tables.some(t => t.derive?.trigger.tableId === selectedTableForMenu.id) : true}
-                        sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1, color: 'warning.main' }}
-                    >
-                        <DeleteIcon sx={{ fontSize: 16 }} color='warning'/>
-                        Delete table
-                    </MenuItem>
+                    {/* Watch for updates option - only shown when table has stream/database source but not actively watching */}
+                    {selectedTableForMenu && 
+                     (selectedTableForMenu.source?.type === 'stream' || selectedTableForMenu.source?.type === 'database') && 
+                     (
+                        <MenuItem 
+                            onClick={(e) => {
+                                e.stopPropagation();
+                                if (selectedTableForMenu) {
+                                    handleOpenStreamingSettingsPopup(selectedTableForMenu, tableMenuAnchorEl!);
+                                }
+                                handleCloseTableMenu();
+                            }}
+                            sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
+                        >
+                            <StreamIcon sx={{ fontSize: 16, color: 'text.secondary' }}/>
+                            Watch for updates
+                        </MenuItem>
+                    )}
+                    {/* Refresh data - hidden for database tables */}
+                    {selectedTableForMenu?.source?.type !== 'database' && (
+                        <MenuItem 
+                            onClick={(e) => {
+                                e.stopPropagation();
+                                if (selectedTableForMenu) {
+                                    handleOpenRefreshDialog(selectedTableForMenu);
+                                }
+                            }}
+                            sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
+                        >
+                            <RefreshIcon sx={{ fontSize: 16, color: 'primary.main' }}/>
+                            Refresh data
+                        </MenuItem>
+                    )}
                 </Menu>
                 {selectedTableForRefresh && (
                     <RefreshDataDialog
@@ -1107,6 +1317,15 @@ let SingleThreadGroupView: FC<{
                         onRefreshComplete={handleRefreshComplete}
                     />
                 )}
+                {selectedTableForStreamingSettings && (
+                    <StreamingSettingsPopup
+                        open={streamingSettingsPopupOpen}
+                        anchorEl={streamingSettingsAnchorEl}
+                        onClose={handleCloseStreamingSettingsPopup}
+                        table={selectedTableForStreamingSettings}
+                        onUpdateSettings={handleUpdateStreamingSettings}
+                    />
+                )}
             </Box>
         );
     }
@@ -1194,18 +1413,39 @@ let SingleThreadGroupView: FC<{
                 }}/>
                 {selectedTableForMenu?.attachedMetadata ? "Edit metadata" : "Attach metadata"}
             </MenuItem>
-            <MenuItem 
-                onClick={(e) => {
-                    e.stopPropagation();
-                    if (selectedTableForMenu) {
-                        handleOpenRefreshDialog(selectedTableForMenu);
-                    }
-                }}
-                sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
-            >
-                <RefreshIcon sx={{ fontSize: 16, color: 'primary.main' }}/>
-                Refresh data
-            </MenuItem>
+            {/* Watch for updates option - only shown when table has stream/database source but not actively watching */}
+            {selectedTableForMenu && 
+             (selectedTableForMenu.source?.type === 'stream' || selectedTableForMenu.source?.type === 'database') && 
+             !selectedTableForMenu.source?.autoRefresh && (
+                <MenuItem 
+                    onClick={(e) => {
+                        e.stopPropagation();
+                        if (selectedTableForMenu) {
+                            handleOpenStreamingSettingsPopup(selectedTableForMenu, tableMenuAnchorEl!);
+                        }
+                        handleCloseTableMenu();
+                    }}
+                    sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
+                >
+                    <StreamIcon sx={{ fontSize: 16, color: 'text.secondary' }}/>
+                    Watch for updates
+                </MenuItem>
+            )}
+            {/* Refresh data - hidden for database tables */}
+            {selectedTableForMenu?.source?.type !== 'database' && (
+                <MenuItem 
+                    onClick={(e) => {
+                        e.stopPropagation();
+                        if (selectedTableForMenu) {
+                            handleOpenRefreshDialog(selectedTableForMenu);
+                        }
+                    }}
+                    sx={{ fontSize: '12px', display: 'flex', alignItems: 'center', gap: 1 }}
+                >
+                    <RefreshIcon sx={{ fontSize: 16, color: 'primary.main' }}/>
+                    Refresh data
+                </MenuItem>
+            )}
             <MenuItem 
                 onClick={(e) => {
                     e.stopPropagation();
@@ -1231,8 +1471,19 @@ let SingleThreadGroupView: FC<{
                 onRefreshComplete={handleRefreshComplete}
             />
         )}
+
+        {/* Streaming settings popup */}
+        {selectedTableForStreamingSettings && (
+            <StreamingSettingsPopup
+                open={streamingSettingsPopupOpen}
+                anchorEl={streamingSettingsAnchorEl}
+                onClose={handleCloseStreamingSettingsPopup}
+                table={selectedTableForStreamingSettings}
+                onUpdateSettings={handleUpdateStreamingSettings}
+            />
+        )}
     </Box>
-}
+    }
 
 const VegaLiteChartElement = memo<{
     chart: Chart,
@@ -1597,7 +1848,7 @@ export const DataThread: FC<{sx?: SxProps}> = function ({ sx }) {
     let view = <Box maxWidth={drawerOpen ? 720 : collaposedViewWidth} sx={{ 
         overflow: 'auto', // Add horizontal scroll when drawer is open
         position: 'relative',
-        display: 'flex', 
+        display: drawerOpen ? '-webkit-box' : 'flex', 
         flexDirection: 'column',
         direction: 'ltr',
         height: 'calc(100% - 16px)',
diff --git a/src/views/DataView.tsx b/src/views/DataView.tsx
index 3d42e45..f1692c5 100644
--- a/src/views/DataView.tsx
+++ b/src/views/DataView.tsx
@@ -74,7 +74,7 @@ export const FreeDataViewFC: FC<FreeDataViewProps> = function DataView() {
                 ? nameSegments.reduce((max, segment) => Math.max(max, segment.length), 0)
                 : name.length;
             const contentLength = Math.max(maxNameSegmentLength, avgLength);
-            const minWidth = Math.max(60, contentLength * 8 > 200 ? 200 : contentLength * 8) + 50; // 8px per character with 50px padding
+            const minWidth = Math.max(60, contentLength * 8 > 240 ? 240 : contentLength * 8) + 50; // 8px per character with 50px padding
             const width = minWidth;
             
             return { minWidth, width };
diff --git a/src/views/EncodingShelfCard.tsx b/src/views/EncodingShelfCard.tsx
index bb230df..449b631 100644
--- a/src/views/EncodingShelfCard.tsx
+++ b/src/views/EncodingShelfCard.tsx
@@ -63,7 +63,6 @@ import DeleteIcon from '@mui/icons-material/Delete';
 import CloseIcon from '@mui/icons-material/Close';
 import LightbulbOutlinedIcon from '@mui/icons-material/LightbulbOutlined';
 import TipsAndUpdatesIcon from '@mui/icons-material/TipsAndUpdates';
-import BugReportIcon from '@mui/icons-material/BugReport';
 import { IdeaChip } from './ChartRecBox';
 
 // Property and state of an encoding shelf
@@ -928,7 +927,6 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
                 </span>
             </Tooltip>
         }
-        
     </Box>
 
     // Ideas display section - get ideas for current chart
@@ -1026,18 +1024,6 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
             >
                 Editor
             </Typography>
-            <Box sx={{ flex: 1 }} />
-            <IconButton
-                size="small"
-                onClick={() => setDevMessageOpen(true)}
-                sx={{ 
-                    width: 20,
-                    height: 20,
-                    fontSize: '10px'
-                }}
-            >
-                <BugReportIcon fontSize="inherit" />
-            </IconButton>
         </Box>
     );
 
@@ -1140,14 +1126,13 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
         </Box>);
 
     const encodingShelfCard = (
-        <>
-            <Card variant='outlined' sx={{ 
-                padding: 0, 
-                maxWidth: "400px", 
-                display: 'flex', 
-                flexDirection: 'column', 
-                backgroundColor: trigger ? "rgba(255, 160, 122, 0.07)" : "" 
-            }}>
+        <Card variant='outlined' sx={{ 
+            padding: 0, 
+            maxWidth: "400px", 
+            display: 'flex', 
+            flexDirection: 'column', 
+            backgroundColor: trigger ? "rgba(255, 160, 122, 0.07)" : "" 
+        }}>
             <ModeToggleHeader />
             {ideateMode ? (
                 <Box sx={{ padding: 1 }}>
@@ -1177,65 +1162,6 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
                 </Box>
             )}
         </Card>
-        <Dialog
-            open={devMessageOpen}
-            onClose={() => setDevMessageOpen(false)}
-            maxWidth="sm"
-            fullWidth
-            PaperProps={{
-                sx: {
-                    borderRadius: 2,
-                    boxShadow: theme.shadows[10],
-                }
-            }}
-        >
-            <DialogTitle sx={{ 
-                pb: 1,
-                fontWeight: 600,
-                fontSize: '1.25rem',
-                color: theme.palette.primary.main
-            }}>
-                👋 Hello from the developers!
-            </DialogTitle>
-            <DialogContent>
-                <Typography variant="body1" sx={{ mb: 2 }}>
-                    How did you find this? We're glad you're exploring!
-                    <br />
-                    Drop us a message at{' '}
-                    <Typography
-                        component="a"
-                        href="https://github.com/microsoft/data-formulator"
-                        target="_blank"
-                        rel="noopener noreferrer"
-                        sx={{
-                            fontSize: 'inherit',
-                            color: theme.palette.primary.main,
-                            textDecoration: 'none',
-                            fontWeight: 500,
-                            '&:hover': {
-                                textDecoration: 'underline',
-                            }
-                        }}
-                    >
-                        github.com/microsoft/data-formulator
-                    </Typography>
-                    {' '}if you have any questions or feedback.
-                </Typography>
-            </DialogContent>
-            <DialogActions sx={{ px: 3, pb: 2 }}>
-                <Button 
-                    onClick={() => setDevMessageOpen(false)}
-                    variant="contained"
-                    sx={{
-                        textTransform: 'none',
-                        borderRadius: 1.5,
-                    }}
-                >
-                    Got it!
-                </Button>
-            </DialogActions>
-        </Dialog>
-        </>
     );
 
     return encodingShelfCard;
diff --git a/src/views/ReportView.tsx b/src/views/ReportView.tsx
index 22562c2..a7ac149 100644
--- a/src/views/ReportView.tsx
+++ b/src/views/ReportView.tsx
@@ -368,6 +368,70 @@ export const ReportView: FC = () => {
         }
     }, [currentReportId]);
 
+    // Auto-refresh chart images when underlying table data changes
+    // This enables real-time chart updates in reports when data is streaming
+    const tableRowSignaturesRef = useRef<Map<string, string>>(new Map());
+    
+    useEffect(() => {
+        if (!currentReportId || mode !== 'post') return;
+        
+        const currentReport = allGeneratedReports.find(r => r.id === currentReportId);
+        if (!currentReport) return;
+        
+        // Get all tables referenced by the report's charts
+        const reportChartIds = currentReport.selectedChartIds;
+        const affectedTableIds = new Set<string>();
+        
+        reportChartIds.forEach(chartId => {
+            const chart = charts.find(c => c.id === chartId);
+            if (chart) {
+                affectedTableIds.add(chart.tableRef);
+            }
+        });
+        
+        // Check if any affected tables have changed
+        let hasChanges = false;
+        affectedTableIds.forEach(tableId => {
+            const table = tables.find(t => t.id === tableId);
+            if (table) {
+                // Create a signature for the table data
+                const rowCount = table.rows.length;
+                const firstRows = JSON.stringify(table.rows.slice(0, 3));
+                const lastRows = JSON.stringify(table.rows.slice(-2));
+                const signature = `${rowCount}:${firstRows}:${lastRows}`;
+                
+                const prevSignature = tableRowSignaturesRef.current.get(tableId);
+                if (prevSignature && prevSignature !== signature) {
+                    hasChanges = true;
+                }
+                tableRowSignaturesRef.current.set(tableId, signature);
+            }
+        });
+        
+        // If data changed, regenerate chart images for the report
+        if (hasChanges) {
+            console.log('[ReportView] Table data changed, refreshing chart images...');
+            
+            reportChartIds.forEach(chartId => {
+                const chart = charts.find(c => c.id === chartId);
+                if (!chart) return;
+                
+                const chartTable = tables.find(t => t.id === chart.tableRef);
+                if (!chartTable) return;
+                
+                if (chart.chartType === 'Table' || chart.chartType === '?') {
+                    return;
+                }
+                
+                getChartImageFromVega(chart, chartTable).then(({ blobUrl, width, height }) => {
+                    if (blobUrl) {
+                        updateCachedReportImages(chart.id, blobUrl, width, height);
+                    }
+                });
+            });
+        }
+    }, [tables, currentReportId, mode, allGeneratedReports, charts]);
+
 
     
     // Sort charts based on data thread ordering
diff --git a/src/views/SelectableDataGrid.tsx b/src/views/SelectableDataGrid.tsx
index 5315022..fcf0473 100644
--- a/src/views/SelectableDataGrid.tsx
+++ b/src/views/SelectableDataGrid.tsx
@@ -20,12 +20,18 @@ import { getIconFromType } from './ViewUtils';
 import { IconButton, TableSortLabel, Typography } from '@mui/material';
 
 import _ from 'lodash';
-import { FieldSource } from '../components/ComponentType';
+import { FieldSource, FieldItem } from '../components/ComponentType';
 
 import FileDownloadIcon from '@mui/icons-material/FileDownload';
 import CloudQueueIcon from '@mui/icons-material/CloudQueue';
 import CasinoIcon from '@mui/icons-material/Casino';
+import ArrowUpwardIcon from '@mui/icons-material/ArrowUpward';
+import ArrowDownwardIcon from '@mui/icons-material/ArrowDownward';
+import UnfoldMoreIcon from '@mui/icons-material/UnfoldMore';
 import { getUrls } from '../app/utils';
+import { useDrag } from 'react-dnd';
+import { useSelector } from 'react-redux';
+import { DataFormulatorState } from '../app/dfSlice';
 
 export interface ColumnDef {
     id: string;
@@ -69,6 +75,170 @@ function getComparator<Key extends keyof any>(
         : (a, b) => -descendingComparator(a, b, orderBy);
 }
 
+// Get color for field source hover highlight
+function getColorForFieldSource(source: string | undefined, theme: any): string {
+    if (!source) {
+        return theme.palette.primary.main; // Default to primary for original fields
+    }
+    
+    switch (source) {
+        case "derived":
+            return theme.palette.derived.main; // Yellow/gold for derived fields
+        case "custom":
+            return theme.palette.custom.main; // Orange for custom fields
+        case "original":
+        default:
+            return theme.palette.primary.main; // Blue for original fields
+    }
+}
+
+// Draggable header component
+interface DraggableHeaderProps {
+    columnDef: ColumnDef;
+    orderBy: string | undefined;
+    order: 'asc' | 'desc';
+    onSortClick: () => void;
+    tableId: string;
+}
+
+const DraggableHeader: React.FC<DraggableHeaderProps> = ({ 
+    columnDef, orderBy, order, onSortClick, tableId 
+}) => {
+    const theme = useTheme();
+    const conceptShelfItems = useSelector((state: DataFormulatorState) => state.conceptShelfItems);
+    
+    // Find the corresponding FieldItem for this column
+    // Try to find by name first, then by constructing the ID for original fields
+    const field = conceptShelfItems.find(f => f.name === columnDef.id) || 
+                  conceptShelfItems.find(f => f.id === `original--${tableId}--${columnDef.id}`);
+    
+    // Only make draggable if we have a field
+    // react-dnd has a drag threshold, so clicks will still work for sorting
+    const [{ isDragging }, dragSource, dragPreview] = useDrag(() => ({
+        type: "concept-card",
+        item: field ? { 
+            type: 'concept-card', 
+            fieldID: field.id, 
+            source: "conceptShelf" 
+        } : undefined,
+        canDrag: !!field,
+        collect: (monitor) => ({
+            isDragging: monitor.isDragging(),
+            handlerId: monitor.getHandlerId(),
+        }),
+    }), [field]);
+
+    let backgroundColor = "white";
+    let borderBottomColor = theme.palette.primary.main;
+    if (columnDef.source == "custom") {
+        backgroundColor = alpha(theme.palette.custom.main, 0.05);
+        borderBottomColor = theme.palette.custom.main;
+    } else {
+        backgroundColor = alpha(theme.palette.primary.main, 0.05);
+        borderBottomColor = theme.palette.primary.main;
+    }
+
+    const opacity = isDragging ? 0.3 : 1;
+    const cursorStyle = field ? (isDragging ? "grabbing" : "grab") : "default";
+    
+    // Enhanced background color on hover for draggable headers - based on field source (derived/original)
+    const hoverBackgroundColor = field 
+        ? alpha(getColorForFieldSource(field.source, theme), 0.1)
+        : backgroundColor;
+    
+    // Determine sort icon
+    const getSortIcon = () => {
+        if (orderBy !== columnDef.id) {
+            return <UnfoldMoreIcon sx={{ fontSize: 16 }} />;
+        }
+        return order === 'asc' 
+            ? <ArrowUpwardIcon sx={{ fontSize: 16 }} />
+            : <ArrowDownwardIcon sx={{ fontSize: 16 }} />;
+    };
+
+    return (
+        <Box 
+            className="data-view-header-container" 
+            ref={field ? dragSource : dragPreview}
+            sx={{ 
+                backgroundColor: backgroundColor, 
+                borderBottomColor, 
+                borderBottomWidth: '2px', 
+                borderBottomStyle: 'solid',
+                opacity,
+                cursor: cursorStyle,
+                display: 'flex',
+                alignItems: 'center',
+                position: 'relative',
+                transition: 'background-color 0.2s ease, box-shadow 0.2s ease',
+                // Ensure cursor applies to TableSortLabel and its children, but not IconButton
+                '& .data-view-header-title, & .data-view-header-title *': {
+                    cursor: cursorStyle,
+                },
+                ...(field && {
+                    '&:hover': {
+                        backgroundColor: hoverBackgroundColor,
+                        boxShadow: '0 2px 4px rgba(0,0,0,0.08)',
+                    },
+                }),
+            }}
+        >
+            {/* Main content area - draggable for concepts, using original TableSortLabel structure */}
+            <TableSortLabel
+                className="data-view-header-title"
+                sx={{ 
+                    display: "flex", 
+                    flexDirection: "row", 
+                    flex: 1,
+                    width: 'calc(100% - 24px)',
+                    cursor: cursorStyle, // Inherit cursor from parent
+                    '& .MuiTableSortLabel-icon': {
+                        display: 'none',
+                    },
+                }}
+                active={orderBy === columnDef.id}
+                direction={orderBy === columnDef.id ? order : 'asc'}
+                onClick={(e) => {
+                    // Prevent sort when dragging
+                    if (!isDragging) {
+                        e.stopPropagation();
+                        onSortClick();
+                    }
+                }}
+            >
+                <span role="img" style={{ fontSize: "inherit", padding: "2px", display: "inline-flex", alignItems: "center" }}>
+                    {getIconFromType(columnDef.dataType)}
+                </span>
+                <Typography sx={{fontSize: 12, overflow: 'hidden', textOverflow: 'ellipsis', whiteSpace: 'nowrap'}}>
+                    {columnDef.label}
+                </Typography>
+            </TableSortLabel>
+            {/* Separate sort handler button */}
+            <Tooltip title={<Typography sx={{fontSize: 10}}>Sort by <b>{columnDef.label}</b></Typography>}>
+                <IconButton
+                    size="small"
+                    onClick={(e) => {
+                        e.stopPropagation();
+                        onSortClick();
+                    }}
+                    sx={{
+                        padding: '2px',
+                        marginLeft: '4px',
+                        marginRight: '2px',
+                        opacity: orderBy === columnDef.id ? 1 : 0.5,
+                        '&:hover': {
+                            opacity: 1,
+                            backgroundColor: alpha(theme.palette.action.hover, 0.2),
+                        },
+                    }}
+                >
+                    {getSortIcon()}
+                </IconButton>
+            </Tooltip>
+        </Box>
+    );
+};
+
 export const SelectableDataGrid: React.FC<SelectableDataGridProps> = ({ 
     tableId, rows, tableName, columnDefs, rowCount, virtual }) => {
 
@@ -192,16 +362,6 @@ export const SelectableDataGrid: React.FC<SelectableDataGridProps> = ({
                         return (
                             <TableRow key='header-fixed' style={{ paddingRight: 0, marginRight: '17px', height: '24px'}}>
                                 {columnDefs.map((columnDef, index) => {
-                                    let backgroundColor = "white";
-                                    let borderBottomColor = theme.palette.primary.main;
-                                    if (columnDef.source == "custom") {
-                                        backgroundColor = alpha(theme.palette.custom.main, 0.05);
-                                        borderBottomColor = theme.palette.custom.main;
-                                    } else {
-                                        backgroundColor = "white";
-                                        borderBottomColor = theme.palette.primary.main;
-                                    }
-
                                     return (
                                         <TableCell
                                             className='data-view-header-cell'
@@ -209,43 +369,31 @@ export const SelectableDataGrid: React.FC<SelectableDataGridProps> = ({
                                             align={columnDef.align}
                                             sx={{p: 0, minWidth: columnDef.minWidth, width: columnDef.width,}}
                                         >
-                                            <Tooltip title={`${columnDef.label}`} >
-                                                <Box className="data-view-header-container" 
-                                                     sx={{ backgroundColor, borderBottomColor, borderBottomWidth: '2px', borderBottomStyle: 'solid'}}>
-                                                    <TableSortLabel
-                                                    className="data-view-header-title"
-                                                    sx={{ display: "flex", flexDirection: "row", width: "100%" }}
-                                                    active={orderBy === columnDef.id}
-                                                    direction={orderBy === columnDef.id ? order : 'asc'}
-                                                    onClick={() => {
-                                                        let newOrder: 'asc' | 'desc' = 'asc';
-                                                        let newOrderBy : string | undefined = columnDef.id;
-                                                        if (orderBy === columnDef.id && order === 'asc') {
-                                                            newOrder = 'desc';
-                                                        } else if (orderBy === columnDef.id && order === 'desc') {
-                                                            newOrder = 'asc';
-                                                            newOrderBy = undefined;
-                                                        } else {
-                                                            newOrder = 'asc';
-                                                        }
+                                            <DraggableHeader
+                                                columnDef={columnDef}
+                                                orderBy={orderBy}
+                                                order={order}
+                                                tableId={tableId}
+                                                onSortClick={() => {
+                                                    let newOrder: 'asc' | 'desc' = 'asc';
+                                                    let newOrderBy : string | undefined = columnDef.id;
+                                                    if (orderBy === columnDef.id && order === 'asc') {
+                                                        newOrder = 'desc';
+                                                    } else if (orderBy === columnDef.id && order === 'desc') {
+                                                        newOrder = 'asc';
+                                                        newOrderBy = undefined;
+                                                    } else {
+                                                        newOrder = 'asc';
+                                                    }
 
-                                                        setOrder(newOrder);
-                                                        setOrderBy(newOrderBy);
-                                                        
-                                                        if (virtual) {
-                                                            fetchVirtualData(newOrderBy ? [newOrderBy] : [], newOrder);
-                                                        }
-                                                    }}
-                                                >
-                                                    <span role="img" style={{ fontSize: "inherit", padding: "2px", display: "inline-flex", alignItems: "center" }}>
-                                                        {getIconFromType(columnDef.dataType)}
-                                                    </span>
-                                                    <Typography className="data-view-header-name">
-                                                        {columnDef.label}
-                                                    </Typography>
-                                                </TableSortLabel>
-                                            </Box>
-                                            </Tooltip>
+                                                    setOrder(newOrder);
+                                                    setOrderBy(newOrderBy);
+                                                    
+                                                    if (virtual) {
+                                                        fetchVirtualData(newOrderBy ? [newOrderBy] : [], newOrder);
+                                                    }
+                                                }}
+                                            />
                                         </TableCell>
                                     );
                                 })}
@@ -256,12 +404,12 @@ export const SelectableDataGrid: React.FC<SelectableDataGridProps> = ({
                         return (
                             <>
                                 {columnDefs.map((column, colIndex) => {
-                                    let backgroundColor = "white";
-                                    if (column.source == "custom") {
-                                        backgroundColor = alpha(theme.palette.custom.main, 0.05);
-                                    } else {
-                                        backgroundColor = "rgba(255,255,255,0.05)";
-                                    }
+                                    let backgroundColor = "rgba(255,255,255,0.05)";
+                                    // if (column.source == "custom") {
+                                    //     backgroundColor = alpha(theme.palette.custom.main, 0.03);
+                                    // } else {
+                                    //     backgroundColor = "rgba(255,255,255,0.05)";
+                                    // }
 
                                     return (
                                         <TableCell
diff --git a/src/views/TableSelectionView.tsx b/src/views/TableSelectionView.tsx
index ba3cbba..0d9182a 100644
--- a/src/views/TableSelectionView.tsx
+++ b/src/views/TableSelectionView.tsx
@@ -6,7 +6,8 @@ import { useEffect } from 'react';
 
 import Typography from '@mui/material/Typography';
 import Box from '@mui/material/Box';
-import { Button, Card, Paper } from '@mui/material';
+import { Button, Card, Paper, Chip } from '@mui/material';
+import StreamIcon from '@mui/icons-material/Stream';
 import { CustomReactTable } from './ReactTable';
 import { createTableFromFromObjectArray } from '../data/utils';
 
@@ -21,6 +22,9 @@ export interface DatasetMetadata {
         format: string;
         sample: any[];
     }[];
+    // Live/streaming dataset properties
+    live?: boolean;
+    refreshIntervalSeconds?: number;
 }
 
 export interface DatasetSelectionViewProps {
@@ -101,7 +105,12 @@ export const DatasetSelectionView: React.FC<DatasetSelectionViewProps> = functio
                                 borderColor: 'primary.main',
                             }}
                         >
-                            {title}
+                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 0.5 }}>
+                                {datasets[i]?.live && (
+                                    <StreamIcon sx={{ fontSize: 14, color: 'success.main' }} />
+                                )}
+                                <span>{title}</span>
+                            </Box>
                         </Button>
                     ))}
                 </Box>
@@ -142,18 +151,35 @@ export const DatasetSelectionView: React.FC<DatasetSelectionViewProps> = functio
                             )
                         });
                         
+                        // Format refresh interval for display
+                        const formatRefreshInterval = (seconds: number) => {
+                            if (seconds < 60) return `${seconds}s`;
+                            if (seconds < 3600) return `${Math.floor(seconds / 60)}m`;
+                            return `${Math.floor(seconds / 3600)}h`;
+                        };
+                        
                         return (
                             <Box key={i}>
-                                <Box sx={{mb: 1, gap: 1, maxWidth: 800, display: "flex", alignItems: "center"}}>
-                                    <Typography sx={{fontSize: 12}}>
-                                        {dataset.description} <Typography variant="caption" sx={{color: "primary.light", fontSize: 10, mx: 0.5}}>[from {dataset.source}]</Typography> 
+                                <Box sx={{mb: 1, gap: 1, maxWidth: 800, display: "flex", alignItems: "center", flexWrap: "wrap"}}>
+                                    <Typography sx={{fontSize: 12, flex: 1, minWidth: 200}}>
+                                        {dataset.description} <Typography variant="caption" sx={{color: "primary.light", fontSize: 10, mx: 0.5}}>[from {dataset.source}]</Typography>
                                     </Typography>
+                                    {dataset.live && dataset.refreshIntervalSeconds && (
+                                        <Chip 
+                                            icon={<StreamIcon sx={{ fontSize: 14 }} />}
+                                            label={`Auto-refresh: ${formatRefreshInterval(dataset.refreshIntervalSeconds)}`}
+                                            size="small"
+                                            color="success"
+                                            variant="outlined"
+                                            sx={{ fontSize: 10, height: 22 }}
+                                        />
+                                    )}
                                     <Box sx={{marginLeft: "auto", flexShrink: 0}} >
                                         <Button size="small" variant="contained" 
                                                 onClick={(event: React.MouseEvent<HTMLElement>) => {
                                                     handleSelectDataset(dataset);
                                                 }}>
-                                            load dataset
+                                            {dataset.live ? 'load live data' : 'load dataset'}
                                         </Button>
                                     </Box>
                                 </Box>
diff --git a/src/views/UnifiedDataUploadDialog.tsx b/src/views/UnifiedDataUploadDialog.tsx
index 82be5f0..225fba9 100644
--- a/src/views/UnifiedDataUploadDialog.tsx
+++ b/src/views/UnifiedDataUploadDialog.tsx
@@ -34,16 +34,21 @@ import DeleteIcon from '@mui/icons-material/Delete';
 import ArrowBackIcon from '@mui/icons-material/ArrowBack';
 import Paper from '@mui/material/Paper';
 
+import StreamIcon from '@mui/icons-material/Stream';
 import { useDispatch, useSelector } from 'react-redux';
 import { DataFormulatorState, dfActions, fetchFieldSemanticType } from '../app/dfSlice';
 import { AppDispatch } from '../app/store';
-import { DictTable } from '../components/ComponentType';
+import { DataSourceConfig, DictTable } from '../components/ComponentType';
 import { createTableFromFromObjectArray, createTableFromText, loadTextDataWrapper, loadBinaryDataWrapper } from '../data/utils';
 import { DataLoadingChat } from './DataLoadingChat';
 import { DatasetSelectionView, DatasetMetadata } from './TableSelectionView';
 import { getUrls } from '../app/utils';
 import { CustomReactTable } from './ReactTable';
 import { DBManagerPane } from './DBTableManager';
+import { 
+    FormControlLabel, 
+    Switch
+} from '@mui/material';
 
 export type UploadTabType = 'menu' | 'upload' | 'paste' | 'url' | 'database' | 'extract' | 'explore';
 
@@ -386,16 +391,22 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
     const [showFullContent, setShowFullContent] = useState<boolean>(false);
     const [isOverSizeLimit, setIsOverSizeLimit] = useState<boolean>(false);
     
-    // URL input state (merged into file upload)
-    const [tableURL, setTableURL] = useState<string>("");
-
-    // File preview state (shared with URL)
+    // File preview state
     const [filePreviewTables, setFilePreviewTables] = useState<DictTable[] | null>(null);
     const [filePreviewLoading, setFilePreviewLoading] = useState<boolean>(false);
     const [filePreviewError, setFilePreviewError] = useState<string | null>(null);
     const [filePreviewFiles, setFilePreviewFiles] = useState<File[]>([]);
     const [filePreviewActiveIndex, setFilePreviewActiveIndex] = useState<number>(0);
 
+    // URL tab state (separate from file upload)
+    const [tableURL, setTableURL] = useState<string>("");
+    const [urlAutoRefresh, setUrlAutoRefresh] = useState<boolean>(false);
+    const [urlRefreshInterval, setUrlRefreshInterval] = useState<number>(60); // default 60 seconds
+    const [urlPreviewTables, setUrlPreviewTables] = useState<DictTable[] | null>(null);
+    const [urlPreviewLoading, setUrlPreviewLoading] = useState<boolean>(false);
+    const [urlPreviewError, setUrlPreviewError] = useState<string | null>(null);
+    const [urlPreviewActiveIndex, setUrlPreviewActiveIndex] = useState<number>(0);
+
     // Sample datasets state
     const [datasetPreviews, setDatasetPreviews] = useState<DatasetMetadata[]>([]);
 
@@ -461,7 +472,14 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                 };
                             }
                         })
-                        return { tables: tables, name: info["name"], description: info["description"], source: info["source"] }
+                        return { 
+                            tables: tables, 
+                            name: info["name"], 
+                            description: info["description"], 
+                            source: info["source"],
+                            live: info["live"],
+                            refreshIntervalSeconds: info["refreshIntervalSeconds"]
+                        }
                     }).filter((t: DatasetMetadata | undefined) => t != undefined);
                     setDatasetPreviews(datasets);
                 });
@@ -475,11 +493,18 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         setIsLargeContent(false);
         setIsOverSizeLimit(false);
         setShowFullContent(false);
-        setTableURL("");
         setFilePreviewTables(null);
         setFilePreviewLoading(false);
         setFilePreviewError(null);
         setFilePreviewFiles([]);
+        // Reset URL tab state
+        setTableURL("");
+        setUrlAutoRefresh(false);
+        setUrlRefreshInterval(60);
+        setUrlPreviewTables(null);
+        setUrlPreviewLoading(false);
+        setUrlPreviewError(null);
+        setUrlPreviewActiveIndex(0);
         onClose();
     }, [onClose]);
 
@@ -493,8 +518,6 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
             setFilePreviewError(null);
             setFilePreviewTables(null);
             setFilePreviewLoading(true);
-            // Clear URL input when file is uploaded
-            setTableURL("");
 
             const MAX_FILE_SIZE = 5 * 1024 * 1024;
             const previewTables: DictTable[] = [];
@@ -581,8 +604,10 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         }
         const table = filePreviewTables[filePreviewActiveIndex];
         if (table) {
-            dispatch(dfActions.loadTable(table));
-            dispatch(fetchFieldSemanticType(table));
+            const sourceConfig: DataSourceConfig = { type: 'file', fileName: filePreviewFiles[0]?.name };
+            const tableWithSource = { ...table, source: sourceConfig };
+            dispatch(dfActions.loadTable(tableWithSource));
+            dispatch(fetchFieldSemanticType(tableWithSource));
             handleClose();
         }
     };
@@ -591,9 +616,12 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         if (!filePreviewTables || filePreviewTables.length === 0) {
             return;
         }
-        for (let table of filePreviewTables) {
-            dispatch(dfActions.loadTable(table));
-            dispatch(fetchFieldSemanticType(table));
+        for (let i = 0; i < filePreviewTables.length; i++) {
+            const table = filePreviewTables[i];
+            const sourceConfig: DataSourceConfig = { type: 'file', fileName: filePreviewFiles[i]?.name || filePreviewFiles[0]?.name };
+            const tableWithSource = { ...table, source: sourceConfig };
+            dispatch(dfActions.loadTable(tableWithSource));
+            dispatch(fetchFieldSemanticType(tableWithSource));
         }
         handleClose();
     };
@@ -661,26 +689,37 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
             table = createTableFromText(uniqueName, pasteContent);
         }
         if (table) {
-            dispatch(dfActions.loadTable(table));
-            dispatch(fetchFieldSemanticType(table));
+            // Add source info for paste data
+            const tableWithSource = { ...table, source: { type: 'paste' as const } };
+            dispatch(dfActions.loadTable(tableWithSource));
+            dispatch(fetchFieldSemanticType(tableWithSource));
             handleClose();
         }
     };
 
 
     const handleURLPreview = (): void => {
-        setFilePreviewLoading(true);
-        setFilePreviewError(null);
-        setFilePreviewTables(null);
-        // Clear file preview when URL is loaded
-        setFilePreviewFiles([]);
+        setUrlPreviewLoading(true);
+        setUrlPreviewError(null);
+        setUrlPreviewTables(null);
+
+        // Support relative URLs by constructing full URL
+        let fullUrl = tableURL;
+        if (tableURL.startsWith('/')) {
+            fullUrl = window.location.origin + tableURL;
+        }
 
         let parts = tableURL.split('/');
-        const baseName = parts[parts.length - 1] || 'dataset';
-        const tableName = getUniqueTableName(baseName, existingNames);
+        const baseName = parts[parts.length - 1]?.split('?')[0] || 'dataset';
+        const tableName = getUniqueTableName(baseName.replace(/\.[^.]+$/, ''), existingNames);
 
-        fetch(tableURL)
-            .then(res => res.text())
+        fetch(fullUrl)
+            .then(res => {
+                if (!res.ok) {
+                    throw new Error(`HTTP ${res.status}: ${res.statusText}`);
+                }
+                return res.text();
+            })
             .then(content => {
                 let table: undefined | DictTable = undefined;
                 try {
@@ -694,22 +733,86 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                 }
 
                 if (table) {
-                    setFilePreviewTables([table]);
+                    setUrlPreviewTables([table]);
                 } else {
-                    setFilePreviewError('Unable to parse data from the provided URL.');
+                    setUrlPreviewError('Unable to parse data from the provided URL.');
                 }
             })
-            .catch(() => {
-                setFilePreviewError('Failed to fetch data from the URL.');
+            .catch((err) => {
+                setUrlPreviewError(`Failed to fetch data: ${err.message}`);
             })
             .finally(() => {
-                setFilePreviewLoading(false);
+                setUrlPreviewLoading(false);
             });
     };
 
-    const hasValidUrlSuffix = tableURL.endsWith('.csv') || tableURL.endsWith('.tsv') || tableURL.endsWith(".json");
+    // URL tab load handlers
+    const handleURLLoadSingleTable = (): void => {
+        if (!urlPreviewTables || urlPreviewTables.length === 0) {
+            return;
+        }
+        const table = urlPreviewTables[urlPreviewActiveIndex];
+        if (table) {
+            let sourceConfig: DataSourceConfig;
+            if (urlAutoRefresh) {
+                sourceConfig = { 
+                    type: 'stream', 
+                    url: tableURL,
+                    autoRefresh: true,
+                    refreshIntervalSeconds: urlRefreshInterval,
+                    lastRefreshed: Date.now()
+                };
+            } else {
+                sourceConfig = { type: 'url', url: tableURL };
+            }
+            const tableWithSource = { ...table, source: sourceConfig };
+            dispatch(dfActions.loadTable(tableWithSource));
+            dispatch(fetchFieldSemanticType(tableWithSource));
+            handleClose();
+        }
+    };
+
+    const handleURLLoadAllTables = (): void => {
+        if (!urlPreviewTables || urlPreviewTables.length === 0) {
+            return;
+        }
+        for (let i = 0; i < urlPreviewTables.length; i++) {
+            const table = urlPreviewTables[i];
+            let sourceConfig: DataSourceConfig;
+            if (urlAutoRefresh) {
+                sourceConfig = { 
+                    type: 'stream', 
+                    url: tableURL,
+                    autoRefresh: true,
+                    refreshIntervalSeconds: urlRefreshInterval,
+                    lastRefreshed: Date.now()
+                };
+            } else {
+                sourceConfig = { type: 'url', url: tableURL };
+            }
+            const tableWithSource = { ...table, source: sourceConfig };
+            dispatch(dfActions.loadTable(tableWithSource));
+            dispatch(fetchFieldSemanticType(tableWithSource));
+        }
+        handleClose();
+    };
+
+    const handleRemoveUrlPreviewTable = (index: number): void => {
+        setUrlPreviewTables((prev) => {
+            if (!prev) return prev;
+            const next = prev.filter((_, i) => i !== index);
+            return next.length > 0 ? next : null;
+        });
+    };
+
+    // URL validation - allow common data file extensions and API endpoints
+    const hasValidUrl = tableURL.trim() !== '' && (
+        tableURL.startsWith('http://') || tableURL.startsWith('https://') || tableURL.startsWith('/')
+    );
     const hasMultipleFileTables = (filePreviewTables?.length || 0) > 1;
+    const hasMultipleUrlTables = (urlPreviewTables?.length || 0) > 1;
     const showFilePreview = filePreviewLoading || !!filePreviewError || (filePreviewTables && filePreviewTables.length > 0);
+    const showUrlPreview = urlPreviewLoading || !!urlPreviewError || (urlPreviewTables && urlPreviewTables.length > 0);
     const hasPasteContent = pasteContent.trim() !== '';
 
     // Data source configurations for the menu
@@ -725,11 +828,19 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         { 
             value: 'upload' as UploadTabType, 
             title: 'Upload File', 
-            description: 'Structured data (CSV, TSV, JSON, Excel) from files or URLs',
+            description: 'Upload local files (CSV, TSV, JSON, Excel)',
             icon: <UploadFileIcon />, 
             disabled: false,
             disabledReason: undefined
         },
+        { 
+            value: 'url' as UploadTabType, 
+            title: 'Load from URL', 
+            description: 'Load data from a URL with optional auto-refresh',
+            icon: <LinkIcon />, 
+            disabled: false,
+            disabledReason: undefined
+        },
         { 
             value: 'paste' as UploadTabType, 
             title: 'Paste Data', 
@@ -748,6 +859,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         },
     ];
 
+
     const databaseDataSources = [
         { 
             value: 'database' as UploadTabType, 
@@ -930,96 +1042,47 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                             inputRef={fileInputRef}
                             onChange={handleFileUpload}
                         />
-                        {serverConfig.DISABLE_FILE_UPLOAD ? (
-                            <Box sx={{ textAlign: 'center', py: 4 }}>
+                        
+                        {/* File Upload Section - only show drop zone when file upload is enabled */}
+                        {!serverConfig.DISABLE_FILE_UPLOAD ? (
+                            <Box
+                                sx={{
+                                    border: '2px dashed',
+                                    borderColor: 'divider',
+                                    borderRadius: 2,
+                                    p: showFilePreview ? 2 : 3,
+                                    textAlign: 'center',
+                                    cursor: 'pointer',
+                                    transition: 'all 0.2s',
+                                    '&:hover': {
+                                        borderColor: 'primary.main',
+                                        backgroundColor: alpha(theme.palette.primary.main, 0.04),
+                                    }
+                                }}
+                                onClick={() => fileInputRef.current?.click()}
+                            >
+                                <UploadFileIcon sx={{ fontSize: showFilePreview ? 28 : 36, color: 'text.secondary', mb: 1 }} />
+                                <Typography variant={showFilePreview ? "body2" : "subtitle1"} gutterBottom>
+                                    Drag & drop file here
+                                </Typography>
+                                <Typography variant="body2" color="text.secondary" sx={{ fontSize: showFilePreview ? '0.75rem' : '0.875rem' }}>
+                                    or <Link component="button" sx={{ textDecoration: 'underline', cursor: 'pointer' }}>Browse</Link>
+                                </Typography>
+                                {!showFilePreview && (
+                                    <Typography variant="caption" color="text.secondary" sx={{ mt: 1, display: 'block' }}>
+                                        Supported: CSV, TSV, JSON, Excel (xlsx, xls)
+                                    </Typography>
+                                )}
+                            </Box>
+                        ) : (
+                            <Box sx={{ textAlign: 'center', py: 4, px: 2 }}>
                                 <Typography color="text.secondary" sx={{ mb: 2 }}>
                                     File upload is disabled in this environment.
                                 </Typography>
                                 <Typography variant="body2" color="text.secondary">
-                                    Install Data Formulator locally to enable file upload. <br />
-                                    <Link 
-                                        href="https://github.com/microsoft/data-formulator" 
-                                        target="_blank" 
-                                        rel="noopener noreferrer"
-                                    >
-                                        https://github.com/microsoft/data-formulator
-                                    </Link>
+                                    Use "Load from URL" to load data from a remote source.
                                 </Typography>
                             </Box>
-                        ) : (
-                            <Box sx={{ 
-                                display: 'flex', 
-                                flexDirection: 'column',
-                                gap: 2,
-                                alignItems: 'stretch',
-                            }}>
-                                <Box
-                                    sx={{
-                                        border: '2px dashed',
-                                        borderColor: 'divider',
-                                        borderRadius: 2,
-                                        p: showFilePreview ? 2 : 3,
-                                        textAlign: 'center',
-                                        cursor: 'pointer',
-                                        transition: 'all 0.2s',
-                                        flex: '1',
-                                        minWidth: showFilePreview ? 0 : 'auto',
-                                        '&:hover': {
-                                            borderColor: 'primary.main',
-                                            backgroundColor: alpha(theme.palette.primary.main, 0.04),
-                                        }
-                                    }}
-                                    onClick={() => fileInputRef.current?.click()}
-                                >
-                                    <UploadFileIcon sx={{ fontSize: showFilePreview ? 28 : 36, color: 'text.secondary', mb: 1 }} />
-                                    <Typography variant={showFilePreview ? "body2" : "subtitle1"} gutterBottom>
-                                        Drag & drop file here
-                                    </Typography>
-                                    <Typography variant="body2" color="text.secondary" sx={{ fontSize: showFilePreview ? '0.75rem' : '0.875rem' }}>
-                                        or <Link component="button" sx={{ textDecoration: 'underline', cursor: 'pointer' }}>Browse</Link>
-                                    </Typography>
-                                    {!showFilePreview && (
-                                        <Typography variant="caption" color="text.secondary" sx={{ mt: 1, display: 'block' }}>
-                                            Supported: CSV, TSV, JSON, Excel (xlsx, xls)
-                                        </Typography>
-                                    )}
-                                </Box>
-
-                                {/* URL Input Section */}
-                                <Box sx={{ 
-                                    display: 'flex', 
-                                    alignItems: 'center', 
-                                    gap: 1,
-                                    flex: '0 0 auto',
-                                }}>
-                                    <TextField
-                                        fullWidth
-                                        placeholder="Load a CSV, TSV, or JSON file from a URL, e.g. https://example.com/data.json"
-                                        value={tableURL}
-                                        onChange={(e) => setTableURL(e.target.value.trim())}
-                                        error={tableURL !== "" && !hasValidUrlSuffix}
-                                        size="small"
-                                        sx={{ 
-                                            flex: 1,
-                                            '& .MuiInputBase-input': {
-                                                fontSize: '0.75rem',
-                                            },
-                                            '& .MuiInputBase-input::placeholder': {
-                                                fontSize: '0.75rem',
-                                            },
-                                        }}
-                                    />
-                                    <Button
-                                        variant="outlined"
-                                        size="small"
-                                        onClick={handleURLPreview}
-                                        disabled={!hasValidUrlSuffix || filePreviewLoading}
-                                        sx={{ textTransform: 'none', whiteSpace: 'nowrap' }}
-                                    >
-                                        Preview
-                                    </Button>
-                                </Box>
-                            </Box>
                         )}
                         </Box>
 
@@ -1030,7 +1093,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                     loading={filePreviewLoading}
                                     error={filePreviewError}
                                     tables={filePreviewTables}
-                                    emptyLabel={serverConfig.DISABLE_FILE_UPLOAD ? 'File upload is disabled.' : 'Select a file to preview.'}
+                                    emptyLabel="Select a file to preview."
                                     meta={filePreviewTables && filePreviewTables.length > 0 ? `${filePreviewTables.length} table${filePreviewTables.length > 1 ? 's' : ''} previewed${hasMultipleFileTables ? ' • Multiple sheets detected' : ''}` : undefined}
                                     onRemoveTable={handleRemoveFilePreviewTable}
                                     activeIndex={filePreviewActiveIndex}
@@ -1040,12 +1103,12 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                         )}
 
                         {filePreviewTables && filePreviewTables.length > 0 && (
-                            <Box sx={{ display: 'flex', justifyContent: 'flex-end', gap: 1 }}>
+                            <Box sx={{ display: 'flex', justifyContent: 'flex-end', gap: 1, alignItems: 'center' }}>
                                 <Button
                                     variant="outlined"
                                     size="small"
                                     onClick={handleFileLoadSingleTable}
-                                    disabled={serverConfig.DISABLE_FILE_UPLOAD || filePreviewLoading}
+                                    disabled={filePreviewLoading}
                                     sx={{ textTransform: 'none' }}
                                 >
                                     Load Table
@@ -1055,7 +1118,189 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                         variant="contained"
                                         size="small"
                                         onClick={handleFileLoadAllTables}
-                                        disabled={serverConfig.DISABLE_FILE_UPLOAD || filePreviewLoading}
+                                        disabled={filePreviewLoading}
+                                        sx={{ textTransform: 'none' }}
+                                    >
+                                        Load All Tables
+                                    </Button>
+                                )}
+                            </Box>
+                        )}
+                    </Box>
+                </TabPanel>
+
+                {/* URL Tab */}
+                <TabPanel value={activeTab} index="url">
+                    <Box sx={{
+                        display: 'flex',
+                        flexDirection: 'column',
+                        height: '100%',
+                        boxSizing: 'border-box',
+                        gap: 2,
+                        p: 2,
+                        justifyContent: showUrlPreview ? 'flex-start' : 'center',
+                    }}>
+                        <Box sx={{ width: '100%', maxWidth: showUrlPreview ? '80%' : 760, alignSelf: 'center', display: 'flex', flexDirection: 'column', gap: 2 }}>
+                            {/* URL Input */}
+                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1 }}>
+                                <TextField
+                                    fullWidth
+                                    placeholder="Enter URL: https://example.com/data.json or /api/data"
+                                    value={tableURL}
+                                    onChange={(e) => setTableURL(e.target.value.trim())}
+                                    error={tableURL !== "" && !hasValidUrl}
+                                    helperText={tableURL !== "" && !hasValidUrl ? "Enter a valid URL starting with http://, https://, or /" : undefined}
+                                    size="small"
+                                    sx={{ 
+                                        flex: 1,
+                                        '& .MuiInputBase-input': {
+                                            fontSize: '0.875rem',
+                                        },
+                                        '& .MuiInputBase-input::placeholder': {
+                                            fontSize: '0.875rem',
+                                        },
+                                    }}
+                                />
+                                <Button
+                                    variant="outlined"
+                                    size="small"
+                                    onClick={handleURLPreview}
+                                    disabled={!hasValidUrl || urlPreviewLoading}
+                                    sx={{ textTransform: 'none', whiteSpace: 'nowrap' }}
+                                >
+                                    Preview
+                                </Button>
+                            </Box>
+
+                            {/* Example APIs */}
+                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, flexWrap: 'wrap' }}>
+                                <Typography variant="caption" color="text.secondary" sx={{ mr: 0.5 }}>
+                                    Try examples:
+                                </Typography>
+                                {[
+                                    { label: 'USGS Earthquakes', url: '/api/demo-stream/earthquakes?timeframe=day&min_magnitude=2.5', description: 'Recent earthquakes worldwide' },
+                                    { label: 'US Weather', url: '/api/demo-stream/weather', description: 'Current weather for major US cities' },
+                                    { label: 'Stock Prices (yahoo finance)', url: '/api/demo-stream/yfinance?symbols=AAPL,MSFT,GOOGL,NVDA', description: 'Stock prices with historical + intraday data' },
+                                ].map((example) => (
+                                    <Chip
+                                        key={example.label}
+                                        label={example.label}
+                                        size="small"
+                                        variant="outlined"
+                                        onClick={() => setTableURL(example.url)}
+                                        title={example.description}
+                                        sx={{ 
+                                            cursor: 'pointer',
+                                            fontSize: '0.75rem',
+                                            height: 24,
+                                            '&:hover': {
+                                                backgroundColor: alpha(theme.palette.primary.main, 0.08),
+                                                borderColor: 'primary.main',
+                                            }
+                                        }}
+                                    />
+                                ))}
+                            </Box>
+                            
+                            {/* Watch/Auto-refresh options - always visible */}
+                            <Paper variant="outlined" sx={{ p: 2, borderRadius: 1 }}>
+                                <Box sx={{ display: 'flex', flexDirection: 'column', gap: 1.5 }}>
+                                    <FormControlLabel
+                                        control={
+                                            <Switch
+                                                checked={urlAutoRefresh}
+                                                onChange={(e) => setUrlAutoRefresh(e.target.checked)}
+                                                size="small"
+                                            />
+                                        }
+                                        label={
+                                            <Box sx={{ height: 24, display: 'flex', flexDirection: 'row', gap: 1, alignItems: 'center' }}>
+                                                <Typography component="span" variant="body2" sx={{ fontWeight: 500 }}>
+                                                    Watch Mode:
+                                                </Typography>
+                                                
+                                                {urlAutoRefresh ? (
+                                                    <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, }}>
+                                                        <Typography variant="body2" color="text.secondary" sx={{ fontSize: '0.8rem' }}>
+                                                            refresh interval
+                                                        </Typography>
+                                                        {[
+                                                            { seconds: 5, label: '5s' },
+                                                            { seconds: 15, label: '15s' },
+                                                            { seconds: 30, label: '30s' },
+                                                            { seconds: 60, label: '1m' },
+                                                            { seconds: 300, label: '5m' },
+                                                            { seconds: 600, label: '10m' },
+                                                            { seconds: 1800, label: '30m' },
+                                                            { seconds: 3600, label: '1h' },
+                                                        ].map((opt) => (
+                                                            <Chip
+                                                                key={opt.seconds}
+                                                                label={opt.label}
+                                                                size="small"
+                                                                variant={urlRefreshInterval === opt.seconds ? 'filled' : 'outlined'}
+                                                                color={urlRefreshInterval === opt.seconds ? 'primary' : 'default'}
+                                                                onClick={() => setUrlRefreshInterval(opt.seconds)}
+                                                                sx={{ 
+                                                                    cursor: 'pointer', 
+                                                                    fontSize: '0.7rem',
+                                                                    height: 24,
+                                                                }}
+                                                            />
+                                                        ))}
+                                                    </Box>
+                                                ) : <Typography sx={{ ml: 'auto' }} component="span" variant="caption" color="text.secondary">
+                                                    automatically check and refresh data from the URL at regular intervals
+                                                </Typography>}
+                                            </Box>
+                                        }
+                                        sx={{ alignItems: 'flex-start', ml: 0 }}
+                                    />
+                                    
+                                    
+                                </Box>
+                            </Paper>
+                        </Box>
+
+                        {showUrlPreview && (
+                            <Box sx={{ width: '90%', alignSelf: 'center' }}>
+                                <PreviewPanel
+                                    title="Preview"
+                                    loading={urlPreviewLoading}
+                                    error={urlPreviewError}
+                                    tables={urlPreviewTables}
+                                    emptyLabel="Enter a URL and click Preview to see data."
+                                    meta={urlPreviewTables && urlPreviewTables.length > 0 ? `${urlPreviewTables.length} table${urlPreviewTables.length > 1 ? 's' : ''} previewed` : undefined}
+                                    onRemoveTable={handleRemoveUrlPreviewTable}
+                                    activeIndex={urlPreviewActiveIndex}
+                                    onActiveIndexChange={setUrlPreviewActiveIndex}
+                                />
+                            </Box>
+                        )}
+
+                        {urlPreviewTables && urlPreviewTables.length > 0 && (
+                            <Box sx={{ display: 'flex', justifyContent: 'flex-end', gap: 1, alignItems: 'center' }}>
+                                {urlAutoRefresh && (
+                                    <Typography variant="caption" color="success.main" sx={{ mr: 1 }}>
+                                        <StreamIcon sx={{ fontSize: 14, verticalAlign: 'middle', mr: 0.5 }} />
+                                        Watch mode: {urlRefreshInterval < 60 ? `${urlRefreshInterval}s` : `${Math.floor(urlRefreshInterval / 60)}m`}
+                                    </Typography>
+                                )}
+                                <Button
+                                    variant="outlined"
+                                    size="small"
+                                    onClick={handleURLLoadSingleTable}
+                                    disabled={urlPreviewLoading}
+                                    sx={{ textTransform: 'none' }}
+                                >
+                                    Load Table
+                                </Button>
+                                {hasMultipleUrlTables && (
+                                    <Button
+                                        variant="contained"
+                                        size="small"
+                                        onClick={handleURLLoadAllTables}
+                                        disabled={urlPreviewLoading}
                                         sx={{ textTransform: 'none' }}
                                     >
                                         Load All Tables
@@ -1191,11 +1436,20 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                         datasets={datasetPreviews} 
                         hideRowNum
                         handleSelectDataset={(dataset) => {
-                            for (let table of dataset.tables) { 
-                                fetch(table.url)
+                            // Check if this is a live dataset
+                            const isLiveDataset = dataset.live === true;
+                            
+                            for (let table of dataset.tables) {
+                                // For live datasets with relative URLs, construct full URL
+                                let fullUrl = table.url;
+                                if (table.url.startsWith('/')) {
+                                    fullUrl = window.location.origin + table.url;
+                                }
+                                
+                                fetch(fullUrl)
                                     .then(res => res.text())
                                     .then(textData => {
-                                        let tableName = table.url.split("/").pop()?.split(".")[0] || 'table-' + Date.now().toString().substring(0, 8);
+                                        let tableName = table.url.split("/").pop()?.split(".")[0]?.split("?")[0] || 'table-' + Date.now().toString().substring(0, 8);
                                         let dictTable;
                                         if (table.format == "csv") {
                                             dictTable = createTableFromText(tableName, textData);
@@ -1203,6 +1457,19 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                             dictTable = createTableFromFromObjectArray(tableName, JSON.parse(textData), true);
                                         } 
                                         if (dictTable) {
+                                            // For live datasets, set up as stream source with auto-refresh
+                                            if (isLiveDataset) {
+                                                dictTable.source = { 
+                                                    type: 'stream', 
+                                                    url: fullUrl,
+                                                    autoRefresh: true,
+                                                    refreshIntervalSeconds: dataset.refreshIntervalSeconds || 60,
+                                                    lastRefreshed: Date.now()
+                                                };
+                                            } else {
+                                                // Regular example data
+                                                dictTable.source = { type: 'example', url: table.url };
+                                            }
                                             dispatch(dfActions.loadTable(dictTable));
                                             dispatch(fetchFieldSemanticType(dictTable));
                                         }
@@ -1213,6 +1480,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                         />
                     </Box>
                 </TabPanel>
+
             </DialogContent>
         </Dialog>
     );

From fa6bc225343852802df03a340e5cd83ce2d9ff86 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Sun, 25 Jan 2026 17:59:24 -0800
Subject: [PATCH 13/21] live data support

---
 py-src/data_formulator/demo_stream_routes.py  | 1168 +++++++++++------
 .../example_datasets_config.py                |   88 --
 src/app/dfSlice.tsx                           |   64 +
 src/app/utils.tsx                             |   12 +-
 src/assets/chart-icon-world-map-min.png       |  Bin 0 -> 4621 bytes
 src/components/ChartTemplates.tsx             |   49 +-
 src/views/DBTableManager.tsx                  |  256 ++--
 src/views/DataFormulator.tsx                  |   38 +-
 src/views/DataThread.tsx                      |  133 +-
 src/views/EncodingShelfThread.tsx             |   15 +-
 src/views/MultiTablePreview.tsx               |  226 ++++
 src/views/TableSelectionView.tsx              |  126 +-
 src/views/UnifiedDataUploadDialog.tsx         | 1020 +++++++-------
 src/views/VisualizationView.tsx               |    3 +-
 14 files changed, 1867 insertions(+), 1331 deletions(-)
 create mode 100644 src/assets/chart-icon-world-map-min.png
 create mode 100644 src/views/MultiTablePreview.tsx

diff --git a/py-src/data_formulator/demo_stream_routes.py b/py-src/data_formulator/demo_stream_routes.py
index e8b5829..6e528f4 100644
--- a/py-src/data_formulator/demo_stream_routes.py
+++ b/py-src/data_formulator/demo_stream_routes.py
@@ -143,8 +143,8 @@ def get_iss():
     """
     global _iss_last_fetch
     
-    minutes = min(60, max(1, int(request.args.get('minutes', 30))))
-    limit = min(500, max(10, int(request.args.get('limit', 100))))
+    minutes = min(90, max(1, int(request.args.get('minutes', 30))))
+    limit = min(500, max(10, int(request.args.get('limit', 500))))
     
     now = datetime.utcnow()
     cutoff = now - timedelta(minutes=minutes)
@@ -182,32 +182,6 @@ def get_iss():
     
     return make_csv_response(rows)
 
-
-@demo_stream_bp.route('/iss/current', methods=['GET'])
-@limiter.limit(ISS_RATE_LIMIT)
-def get_iss_current():
-    """
-    Current ISS position only (single row).
-    Use /iss for trajectory tracking over time.
-    Recommended refresh: 5 seconds
-    """
-    try:
-        response = requests.get("http://api.open-notify.org/iss-now.json", timeout=10)
-        response.raise_for_status()
-        data = response.json()
-        
-        position = data.get("iss_position", {})
-        rows = [{
-            "timestamp": datetime.utcfromtimestamp(data.get("timestamp", 0)).isoformat() + "Z",
-            "latitude": float(position.get("latitude", 0)),
-            "longitude": float(position.get("longitude", 0)),
-            "fetched_at": datetime.utcnow().isoformat() + "Z"
-        }]
-        return make_csv_response(rows)
-    except Exception as e:
-        return Response(f"error,{str(e)}", mimetype='text/csv'), 500
-
-
 # ============================================================================
 # USGS Earthquakes - Accumulating dataset of seismic events
 # Data naturally grows over time as new earthquakes occur
@@ -353,14 +327,26 @@ def get_earthquakes():
 # ============================================================================
 
 WEATHER_CITIES = [
-    {"name": "Seattle", "lat": 47.6062, "lon": -122.3321},
-    {"name": "New York", "lat": 40.7128, "lon": -74.0060},
-    {"name": "Los Angeles", "lat": 34.0522, "lon": -118.2437},
-    {"name": "Chicago", "lat": 41.8781, "lon": -87.6298},
-    {"name": "Miami", "lat": 25.7617, "lon": -80.1918},
-    {"name": "Denver", "lat": 39.7392, "lon": -104.9903},
-    {"name": "Boston", "lat": 42.3601, "lon": -71.0589},
-    {"name": "Phoenix", "lat": 33.4484, "lon": -112.0740},
+    {"name": "Seattle", "lat": 47.6062, "lon": -122.3321, "state": "WA"},
+    {"name": "New York", "lat": 40.7128, "lon": -74.0060, "state": "NY"},
+    {"name": "Los Angeles", "lat": 34.0522, "lon": -118.2437, "state": "CA"},
+    {"name": "Chicago", "lat": 41.8781, "lon": -87.6298, "state": "IL"},
+    {"name": "Miami", "lat": 25.7617, "lon": -80.1918, "state": "FL"},
+    {"name": "Denver", "lat": 39.7392, "lon": -104.9903, "state": "CO"},
+    {"name": "Boston", "lat": 42.3601, "lon": -71.0589, "state": "MA"},
+    {"name": "Phoenix", "lat": 33.4484, "lon": -112.0740, "state": "AZ"},
+    {"name": "Atlanta", "lat": 33.7490, "lon": -84.3880, "state": "GA"},
+    {"name": "Dallas", "lat": 32.7767, "lon": -96.7970, "state": "TX"},
+    {"name": "Houston", "lat": 29.7604, "lon": -95.3698, "state": "TX"},
+    {"name": "Portland", "lat": 45.5152, "lon": -122.6784, "state": "OR"},
+    {"name": "San Francisco", "lat": 37.7749, "lon": -122.4194, "state": "CA"},
+    {"name": "Las Vegas", "lat": 36.1699, "lon": -115.1398, "state": "NV"},
+    {"name": "Minneapolis", "lat": 44.9778, "lon": -93.2650, "state": "MN"},
+    {"name": "Detroit", "lat": 42.3314, "lon": -83.0458, "state": "MI"},
+    {"name": "Philadelphia", "lat": 39.9526, "lon": -75.1652, "state": "PA"},
+    {"name": "Washington", "lat": 38.9072, "lon": -77.0369, "state": "DC"},
+    {"name": "Nashville", "lat": 36.1627, "lon": -86.7816, "state": "TN"},
+    {"name": "New Orleans", "lat": 29.9511, "lon": -90.0715, "state": "LA"},
 ]
 
 @demo_stream_bp.route('/weather', methods=['GET'])
@@ -368,17 +354,63 @@ def get_earthquakes():
 def get_weather():
     """
     Current weather for major US cities. Updates every 15 minutes.
+    
+    Query params:
+        - cities: Comma-separated list of city names (default: all cities)
+                  Example: cities=Seattle,New York,Los Angeles
+        - fields: Comma-separated list of fields to include (default: all)
+                  Available: temperature,humidity,wind,precipitation,pressure,cloud_cover
+    
     Recommended refresh: 300 seconds
     """
     fetched_at = datetime.utcnow().isoformat() + "Z"
     rows = []
     
-    for city in WEATHER_CITIES:
+    # Parse city filter
+    cities_param = request.args.get('cities', '').strip()
+    if cities_param:
+        city_names = [c.strip() for c in cities_param.split(',')]
+        cities_to_fetch = [c for c in WEATHER_CITIES if c["name"] in city_names]
+        if not cities_to_fetch:
+            # If no matches, use all cities
+            cities_to_fetch = WEATHER_CITIES
+    else:
+        cities_to_fetch = WEATHER_CITIES
+    
+    # Parse fields filter
+    fields_param = request.args.get('fields', '').strip()
+    include_all = not fields_param
+    include_temp = include_all or 'temperature' in fields_param
+    include_humidity = include_all or 'humidity' in fields_param
+    include_wind = include_all or 'wind' in fields_param
+    include_precip = include_all or 'precipitation' in fields_param
+    include_pressure = include_all or 'pressure' in fields_param
+    include_cloud = include_all or 'cloud_cover' in fields_param
+    
+    for city in cities_to_fetch:
         try:
+            # Build current weather parameters
+            current_fields = []
+            if include_temp:
+                current_fields.append("temperature_2m")
+            if include_humidity:
+                current_fields.append("relative_humidity_2m")
+            if include_wind:
+                current_fields.extend(["wind_speed_10m", "wind_direction_10m"])
+            if include_precip:
+                current_fields.append("precipitation")
+            if include_pressure:
+                current_fields.append("surface_pressure")
+            if include_cloud:
+                current_fields.append("cloud_cover")
+            
+            if not current_fields:
+                current_fields = ["temperature_2m", "relative_humidity_2m", "wind_speed_10m", "precipitation"]
+            
             params = {
                 "latitude": city["lat"],
                 "longitude": city["lon"],
-                "current": "temperature_2m,relative_humidity_2m,wind_speed_10m,precipitation",
+                "current": ",".join(current_fields),
                 "timezone": "auto"
             }
             response = requests.get("https://api.open-meteo.com/v1/forecast", params=params, timeout=10)
@@ -386,16 +418,29 @@ def get_weather():
             data = response.json()
             current = data.get("current", {})
             
-            rows.append({
+            row = {
                 "city": city["name"],
+                "state": city.get("state", ""),
                 "latitude": city["lat"],
                 "longitude": city["lon"],
-                "temperature_c": current.get("temperature_2m"),
-                "humidity_percent": current.get("relative_humidity_2m"),
-                "wind_speed_kmh": current.get("wind_speed_10m"),
-                "precipitation_mm": current.get("precipitation"),
                 "fetched_at": fetched_at
-            })
+            }
+            
+            if include_temp:
+                row["temperature_c"] = current.get("temperature_2m")
+            if include_humidity:
+                row["humidity_percent"] = current.get("relative_humidity_2m")
+            if include_wind:
+                row["wind_speed_kmh"] = current.get("wind_speed_10m")
+                row["wind_direction_deg"] = current.get("wind_direction_10m")
+            if include_precip:
+                row["precipitation_mm"] = current.get("precipitation")
+            if include_pressure:
+                row["pressure_hpa"] = current.get("surface_pressure")
+            if include_cloud:
+                row["cloud_cover_percent"] = current.get("cloud_cover")
+            
+            rows.append(row)
         except Exception as e:
             logger.warning(f"Failed to fetch weather for {city['name']}: {e}")
     
@@ -411,340 +456,544 @@ def get_weather():
 @limiter.limit(WEATHER_RATE_LIMIT)
 def get_weather_history():
     """
-    Hourly weather history for a location. Dataset grows with each hour.
+    Hourly weather history for one or more locations. Dataset grows with each hour.
     
     Query params:
         - city: City name (default: Seattle) - one of the WEATHER_CITIES
-        - days: Number of past days to include (default: 7, max: 14)
+                  Can also be comma-separated list: city=Seattle,New York,Los Angeles
+        - cities: Alternative parameter name for comma-separated list of city names
+        - days: Number of past days to include (default: 7, max: 92 for archive, 14 for forecast)
+        - use_archive: 'true' to use historical archive API (for data older than 5 days, default: 'auto')
     
     Use case:
         - Track temperature/weather trends over the past week
         - Each hour, a new row appears in the dataset
         - Great for visualizing weather patterns
+        - Use days=30 with use_archive=true for month-long analysis
+        - Compare weather history across multiple cities
     
     Recommended refresh: 3600 seconds (hourly)
     """
-    city_name = request.args.get('city', 'Seattle')
-    days = min(14, max(1, int(request.args.get('days', 7))))
+    # Support both 'city' and 'cities' parameters for backward compatibility
+    city_param = request.args.get('city', '').strip()
+    cities_param = request.args.get('cities', '').strip()
     
-    # Find city coordinates
-    city = next((c for c in WEATHER_CITIES if c["name"].lower() == city_name.lower()), WEATHER_CITIES[0])
+    # Use cities if provided, otherwise fall back to city
+    cities_input = cities_param if cities_param else city_param
+    
+    days = min(92, max(1, int(request.args.get('days', 7))))
+    use_archive_param = request.args.get('use_archive', 'auto').lower()
+    
+    # Parse city filter - support both single city and comma-separated list
+    if cities_input:
+        city_names = [c.strip() for c in cities_input.split(',')]
+        cities_to_fetch = [c for c in WEATHER_CITIES if c["name"] in city_names]
+        if not cities_to_fetch:
+            # If no matches, default to Seattle
+            cities_to_fetch = [WEATHER_CITIES[0]]
+    else:
+        # Default to Seattle if no cities specified
+        cities_to_fetch = [WEATHER_CITIES[0]]
     
     fetched_at = datetime.utcnow().isoformat() + "Z"
+    rows = []
     
-    try:
-        # Open-Meteo historical/archive API
-        end_date = datetime.utcnow()
-        start_date = end_date - timedelta(days=days)
-        
-        params = {
-            "latitude": city["lat"],
-            "longitude": city["lon"],
-            "hourly": "temperature_2m,relative_humidity_2m,wind_speed_10m,precipitation,weather_code",
-            "timezone": "auto",
-            "start_date": start_date.strftime("%Y-%m-%d"),
-            "end_date": end_date.strftime("%Y-%m-%d")
-        }
-        
-        response = requests.get("https://api.open-meteo.com/v1/forecast", params=params, timeout=30)
-        response.raise_for_status()
-        data = response.json()
-        
-        hourly = data.get("hourly", {})
-        times = hourly.get("time", [])
-        temps = hourly.get("temperature_2m", [])
-        humidity = hourly.get("relative_humidity_2m", [])
-        wind = hourly.get("wind_speed_10m", [])
-        precip = hourly.get("precipitation", [])
-        weather_codes = hourly.get("weather_code", [])
-        
-        # Weather code descriptions
-        weather_desc = {
-            0: "Clear", 1: "Mainly Clear", 2: "Partly Cloudy", 3: "Overcast",
-            45: "Foggy", 48: "Depositing Rime Fog",
-            51: "Light Drizzle", 53: "Moderate Drizzle", 55: "Dense Drizzle",
-            61: "Slight Rain", 63: "Moderate Rain", 65: "Heavy Rain",
-            71: "Slight Snow", 73: "Moderate Snow", 75: "Heavy Snow",
-            80: "Slight Showers", 81: "Moderate Showers", 82: "Violent Showers",
-            95: "Thunderstorm", 96: "Thunderstorm with Hail", 99: "Thunderstorm with Heavy Hail"
-        }
-        
-        rows = []
-        for i, time_str in enumerate(times):
-            code = weather_codes[i] if i < len(weather_codes) else 0
-            rows.append({
-                "city": city["name"],
-                "timestamp": time_str + ":00Z" if ":" in time_str else time_str,
-                "temperature_c": temps[i] if i < len(temps) else None,
-                "humidity_percent": humidity[i] if i < len(humidity) else None,
-                "wind_speed_kmh": wind[i] if i < len(wind) else None,
-                "precipitation_mm": precip[i] if i < len(precip) else None,
-                "weather_code": code,
-                "weather": weather_desc.get(code, "Unknown"),
-                "fetched_at": fetched_at
-            })
-        
-        return make_csv_response(rows)
-    except Exception as e:
-        logger.warning(f"Failed to fetch weather history: {e}")
-        return Response(f"error,{str(e)}", mimetype='text/csv'), 500
+    end_date = datetime.utcnow()
+    start_date = end_date - timedelta(days=days)
+    
+    # Determine which API to use
+    # Archive API has 5-day delay, so use forecast API for recent data (< 6 days)
+    # unless explicitly requested
+    use_archive = False
+    if use_archive_param == 'true':
+        use_archive = True
+    elif use_archive_param == 'false':
+        use_archive = False
+    else:  # 'auto'
+        # Use archive for data older than 6 days
+        use_archive = days > 6
+    
+    # Weather code descriptions (WMO Weather interpretation codes)
+    weather_desc = {
+        0: "Clear", 1: "Mainly Clear", 2: "Partly Cloudy", 3: "Overcast",
+        45: "Foggy", 48: "Depositing Rime Fog",
+        51: "Light Drizzle", 53: "Moderate Drizzle", 55: "Dense Drizzle",
+        61: "Slight Rain", 63: "Moderate Rain", 65: "Heavy Rain",
+        71: "Slight Snow", 73: "Moderate Snow", 75: "Heavy Snow",
+        80: "Slight Showers", 81: "Moderate Showers", 82: "Violent Showers",
+        85: "Slight Snow Showers", 86: "Heavy Snow Showers",
+        95: "Thunderstorm", 96: "Thunderstorm with Hail", 99: "Thunderstorm with Heavy Hail"
+    }
+    
+    for city in cities_to_fetch:
+        try:
+            params = {
+                "latitude": city["lat"],
+                "longitude": city["lon"],
+                "hourly": "temperature_2m,relative_humidity_2m,wind_speed_10m,precipitation,weather_code,pressure_msl",
+                "timezone": "auto",
+                "start_date": start_date.strftime("%Y-%m-%d"),
+                "end_date": end_date.strftime("%Y-%m-%d")
+            }
+            
+            # Use archive API for historical data, forecast API for recent data
+            if use_archive:
+                api_url = "https://api.open-meteo.com/v1/archive"
+            else:
+                api_url = "https://api.open-meteo.com/v1/forecast"
+            
+            response = requests.get(api_url, params=params, timeout=30)
+            response.raise_for_status()
+            data = response.json()
+            
+            hourly = data.get("hourly", {})
+            times = hourly.get("time", [])
+            temps = hourly.get("temperature_2m", [])
+            humidity = hourly.get("relative_humidity_2m", [])
+            wind = hourly.get("wind_speed_10m", [])
+            precip = hourly.get("precipitation", [])
+            weather_codes = hourly.get("weather_code", [])
+            pressure = hourly.get("pressure_msl", [])
+            
+            for i, time_str in enumerate(times):
+                code = weather_codes[i] if i < len(weather_codes) else 0
+                # Parse timestamp - handle both formats
+                if "T" in time_str:
+                    timestamp_str = time_str
+                else:
+                    timestamp_str = time_str + "T00:00:00Z"
+                
+                rows.append({
+                    "city": city["name"],
+                    "state": city.get("state", ""),
+                    "timestamp": timestamp_str,
+                    "temperature_c": round(temps[i], 1) if i < len(temps) and temps[i] is not None else None,
+                    "humidity_percent": humidity[i] if i < len(humidity) and humidity[i] is not None else None,
+                    "wind_speed_kmh": round(wind[i], 1) if i < len(wind) and wind[i] is not None else None,
+                    "precipitation_mm": round(precip[i], 2) if i < len(precip) and precip[i] is not None else None,
+                    "pressure_hpa": round(pressure[i], 1) if i < len(pressure) and pressure[i] is not None else None,
+                    "weather_code": code,
+                    "weather": weather_desc.get(code, "Unknown"),
+                    "fetched_at": fetched_at
+                })
+        except Exception as e:
+            logger.warning(f"Failed to fetch weather history for {city['name']}: {e}")
+    
+    # Sort by city, then timestamp
+    rows.sort(key=lambda x: (x["city"], x["timestamp"]))
+    
+    return make_csv_response(rows)
 
 
 # ============================================================================
-# NWS Weather Forecast - Updates every few hours
+# Weather Forecast (Open-Meteo) - Multi-day forecasts for multiple cities
 # Recommended refresh: 3600 seconds (1 hour)
 # ============================================================================
 
-NWS_LOCATIONS = {
-    "seattle": {"name": "Seattle, WA", "office": "SEW", "gridX": 124, "gridY": 67},
-    "new_york": {"name": "New York, NY", "office": "OKX", "gridX": 33, "gridY": 37},
-    "los_angeles": {"name": "Los Angeles, CA", "office": "LOX", "gridX": 154, "gridY": 44},
-    "chicago": {"name": "Chicago, IL", "office": "LOT", "gridX": 65, "gridY": 76},
-}
+@demo_stream_bp.route('/weather/forecast', methods=['GET'])
+@limiter.limit(WEATHER_RATE_LIMIT)
+def get_weather_forecast():
+    """
+    Multi-day weather forecast for US cities. Updates every few hours.
+    
+    Query params:
+        - cities: Comma-separated list of city names (default: all cities)
+                  Example: cities=Seattle,New York,Los Angeles
+        - days: Number of forecast days (default: 7, max: 16)
+        - hourly: 'true' to get hourly forecast data (default: 'false' for daily)
+    
+    Use case:
+        - Compare forecasts across multiple cities
+        - Track upcoming weather patterns
+        - Plan based on forecasted conditions
+        - Use hourly=true for detailed hourly forecasts
+    
+    Recommended refresh: 3600 seconds (1 hour)
+    """
+    cities_param = request.args.get('cities', '').strip()
+    days = min(16, max(1, int(request.args.get('days', 7))))
+    hourly_mode = request.args.get('hourly', 'false').lower() == 'true'
+    
+    # Parse city filter
+    if cities_param:
+        city_names = [c.strip() for c in cities_param.split(',')]
+        cities_to_fetch = [c for c in WEATHER_CITIES if c["name"] in city_names]
+        if not cities_to_fetch:
+            cities_to_fetch = WEATHER_CITIES
+    else:
+        cities_to_fetch = WEATHER_CITIES
+    
+    fetched_at = datetime.utcnow().isoformat() + "Z"
+    rows = []
+    
+    for city in cities_to_fetch:
+        try:
+            if hourly_mode:
+                # Hourly forecast
+                params = {
+                    "latitude": city["lat"],
+                    "longitude": city["lon"],
+                    "hourly": "temperature_2m,relative_humidity_2m,wind_speed_10m,precipitation,weather_code,pressure_msl",
+                    "forecast_days": days,
+                    "timezone": "auto"
+                }
+                response = requests.get("https://api.open-meteo.com/v1/forecast", params=params, timeout=30)
+                response.raise_for_status()
+                data = response.json()
+                
+                hourly = data.get("hourly", {})
+                times = hourly.get("time", [])
+                temps = hourly.get("temperature_2m", [])
+                humidity = hourly.get("relative_humidity_2m", [])
+                wind = hourly.get("wind_speed_10m", [])
+                precip = hourly.get("precipitation", [])
+                weather_codes = hourly.get("weather_code", [])
+                pressure = hourly.get("pressure_msl", [])
+                
+                weather_desc = {
+                    0: "Clear", 1: "Mainly Clear", 2: "Partly Cloudy", 3: "Overcast",
+                    45: "Foggy", 48: "Depositing Rime Fog",
+                    51: "Light Drizzle", 53: "Moderate Drizzle", 55: "Dense Drizzle",
+                    61: "Slight Rain", 63: "Moderate Rain", 65: "Heavy Rain",
+                    71: "Slight Snow", 73: "Moderate Snow", 75: "Heavy Snow",
+                    80: "Slight Showers", 81: "Moderate Showers", 82: "Violent Showers",
+                    85: "Slight Snow Showers", 86: "Heavy Snow Showers",
+                    95: "Thunderstorm", 96: "Thunderstorm with Hail", 99: "Thunderstorm with Heavy Hail"
+                }
+                
+                for i, time_str in enumerate(times):
+                    code = weather_codes[i] if i < len(weather_codes) else 0
+                    rows.append({
+                        "city": city["name"],
+                        "state": city.get("state", ""),
+                        "timestamp": time_str,
+                        "temperature_c": round(temps[i], 1) if i < len(temps) and temps[i] is not None else None,
+                        "humidity_percent": humidity[i] if i < len(humidity) and humidity[i] is not None else None,
+                        "wind_speed_kmh": round(wind[i], 1) if i < len(wind) and wind[i] is not None else None,
+                        "precipitation_mm": round(precip[i], 2) if i < len(precip) and precip[i] is not None else None,
+                        "pressure_hpa": round(pressure[i], 1) if i < len(pressure) and pressure[i] is not None else None,
+                        "weather_code": code,
+                        "weather": weather_desc.get(code, "Unknown"),
+                        "fetched_at": fetched_at
+                    })
+            else:
+                # Daily forecast
+                params = {
+                    "latitude": city["lat"],
+                    "longitude": city["lon"],
+                    "daily": "temperature_2m_max,temperature_2m_min,precipitation_sum,wind_speed_10m_max,weather_code",
+                    "forecast_days": days,
+                    "timezone": "auto"
+                }
+                response = requests.get("https://api.open-meteo.com/v1/forecast", params=params, timeout=30)
+                response.raise_for_status()
+                data = response.json()
+                
+                daily = data.get("daily", {})
+                times = daily.get("time", [])
+                temp_max = daily.get("temperature_2m_max", [])
+                temp_min = daily.get("temperature_2m_min", [])
+                precip = daily.get("precipitation_sum", [])
+                wind = daily.get("wind_speed_10m_max", [])
+                weather_codes = daily.get("weather_code", [])
+                
+                weather_desc = {
+                    0: "Clear", 1: "Mainly Clear", 2: "Partly Cloudy", 3: "Overcast",
+                    45: "Foggy", 48: "Depositing Rime Fog",
+                    51: "Light Drizzle", 53: "Moderate Drizzle", 55: "Dense Drizzle",
+                    61: "Slight Rain", 63: "Moderate Rain", 65: "Heavy Rain",
+                    71: "Slight Snow", 73: "Moderate Snow", 75: "Heavy Snow",
+                    80: "Slight Showers", 81: "Moderate Showers", 82: "Violent Showers",
+                    85: "Slight Snow Showers", 86: "Heavy Snow Showers",
+                    95: "Thunderstorm", 96: "Thunderstorm with Hail", 99: "Thunderstorm with Heavy Hail"
+                }
+                
+                for i, time_str in enumerate(times):
+                    code = weather_codes[i] if i < len(weather_codes) else 0
+                    rows.append({
+                        "city": city["name"],
+                        "state": city.get("state", ""),
+                        "date": time_str,
+                        "temperature_max_c": round(temp_max[i], 1) if i < len(temp_max) and temp_max[i] is not None else None,
+                        "temperature_min_c": round(temp_min[i], 1) if i < len(temp_min) and temp_min[i] is not None else None,
+                        "precipitation_mm": round(precip[i], 2) if i < len(precip) and precip[i] is not None else None,
+                        "wind_speed_max_kmh": round(wind[i], 1) if i < len(wind) and wind[i] is not None else None,
+                        "weather_code": code,
+                        "weather": weather_desc.get(code, "Unknown"),
+                        "fetched_at": fetched_at
+                    })
+        except Exception as e:
+            logger.warning(f"Failed to fetch forecast for {city['name']}: {e}")
+    
+    return make_csv_response(rows)
+
 
-@demo_stream_bp.route('/forecast/<location>', methods=['GET'])
+# ============================================================================
+# Today's Weather Comparison - Current weather across multiple cities
+# Recommended refresh: 300 seconds (5 minutes)
+# ============================================================================
+
+@demo_stream_bp.route('/weather/today', methods=['GET'])
 @limiter.limit(WEATHER_RATE_LIMIT)
-def get_forecast(location: str):
+def get_weather_today():
     """
-    7-day forecast from NWS. Updates every few hours.
-    Locations: seattle, new_york, los_angeles, chicago
-    Recommended refresh: 3600 seconds
+    Today's current weather for multiple US cities - perfect for comparison.
+    
+    Query params:
+        - cities: Comma-separated list of city names (default: all cities)
+                  Example: cities=Seattle,New York,Los Angeles,Miami
+        - limit: Maximum number of cities to return (default: 20, max: 50)
+    
+    Use case:
+        - Compare current weather conditions across US cities
+        - Visualize temperature, humidity, wind patterns geographically
+        - Great for maps, bar charts, and comparison visualizations
+        - Perfect for "weather dashboard" style analysis
+    
+    Recommended refresh: 300 seconds (5 minutes)
     """
-    loc_key = location.lower().replace("-", "_")
-    if loc_key not in NWS_LOCATIONS:
-        return Response(f"error,Unknown location. Use: {','.join(NWS_LOCATIONS.keys())}", mimetype='text/csv'), 400
+    cities_param = request.args.get('cities', '').strip()
+    limit = min(50, max(1, int(request.args.get('limit', 20))))
     
-    loc = NWS_LOCATIONS[loc_key]
+    # Parse city filter
+    if cities_param:
+        city_names = [c.strip() for c in cities_param.split(',')]
+        cities_to_fetch = [c for c in WEATHER_CITIES if c["name"] in city_names][:limit]
+        if not cities_to_fetch:
+            cities_to_fetch = WEATHER_CITIES[:limit]
+    else:
+        cities_to_fetch = WEATHER_CITIES[:limit]
     
-    try:
-        url = f"https://api.weather.gov/gridpoints/{loc['office']}/{loc['gridX']},{loc['gridY']}/forecast"
-        headers = {"User-Agent": "(DataFormulator, demo@example.com)"}
-        response = requests.get(url, headers=headers, timeout=30)
-        response.raise_for_status()
-        data = response.json()
-        
-        fetched_at = datetime.utcnow().isoformat() + "Z"
-        rows = []
-        
-        for period in data.get("properties", {}).get("periods", []):
+    fetched_at = datetime.utcnow().isoformat() + "Z"
+    rows = []
+    
+    for city in cities_to_fetch:
+        try:
+            params = {
+                "latitude": city["lat"],
+                "longitude": city["lon"],
+                "current": "temperature_2m,relative_humidity_2m,wind_speed_10m,wind_direction_10m,precipitation,pressure_msl,cloud_cover,weather_code",
+                "timezone": "auto"
+            }
+            response = requests.get("https://api.open-meteo.com/v1/forecast", params=params, timeout=10)
+            response.raise_for_status()
+            data = response.json()
+            current = data.get("current", {})
+            
+            weather_desc = {
+                0: "Clear", 1: "Mainly Clear", 2: "Partly Cloudy", 3: "Overcast",
+                45: "Foggy", 48: "Depositing Rime Fog",
+                51: "Light Drizzle", 53: "Moderate Drizzle", 55: "Dense Drizzle",
+                61: "Slight Rain", 63: "Moderate Rain", 65: "Heavy Rain",
+                71: "Slight Snow", 73: "Moderate Snow", 75: "Heavy Snow",
+                80: "Slight Showers", 81: "Moderate Showers", 82: "Violent Showers",
+                85: "Slight Snow Showers", 86: "Heavy Snow Showers",
+                95: "Thunderstorm", 96: "Thunderstorm with Hail", 99: "Thunderstorm with Heavy Hail"
+            }
+            
+            weather_code = current.get("weather_code", 0)
+            
             rows.append({
-                "location": loc["name"],
-                "period": period.get("name"),
-                "temperature": period.get("temperature"),
-                "temperature_unit": period.get("temperatureUnit"),
-                "wind_speed": period.get("windSpeed"),
-                "wind_direction": period.get("windDirection"),
-                "forecast": period.get("shortForecast"),
+                "city": city["name"],
+                "state": city.get("state", ""),
+                "latitude": city["lat"],
+                "longitude": city["lon"],
+                "temperature_c": round(current.get("temperature_2m"), 1) if current.get("temperature_2m") is not None else None,
+                "temperature_f": round(current.get("temperature_2m") * 9/5 + 32, 1) if current.get("temperature_2m") is not None else None,
+                "humidity_percent": current.get("relative_humidity_2m"),
+                "wind_speed_kmh": round(current.get("wind_speed_10m"), 1) if current.get("wind_speed_10m") is not None else None,
+                "wind_direction_deg": current.get("wind_direction_10m"),
+                "precipitation_mm": round(current.get("precipitation"), 2) if current.get("precipitation") is not None else None,
+                "pressure_hpa": round(current.get("pressure_msl"), 1) if current.get("pressure_msl") is not None else None,
+                "cloud_cover_percent": current.get("cloud_cover"),
+                "weather_code": weather_code,
+                "weather": weather_desc.get(weather_code, "Unknown"),
                 "fetched_at": fetched_at
             })
-        
-        return make_csv_response(rows)
-    except Exception as e:
-        return Response(f"error,{str(e)}", mimetype='text/csv'), 500
+        except Exception as e:
+            logger.warning(f"Failed to fetch weather for {city['name']}: {e}")
+    
+    return make_csv_response(rows)
 
 
 # ============================================================================
 # yfinance - Stock/Financial Data via Yahoo Finance
-# Single unified API with historical daily data + recent 15min intraday data
-# Recommended refresh: 300 seconds (5 minutes) during market hours
+# Three pre-baked APIs: history (daily), recent (intraday), financials (metrics)
 # ============================================================================
 
 DEFAULT_SYMBOLS = ["AAPL", "MSFT", "GOOGL", "AMZN", "META", "NVDA", "TSLA"]
 
+# S&P 100 Companies (as of 2024)
+SP100_SYMBOLS = [
+    # Technology
+    "AAPL", "MSFT", "GOOGL", "GOOG", "META", "NVDA", "AVGO", "ORCL", "CRM", "CSCO",
+    "ACN", "ADBE", "AMD", "INTC", "IBM", "QCOM", "TXN",
+    # Consumer/Retail
+    "AMZN", "TSLA", "HD", "MCD", "NKE", "SBUX", "TGT", "LOW", "COST",
+    # Financial Services
+    "JPM", "V", "MA", "BAC", "WFC", "GS", "MS", "BLK", "SPGI", "AXP", "C", "BK",
+    # Healthcare
+    "UNH", "JNJ", "LLY", "PFE", "ABBV", "MRK", "TMO", "ABT", "DHR", "BMY", "AMGN", 
+    "GILD", "MDT", "CVS",
+    # Energy
+    "XOM", "CVX", "COP", "SLB",
+    # Industrials
+    "CAT", "GE", "HON", "UNP", "UPS", "RTX", "BA", "LMT", "DE", "MMM", "EMR",
+    # Consumer Staples
+    "PG", "KO", "PEP", "WMT", "PM", "MO", "CL", "MDLZ",
+    # Communications
+    "DIS", "CMCSA", "NFLX", "T", "VZ", "TMUS",
+    # Utilities & Real Estate
+    "NEE", "DUK", "SO",
+    # Materials
+    "LIN", "DOW",
+    # Other Major Companies
+    "BRK-B", "PYPL", "NOW", "INTU", "AMAT", "ADI", "MU", "LRCX", "KLAC",
+    "SCHW", "CB", "PNC", "USB", "TFC",
+    "ISRG", "VRTX", "REGN", "ZTS", "SYK", "ELV",
+    "F", "GM",
+    "ADP", "FIS", "ITW", "GD", "NOC",
+    "EXC", "AEP", "D", "SRE", "PEG"
+]
+
+
+# Helper functions for yfinance endpoints
+def _yf_is_valid(val):
+    """Check if value is valid (not NaN/None)"""
+    try:
+        return val is not None and not (isinstance(val, float) and math.isnan(val))
+    except:
+        return False
+
 
-@demo_stream_bp.route('/yfinance', methods=['GET'])
+def _yf_format_timestamp(date_obj):
+    """Convert pandas Timestamp or datetime to string"""
+    try:
+        if hasattr(date_obj, 'tz_convert'):
+            date_utc = date_obj.tz_convert('UTC')
+        elif hasattr(date_obj, 'tz_localize') and date_obj.tz is not None:
+            date_utc = date_obj.tz_convert('UTC')
+        else:
+            date_utc = date_obj
+        
+        if hasattr(date_utc, 'to_pydatetime'):
+            date_utc = date_utc.to_pydatetime()
+        elif hasattr(date_utc, 'timestamp'):
+            date_utc = datetime.fromtimestamp(date_utc.timestamp())
+        
+        if isinstance(date_utc, datetime):
+            return date_utc.strftime("%Y-%m-%d %H:%M:%S")
+        else:
+            return str(date_utc)
+    except:
+        return str(date_obj)
+
+
+@demo_stream_bp.route('/yfinance/history', methods=['GET'])
 @limiter.limit(YFINANCE_RATE_LIMIT)
-def get_yfinance():
+def get_yfinance_history():
     """
-    Stock prices via yfinance with historical daily data + recent intraday data (15min intervals).
+    6-month daily stock price history via yfinance.
     
-    Returns a complete dataset combining:
-    - Historical daily data from start_date (default: 6 months ago)
-    - Recent intraday data at 15-minute intervals (last ~5-7 days)
-    - Today's live intraday data points
+    Returns daily OHLCV data for the last 6 months.
     
     Query params:
         - symbols: comma-separated stock symbols (default: AAPL,MSFT,GOOGL,AMZN,META,NVDA,TSLA)
-        - start_date: YYYY-MM-DD format (default: 6 months ago)
     
-    Example use case:
-        - /api/demo-stream/yfinance?symbols=AAPL,MSFT&start_date=2025-07-01
-        - Returns daily data from July 2025, plus recent 15min intraday data
-        - New data appears each trading day
+    Example:
+        /api/demo-stream/yfinance/history?symbols=AAPL,MSFT,GOOGL
     
-    Recommended refresh: 300 seconds (5 minutes) during market hours
+    Recommended refresh: 3600 seconds (1 hour)
     """
     symbols_param = request.args.get('symbols', ','.join(DEFAULT_SYMBOLS))
     symbols = [s.strip().upper() for s in symbols_param.split(',') if s.strip()][:10]
     
     now = datetime.utcnow()
-    today = now.date()
+    start_date = now - timedelta(days=180)  # 6 months
     
-    # Parse start_date, default to 6 months ago
-    start_date_str = request.args.get('start_date')
-    if start_date_str:
+    fetched_at = now.isoformat() + "Z"
+    rows = []
+    
+    for symbol in symbols:
         try:
-            start_date = datetime.strptime(start_date_str, "%Y-%m-%d")
-        except:
-            start_date = now - timedelta(days=180)
-    else:
-        start_date = now - timedelta(days=180)
+            ticker = yf.Ticker(symbol)
+            hist = ticker.history(start=start_date.strftime("%Y-%m-%d"), end=now.strftime("%Y-%m-%d"))
+            
+            for date, row in hist.iterrows():
+                try:
+                    date_str = date.strftime("%Y-%m-%d") if hasattr(date, 'strftime') else str(date)
+                except:
+                    date_str = str(date)
+                
+                rows.append({
+                    "symbol": symbol,
+                    "date": date_str,
+                    "open": round(row["Open"], 2) if _yf_is_valid(row["Open"]) else None,
+                    "high": round(row["High"], 2) if _yf_is_valid(row["High"]) else None,
+                    "low": round(row["Low"], 2) if _yf_is_valid(row["Low"]) else None,
+                    "close": round(row["Close"], 2) if _yf_is_valid(row["Close"]) else None,
+                    "volume": int(row["Volume"]) if _yf_is_valid(row["Volume"]) else None,
+                    "fetched_at": fetched_at
+                })
+                    
+        except Exception as e:
+            logger.warning(f"Failed to fetch history for {symbol}: {e}")
     
-    # Calculate number of days
-    days = (now - start_date).days
+    # Sort by symbol, then date
+    rows.sort(key=lambda x: (x["symbol"], x["date"]))
     
-    # yfinance typically provides intraday data for last 5-7 days
-    intraday_days_limit = 7
-    intraday_interval = '15m'
+    return make_csv_response(rows)
+
+
+@demo_stream_bp.route('/yfinance/recent', methods=['GET'])
+@limiter.limit(YFINANCE_RATE_LIMIT)
+def get_yfinance_recent():
+    """
+    Recent intraday stock prices (15-minute intervals) via yfinance.
     
-    fetched_at = now.isoformat() + "Z"
-    rows = []
+    Returns 15-minute interval data for the last 5 trading days.
+    yfinance typically provides intraday data for the last 5-7 days only.
     
-    # Helper to check if value is valid (not NaN/None)
-    def is_valid(val):
-        try:
-            return val is not None and not (isinstance(val, float) and math.isnan(val))
-        except:
-            return False
+    Query params:
+        - symbols: comma-separated stock symbols (default: AAPL,MSFT,GOOGL,AMZN,META,NVDA,TSLA)
     
-    # Helper to format timestamp
-    def format_timestamp(date_obj):
-        """Convert pandas Timestamp or datetime to string"""
-        try:
-            if hasattr(date_obj, 'tz_convert'):
-                date_utc = date_obj.tz_convert('UTC')
-            elif hasattr(date_obj, 'tz_localize') and date_obj.tz is not None:
-                date_utc = date_obj.tz_convert('UTC')
-            else:
-                date_utc = date_obj
-            
-            if hasattr(date_utc, 'to_pydatetime'):
-                date_utc = date_utc.to_pydatetime()
-            elif hasattr(date_utc, 'timestamp'):
-                date_utc = datetime.fromtimestamp(date_utc.timestamp())
-            
-            if isinstance(date_utc, datetime):
-                return date_utc.strftime("%Y-%m-%d %H:%M:%S")
-            else:
-                return str(date_utc)
-        except:
-            return str(date_obj)
+    Example:
+        /api/demo-stream/yfinance/recent?symbols=AAPL,MSFT,GOOGL
+    
+    Recommended refresh: 300 seconds (5 minutes) during market hours
+    """
+    symbols_param = request.args.get('symbols', ','.join(DEFAULT_SYMBOLS))
+    symbols = [s.strip().upper() for s in symbols_param.split(',') if s.strip()][:10]
+    
+    now = datetime.utcnow()
+    fetched_at = now.isoformat() + "Z"
+    rows = []
     
     for symbol in symbols:
         try:
             ticker = yf.Ticker(symbol)
             
-            # Get historical daily data for older period (before intraday range)
-            daily_days = max(0, days - intraday_days_limit)
+            # Get 5 days of 15-minute interval data
+            hist = ticker.history(interval='15m', period='5d')
             
-            if daily_days > 0:
-                daily_end = now - timedelta(days=intraday_days_limit)
-                hist_daily = ticker.history(start=start_date.strftime("%Y-%m-%d"), end=daily_end.strftime("%Y-%m-%d"))
-                
-                for date, row in hist_daily.iterrows():
-                    try:
-                        if hasattr(date, 'strftime'):
-                            date_str = date.strftime("%Y-%m-%d")
-                        else:
-                            date_str = str(date)
-                    except:
-                        date_str = str(date)
-                    
-                    rows.append({
-                        "symbol": symbol,
-                        "timestamp": date_str + " 00:00:00",
-                        "date": date_str,
-                        "open": round(row["Open"], 2) if is_valid(row["Open"]) else None,
-                        "high": round(row["High"], 2) if is_valid(row["High"]) else None,
-                        "low": round(row["Low"], 2) if is_valid(row["Low"]) else None,
-                        "close": round(row["Close"], 2) if is_valid(row["Close"]) else None,
-                        "volume": int(row["Volume"]) if is_valid(row["Volume"]) else None,
-                        "data_type": "daily",
-                        "fetched_at": fetched_at
-                    })
-            
-            # Get recent intraday data at 15min intervals (last 5-7 days excluding today)
-            try:
-                hist_intraday = ticker.history(interval=intraday_interval, period='7d')
-                
-                if not hist_intraday.empty:
-                    for date, row in hist_intraday.iterrows():
-                        # Skip today (we'll get it separately to ensure latest)
-                        try:
-                            if hasattr(date, 'date'):
-                                date_only = date.date()
-                            elif hasattr(date, 'to_pydatetime'):
-                                date_only = date.to_pydatetime().date()
-                            else:
-                                date_only = date
-                            
-                            if isinstance(date_only, str):
-                                date_only = datetime.strptime(date_only, "%Y-%m-%d").date()
-                            
-                            if date_only == today:
-                                continue  # Skip today, will get it below
-                        except:
-                            pass
-                        
-                        timestamp_str = format_timestamp(date)
-                        
-                        rows.append({
-                            "symbol": symbol,
-                            "timestamp": timestamp_str,
-                            "date": timestamp_str.split()[0] if ' ' in timestamp_str else str(date),
-                            "open": round(row["Open"], 2) if is_valid(row["Open"]) else None,
-                            "high": round(row["High"], 2) if is_valid(row["High"]) else None,
-                            "low": round(row["Low"], 2) if is_valid(row["Low"]) else None,
-                            "close": round(row["Close"], 2) if is_valid(row["Close"]) else None,
-                            "volume": int(row["Volume"]) if is_valid(row["Volume"]) else None,
-                            "data_type": "intraday",
-                            "fetched_at": fetched_at
-                        })
-            except Exception as e:
-                logger.warning(f"Failed to fetch intraday historical for {symbol}: {e}")
-            
-            # Get today's intraday data (always fetch to ensure latest)
-            hist_intraday_today = ticker.history(interval=intraday_interval, period='1d')
-            
-            if not hist_intraday_today.empty:
-                for date, row in hist_intraday_today.iterrows():
-                    timestamp_str = format_timestamp(date)
+            if not hist.empty:
+                for date, row in hist.iterrows():
+                    timestamp_str = _yf_format_timestamp(date)
                     
                     rows.append({
                         "symbol": symbol,
                         "timestamp": timestamp_str,
-                        "date": today.strftime("%Y-%m-%d"),
-                        "open": round(row["Open"], 2) if is_valid(row["Open"]) else None,
-                        "high": round(row["High"], 2) if is_valid(row["High"]) else None,
-                        "low": round(row["Low"], 2) if is_valid(row["Low"]) else None,
-                        "close": round(row["Close"], 2) if is_valid(row["Close"]) else None,
-                        "volume": int(row["Volume"]) if is_valid(row["Volume"]) else None,
-                        "data_type": "intraday",
+                        "date": timestamp_str.split()[0] if ' ' in timestamp_str else str(date),
+                        "open": round(row["Open"], 2) if _yf_is_valid(row["Open"]) else None,
+                        "high": round(row["High"], 2) if _yf_is_valid(row["High"]) else None,
+                        "low": round(row["Low"], 2) if _yf_is_valid(row["Low"]) else None,
+                        "close": round(row["Close"], 2) if _yf_is_valid(row["Close"]) else None,
+                        "volume": int(row["Volume"]) if _yf_is_valid(row["Volume"]) else None,
                         "fetched_at": fetched_at
                     })
-            else:
-                # If no intraday data, try to get today's price
-                try:
-                    info = ticker.info
-                    price = info.get('currentPrice') or info.get('regularMarketPrice') or info.get('previousClose')
-                    if price:
-                        rows.append({
-                            "symbol": symbol,
-                            "timestamp": today.strftime("%Y-%m-%d") + " 00:00:00",
-                            "date": today.strftime("%Y-%m-%d"),
-                            "open": price,
-                            "high": price,
-                            "low": price,
-                            "close": price,
-                            "volume": info.get('volume', 0),
-                            "data_type": "daily",
-                            "fetched_at": fetched_at
-                        })
-                except:
-                    pass
                     
         except Exception as e:
-            logger.warning(f"Failed to fetch data for {symbol}: {e}")
+            logger.warning(f"Failed to fetch recent data for {symbol}: {e}")
     
     # Sort by symbol, then timestamp
     rows.sort(key=lambda x: (x["symbol"], x["timestamp"]))
@@ -752,75 +1001,176 @@ def format_timestamp(date_obj):
     return make_csv_response(rows)
 
 
+@demo_stream_bp.route('/yfinance/financials', methods=['GET'])
+@limiter.limit(YFINANCE_RATE_LIMIT)
+def get_yfinance_financials():
+    """
+    Key financial metrics snapshot via yfinance for S&P 100 companies.
+    
+    Returns current financial data for each stock including market cap,
+    P/E ratio, EPS, dividend yield, 52-week range, and more.
+    
+    Query params:
+        - symbols: comma-separated stock symbols (default: all S&P 100 companies)
+    
+    Example:
+        /api/demo-stream/yfinance/financials
+        /api/demo-stream/yfinance/financials?symbols=AAPL,MSFT,GOOGL,AMZN
+    
+    Recommended refresh: 3600 seconds (1 hour)
+    """
+    symbols_param = request.args.get('symbols')
+    if symbols_param:
+        symbols = [s.strip().upper() for s in symbols_param.split(',') if s.strip()]
+    else:
+        symbols = SP100_SYMBOLS
+    
+    now = datetime.utcnow()
+    fetched_at = now.isoformat() + "Z"
+    rows = []
+    
+    for symbol in symbols:
+        try:
+            ticker = yf.Ticker(symbol)
+            info = ticker.info
+            
+            # Extract key financial metrics
+            rows.append({
+                "symbol": symbol,
+                "name": info.get('shortName') or info.get('longName') or symbol,
+                "sector": info.get('sector') or 'N/A',
+                "industry": info.get('industry') or 'N/A',
+                "current_price": round(info.get('currentPrice') or info.get('regularMarketPrice') or 0, 2),
+                "previous_close": round(info.get('previousClose') or 0, 2),
+                "market_cap": info.get('marketCap') or 0,
+                "pe_ratio": round(info.get('trailingPE') or 0, 2) if info.get('trailingPE') else None,
+                "forward_pe": round(info.get('forwardPE') or 0, 2) if info.get('forwardPE') else None,
+                "eps": round(info.get('trailingEps') or 0, 2) if info.get('trailingEps') else None,
+                "dividend_yield": round((info.get('dividendYield') or 0) * 100, 2) if info.get('dividendYield') else 0,
+                "week_52_high": round(info.get('fiftyTwoWeekHigh') or 0, 2),
+                "week_52_low": round(info.get('fiftyTwoWeekLow') or 0, 2),
+                "avg_volume": info.get('averageVolume') or 0,
+                "beta": round(info.get('beta') or 0, 2) if info.get('beta') else None,
+                "profit_margin": round((info.get('profitMargins') or 0) * 100, 2) if info.get('profitMargins') else None,
+                "revenue": info.get('totalRevenue') or 0,
+                "fetched_at": fetched_at
+            })
+                    
+        except Exception as e:
+            logger.warning(f"Failed to fetch financials for {symbol}: {e}")
+    
+    # Sort by symbol
+    rows.sort(key=lambda x: x["symbol"])
+    
+    return make_csv_response(rows)
+
+
 # ============================================================================
-# Mock Live Sales Feed - Updates every second (for demo)
-# Rich schema with programmatically correlated data
+# Mock Live Sales Feed - Accumulating dataset with rolling 1000 records
+# Similar to ISS tracking - data accumulates in memory
+# Recommended refresh: 1-5 seconds
 # ============================================================================
 
+# Thread-safe storage for sales transaction history
+_sales_lock = threading.Lock()
+_sales_history: deque = deque(maxlen=1000)  # Keep last 1000 transactions
+_sales_last_update: Optional[datetime] = None
+
+# Products with realistic pricing and popularity
+_SALES_PRODUCTS = [
+    {"name": "Wireless Headphones", "category": "Electronics", "base_price": 79.99, "popularity": 0.15},
+    {"name": "Smart Watch", "category": "Electronics", "base_price": 199.99, "popularity": 0.10},
+    {"name": "Running Shoes", "category": "Sports", "base_price": 129.99, "popularity": 0.12},
+    {"name": "Yoga Mat", "category": "Sports", "base_price": 34.99, "popularity": 0.08},
+    {"name": "Coffee Maker", "category": "Home", "base_price": 89.99, "popularity": 0.09},
+    {"name": "Desk Lamp", "category": "Home", "base_price": 45.99, "popularity": 0.07},
+    {"name": "Backpack", "category": "Accessories", "base_price": 59.99, "popularity": 0.11},
+    {"name": "Water Bottle", "category": "Accessories", "base_price": 24.99, "popularity": 0.13},
+    {"name": "Bluetooth Speaker", "category": "Electronics", "base_price": 49.99, "popularity": 0.08},
+    {"name": "Fitness Tracker", "category": "Electronics", "base_price": 69.99, "popularity": 0.07},
+]
+
+_SALES_REGIONS = ["North America", "Europe", "Asia Pacific", "Latin America"]
+_SALES_REGION_WEIGHTS = [0.45, 0.30, 0.18, 0.07]
+
+_SALES_CHANNELS = ["Web", "Mobile App", "In-Store", "Partner"]
+_SALES_CHANNEL_WEIGHTS = [0.40, 0.35, 0.15, 0.10]
+
+
+def _generate_sale_transaction(timestamp: datetime) -> Dict[str, Any]:
+    """Generate a single sale transaction"""
+    product = random.choices(_SALES_PRODUCTS, weights=[p["popularity"] for p in _SALES_PRODUCTS])[0]
+    region = random.choices(_SALES_REGIONS, weights=_SALES_REGION_WEIGHTS)[0]
+    channel = random.choices(_SALES_CHANNELS, weights=_SALES_CHANNEL_WEIGHTS)[0]
+    
+    quantity = random.choices([1, 2, 3, 4, 5], weights=[0.5, 0.25, 0.15, 0.07, 0.03])[0]
+    discount = random.choices([0, 5, 10, 15, 20], weights=[0.6, 0.15, 0.12, 0.08, 0.05])[0]
+    
+    unit_price = round(product["base_price"] * (1 - discount / 100), 2)
+    total = round(unit_price * quantity, 2)
+    
+    return {
+        "transaction_id": f"TX{int(timestamp.timestamp() * 1000) % 100000000:08d}",
+        "timestamp": timestamp.isoformat() + "Z",
+        "product": product["name"],
+        "category": product["category"],
+        "quantity": quantity,
+        "unit_price": unit_price,
+        "discount_pct": discount,
+        "total": total,
+        "region": region,
+        "channel": channel,
+    }
+
 
 @demo_stream_bp.route('/live-sales', methods=['GET'])
 @limiter.limit(MOCK_RATE_LIMIT)
 def get_live_sales():
     """
-    Simulated live sales feed. Updates every second.
-    Each refresh shows recent "transactions" with product details.
-    Recommended refresh: 1 second
+    Simulated live sales feed with accumulating transaction history.
+    Data accumulates in memory and maintains a rolling record of the last 1000 transactions.
+    Each refresh may add new transactions and returns the complete accumulated dataset.
+    
+    Query params:
+        - limit: Maximum number of records to return (default: 1000, max: 1000)
+    
+    Recommended refresh: 1-5 seconds
     """
+    global _sales_last_update
+    
     now = datetime.utcnow()
-    hour_of_day = now.hour + now.minute / 60
-    
-    # Products with realistic pricing and popularity
-    products = [
-        {"name": "Wireless Headphones", "category": "Electronics", "base_price": 79.99, "popularity": 0.15},
-        {"name": "Smart Watch", "category": "Electronics", "base_price": 199.99, "popularity": 0.10},
-        {"name": "Running Shoes", "category": "Sports", "base_price": 129.99, "popularity": 0.12},
-        {"name": "Yoga Mat", "category": "Sports", "base_price": 34.99, "popularity": 0.08},
-        {"name": "Coffee Maker", "category": "Home", "base_price": 89.99, "popularity": 0.09},
-        {"name": "Desk Lamp", "category": "Home", "base_price": 45.99, "popularity": 0.07},
-        {"name": "Backpack", "category": "Accessories", "base_price": 59.99, "popularity": 0.11},
-        {"name": "Water Bottle", "category": "Accessories", "base_price": 24.99, "popularity": 0.13},
-        {"name": "Bluetooth Speaker", "category": "Electronics", "base_price": 49.99, "popularity": 0.08},
-        {"name": "Fitness Tracker", "category": "Electronics", "base_price": 69.99, "popularity": 0.07},
-    ]
-    
-    regions = ["North America", "Europe", "Asia Pacific", "Latin America"]
-    region_weights = [0.45, 0.30, 0.18, 0.07]
-    
-    channels = ["Web", "Mobile App", "In-Store", "Partner"]
-    channel_weights = [0.40, 0.35, 0.15, 0.10]
-    
-    # Generate 5-10 recent transactions
-    num_transactions = random.randint(5, 10)
-    rows = []
+    limit = min(1000, max(1, int(request.args.get('limit', 1000))))
     
-    for i in range(num_transactions):
-        product = random.choices(products, weights=[p["popularity"] for p in products])[0]
-        region = random.choices(regions, weights=region_weights)[0]
-        channel = random.choices(channels, weights=channel_weights)[0]
-        
-        quantity = random.choices([1, 2, 3, 4, 5], weights=[0.5, 0.25, 0.15, 0.07, 0.03])[0]
-        discount = random.choices([0, 5, 10, 15, 20], weights=[0.6, 0.15, 0.12, 0.08, 0.05])[0]
+    # Generate new transactions if enough time has passed (at least 1 second)
+    with _sales_lock:
+        should_update = _sales_last_update is None or (now - _sales_last_update).total_seconds() >= 1
         
-        unit_price = round(product["base_price"] * (1 - discount / 100), 2)
-        total = round(unit_price * quantity, 2)
-        
-        # Transaction time within the last minute
-        tx_time = now - timedelta(seconds=random.randint(0, 60))
+        if should_update:
+            # If no data exists yet, generate initial batch of transactions
+            if len(_sales_history) == 0:
+                # Generate 5-10 initial transactions
+                num_initial = random.randint(5, 10)
+                for _ in range(num_initial):
+                    tx_time = now - timedelta(seconds=random.randint(0, 60))
+                    transaction = _generate_sale_transaction(tx_time)
+                    transaction["fetched_at"] = now.isoformat() + "Z"
+                    _sales_history.append(transaction)
+            else:
+                # Generate 1-3 new transactions per update
+                num_new_transactions = random.randint(1, 3)
+                for _ in range(num_new_transactions):
+                    # Spread transactions over the last second
+                    tx_time = now - timedelta(milliseconds=random.randint(0, 1000))
+                    transaction = _generate_sale_transaction(tx_time)
+                    transaction["fetched_at"] = now.isoformat() + "Z"
+                    _sales_history.append(transaction)
+            
+            _sales_last_update = now
         
-        rows.append({
-            "transaction_id": f"TX{int(tx_time.timestamp() * 1000) % 1000000:06d}",
-            "timestamp": tx_time.isoformat() + "Z",
-            "product": product["name"],
-            "category": product["category"],
-            "quantity": quantity,
-            "unit_price": unit_price,
-            "discount_pct": discount,
-            "total": total,
-            "region": region,
-            "channel": channel,
-        })
-    
-    # Sort by timestamp descending
+        # Return all accumulated records (up to limit)
+        rows = list(_sales_history)[-limit:]
+    
+    # Sort by timestamp descending (most recent first)
     rows.sort(key=lambda x: x["timestamp"], reverse=True)
     
     return make_csv_response(rows)
@@ -844,81 +1194,61 @@ def get_info():
             "Use date parameters to track data from a specific point in time"
         ],
         "demo_examples": [
+            # Stock Market Data - History, Intraday, and Financials
             {
-                "id": "yfinance",
-                "url": "/api/demo-stream/yfinance?symbols=AAPL,MSFT,GOOGL",
-                "name": "Stock Data (6 months + Intraday)",
-                "refresh_seconds": 300,
-                "description": "Historical daily data (6 months default) + recent 15min intraday data + today's live prices (via yfinance)",
-                "params": {
-                    "symbols": "Comma-separated stock symbols (max 10)",
-                    "start_date": "YYYY-MM-DD start date (default: 6 months ago)"
-                }
+                "id": "stocks-history",
+                "url": "/api/demo-stream/yfinance/history?symbols=AAPL,MSFT,GOOGL,AMZN,META,NVDA",
+                "name": "📈 Yahoo Finance: 6-Month Stock Price History - Tech Companies (updates daily)",
+                "refresh_seconds": 86400,
             },
             {
-                "id": "yfinance-ytd",
-                "url": f"/api/demo-stream/yfinance?symbols=AAPL,NVDA,TSLA&start_date={datetime.utcnow().strftime('%Y')}-01-01",
-                "name": "Stock Data (Year to Date)",
-                "refresh_seconds": 300,
-                "description": "Year-to-date stock data with daily history + recent intraday (via yfinance)"
+                "id": "stocks-intraday",
+                "url": "/api/demo-stream/yfinance/recent?symbols=AAPL,MSFT,GOOGL,AMZN,META,NVDA,TSLA",
+                "name": "📈 Yahoo Finance: Recent Intraday Stock Prices - Tech Companies (updates every 15 min)",
+                "refresh_seconds": 900,
             },
             {
-                "id": "iss-trajectory",
-                "url": "/api/demo-stream/iss?minutes=30",
-                "name": "ISS Trajectory",
-                "refresh_seconds": 5,
-                "description": "ISS orbital path - positions accumulate over time",
-                "params": {
-                    "minutes": "Minutes of history (1-60, default 30)",
-                    "limit": "Max points to return (10-500)"
-                }
+                "id": "stocks-financials",
+                "url": "/api/demo-stream/yfinance/financials",
+                "name": "📈 Yahoo Finance: S&P 100 Key Financial Metrics (updates daily)",
+                "refresh_seconds": 86400,
             },
+            # ISS Tracking Variations
             {
-                "id": "earthquakes-week",
+                "id": "iss-trajectory-recent",
+                "url": "/api/demo-stream/iss",
+                "name": "🛰️ Open Notify: International Space Station Real-time Positions (updates every 30 sec)",
+                "refresh_seconds": 30,
+            },
+            
+            # Earthquake Data Variations
+            {
+                "id": "earthquakes-significant-week",
                 "url": "/api/demo-stream/earthquakes?timeframe=week&min_magnitude=4",
-                "name": "Earthquakes (Week, M4+)",
+                "name": "🌍 USGS: Significant Earthquakes Worldwide - Last Week (updates every minute)",
                 "refresh_seconds": 60,
-                "description": "Significant earthquakes - new quakes appear over time",
-                "params": {
-                    "timeframe": "hour, day, week, month",
-                    "min_magnitude": "Minimum magnitude filter",
-                    "max_magnitude": "Maximum magnitude filter (optional)",
-                    "since": "ISO datetime - only quakes after this time",
-                    "limit": "Max results (1-20000, default 20000)",
-                    "use_query_api": "true to use query API for large datasets (default false)"
-                }
             },
+
+            # Weather Data Variations
             {
-                "id": "earthquakes-large",
-                "url": "/api/demo-stream/earthquakes?timeframe=month&min_magnitude=2&use_query_api=true&limit=10000",
-                "name": "Earthquakes (Month, Large Dataset)",
-                "refresh_seconds": 300,
-                "description": "Large dataset with up to 10,000 earthquakes from the past month"
+                "id": "weather-today-all-cities",
+                "url": "/api/demo-stream/weather/today",
+                "name": "🌤️ Open Meteo: Today's Weather - 20 Major US Cities (updates daily)",
+                "refresh_seconds": 86400,
             },
             {
-                "id": "weather-history",
-                "url": "/api/demo-stream/weather/history?city=Seattle&days=7",
-                "name": "Weather History (7 days)",
+                "id": "weather-forecast-hourly",
+                "url": "/api/demo-stream/weather/forecast?days=3&hourly=true",
+                "name": "🌤️ Open Meteo: 3-Day Hourly Weather Forecast - US Cities (updates hourly)",
                 "refresh_seconds": 3600,
-                "description": "Hourly weather data - new hours appear over time",
-                "params": {
-                    "city": "City name (Seattle, New York, etc.)",
-                    "days": "Past days to include (1-14)"
-                }
             },
+            
+            # Live Sales & E-commerce Variations
             {
-                "id": "live-sales",
+                "id": "live-sales-feed",
                 "url": "/api/demo-stream/live-sales",
-                "name": "Live Sales Feed",
-                "refresh_seconds": 1,
-                "description": "Simulated e-commerce transactions"
-            },
-            {
-                "id": "weather-current",
-                "url": "/api/demo-stream/weather",
-                "name": "Weather (Current)",
-                "refresh_seconds": 300,
-                "description": "Current conditions for 8 US cities"
+                "name": "💰 Simulated: Live E-commerce Sales Feed (updates every 5 seconds)",
+                "refresh_seconds": 5,
             }
         ],
         "usage": "Click any example to load it, or enter a custom URL. Set auto-refresh to watch data change over time."
diff --git a/py-src/data_formulator/example_datasets_config.py b/py-src/data_formulator/example_datasets_config.py
index 7991603..610e2be 100644
--- a/py-src/data_formulator/example_datasets_config.py
+++ b/py-src/data_formulator/example_datasets_config.py
@@ -414,94 +414,6 @@
             }
         ]
     },
-    # ==========================================================================
-    # LIVE DATA EXAMPLES - Auto-refresh streaming datasets
-    # ==========================================================================
-    {
-        'source': 'demo',
-        'name': 'Live Sales Feed (Live)',
-        'description': 'Simulated e-commerce transactions with product details, regions, and channels. Updates every 1 second.',
-        'live': True,
-        'refreshIntervalSeconds': 1,
-        'tables': [
-            {
-                "format": 'csv',
-                "url": '/api/demo-stream/live-sales',
-                "sample": '''transaction_id,timestamp,product,category,quantity,unit_price,discount_pct,total,region,channel
-TX123456,2024-01-15T10:30:00Z,Wireless Headphones,Electronics,2,71.99,10,143.98,North America,Web
-TX123457,2024-01-15T10:29:45Z,Running Shoes,Sports,1,129.99,0,129.99,Europe,Mobile App
-TX123458,2024-01-15T10:29:30Z,Coffee Maker,Home,1,80.99,10,80.99,Asia Pacific,Web'''
-            }
-        ]
-    },
-    {
-        'source': 'open-notify.org',
-        'name': 'ISS Location (Live)',
-        'description': 'Real-time International Space Station position trajectory. Updates every 5 seconds.',
-        'live': True,
-        'refreshIntervalSeconds': 5,
-        'tables': [
-            {
-                "format": 'csv',
-                "url": '/api/demo-stream/iss',
-                "sample": '''timestamp,latitude,longitude,fetched_at
-2024-01-15T10:30:00Z,45.234,-122.456,2024-01-15T10:30:00Z
-2024-01-15T10:29:55Z,45.123,-122.345,2024-01-15T10:29:55Z
-2024-01-15T10:29:50Z,45.012,-122.234,2024-01-15T10:29:50Z'''
-            }
-        ]
-    },
-    {
-        'source': 'USGS',
-        'name': 'Earthquakes (Live)',
-        'description': 'Real-time earthquake data from USGS. New quakes appear over time. Updates every 60 seconds.',
-        'live': True,
-        'refreshIntervalSeconds': 60,
-        'tables': [
-            {
-                "format": 'csv',
-                "url": '/api/demo-stream/earthquakes?timeframe=hour',
-                "sample": '''id,time,latitude,longitude,depth_km,magnitude,place,type,status,felt,cdi,mmi,tsunami,sig,net,code,url,fetched_at
-us7000abc1,2024-01-15T10:25:00Z,36.234,-117.456,5.2,2.5,"10km N of Ridgecrest, CA",earthquake,reviewed,,,0,0,125,us,abc1,https://earthquake.usgs.gov/earthquakes/eventpage/us7000abc1,2024-01-15T10:30:00Z
-us7000abc2,2024-01-15T10:15:00Z,61.123,-150.345,45.8,3.1,"50km S of Anchorage, AK",earthquake,automatic,5,,0,0,180,us,abc2,https://earthquake.usgs.gov/earthquakes/eventpage/us7000abc2,2024-01-15T10:30:00Z'''
-            }
-        ]
-    },
-    {
-        'source': 'Open-Meteo',
-        'name': 'Weather (Live)',
-        'description': 'Current weather conditions for major US cities. Updates every 5 minutes.',
-        'live': True,
-        'refreshIntervalSeconds': 300,
-        'tables': [
-            {
-                "format": 'csv',
-                "url": '/api/demo-stream/weather',
-                "sample": '''city,latitude,longitude,temperature_c,humidity_percent,wind_speed_kmh,precipitation_mm,fetched_at
-Seattle,47.6062,-122.3321,8.5,72,12.5,0.2,2024-01-15T10:30:00Z
-New York,40.7128,-74.006,2.3,65,18.2,0.0,2024-01-15T10:30:00Z
-Los Angeles,34.0522,-118.2437,15.8,55,8.3,0.0,2024-01-15T10:30:00Z'''
-            }
-        ]
-    },
-    {
-        'source': 'yfinance',
-        'name': 'Stock Prices (Live)',
-        'description': 'Stock prices with 6 months of daily history + recent 15-minute intraday data. Updates every 5 minutes during market hours.',
-        'live': True,
-        'refreshIntervalSeconds': 300,
-        'tables': [
-            {
-                "format": 'csv',
-                "url": '/api/demo-stream/yfinance?symbols=AAPL,MSFT,GOOGL,NVDA',
-                "sample": '''symbol,timestamp,date,open,high,low,close,volume,data_type,fetched_at
-AAPL,2024-01-15 14:30:00,2024-01-15,185.50,186.20,185.30,185.95,1234567,intraday,2024-01-15T19:35:00Z
-MSFT,2024-01-15 14:30:00,2024-01-15,388.75,389.50,388.25,389.10,987654,intraday,2024-01-15T19:35:00Z
-GOOGL,2024-01-15 14:30:00,2024-01-15,141.20,141.80,141.00,141.55,654321,intraday,2024-01-15T19:35:00Z
-NVDA,2024-01-15 14:30:00,2024-01-15,545.20,548.80,544.50,547.35,2345678,intraday,2024-01-15T19:35:00Z'''
-            }
-        ]
-    }
 ]
 
 
diff --git a/src/app/dfSlice.tsx b/src/app/dfSlice.tsx
index e1a17e3..0daab0b 100644
--- a/src/app/dfSlice.tsx
+++ b/src/app/dfSlice.tsx
@@ -182,6 +182,55 @@ let getUnrefedDerivedTableIds = (state: DataFormulatorState) => {
     let tableWithDescendants = state.tables.filter(table => state.tables.some(t => t.derive?.trigger.tableId == table.id)).map(t => t.id);
 
     return state.tables.filter(table => table.derive && !tableWithDescendants.includes(table.id) && !chartRefedTables.includes(table.id)).map(t => t.id);
+}
+
+// Helper function to auto-populate latitude/longitude encodings for map charts
+let autoPopulateMapEncodings = (chart: Chart, table: DictTable | undefined, conceptShelfItems: FieldItem[]) => {
+    if (!table) return;
+    
+    // Patterns to match latitude/longitude column names
+    const latPatterns = ['latitude', 'lat'];
+    const lonPatterns = ['longitude', 'lon', 'lng', 'long'];
+    
+    // Find latitude column (exact match first, then partial match)
+    let latColumn = table.names.find(name => 
+        latPatterns.some(p => name.toLowerCase() === p)
+    );
+    if (!latColumn) {
+        latColumn = table.names.find(name => 
+            latPatterns.some(p => name.toLowerCase().includes(p))
+        );
+    }
+    
+    // Find longitude column (exact match first, then partial match)
+    let lonColumn = table.names.find(name => 
+        lonPatterns.some(p => name.toLowerCase() === p)
+    );
+    if (!lonColumn) {
+        lonColumn = table.names.find(name => 
+            lonPatterns.some(p => name.toLowerCase().includes(p))
+        );
+    }
+    
+    // Auto-populate latitude encoding if found and not already set
+    if (latColumn && chart.encodingMap.latitude?.fieldID == undefined) {
+        const latField = conceptShelfItems.find(f => 
+            f.name === latColumn && table.names.includes(f.name)
+        );
+        if (latField) {
+            chart.encodingMap.latitude = { fieldID: latField.id };
+        }
+    }
+    
+    // Auto-populate longitude encoding if found and not already set
+    if (lonColumn && chart.encodingMap.longitude?.fieldID == undefined) {
+        const lonField = conceptShelfItems.find(f => 
+            f.name === lonColumn && table.names.includes(f.name)
+        );
+        if (lonField) {
+            chart.encodingMap.longitude = { fieldID: lonField.id };
+        }
+    }
 } 
 
 let deleteChartsRoutine = (state: DataFormulatorState, chartIds: string[]) => {
@@ -603,6 +652,13 @@ export const dataFormulatorSlice = createSlice({
             let chartType = action.payload.chartType;
             let tableId = action.payload.tableId || state.tables[0].id;
             let freshChart = generateFreshChart(tableId, chartType, "user") as Chart;
+            
+            // Auto-populate latitude/longitude for map charts
+            if (chartType.toLowerCase().includes('map')) {
+                let table = state.tables.find(t => t.id === tableId);
+                autoPopulateMapEncodings(freshChart, table, state.conceptShelfItems);
+            }
+            
             state.charts = [ freshChart , ...state.charts];
             state.focusedTableId = tableId;
             state.focusedChartId = freshChart.id;
@@ -652,6 +708,14 @@ export const dataFormulatorSlice = createSlice({
             let chart = dfSelectors.getAllCharts(state).find(c => c.id == chartId);
             if (chart) {
                 chart = adaptChart(chart, getChartTemplate(chartType) as ChartTemplate);
+                
+                // Auto-populate latitude/longitude for map charts
+                if (chartType.toLowerCase().includes('map')) {
+                    let allCharts = dfSelectors.getAllCharts(state);
+                    let table = getDataTable(chart, state.tables, allCharts, state.conceptShelfItems);
+                    autoPopulateMapEncodings(chart, table, state.conceptShelfItems);
+                }
+                
                 dfSelectors.replaceChart(state, chart);
             }
         },
diff --git a/src/app/utils.tsx b/src/app/utils.tsx
index 8eb2148..3412b06 100644
--- a/src/app/utils.tsx
+++ b/src/app/utils.tsx
@@ -688,7 +688,17 @@ export const assembleVegaChart = (
         if (temporalKeys.length > 0) {
             values = values.map((r: any) => { 
                 for (let temporalKey of temporalKeys) {
-                    r[temporalKey] = String(r[temporalKey]);
+                    const val = r[temporalKey];
+                    // Convert numeric timestamps to ISO date strings for Vega-Lite compatibility
+                    if (typeof val === 'number') {
+                        // Detect if timestamp is in seconds (10 digits) or milliseconds (13 digits)
+                        const timestamp = val < 1e12 ? val * 1000 : val;
+                        r[temporalKey] = new Date(timestamp).toISOString();
+                    } else if (val instanceof Date) {
+                        r[temporalKey] = val.toISOString();
+                    } else {
+                        r[temporalKey] = String(val);
+                    }
                 }
                 return r;
             })
diff --git a/src/assets/chart-icon-world-map-min.png b/src/assets/chart-icon-world-map-min.png
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diff --git a/src/components/ChartTemplates.tsx b/src/components/ChartTemplates.tsx
index 980770b..c26575e 100644
--- a/src/components/ChartTemplates.tsx
+++ b/src/components/ChartTemplates.tsx
@@ -28,6 +28,7 @@ import chartIconCustomArea from '../assets/chart-icon-custom-area-min.png';
 import chartIconPie from '../assets/chart-icon-pie-min.png';
 import chartIconUSMap from '../assets/chart-icon-us-map-min.png';
 import chartIconPyramid from '../assets/chart-icon-pyramid-min.png';
+import chartIconWorldMap from '../assets/chart-icon-world-map-min.png';
 
 // Chart Icon Component using static imports
 const ChartIcon: React.FC<{ src: string; alt?: string }> = ({ src, alt = "" }) => {
@@ -385,7 +386,7 @@ const barCharts: ChartTemplate[] = [
 
 const mapCharts: ChartTemplate[] = [
     {
-        "chart": "US Map with Points",
+        "chart": "US Map",
         "icon": <ChartIcon src={chartIconUSMap} />,
         "template": {
             "width": 500,
@@ -429,6 +430,52 @@ const mapCharts: ChartTemplate[] = [
             "color": ["layer", 1, "encoding", "color"],
             "size": ["layer", 1, "encoding", "size"]
         }
+    },
+    {
+        "chart": "World Map",
+        "icon": <ChartIcon src={chartIconWorldMap} />,
+        "template": {
+            "width": 600,
+            "height": 350,
+            "layer": [
+                {
+                    "data": {
+                        "url": "https://vega.github.io/vega-lite/data/world-110m.json",
+                        "format": {
+                            "type": "topojson",
+                            "feature": "countries"
+                        }
+                    },
+                    "projection": {
+                        "type": "equalEarth"
+                    },
+                    "mark": {
+                        "type": "geoshape",
+                        "fill": "lightgray",
+                        "stroke": "white"
+                    }
+                },
+                {
+                    "projection": {
+                        "type": "equalEarth"
+                    },
+                    "mark": "circle",
+                    "encoding": {
+                        "longitude": { },
+                        "latitude": { },
+                        "size": {},
+                        "color": {}
+                    }
+                }
+            ]
+        },
+        "channels": ["longitude", "latitude", "color", "size"],
+        "paths": {
+            "longitude": ["layer", 1, "encoding", "longitude"],
+            "latitude": ["layer", 1, "encoding", "latitude"],
+            "color": ["layer", 1, "encoding", "color"],
+            "size": ["layer", 1, "encoding", "size"]
+        }
     }
 ]
 
diff --git a/src/views/DBTableManager.tsx b/src/views/DBTableManager.tsx
index 449700f..64662a9 100644
--- a/src/views/DBTableManager.tsx
+++ b/src/views/DBTableManager.tsx
@@ -44,6 +44,7 @@ import ExpandMoreIcon from '@mui/icons-material/ExpandMore';
 import TableRowsIcon from '@mui/icons-material/TableRows';
 import RefreshIcon from '@mui/icons-material/Refresh';
 import SearchIcon from '@mui/icons-material/Search';
+import StreamIcon from '@mui/icons-material/Stream';
 
 import { getUrls, fetchWithSession } from '../app/utils';
 import { CustomReactTable } from './ReactTable';
@@ -186,10 +187,7 @@ export const DBManagerPane: React.FC<{
     const serverConfig = useSelector((state: DataFormulatorState) => state.serverConfig);
     const dataLoaderConnectParams = useSelector((state: DataFormulatorState) => state.dataLoaderConnectParams);
 
-    
-    // Support both controlled and uncontrolled modes
-    const [tableAnalysisMap, setTableAnalysisMap] = useState<Record<string, ColumnStatistics[] | null>>({});
-    
+
     // maps data loader type to list of param defs
     const [dataLoaderMetadata, setDataLoaderMetadata] = useState<Record<string, {
         params: {name: string, default: string, type: string, required: boolean, description: string}[], 
@@ -209,12 +207,12 @@ export const DBManagerPane: React.FC<{
     
     // Watch/auto-refresh settings for the currently selected table
     const [watchEnabled, setWatchEnabled] = useState<boolean>(false);
-    const [watchInterval, setWatchInterval] = useState<number>(60);
+    const [watchInterval, setWatchInterval] = useState<number>(600);
     
     // Reset watch settings when selected table changes
     useEffect(() => {
         setWatchEnabled(false);
-        setWatchInterval(60);
+        setWatchInterval(600);
     }, [selectedTabKey]);
     
     // Helper to format interval for display
@@ -421,40 +419,6 @@ export const DBManagerPane: React.FC<{
         }
     };
 
-    // Handle data analysis - auto-fetch when table is selected
-    const handleAnalyzeData = useCallback(async (tableName: string) => {
-        if (!tableName) return;
-        if (tableAnalysisMap[tableName]) return;
-
-        try {
-            const response = await fetchWithSession(getUrls().GET_COLUMN_STATS, {
-                method: 'POST',
-                headers: {
-                    'Content-Type': 'application/json',
-                },
-                body: JSON.stringify({ table_name: tableName })
-            }, dispatch);
-            const data = await response.json();
-            if (data.status === 'success') {
-                // Update the analysis map with the new results
-                setTableAnalysisMap(prevMap => ({
-                    ...prevMap,
-                    [tableName]: data.statistics
-                }));
-            }
-        } catch (error) {
-            console.error('Failed to analyze table data:', error);
-            // Don't show error message for auto-fetch, just fail silently
-        }
-    }, [tableAnalysisMap]);
-
-    // Auto-fetch stats when a table is selected
-    useEffect(() => {
-        if (selectedTabKey && selectedDataLoader === "") {
-            handleAnalyzeData(selectedTabKey);
-        }
-    }, [selectedTabKey, selectedDataLoader, handleAnalyzeData]);
-
     const handleAddTableToDF = (dbTable: DBTable, refreshSettings?: {autoRefresh: boolean, refreshIntervalSeconds: number}) => {
         const convertSqlTypeToAppType = (sqlType: string): Type => {
             // Convert SQL types to application types
@@ -933,8 +897,6 @@ export const DBManagerPane: React.FC<{
             if (selectedTabKey !== t.name) return null;
             
             const currentTable = t;
-            const columnStats = tableAnalysisMap[currentTable.name] ?? [];
-            const statsMap = new Map(columnStats.map((stat: ColumnStatistics) => [stat.column, stat]));
             
             return (
                 <Box key={t.name} sx={{ maxWidth: '100%', overflowX: 'auto', display: 'flex', flexDirection: 'column', gap: 1 }}>
@@ -957,87 +919,33 @@ export const DBManagerPane: React.FC<{
                             </IconButton>
                         </Tooltip>
                     </Box>
-                    <Box sx={{ border: '1px solid', borderColor: 'divider', borderRadius: 1, p: 1 }}>
-                        <Box sx={{ position: 'relative' }}>
-                            <TableContainer sx={{ maxHeight: 340, overflow: 'auto' }}>
-                                <Table stickyHeader aria-label="sticky table" size="small">
-                                    <TableHead>
-                                        <TableRow>
-                                            {currentTable.columns.map((col) => {
-                                                const stat = statsMap.get(col.name);
-                                                return (
-                                                    <TableCell
-                                                        key={col.name}
-                                                        sx={{
-                                                            minWidth: 80,
-                                                            fontSize: 10,
-                                                            color: "#333",
-                                                            backgroundColor: '#fff',
-                                                            borderBottomColor: theme.palette.primary.main,
-                                                            borderBottomWidth: '1px',
-                                                            borderBottomStyle: 'solid',
-                                                            padding: '4px 6px',
-                                                            verticalAlign: 'top'
-                                                        }}
-                                                    >
-                                                        <Box sx={{ display: 'flex', flexDirection: 'column', gap: 0.5 }}>
-                                                            <Typography sx={{ fontSize: 11, fontWeight: 600, lineHeight: 1.2 }}>
-                                                                {col.name}
-                                                            </Typography>
-                                                            {stat ? (
-                                                                <Typography sx={{ fontSize: 9, color: 'text.secondary', lineHeight: 1.2 }}>
-                                                                    {stat.type}
-                                                                </Typography>
-                                                            ) : (
-                                                                <Typography sx={{ fontSize: 9, color: 'text.disabled', lineHeight: 1.2, fontStyle: 'italic' }}>
-                                                                    {col.type}
-                                                                </Typography>
-                                                            )}
-                                                        </Box>
-                                                    </TableCell>
-                                                );
-                                            })}
-                                        </TableRow>
-                                    </TableHead>
-                                    <TableBody>
-                                        {currentTable.sample_rows.slice(0, 9).map((row: any, rowIdx: number) => (
-                                            <TableRow 
-                                                hover 
-                                                tabIndex={-1} 
-                                                key={rowIdx} 
-                                                sx={{ background: rowIdx % 2 == 0 ? '#F0F0F0' : "none" }}
-                                            >
-                                                {currentTable.columns.map((col) => {
-                                                    const value = row[col.name];
-                                                    return (
-                                                        <TableCell
-                                                            key={col.name}
-                                                            sx={{
-                                                                fontSize: 10,
-                                                                maxWidth: "80px",
-                                                                padding: "6px",
-                                                                overflow: "clip",
-                                                                textOverflow: "ellipsis",
-                                                                whiteSpace: "nowrap"
-                                                            }}
-                                                        >
-                                                            {String(value ?? '')}
-                                                        </TableCell>
-                                                    );
-                                                })}
-                                            </TableRow>
-                                        ))}
-                                    </TableBody>
-                                </Table>
-                            </TableContainer>
-                            {currentTable.row_count > 10 && (
-                                <Box sx={{ px: 1, py: 0.5}}>
-                                    <Typography variant="caption" sx={{ fontSize: 9, color: 'text.secondary', fontStyle: 'italic' }}>
-                                        Showing first 9 rows of {currentTable.row_count} total rows
-                                    </Typography>
-                                </Box>
-                            )}
-                        </Box>
+                    <Box sx={{ }}>
+                        <Card variant="outlined" sx={{ position: 'relative' }}>
+                            <CustomReactTable
+                                rows={currentTable.sample_rows.slice(0, 9).map((row: any) => {
+                                    return Object.fromEntries(
+                                        currentTable.columns.map((col) => [col.name, String(row[col.name] ?? '')])
+                                    );
+                                })}
+                                columnDefs={currentTable.columns.map((col) => ({
+                                    id: col.name,
+                                    label: col.name,
+                                    minWidth: 80
+                                }))}
+                                rowsPerPageNum={-1}
+                                compact={false}
+                                maxCellWidth={80}
+                                isIncompleteTable={currentTable.row_count > 10}
+                                maxHeight={340}
+                            />
+                        </Card>
+                        {currentTable.row_count > 10 && (
+                            <Box sx={{ px: 1, py: 0.5}}>
+                                <Typography variant="caption" sx={{ fontSize: 9, color: 'text.secondary', fontStyle: 'italic' }}>
+                                    Showing first 9 rows of {currentTable.row_count} total rows
+                                </Typography>
+                            </Box>
+                        )}
                     </Box>
                     {tables.some(t => t.id === currentTable.name) ? (
                         <Box 
@@ -1057,58 +965,64 @@ export const DBManagerPane: React.FC<{
                             </Typography>
                         </Box>
                     ) : (
-                        <Box sx={{ ml: 2, display: 'flex', flexDirection: 'row', gap: 1 }}>
+                        <Box sx={{  display: 'flex', flexDirection: 'row', alignItems: 'center', gap: 1, mt: 2 }}>
                             {/* Watch settings - only show for tables that can be refreshed */}
                             {currentTable.source_metadata && (
-                                <Box sx={{ display: 'flex', gap: 1 }}>
-                                    <FormControlLabel
-                                        control={
-                                            <Switch
-                                                checked={watchEnabled}
-                                                onChange={(e) => setWatchEnabled(e.target.checked)}
-                                                size="small"
-                                            />
-                                        }
-                                        label={
-                                            <Typography variant="body2" sx={{ fontSize: 12 }}>
-                                                Watch for updates
-                                            </Typography>
-                                        }
-                                        sx={{ mr: 0 }}
-                                    />
-                                    {watchEnabled && (
-                                        <Box sx={{ display: 'flex', alignItems: 'center', gap: 0.5, minWidth: 100 }}>
-                                            <Typography variant="body2" sx={{ fontSize: 11, color: 'text.secondary' }}>
-                                                every
-                                            </Typography>
-                                            <TextField
-                                                select
-                                                size="small"
-                                                value={watchInterval}
-                                                onChange={(e) => setWatchInterval(Number(e.target.value))}
-                                                sx={{ 
-                                                    minWidth: 70,
-                                                    '& .MuiInputBase-root': { fontSize: 11, height: 28 },
-                                                    '& .MuiSelect-select': { py: 0.5 }
-                                                }}
-                                            >
-                                                <MenuItem value={1}>1s</MenuItem>
-                                                <MenuItem value={10}>10s</MenuItem>
-                                                <MenuItem value={30}>30s</MenuItem>
-                                                <MenuItem value={60}>1m</MenuItem>
-                                                <MenuItem value={300}>5m</MenuItem>
-                                                <MenuItem value={600}>10m</MenuItem>
-                                                <MenuItem value={1800}>30m</MenuItem>
-                                                <MenuItem value={3600}>1h</MenuItem>
-                                            </TextField>
-                                        </Box>
-                                    )}
-                                </Box>
+                                <Paper variant="outlined" sx={{ px: 2, py: 1, borderRadius: 1 }}>
+                                    <Box sx={{ display: 'flex', flexDirection: 'row', gap: 1, alignItems: 'center', height: 24 }}>
+                                        <FormControlLabel
+                                            control={
+                                                <Switch
+                                                    checked={watchEnabled}
+                                                    onChange={(e) => setWatchEnabled(e.target.checked)}
+                                                    size="small"
+                                                />
+                                            }
+                                            label={
+                                                <Typography component="span" variant="body2" sx={{ fontWeight: 500 }}>
+                                                    Watch Mode
+                                                </Typography>
+                                            }
+                                        />
+                                        {watchEnabled ? (
+                                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, }}>
+                                                <Typography variant="body2" color="text.secondary" sx={{ fontSize: '0.8rem' }}>
+                                                    check for updates every
+                                                </Typography>
+                                                {[
+                                                    { seconds: 10, label: '10s' },
+                                                    { seconds: 30, label: '30s' },
+                                                    { seconds: 60, label: '1m' },
+                                                    { seconds: 300, label: '5m' },
+                                                    { seconds: 600, label: '10m' },
+                                                    { seconds: 1800, label: '30m' },
+                                                    { seconds: 3600, label: '1h' },
+                                                    { seconds: 86400, label: '24h' },
+                                                ].map((opt) => (
+                                                    <Chip
+                                                        key={opt.seconds}
+                                                        label={opt.label}
+                                                        size="small"
+                                                        variant={watchInterval === opt.seconds ? 'filled' : 'outlined'}
+                                                        color={watchInterval === opt.seconds ? 'primary' : 'default'}
+                                                        onClick={() => setWatchInterval(opt.seconds)}
+                                                        sx={{ 
+                                                            cursor: 'pointer', 
+                                                            fontSize: '0.7rem',
+                                                            height: 24,
+                                                        }}
+                                                    />
+                                                ))}
+                                            </Box>
+                                        ) : <Typography component="span" variant="caption" color="text.secondary">
+                                            automatically check and refresh data from the database at regular intervals
+                                        </Typography>}
+                                    </Box>
+                                </Paper>
                             )}
                             <Button 
                                 variant="contained"
-                                size="small"
-                                sx={{ textTransform: 'none', ml: 'auto' }}
+                                sx={{ textTransform: 'none', ml: 'auto'}}
                                 disabled={isUploading || dbTables.length === 0 || dbTables.find(t => t.name === selectedTabKey) === undefined}
                                 onClick={() => {
                                     let t = dbTables.find(t => t.name === selectedTabKey);
@@ -1119,7 +1033,7 @@ export const DBManagerPane: React.FC<{
                                         } : undefined);
                                     }
                                 }}>
-                                Load {watchEnabled? 'Streaming' : ''} Table {watchEnabled && currentTable.source_metadata ? `(watching every ${formatInterval(watchInterval)})` : ''}
+                                Load {watchEnabled? 'Live' : ''} Table
                             </Button>
                         </Box>
                     )}
diff --git a/src/views/DataFormulator.tsx b/src/views/DataFormulator.tsx
index a4441ad..35b9130 100644
--- a/src/views/DataFormulator.tsx
+++ b/src/views/DataFormulator.tsx
@@ -18,7 +18,6 @@ import { Allotment } from "allotment";
 import "allotment/dist/style.css";
 
 import {
-
     Typography,
     Box,
     Tooltip,
@@ -27,13 +26,6 @@ import {
     useTheme,
     alpha,
 } from '@mui/material';
-import {
-    FolderOpen as FolderOpenIcon,
-    ContentPaste as ContentPasteIcon,
-    Category as CategoryIcon,
-    CloudQueue as CloudQueueIcon,
-    AutoFixNormal as AutoFixNormalIcon,
-} from '@mui/icons-material';
 
 import { FreeDataViewFC } from './DataView';
 import { VisualizationViewFC } from './VisualizationView';
@@ -48,7 +40,7 @@ import dfLogo from '../assets/df-logo.png';
 import exampleImageTable from "../assets/example-image-table.png";
 import { ModelSelectionButton } from './ModelSelectionDialog';
 import { getUrls } from '../app/utils';
-import { UnifiedDataUploadDialog, UploadTabType } from './UnifiedDataUploadDialog';
+import { UnifiedDataUploadDialog, UploadTabType, DataLoadMenu } from './UnifiedDataUploadDialog';
 import { ReportView } from './ReportView';
 import { ExampleSession, exampleSessions, ExampleSessionCard } from './ExampleSessions';
 import { useDataRefresh, useDerivedTableRefresh } from '../app/useDataRefresh';
@@ -59,6 +51,7 @@ export const DataFormulatorFC = ({ }) => {
     const models = useSelector((state: DataFormulatorState) => state.models);
     const selectedModelId = useSelector((state: DataFormulatorState) => state.selectedModelId);
     const viewMode = useSelector((state: DataFormulatorState) => state.viewMode);
+    const serverConfig = useSelector((state: DataFormulatorState) => state.serverConfig);
     const theme = useTheme();
 
     const dispatch = useDispatch();
@@ -286,28 +279,11 @@ export const DataFormulatorFC = ({ }) => {
                 Explore data with visualizations, powered by AI agents. 
             </Typography>
             <Box sx={{my: 4}}>
-                <Typography sx={{ 
-                    maxWidth: 1100, fontSize: 32, color: alpha(theme.palette.text.primary, 0.8), 
-                    lineHeight: 2,
-                    '& span': { 
-                        textTransform: 'uppercase',
-                        letterSpacing: '0.02em',
-                        textDecoration: 'underline', textUnderlineOffset: '0.2em', 
-                        cursor: 'pointer', color: theme.palette.primary.main,
-                        '&:hover': {
-                            color: theme.palette.primary.dark,
-                        }
-                    }}}>
-                    To begin, 
-                    {' '}<span onClick={() => openUploadDialog('extract')}>extract</span>{' '}
-                    data from images or text documents, load {' '}
-                    {' '}<span onClick={() => openUploadDialog('explore')}>examples</span>{' '}, 
-                    upload data from{' '}
-                    {' '}<span onClick={() => openUploadDialog('paste')}>clipboard</span> or {' '}
-                    {' '}<span onClick={() => openUploadDialog('upload')}>files</span>{' '}, 
-                    or connect to a{' '}
-                    {' '}<span onClick={() => openUploadDialog('database')}>database</span>{' '}.
-                </Typography>
+                <DataLoadMenu 
+                    onSelectTab={(tab) => openUploadDialog(tab)}
+                    serverConfig={serverConfig}
+                    variant="page"
+                />
                 <UnifiedDataUploadDialog 
                     open={uploadDialogOpen}
                     onClose={() => setUploadDialogOpen(false)}
diff --git a/src/views/DataThread.tsx b/src/views/DataThread.tsx
index 5a2077b..3cffa9a 100644
--- a/src/views/DataThread.tsx
+++ b/src/views/DataThread.tsx
@@ -76,6 +76,7 @@ import { RefreshDataDialog } from './RefreshDataDialog';
 import { getUrls } from '../app/utils';
 import { AppDispatch } from '../app/store';
 import StopIcon from '@mui/icons-material/Stop';
+import { useDataRefresh } from '../app/useDataRefresh';
 
 export const ThinkingBanner = (message: string, sx?: SxProps) => (
     <Box sx={{ 
@@ -129,7 +130,8 @@ const StreamingSettingsPopup = memo<{
     onClose: () => void;
     table: DictTable;
     onUpdateSettings: (autoRefresh: boolean, refreshIntervalSeconds?: number) => void;
-}>(({ open, anchorEl, onClose, table, onUpdateSettings }) => {
+    onRefreshNow?: () => void;
+}>(({ open, anchorEl, onClose, table, onUpdateSettings, onRefreshNow }) => {
     const [refreshInterval, setRefreshInterval] = useState<number>(
         table.source?.refreshIntervalSeconds || 60
     );
@@ -137,6 +139,7 @@ const StreamingSettingsPopup = memo<{
         table.source?.autoRefresh || false
     );
     const [selectMenuOpen, setSelectMenuOpen] = useState<boolean>(false);
+    const [isRefreshing, setIsRefreshing] = useState<boolean>(false);
 
     useEffect(() => {
         if (open) {
@@ -160,6 +163,17 @@ const StreamingSettingsPopup = memo<{
         }
     };
 
+    const handleRefreshNow = async () => {
+        if (onRefreshNow && !isRefreshing) {
+            setIsRefreshing(true);
+            try {
+                await onRefreshNow();
+            } finally {
+                setIsRefreshing(false);
+            }
+        }
+    };
+
     const handleClickAway = (event: MouseEvent | TouchEvent) => {
         // Don't close if the select menu is open
         if (selectMenuOpen) {
@@ -196,56 +210,76 @@ const StreamingSettingsPopup = memo<{
                         borderColor: 'divider'
                     }}
                 >
-                    <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, flexWrap: 'nowrap' }}>
-                        <FormControlLabel
-                            control={
-                                <Switch
-                                    checked={autoRefresh}
-                                    onChange={(e) => handleAutoRefreshChange(e.target.checked)}
-                                    size="small"
-                                />
-                            }
-                            label={
-                                <Typography variant="body2" sx={{ fontSize: 11 }}>
-                                    Watch for updates
-                                </Typography>
-                            }
-                            sx={{ mr: 0 }}
-                        />
-                        {autoRefresh && (
-                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 0.5, minWidth: 100 }}>
-                                <Typography variant="body2" sx={{ fontSize: 11, color: 'text.secondary' }}>
-                                    every
-                                </Typography>
-                                <TextField
-                                    select
+                    <Box sx={{ display: 'flex', flexDirection: 'column', gap: 1 }}>
+                        <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, flexWrap: 'nowrap' }}>
+                            <FormControlLabel
+                                control={
+                                    <Switch
+                                        checked={autoRefresh}
+                                        onChange={(e) => handleAutoRefreshChange(e.target.checked)}
+                                        size="small"
+                                    />
+                                }
+                                label={
+                                    <Typography variant="body2" sx={{ fontSize: 11 }}>
+                                        Watch for updates
+                                    </Typography>
+                                }
+                                sx={{ mr: 0 }}
+                            />
+                            {autoRefresh && (
+                                <Box sx={{ display: 'flex', alignItems: 'center', gap: 0.5, minWidth: 100 }}>
+                                    <Typography variant="body2" sx={{ fontSize: 11, color: 'text.secondary' }}>
+                                        every
+                                    </Typography>
+                                    <TextField
+                                        select
+                                        size="small"
+                                        value={refreshInterval}
+                                        onChange={(e) => handleIntervalChange(Number(e.target.value))}
+                                        slotProps={{
+                                            select: {
+                                                open: selectMenuOpen,
+                                                onOpen: () => setSelectMenuOpen(true),
+                                                onClose: () => setSelectMenuOpen(false)
+                                            }
+                                        }}
+                                        sx={{ 
+                                            minWidth: 70,
+                                            '& .MuiInputBase-root': { fontSize: 11, height: 28 },
+                                            '& .MuiSelect-select': { py: 0.5 }
+                                        }}
+                                    >
+                                        <MenuItem value={1}>1s</MenuItem>
+                                        <MenuItem value={10}>10s</MenuItem>
+                                        <MenuItem value={30}>30s</MenuItem>
+                                        <MenuItem value={60}>1m</MenuItem>
+                                        <MenuItem value={300}>5m</MenuItem>
+                                        <MenuItem value={600}>10m</MenuItem>
+                                        <MenuItem value={1800}>30m</MenuItem>
+                                        <MenuItem value={3600}>1h</MenuItem>
+                                        <MenuItem value={86400}>24h</MenuItem>
+                                    </TextField>
+                                </Box>
+                            )}
+                            {onRefreshNow && (
+                                <Button
+                                    variant="outlined"
                                     size="small"
-                                    value={refreshInterval}
-                                    onChange={(e) => handleIntervalChange(Number(e.target.value))}
-                                    slotProps={{
-                                        select: {
-                                            open: selectMenuOpen,
-                                            onOpen: () => setSelectMenuOpen(true),
-                                            onClose: () => setSelectMenuOpen(false)
-                                        }
-                                    }}
-                                    sx={{ 
-                                        minWidth: 70,
-                                        '& .MuiInputBase-root': { fontSize: 11, height: 28 },
-                                        '& .MuiSelect-select': { py: 0.5 }
+                                    onClick={handleRefreshNow}
+                                    disabled={isRefreshing}
+                                    startIcon={isRefreshing ? <CircularProgress size={14} /> : <RefreshIcon sx={{ fontSize: 14 }} />}
+                                    sx={{
+                                        fontSize: 11,
+                                        textTransform: 'none',
+                                        height: 28,
+                                        alignSelf: 'flex-start'
                                     }}
                                 >
-                                    <MenuItem value={1}>1s</MenuItem>
-                                    <MenuItem value={10}>10s</MenuItem>
-                                    <MenuItem value={30}>30s</MenuItem>
-                                    <MenuItem value={60}>1m</MenuItem>
-                                    <MenuItem value={300}>5m</MenuItem>
-                                    <MenuItem value={600}>10m</MenuItem>
-                                    <MenuItem value={1800}>30m</MenuItem>
-                                    <MenuItem value={3600}>1h</MenuItem>
-                                </TextField>
-                            </Box>
-                        )}
+                                    Refresh now
+                                </Button>
+                            )}
+                        </Box>
                     </Box>
                 </Paper>
             </ClickAwayListener>
@@ -668,6 +702,7 @@ let SingleThreadGroupView: FC<{
 }) {
 
     let tables = useSelector((state: DataFormulatorState) => state.tables);
+    const { manualRefresh } = useDataRefresh();
 
     let leafTableIds = leafTables.map(lt => lt.id);
     let parentTableId = leafTables[0].derive?.trigger.tableId || undefined;
@@ -1324,6 +1359,7 @@ let SingleThreadGroupView: FC<{
                         onClose={handleCloseStreamingSettingsPopup}
                         table={selectedTableForStreamingSettings}
                         onUpdateSettings={handleUpdateStreamingSettings}
+                        onRefreshNow={() => manualRefresh(selectedTableForStreamingSettings.id)}
                     />
                 )}
             </Box>
@@ -1480,6 +1516,7 @@ let SingleThreadGroupView: FC<{
                 onClose={handleCloseStreamingSettingsPopup}
                 table={selectedTableForStreamingSettings}
                 onUpdateSettings={handleUpdateStreamingSettings}
+                onRefreshNow={() => manualRefresh(selectedTableForStreamingSettings.id)}
             />
         )}
     </Box>
diff --git a/src/views/EncodingShelfThread.tsx b/src/views/EncodingShelfThread.tsx
index d2f6d89..415da04 100644
--- a/src/views/EncodingShelfThread.tsx
+++ b/src/views/EncodingShelfThread.tsx
@@ -173,7 +173,12 @@ export const EncodingShelfThread: FC<EncodingShelfThreadProps> = function ({ cha
     
     const dispatch = useDispatch<AppDispatch>();
 
-    const interleaveArrays: any = (a: any[], b: any[], spaceElement?: any) => a.length ? [a[0], spaceElement || '',...interleaveArrays(b, a.slice(1), spaceElement)] : b;
+    const interleaveArrays: any = (a: any[], b: any[], spaceElement?: any): any[] => {
+        if (a.length === 0) return b;
+        // Filter out null/undefined and empty strings to avoid key warnings
+        const result = [a[0], ...interleaveArrays(b, a.slice(1), spaceElement)];
+        return result.filter(x => x !== null && x !== undefined && x !== '');
+    };
 
     let previousInstructions : any = ""
 
@@ -199,7 +204,7 @@ export const EncodingShelfThread: FC<EncodingShelfThreadProps> = function ({ cha
             return null;
         }
         return buildTableCard(tableId);
-    });
+    }).filter(x => x !== null);
 
     let leafTable = tables.find(t => t.id == activeTableThread[activeTableThread.length - 1]) as DictTable;
 
@@ -237,7 +242,7 @@ export const EncodingShelfThread: FC<EncodingShelfThreadProps> = function ({ cha
     previousInstructions = truncated ? 
         <Box  sx={{padding: '4px 0px', display: 'flex', flexDirection: "column" }}>
             {tableList[0]}
-            <Box sx={{height: '24px', borderLeft: '1px dashed darkgray', 
+            <Box key="truncated-indicator" sx={{height: '24px', borderLeft: '1px dashed darkgray', 
                 position: 'relative',
                 ml: '8px', display: 'flex', alignItems: 'center', cursor: 'pointer',
                 '&:hover': {
@@ -266,7 +271,7 @@ export const EncodingShelfThread: FC<EncodingShelfThreadProps> = function ({ cha
         let leafUserCharts = allCharts.filter(c => c.tableRef == resultTable.id).filter(c => c.source == "user");
 
         let endChartCards = leafUserCharts.map((c) => {
-            return <Card variant="outlined" className={"hover-card"} 
+            return <Card key={`end-chart-${c.id}`} variant="outlined" className={"hover-card"} 
                             onClick={() => { 
                                 dispatch(dfActions.setFocusedChart(c.id));
                                 dispatch(dfActions.setFocusedTable(c.tableRef));
@@ -283,7 +288,7 @@ export const EncodingShelfThread: FC<EncodingShelfThreadProps> = function ({ cha
                                         backgroundSize: '1px 6px, 3px 100%'}}></Box>
             </Box>
             {buildTableCard(resultTable.id)}
-            <Box key="post-instruction" sx={{width: '17px', height: '12px'}}>
+            <Box key="post-instruction-2" sx={{width: '17px', height: '12px'}}>
                 <Box sx={{padding:0, width: '1px', margin:'auto', height: '100%',
                                         backgroundImage: 'linear-gradient(180deg, darkgray, darkgray 75%, transparent 75%, transparent 100%)',
                                         backgroundSize: '1px 6px, 3px 100%'}}></Box>
diff --git a/src/views/MultiTablePreview.tsx b/src/views/MultiTablePreview.tsx
new file mode 100644
index 0000000..55a17c1
--- /dev/null
+++ b/src/views/MultiTablePreview.tsx
@@ -0,0 +1,226 @@
+// Copyright (c) Microsoft Corporation.
+// Licensed under the MIT License.
+
+import * as React from 'react';
+import { useState, useEffect } from 'react';
+import {
+    Box,
+    Chip,
+    IconButton,
+    Typography,
+    Tooltip,
+    LinearProgress,
+    alpha,
+    Card,
+} from '@mui/material';
+import DeleteIcon from '@mui/icons-material/Delete';
+import { DictTable } from '../components/ComponentType';
+import { CustomReactTable } from './ReactTable';
+
+export interface MultiTablePreviewProps {
+    /** Loading state indicator */
+    loading?: boolean;
+    /** Error message to display */
+    error?: string | null;
+    /** Single table for backwards compatibility */
+    table?: DictTable | null;
+    /** Array of tables to preview */
+    tables?: DictTable[] | null;
+    /** Label to show when no tables are available */
+    emptyLabel?: string;
+    /** Optional metadata string to display */
+    meta?: string;
+    /** Callback when a table is removed (enables delete button) */
+    onRemoveTable?: (index: number) => void;
+    /** Controlled active index */
+    activeIndex?: number;
+    /** Callback when active index changes */
+    onActiveIndexChange?: (index: number) => void;
+    /** Maximum height for the table container */
+    maxHeight?: number;
+    /** Maximum number of rows to display */
+    maxRows?: number;
+    /** Whether to use compact mode for the table */
+    compact?: boolean;
+    /** Whether to show the "Preview" label */
+    showPreviewLabel?: boolean;
+}
+
+export const MultiTablePreview: React.FC<MultiTablePreviewProps> = ({
+    loading = false,
+    error = null,
+    table,
+    tables,
+    emptyLabel = 'No tables to preview.',
+    meta,
+    onRemoveTable,
+    activeIndex: controlledActiveIndex,
+    onActiveIndexChange,
+    maxHeight = 200,
+    maxRows = 12,
+    compact = true,
+}) => {
+    const previewTables = tables ?? (table ? [table] : null);
+    const [internalActiveIndex, setInternalActiveIndex] = useState(0);
+    const activeIndex = controlledActiveIndex !== undefined ? controlledActiveIndex : internalActiveIndex;
+    const setActiveIndex = onActiveIndexChange || setInternalActiveIndex;
+
+    useEffect(() => {
+        if (!previewTables || previewTables.length === 0) {
+            if (onActiveIndexChange) {
+                onActiveIndexChange(0);
+            } else {
+                setInternalActiveIndex(0);
+            }
+            return;
+        }
+        if (activeIndex > previewTables.length - 1) {
+            const newIndex = previewTables.length - 1;
+            if (onActiveIndexChange) {
+                onActiveIndexChange(newIndex);
+            } else {
+                setInternalActiveIndex(newIndex);
+            }
+        }
+    }, [previewTables, activeIndex, onActiveIndexChange]);
+
+    const activeTable = previewTables && previewTables.length > 0 ? previewTables[activeIndex] : null;
+
+    return (
+        <Box
+            sx={{
+                p: 1,
+                display: 'flex',
+                flexDirection: 'column',
+                gap: 1,
+                minHeight: 120,
+            }}
+        >
+            {loading && <LinearProgress />}
+
+            {error && (
+                <Typography variant="caption" color="error">
+                    {error}
+                </Typography>
+            )}
+
+            {!loading && !error && (!previewTables || previewTables.length === 0) && (
+                <Typography variant="caption" color="text.secondary">
+                    {emptyLabel}
+                </Typography>
+            )}
+
+            {previewTables && previewTables.length > 0 && (
+                <Box>
+                    {/* Table selection chips */}
+                    <Box
+                        sx={{
+                            display: 'flex',
+                            alignItems: 'center',
+                            flexWrap: 'wrap',
+                            gap: 0.25,
+                            mb: 0.5,
+                            pb: 0.25,
+                        }}
+                    >
+                        <Typography variant="caption" sx={{ mx: 0.5 }}>
+                            Preview
+                        </Typography>
+                        {previewTables.map((t, idx) => {
+                            const label = t.displayId || t.id;
+                            const isSelected = idx === activeIndex;
+                            return (
+                                <Tooltip key={`${t.id}-${idx}`} title={label} placement="top" arrow>
+                                    <Chip
+                                        label={label}
+                                        size="small"
+                                        onClick={() => {
+                                            if (onActiveIndexChange) {
+                                                onActiveIndexChange(idx);
+                                            } else {
+                                                setInternalActiveIndex(idx);
+                                            }
+                                        }}
+                                        sx={{
+                                            borderRadius: 1,
+                                            cursor: 'pointer',
+                                            maxWidth: 160,
+                                            backgroundColor: (theme) =>
+                                                isSelected
+                                                    ? alpha(theme.palette.primary.main, 0.12)
+                                                    : 'transparent',
+                                            borderColor: (theme) =>
+                                                isSelected
+                                                    ? alpha(theme.palette.primary.main, 0.5)
+                                                    : undefined,
+                                            color: (theme) =>
+                                                isSelected
+                                                    ? theme.palette.primary.main
+                                                    : theme.palette.text.secondary,
+                                            '& .MuiChip-label': {
+                                                fontSize: '0.625rem',
+                                                overflow: 'hidden',
+                                                textOverflow: 'ellipsis',
+                                                whiteSpace: 'nowrap',
+                                                maxWidth: 140,
+                                            },
+                                            '&:hover': {
+                                                backgroundColor: (theme) =>
+                                                    isSelected
+                                                        ? alpha(theme.palette.primary.main, 0.16)
+                                                        : alpha(theme.palette.primary.main, 0.08),
+                                            },
+                                        }}
+                                    />
+                                </Tooltip>
+                            );
+                        })}
+                        {onRemoveTable && (
+                            <Tooltip title="Remove table" placement="top" arrow>    
+                                <IconButton
+                                    size="small"
+                                    color="error"
+                                    onClick={() => onRemoveTable(activeIndex)}
+                                    sx={{ ml: 'auto', flexShrink: 0 }}
+                                    aria-label="Remove table"
+                                >
+                                    <DeleteIcon fontSize="small" />
+                                </IconButton>
+                            </Tooltip>
+                        )}
+                    </Box>
+
+                    {activeTable && (
+                        <Box>
+                            <Card variant="outlined" sx={{ pb: 0.5 }}>
+                                <CustomReactTable
+                                    rows={activeTable.rows.slice(0, maxRows)}
+                                    columnDefs={activeTable.names.map(name => ({
+                                        id: name,
+                                        label: name,
+                                        minWidth: 60,
+                                    }))}
+                                    rowsPerPageNum={-1}
+                                    compact={compact}
+                                    isIncompleteTable={activeTable.rows.length > maxRows}
+                                    maxHeight={maxHeight}
+                                />
+                            </Card>
+                            <Typography variant="caption" color="text.secondary">
+                                {activeTable.rows.length} rows × {activeTable.names.length} columns
+                            </Typography>
+                        </Box>
+                    )}
+
+                    {meta && (
+                        <Typography variant="caption" color="text.secondary" sx={{ mt: 0.5, display: 'block' }}>
+                            {meta}
+                        </Typography>
+                    )}
+                </Box>
+            )}
+        </Box>
+    );
+};
+
+export default MultiTablePreview;
diff --git a/src/views/TableSelectionView.tsx b/src/views/TableSelectionView.tsx
index 0d9182a..a7ceab5 100644
--- a/src/views/TableSelectionView.tsx
+++ b/src/views/TableSelectionView.tsx
@@ -2,14 +2,15 @@
 // Licensed under the MIT License.
 
 import * as React from 'react';
-import { useEffect } from 'react';
+import { useEffect, useState, useMemo } from 'react';
 
 import Typography from '@mui/material/Typography';
 import Box from '@mui/material/Box';
-import { Button, Card, Paper, Chip } from '@mui/material';
+import { Button, Chip } from '@mui/material';
 import StreamIcon from '@mui/icons-material/Stream';
-import { CustomReactTable } from './ReactTable';
 import { createTableFromFromObjectArray } from '../data/utils';
+import { MultiTablePreview } from './MultiTablePreview';
+import { DictTable } from '../components/ComponentType';
 
 // Update the interface to support multiple tables per dataset
 export interface DatasetMetadata {
@@ -33,10 +34,10 @@ export interface DatasetSelectionViewProps {
     hideRowNum?: boolean;
 }
 
-
 export const DatasetSelectionView: React.FC<DatasetSelectionViewProps> = function DatasetSelectionView({ datasets, handleSelectDataset, hideRowNum  }) {
 
-    const [selectedDatasetName, setSelectedDatasetName] = React.useState<string | undefined>(undefined);
+    const [selectedDatasetName, setSelectedDatasetName] = useState<string | undefined>(undefined);
+    const [tableActiveIndex, setTableActiveIndex] = useState<number>(0);
 
     useEffect(() => {
         if (datasets.length > 0) {
@@ -44,6 +45,11 @@ export const DatasetSelectionView: React.FC<DatasetSelectionViewProps> = functio
         }
     }, [datasets]);
 
+    // Reset table active index when dataset changes
+    useEffect(() => {
+        setTableActiveIndex(0);
+    }, [selectedDatasetName]);
+
     const handleDatasetSelect = (index: number) => {
         setSelectedDatasetName(datasets[index].name);
     };
@@ -59,6 +65,21 @@ export const DatasetSelectionView: React.FC<DatasetSelectionViewProps> = functio
         datasetTitles.push(title);
     }
 
+    // Convert dataset tables to DictTable objects for the preview
+    const selectedDataset = datasets.find(d => d.name === selectedDatasetName);
+    const previewTables: DictTable[] = useMemo(() => {
+        if (!selectedDataset) return [];
+        return selectedDataset.tables.map((table) => {
+            const dictTable = createTableFromFromObjectArray(table.table_name, table.sample, true);
+            // Use the table name from URL as displayId for better labeling
+            const displayName = table.url.split("/").pop()?.split(".")[0]?.split("?")[0] || table.table_name;
+            return {
+                ...dictTable,
+                displayId: displayName,
+            };
+        });
+    }, [selectedDataset]);
+
     return (
         <Box sx={{ bgcolor: 'background.paper', display: 'flex', height: '100%', borderRadius: 2, overflow: 'hidden' }} >
             {/* Button navigation */}
@@ -119,74 +140,35 @@ export const DatasetSelectionView: React.FC<DatasetSelectionViewProps> = functio
             {/* Content area */}
             <Box sx={{ flex: 1, overflow: 'hidden', minWidth: 0, minHeight: 0, height: '100%', position: 'relative' }}>
                 <Box sx={{ height: '100%', overflowY: 'auto', overflowX: 'hidden', p: 2, minWidth: 0, overscrollBehavior: 'contain' }}>
-                    {datasets.map((dataset, i) => {
-                        if (dataset.name !== selectedDatasetName) return null;
-
-                        let tableComponents = dataset.tables.map((table, j) => {
-                            let t = createTableFromFromObjectArray(table.table_name, table.sample, true);
-                            let maxDisplayRows = dataset.tables.length > 1 ? 5 : 9;
-                            if (t.rows.length < maxDisplayRows) {
-                                maxDisplayRows = t.rows.length - 1;
-                            }
-                            let sampleRows = [
-                                ...t.rows.slice(0,maxDisplayRows), 
-                                Object.fromEntries(t.names.map(n => [n, "..."]))
-                            ];
-                            let colDefs = t.names.map(name => { return {
-                                id: name, label: name, minWidth: 60, align: undefined, format: (v: any) => v,
-                            }})
-
-                            return (
-                                <Box key={j}>
-                                    <Typography variant="subtitle2" sx={{ mb: 1, fontSize: 12}} color="text.secondary">
-                                        {table.url.split("/").pop()?.split(".")[0]}  ({Object.keys(t.rows[0]).length} columns{hideRowNum ? "" : ` ⨉ ${t.rows.length} rows`})
-                                    </Typography>
-                                    <Box sx={{ maxWidth: '100%', overflowX: 'auto', display: 'flex', flexDirection: 'column', mb: 1 }}>
-                                        <Card variant="outlined" sx={{
-                                            width: 800, minWidth: 'fit-content', padding: "0px"}}>
-                                            <CustomReactTable rows={sampleRows} columnDefs={colDefs} rowsPerPageNum={-1} compact={false} />
-                                        </Card>
-                                    </Box>
-                                </Box>
-                            )
-                        });
-                        
-                        // Format refresh interval for display
-                        const formatRefreshInterval = (seconds: number) => {
-                            if (seconds < 60) return `${seconds}s`;
-                            if (seconds < 3600) return `${Math.floor(seconds / 60)}m`;
-                            return `${Math.floor(seconds / 3600)}h`;
-                        };
-                        
-                        return (
-                            <Box key={i}>
-                                <Box sx={{mb: 1, gap: 1, maxWidth: 800, display: "flex", alignItems: "center", flexWrap: "wrap"}}>
-                                    <Typography sx={{fontSize: 12, flex: 1, minWidth: 200}}>
-                                        {dataset.description} <Typography variant="caption" sx={{color: "primary.light", fontSize: 10, mx: 0.5}}>[from {dataset.source}]</Typography>
-                                    </Typography>
-                                    {dataset.live && dataset.refreshIntervalSeconds && (
-                                        <Chip 
-                                            icon={<StreamIcon sx={{ fontSize: 14 }} />}
-                                            label={`Auto-refresh: ${formatRefreshInterval(dataset.refreshIntervalSeconds)}`}
-                                            size="small"
-                                            color="success"
-                                            variant="outlined"
-                                            sx={{ fontSize: 10, height: 22 }}
-                                        />
-                                    )}
-                                    <Box sx={{marginLeft: "auto", flexShrink: 0}} >
-                                        <Button size="small" variant="contained" 
-                                                onClick={(event: React.MouseEvent<HTMLElement>) => {
-                                                    handleSelectDataset(dataset);
-                                                }}>
-                                            {dataset.live ? 'load live data' : 'load dataset'}
-                                        </Button>
-                                    </Box>
-                                </Box>
-                                {tableComponents}
+                    {selectedDataset && (
+                        <Box>
+                            <Box sx={{mb: 1, gap: 1, maxWidth: 800, display: "flex", alignItems: "center", flexWrap: "wrap"}}>
+                                <Typography sx={{fontSize: 12, flex: 1, minWidth: 200}}>
+                                    {selectedDataset.description} <Typography variant="caption" sx={{color: "primary.light", fontSize: 10, mx: 0.5}}>[from {selectedDataset.source}]</Typography>
+                                </Typography>
+                            </Box>
+                            <Box sx={{ maxWidth: 800 }}>
+                                <MultiTablePreview
+                                    tables={previewTables}
+                                    emptyLabel="No tables available."
+                                    activeIndex={tableActiveIndex}
+                                    onActiveIndexChange={setTableActiveIndex}
+                                    maxHeight={280}
+                                    maxRows={12}
+                                    compact={false}
+                                    showPreviewLabel={false}
+                                />
+                            </Box>
+                            <Box sx={{display: 'flex', justifyContent: 'center', mt: 2}} >
+                                <Button variant="contained" sx={{ width: 240 }}
+                                        onClick={(event: React.MouseEvent<HTMLElement>) => {
+                                            handleSelectDataset(selectedDataset);
+                                        }}>
+                                    load dataset
+                                </Button>
                             </Box>
-                        );
-                    })}
+                        </Box>
+                    )}
                 </Box>
             </Box>
         </Box>
diff --git a/src/views/UnifiedDataUploadDialog.tsx b/src/views/UnifiedDataUploadDialog.tsx
index 225fba9..96ab382 100644
--- a/src/views/UnifiedDataUploadDialog.tsx
+++ b/src/views/UnifiedDataUploadDialog.tsx
@@ -14,12 +14,10 @@ import {
     TextField,
     Typography,
     Tooltip,
-    LinearProgress,
     Link,
     Input,
     alpha,
     useTheme,
-    Card,
 } from '@mui/material';
 
 import CloseIcon from '@mui/icons-material/Close';
@@ -30,7 +28,6 @@ import StorageIcon from '@mui/icons-material/Storage';
 import ImageSearchIcon from '@mui/icons-material/ImageSearch';
 import ExploreIcon from '@mui/icons-material/Explore';
 import RestartAltIcon from '@mui/icons-material/RestartAlt';
-import DeleteIcon from '@mui/icons-material/Delete';
 import ArrowBackIcon from '@mui/icons-material/ArrowBack';
 import Paper from '@mui/material/Paper';
 
@@ -43,8 +40,8 @@ import { createTableFromFromObjectArray, createTableFromText, loadTextDataWrappe
 import { DataLoadingChat } from './DataLoadingChat';
 import { DatasetSelectionView, DatasetMetadata } from './TableSelectionView';
 import { getUrls } from '../app/utils';
-import { CustomReactTable } from './ReactTable';
 import { DBManagerPane } from './DBTableManager';
+import { MultiTablePreview } from './MultiTablePreview';
 import { 
     FormControlLabel, 
     Switch
@@ -85,190 +82,6 @@ interface DataSourceCardProps {
     disabledReason?: string;
 }
 
-interface PreviewPanelProps {
-    title: string;
-    loading: boolean;
-    error: string | null;
-    table?: DictTable | null;
-    tables?: DictTable[] | null;
-    emptyLabel: string;
-    meta?: string;
-    onRemoveTable?: (index: number) => void;
-    activeIndex?: number;
-    onActiveIndexChange?: (index: number) => void;
-}
-
-const PreviewPanel: React.FC<PreviewPanelProps> = ({
-    title,
-    loading,
-    error,
-    table,
-    tables,
-    emptyLabel,
-    meta,
-    onRemoveTable,
-    activeIndex: controlledActiveIndex,
-    onActiveIndexChange,
-}) => {
-    const previewTables = tables ?? (table ? [table] : null);
-    const [internalActiveIndex, setInternalActiveIndex] = useState(0);
-    const activeIndex = controlledActiveIndex !== undefined ? controlledActiveIndex : internalActiveIndex;
-    const setActiveIndex = onActiveIndexChange || setInternalActiveIndex;
-
-    useEffect(() => {
-        if (!previewTables || previewTables.length === 0) {
-            if (onActiveIndexChange) {
-                onActiveIndexChange(0);
-            } else {
-                setInternalActiveIndex(0);
-            }
-            return;
-        }
-        if (activeIndex > previewTables.length - 1) {
-            const newIndex = previewTables.length - 1;
-            if (onActiveIndexChange) {
-                onActiveIndexChange(newIndex);
-            } else {
-                setInternalActiveIndex(newIndex);
-            }
-        }
-    }, [previewTables, activeIndex, onActiveIndexChange]);
-
-    const activeTable = previewTables && previewTables.length > 0 ? previewTables[activeIndex] : null;
-    return (
-        <Box
-            sx={{
-                p: 1,
-                display: 'flex',
-                flexDirection: 'column',
-                gap: 1,
-                minHeight: 120,
-            }}
-        >
-            {loading && <LinearProgress />}
-
-            {error && (
-                <Typography variant="caption" color="error">
-                    {error}
-                </Typography>
-            )}
-
-            {!loading && !error && (!previewTables || previewTables.length === 0) && (
-                <Typography variant="caption" color="text.secondary">
-                    {emptyLabel}
-                </Typography>
-            )}
-
-            {previewTables && previewTables.length > 0 && (
-                <Box>
-                    <Box
-                        sx={{
-                            display: 'flex',
-                            alignItems: 'center',
-                            flexWrap: 'nowrap',
-                            gap: 0.25,
-                            mb: 0.5,
-                            pb: 0.25,
-                            overflowX: 'auto',
-                            overflowY: 'hidden',
-                            '&::-webkit-scrollbar': { height: 4 },
-                            '&::-webkit-scrollbar-thumb': {
-                                backgroundColor: 'action.disabled',
-                                borderRadius: 4,
-                            },
-                        }}
-                    >
-                        <Typography variant="caption" sx={{ fontSize: '0.625rem', fontWeight: 'bold' }}>Preview</Typography>
-                        {previewTables.map((t, idx) => {
-                            const label = t.displayId || t.id;
-                            const isSelected = idx === activeIndex;
-                            return (
-                                <Tooltip key={`${t.id}-${idx}`} title={label} placement="top" arrow>
-                                    <Chip
-                                        label={label}
-                                        size="small"
-                                        onClick={() => {
-                                            if (onActiveIndexChange) {
-                                                onActiveIndexChange(idx);
-                                            } else {
-                                                setInternalActiveIndex(idx);
-                                            }
-                                        }}
-                                        sx={{
-                                            borderRadius: 1,
-                                            cursor: 'pointer',
-                                            maxWidth: 160,
-                                            backgroundColor: (theme) => 
-                                                isSelected 
-                                                    ? alpha(theme.palette.primary.main, 0.12)
-                                                    : 'transparent',
-                                            borderColor: (theme) => 
-                                                isSelected 
-                                                    ? alpha(theme.palette.primary.main, 0.5)
-                                                    : undefined,
-                                            color: (theme) => 
-                                                isSelected 
-                                                    ? theme.palette.primary.main
-                                                    : theme.palette.text.secondary,
-                                            '& .MuiChip-label': {
-                                                fontSize: '0.625rem',
-                                                overflow: 'hidden',
-                                                textOverflow: 'ellipsis',
-                                                whiteSpace: 'nowrap',
-                                                maxWidth: 140,
-                                            },
-                                            '&:hover': {
-                                                backgroundColor: (theme) => 
-                                                    isSelected 
-                                                        ? alpha(theme.palette.primary.main, 0.16)
-                                                        : alpha(theme.palette.primary.main, 0.08),
-                                            },
-                                        }}
-                                    />
-                                </Tooltip>
-                            );
-                        })}
-                        {onRemoveTable && (
-                            <IconButton
-                                size="small"
-                                color="error"
-                                onClick={() => onRemoveTable(activeIndex)}
-                                sx={{ ml: 'auto', flexShrink: 0 }}
-                                aria-label="Remove table"
-                            >
-                                <DeleteIcon fontSize="small" />
-                            </IconButton>
-                        )}
-                    </Box>
-
-                    {activeTable && (
-                        <Box>
-                            <Card variant="outlined" sx={{ pb: 0.5 }}>
-                                <CustomReactTable
-                                    rows={activeTable.rows.slice(0, 12)}
-                                    columnDefs={activeTable.names.map(name => ({
-                                        id: name,
-                                        label: name,
-                                        minWidth: 60,
-                                    }))}
-                                    rowsPerPageNum={-1}
-                                    compact={true}
-                                    isIncompleteTable={activeTable.rows.length > 12}
-                                    maxHeight={200}
-                                />
-                            
-                            </Card>
-                            <Typography variant="caption" color="text.secondary">
-                            {activeTable.rows.length} rows × {activeTable.names.length} columns
-                        </Typography>
-                      </Box>
-                    )}
-                </Box>
-            )}
-        </Box>
-    );
-};
-
 const DataSourceCard: React.FC<DataSourceCardProps> = ({ 
     icon, 
     title, 
@@ -363,6 +176,279 @@ const getUniqueTableName = (baseName: string, existingNames: Set<string>): strin
     return uniqueName;
 };
 
+// Reusable Data Load Menu Component
+export interface DataLoadMenuProps {
+    onSelectTab: (tab: UploadTabType) => void;
+    serverConfig?: { DISABLE_DATABASE?: boolean };
+    variant?: 'dialog' | 'page'; // 'dialog' uses smaller cards, 'page' uses larger cards
+}
+
+export const DataLoadMenu: React.FC<DataLoadMenuProps> = ({ 
+    onSelectTab, 
+    serverConfig = { DISABLE_DATABASE: false },
+    variant = 'dialog'
+}) => {
+    const theme = useTheme();
+    // Data source configurations
+    const regularDataSources = [
+        { 
+            value: 'explore' as UploadTabType, 
+            title: 'Sample Datasets', 
+            description: 'Explore and load curated example datasets',
+            icon: <ExploreIcon />, 
+            disabled: false,
+            disabledReason: undefined
+        },
+        { 
+            value: 'upload' as UploadTabType, 
+            title: 'Upload File', 
+            description: 'Upload local files (CSV, TSV, JSON, Excel)',
+            icon: <UploadFileIcon />, 
+            disabled: false,
+            disabledReason: undefined
+        },
+        { 
+            value: 'paste' as UploadTabType, 
+            title: 'Paste Data', 
+            description: 'Paste tabular data directly from clipboard',
+            icon: <ContentPasteIcon />, 
+            disabled: false,
+            disabledReason: undefined
+        },
+        { 
+            value: 'extract' as UploadTabType, 
+            title: 'Extract Unstructured Data', 
+            description: 'Extract tables from images or text using AI',
+            icon: <ImageSearchIcon />, 
+            disabled: false,
+            disabledReason: undefined
+        },
+    ];
+
+    const liveDataSources = [
+        { 
+            value: 'url' as UploadTabType, 
+            title: 'Load from URL', 
+            description: 'Load data from a URL with optional auto-refresh',
+            icon: <LinkIcon />, 
+            disabled: false,
+            disabledReason: undefined
+        },
+        { 
+            value: 'database' as UploadTabType, 
+            title: 'Database', 
+            description: 'Connect to databases or data services',
+            icon: <StorageIcon />, 
+            disabled: serverConfig.DISABLE_DATABASE,
+            disabledReason: 'Database connection is disabled in this environment'
+        },
+    ];
+
+    if (variant === 'page') {
+        // Page variant: 3-column grid, first column for liveDataSources, second 2 columns for regularDataSources
+        return (
+            <Box sx={{ 
+                width: '100%',
+                display: 'grid',
+                gridTemplateColumns: 'minmax(0, 1fr) repeat(2, minmax(0, 1fr))',
+                gridTemplateRows: 'auto repeat(2, auto)',
+                gap: 1.5,
+                rowGap: 2,
+                mx: 0,
+                textAlign: 'left',
+            }}>
+                {/* Section Titles */}
+                <Typography 
+                    variant="body2" 
+                    color="text.secondary" 
+                    sx={{ 
+                        gridColumn: 1,
+                        gridRow: 1,
+                        textAlign: 'left',
+                        letterSpacing: '0.02em',
+                        display: 'flex',
+                        alignItems: 'center',
+                        gap: 1,
+                        position: 'relative',
+                        zIndex: 1,
+                        marginRight: 3, // Extra space between first column and other columns
+                    }}
+                >
+                    <StreamIcon sx={{ fontSize: 14, animation: 'pulse 2s infinite', '@keyframes pulse': {
+                        '0%': { opacity: 1, color: 'primary.main' },
+                        '50%': { opacity: 0.5, color: 'primary.light' },
+                        '100%': { opacity: 1, color: 'primary.main' },
+                    }, }} /> Connect to live data sources
+                </Typography>
+                <Typography 
+                    variant="body2" 
+                    color="text.secondary" 
+                    sx={{ 
+                        gridColumn: '2 / 3',
+                        gridRow: 1,
+                        textAlign: 'left',
+                        letterSpacing: '0.02em'
+                    }}
+                >
+                    Load local data
+                </Typography>
+                
+                {/* Background for Live Data Column */}
+                <Box
+                    sx={{
+                        gridColumn: 1,
+                        gridRow: '1 / -1',
+                        backgroundColor: alpha(theme.palette.primary.main, 0.03),
+                        borderRadius: 1,
+                        position: 'relative',
+                        zIndex: 0,
+                        // Extend into gaps to create continuous background
+                        marginTop: '-16px', // Extend into row gaps (2 * 8px = 16px)
+                        marginBottom: '-16px',
+                        marginLeft: '-12px', // Extend into left column gap (1.5 * 8px = 12px)
+                        marginRight: '12px', // Extra space between first column and other columns (3 * 8px = 24px total)
+                        paddingTop: '16px',
+                        paddingBottom: '16px',
+                        paddingLeft: '12px',
+                        paddingRight: '12px',
+                    }}
+                />
+                
+                {/* Live Data Sources - fill last column, 2 rows */}
+                {liveDataSources.map((source, index) => (
+                    <Box
+                        key={source.value}
+                        sx={{
+                            gridColumn: 1,
+                            gridRow: index + 2, // Start from row 2 (after title row)
+                            position: 'relative',
+                            zIndex: 1,
+                            marginRight: 3, // Extra space between first column and other columns
+                        }}
+                    >
+                        <DataSourceCard
+                            icon={source.icon}
+                            title={source.title}
+                            description={source.description}
+                            onClick={() => onSelectTab(source.value)}
+                            disabled={source.disabled}
+                            disabledReason={source.disabledReason}
+                        />
+                    </Box>
+                ))}
+                {/* Regular Data Sources - fill first 2 columns, 2 rows */}
+                {regularDataSources.map((source, index) => (
+                    <Box
+                        key={source.value}
+                        sx={{
+                            gridColumn: (index % 2) + 2,
+                            gridRow: Math.floor(index / 2) + 2, // Start from row 2 (after title row)
+                        }}
+                    >
+                        <DataSourceCard
+                            icon={source.icon}
+                            title={source.title}
+                            description={source.description}
+                            onClick={() => onSelectTab(source.value)}
+                            disabled={source.disabled}
+                            disabledReason={source.disabledReason}
+                        />
+                    </Box>
+                ))}
+                
+            </Box>
+        );
+    }
+
+    // Dialog variant: original two-section layout
+    return (
+        <Box sx={{ 
+            width: '100%',
+            maxWidth: 860,
+            display: 'flex',
+            flexDirection: 'column',
+            gap: 2,
+            mx: 0,
+            textAlign: 'left',
+        }}>
+            {/* Local Data Sources */}
+            <Typography 
+                variant="body2" 
+                color="text.secondary" 
+                sx={{ 
+                    textAlign: 'left',
+                    mb: 1,
+                    mt: 1,
+                    opacity: 0.6,
+                    fontSize: '0.75rem',
+                    letterSpacing: '0.02em'
+                }}
+            >
+                Local data
+            </Typography>
+
+            <Box sx={{ 
+                display: 'grid', 
+                gridTemplateColumns: 'repeat(2, minmax(0, 1fr))',
+                gap: 1.5,
+                mb: 0,
+            }}>
+                {regularDataSources.map((source) => (
+                    <DataSourceCard
+                        key={source.value}
+                        icon={source.icon}
+                        title={source.title}
+                        description={source.description}
+                        onClick={() => onSelectTab(source.value)}
+                        disabled={source.disabled}
+                        disabledReason={source.disabledReason}
+                    />
+                ))}
+            </Box>
+
+            {/* Live Data Sources */}
+            <Typography 
+                variant="body2" 
+                color="text.secondary" 
+                sx={{ 
+                    textAlign: 'left',
+                    my: 1,
+                    opacity: 0.6,
+                    fontSize: '0.75rem',
+                    letterSpacing: '0.02em',
+                    display: 'flex',
+                    alignItems: 'center',
+                    gap: 1,
+                }}
+            >
+                <StreamIcon sx={{ fontSize: 14, animation: 'pulse 2s infinite', '@keyframes pulse': {
+                    '0%': { opacity: 1, color: 'primary.main' },
+                    '50%': { opacity: 0.5, color: 'primary.light' },
+                    '100%': { opacity: 1, color: 'primary.main' },
+                }, }} /> Or connect to a data source (with optional auto-refresh)
+            </Typography>
+
+            <Box sx={{ 
+                display: 'grid', 
+                gridTemplateColumns: 'repeat(2, minmax(0, 1fr))',
+                gap: 1.5,
+            }}>
+                {liveDataSources.map((source) => (
+                    <DataSourceCard
+                        key={source.value}
+                        icon={source.icon}
+                        title={source.title}
+                        description={source.description}
+                        onClick={() => onSelectTab(source.value)}
+                        disabled={source.disabled}
+                        disabledReason={source.disabledReason}
+                    />
+                ))}
+            </Box>
+        </Box>
+    );
+};
+
 export interface UnifiedDataUploadDialogProps {
     open: boolean;
     onClose: () => void;
@@ -383,6 +469,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
 
     const [activeTab, setActiveTab] = useState<UploadTabType>(initialTab === 'menu' ? 'menu' : initialTab);
     const fileInputRef = useRef<HTMLInputElement>(null);
+    const urlInputRef = useRef<HTMLInputElement>(null);
 
     // Paste tab state
     const [pasteContent, setPasteContent] = useState<string>("");
@@ -406,6 +493,9 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
     const [urlPreviewLoading, setUrlPreviewLoading] = useState<boolean>(false);
     const [urlPreviewError, setUrlPreviewError] = useState<string | null>(null);
     const [urlPreviewActiveIndex, setUrlPreviewActiveIndex] = useState<number>(0);
+    
+    // Example URLs state
+    const [exampleUrls, setExampleUrls] = useState<Array<{ label: string; url: string; refreshSeconds: number }>>([]);
 
     // Sample datasets state
     const [datasetPreviews, setDatasetPreviews] = useState<DatasetMetadata[]>([]);
@@ -427,62 +517,78 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
     useEffect(() => {
         if (open && activeTab === 'explore') {
             fetch(`${getUrls().EXAMPLE_DATASETS}`)
-                .then((response) => response.json())
-                .then((result) => {
-                    let datasets: DatasetMetadata[] = result.map((info: any) => {
-                        let tables = info["tables"].map((table: any) => {
-                            if (table["format"] == "json") {
-                                return {
-                                    table_name: table["name"],
-                                    url: table["url"],
-                                    format: table["format"],
-                                    sample: table["sample"],
-                                }
+            .then((response) => response.json())
+            .then((result) => {
+                let datasets: DatasetMetadata[] = result.map((info: any) => {
+                    let tables = info["tables"].map((table: any) => {
+                        if (table["format"] == "json") {
+                            return {
+                                table_name: table["name"],
+                                url: table["url"],
+                                format: table["format"],
+                                sample: table["sample"],
                             }
-                            else if (table["format"] == "csv" || table["format"] == "tsv") {
-                                const delimiter = table["format"] === "csv" ? "," : "\t";
-                                const rows = table["sample"]
-                                    .split("\n")
-                                    .map((row: string) => row.split(delimiter));
-                                
-                                if (rows.length > 0) {
-                                    const headers = rows[0];
-                                    const dataRows = rows.slice(1);
-                                    const sampleData = dataRows.map((row: string[]) => {
-                                        const obj: any = {};
-                                        headers.forEach((header: string, index: number) => {
-                                            obj[header] = row[index] || '';
-                                        });
-                                        return obj;
+                        }
+                        else if (table["format"] == "csv" || table["format"] == "tsv") {
+                            const delimiter = table["format"] === "csv" ? "," : "\t";
+                            const rows = table["sample"]
+                                .split("\n")
+                                .map((row: string) => row.split(delimiter));
+                            
+                            if (rows.length > 0) {
+                                const headers = rows[0];
+                                const dataRows = rows.slice(1);
+                                const sampleData = dataRows.map((row: string[]) => {
+                                    const obj: any = {};
+                                    headers.forEach((header: string, index: number) => {
+                                        obj[header] = row[index] || '';
                                     });
-                                    
-                                    return {
-                                        table_name: table["name"],
-                                        url: table["url"],
-                                        format: table["format"],
-                                        sample: sampleData,
-                                    };
-                                }
+                                    return obj;
+                                });
                                 
                                 return {
                                     table_name: table["name"],
                                     url: table["url"],
                                     format: table["format"],
-                                    sample: [],
+                                    sample: sampleData,
                                 };
                             }
-                        })
-                        return { 
-                            tables: tables, 
-                            name: info["name"], 
-                            description: info["description"], 
-                            source: info["source"],
-                            live: info["live"],
-                            refreshIntervalSeconds: info["refreshIntervalSeconds"]
+                            
+                            return {
+                                table_name: table["name"],
+                                url: table["url"],
+                                format: table["format"],
+                                sample: [],
+                            };
                         }
-                    }).filter((t: DatasetMetadata | undefined) => t != undefined);
-                    setDatasetPreviews(datasets);
-                });
+                    })
+                    return { 
+                        tables: tables, 
+                        name: info["name"], 
+                        source: info["source"],
+                        live: info["live"],
+                        refreshIntervalSeconds: info["refreshIntervalSeconds"]
+                    }
+                }).filter((t: DatasetMetadata | undefined) => t != undefined);
+                setDatasetPreviews(datasets);
+            });
+        } else if (open && activeTab === 'url') {
+            fetch(`${window.location.origin}/api/demo-stream/info`)
+            .then(res => res.json())
+            .then(data => {
+                const demoExamples = data.demo_examples
+                    .map((ex: any) => ({
+                        label: ex.name,
+                        url: ex.url,
+                        refreshSeconds: ex.refresh_seconds || 60
+                }));
+                
+                setExampleUrls(demoExamples);
+            })
+            .catch((err) => {
+                console.error('Failed to load examples:', err);
+            })
+            .finally(() => { });
         }
     }, [open, activeTab]);
 
@@ -505,6 +611,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         setUrlPreviewLoading(false);
         setUrlPreviewError(null);
         setUrlPreviewActiveIndex(0);
+        setExampleUrls([]);
         onClose();
     }, [onClose]);
 
@@ -698,18 +805,22 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
     };
 
 
-    const handleURLPreview = (): void => {
+    const handleURLPreview = (urlToUse: string): void => {
+        if (!urlToUse) {
+            return;
+        }
         setUrlPreviewLoading(true);
         setUrlPreviewError(null);
         setUrlPreviewTables(null);
 
+
         // Support relative URLs by constructing full URL
-        let fullUrl = tableURL;
-        if (tableURL.startsWith('/')) {
-            fullUrl = window.location.origin + tableURL;
+        let fullUrl = urlToUse;
+        if (urlToUse.startsWith('/')) {
+            fullUrl = window.location.origin + urlToUse;
         }
 
-        let parts = tableURL.split('/');
+        let parts = urlToUse.split('/');
         const baseName = parts[parts.length - 1]?.split('?')[0] || 'dataset';
         const tableName = getUniqueTableName(baseName.replace(/\.[^.]+$/, ''), existingNames);
 
@@ -723,29 +834,49 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
             .then(content => {
                 let table: undefined | DictTable = undefined;
                 try {
+                    // Try parsing as JSON first
                     let jsonContent = JSON.parse(content);
                     if (!Array.isArray(jsonContent)) {
                         throw new Error('JSON content must be an array of objects.');
                     }
                     table = createTableFromFromObjectArray(tableName, jsonContent, true);
-                } catch (error) {
-                    table = createTableFromText(tableName, content);
+                } catch (jsonError) {
+                    // If JSON parsing fails, try JSONL (JSON Lines) format
+                    try {
+                        const lines = content.trim().split('\n').filter(line => line.trim() !== '');
+                        const jsonlObjects = lines.map(line => {
+                            try {
+                                return JSON.parse(line);
+                            } catch (e) {
+                                throw new Error(`Invalid JSONL line: ${line.substring(0, 50)}...`);
+                            }
+                        });
+                        if (jsonlObjects.length > 0 && typeof jsonlObjects[0] === 'object' && jsonlObjects[0] !== null) {
+                            table = createTableFromFromObjectArray(tableName, jsonlObjects, true);
+                        } else {
+                            throw new Error('JSONL must contain objects.');
+                        }
+                    } catch (jsonlError) {
+                        // If JSONL parsing fails, try CSV/TSV
+                        table = createTableFromText(tableName, content);
+                    }
                 }
 
                 if (table) {
                     setUrlPreviewTables([table]);
                 } else {
-                    setUrlPreviewError('Unable to parse data from the provided URL.');
+                    setUrlPreviewError('Unable to parse data from the provided URL. Please ensure the URL points to CSV, JSON, or JSONL data.');
                 }
             })
             .catch((err) => {
-                setUrlPreviewError(`Failed to fetch data: ${err.message}`);
+                setUrlPreviewError(`Failed to fetch data: ${err.message}. Please ensure the URL points to CSV, JSON, or JSONL data.`);
             })
             .finally(() => {
                 setUrlPreviewLoading(false);
             });
     };
 
+
     // URL tab load handlers
     const handleURLLoadSingleTable = (): void => {
         if (!urlPreviewTables || urlPreviewTables.length === 0) {
@@ -806,78 +937,27 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
     };
 
     // URL validation - allow common data file extensions and API endpoints
-    const hasValidUrl = tableURL.trim() !== '' && (
-        tableURL.startsWith('http://') || tableURL.startsWith('https://') || tableURL.startsWith('/')
+    const hasValidUrl = (tableURL || '').trim() !== '' && (
+        (tableURL || '').startsWith('http://') || (tableURL || '').startsWith('https://') || (tableURL || '').startsWith('/')
     );
     const hasMultipleFileTables = (filePreviewTables?.length || 0) > 1;
     const hasMultipleUrlTables = (urlPreviewTables?.length || 0) > 1;
     const showFilePreview = filePreviewLoading || !!filePreviewError || (filePreviewTables && filePreviewTables.length > 0);
     const showUrlPreview = urlPreviewLoading || !!urlPreviewError || (urlPreviewTables && urlPreviewTables.length > 0);
-    const hasPasteContent = pasteContent.trim() !== '';
-
-    // Data source configurations for the menu
-    const regularDataSources = [
-        { 
-            value: 'explore' as UploadTabType, 
-            title: 'Sample Datasets', 
-            description: 'Explore and load curated example datasets',
-            icon: <ExploreIcon />, 
-            disabled: false,
-            disabledReason: undefined
-        },
-        { 
-            value: 'upload' as UploadTabType, 
-            title: 'Upload File', 
-            description: 'Upload local files (CSV, TSV, JSON, Excel)',
-            icon: <UploadFileIcon />, 
-            disabled: false,
-            disabledReason: undefined
-        },
-        { 
-            value: 'url' as UploadTabType, 
-            title: 'Load from URL', 
-            description: 'Load data from a URL with optional auto-refresh',
-            icon: <LinkIcon />, 
-            disabled: false,
-            disabledReason: undefined
-        },
-        { 
-            value: 'paste' as UploadTabType, 
-            title: 'Paste Data', 
-            description: 'Paste tabular data directly from clipboard',
-            icon: <ContentPasteIcon />, 
-            disabled: false,
-            disabledReason: undefined
-        },
-        { 
-            value: 'extract' as UploadTabType, 
-            title: 'Extract from Documents', 
-            description: 'Extract tables from images, PDFs, or documents using AI',
-            icon: <ImageSearchIcon />, 
-            disabled: false,
-            disabledReason: undefined
-        },
-    ];
-
-
-    const databaseDataSources = [
-        { 
-            value: 'database' as UploadTabType, 
-            title: 'Database', 
-            description: 'Connect to databases or data services',
-            icon: <StorageIcon />, 
-            disabled: serverConfig.DISABLE_DATABASE,
-            disabledReason: 'Database connection is disabled in this environment'
-        },
-    ];
-
-    // Combined config for finding tab titles
-    const dataSourceConfig = [...regularDataSources, ...databaseDataSources];
+    const hasPasteContent = (pasteContent || '').trim() !== '';
 
     // Get current tab title for header
     const getCurrentTabTitle = () => {
-        const tab = dataSourceConfig.find(t => t.value === activeTab);
-        return tab?.title || 'Add Data';
+        const tabTitles: Record<UploadTabType, string> = {
+            'menu': 'Load Data',
+            'explore': 'Sample Datasets',
+            'upload': 'Upload File',
+            'paste': 'Paste Data',
+            'extract': 'Extract from Documents',
+            'url': 'Load from URL',
+            'database': 'Database',
+        };
+        return tabTitles[activeTab] || 'Add Data';
     };
 
     return (
@@ -941,81 +1021,11 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                 {/* Main Menu */}
                 <TabPanel value={activeTab} index="menu">
                     <Box sx={{ p: 2, boxSizing: 'border-box', width: '100%', height: '100%', display: 'flex', justifyContent: 'center', alignItems: 'center' }}>
-                        <Box sx={{ 
-                            width: '100%',
-                            maxWidth: 860,
-                            display: 'flex',
-                            flexDirection: 'column',
-                            gap: 2,
-                        }}>
-                            {/* Section hint */}
-                            <Typography 
-                                variant="body2" 
-                                color="text.secondary" 
-                                sx={{ 
-                                    textAlign: 'left',
-                                    my: 1,
-                                    opacity: 0.6,
-                                    fontSize: '0.75rem',
-                                    letterSpacing: '0.02em'
-                                }}
-                            >
-                                Local data
-                            </Typography>
-
-                            {/* Regular Data Sources Group */}
-                            <Box sx={{ 
-                                display: 'grid', 
-                                gridTemplateColumns: 'repeat(2, minmax(0, 1fr))',
-                                gap: 1.5,
-                            }}>
-                                {regularDataSources.map((source) => (
-                                    <DataSourceCard
-                                        key={source.value}
-                                        icon={source.icon}
-                                        title={source.title}
-                                        description={source.description}
-                                        onClick={() => setActiveTab(source.value)}
-                                        disabled={source.disabled}
-                                        disabledReason={source.disabledReason}
-                                    />
-                                ))}
-                            </Box>
-
-                            {/* Section hint */}
-                            <Typography 
-                                variant="body2" 
-                                color="text.secondary" 
-                                sx={{ 
-                                    textAlign: 'left',
-                                    my: 1,
-                                    opacity: 0.6,
-                                    fontSize: '0.75rem',
-                                    letterSpacing: '0.02em'
-                                }}
-                            >
-                                Or connect to a database
-                            </Typography>
-
-                            {/* Database Data Sources Group */}
-                            <Box sx={{ 
-                                display: 'grid', 
-                                gridTemplateColumns: 'repeat(2, minmax(0, 1fr))',
-                                gap: 1.5,
-                            }}>
-                                {databaseDataSources.map((source) => (
-                                    <DataSourceCard
-                                        key={source.value}
-                                        icon={source.icon}
-                                        title={source.title}
-                                        description={source.description}
-                                        onClick={() => setActiveTab(source.value)}
-                                        disabled={source.disabled}
-                                        disabledReason={source.disabledReason}
-                                    />
-                                ))}
-                            </Box>
-                        </Box>
+                        <DataLoadMenu 
+                            onSelectTab={(tab) => setActiveTab(tab)}
+                            serverConfig={serverConfig}
+                            variant="dialog"
+                        />
                     </Box>
                 </TabPanel>
 
@@ -1088,13 +1098,11 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
 
                         {showFilePreview && (
                             <Box sx={{ width: '90%', alignSelf: 'center' }}>
-                                <PreviewPanel
-                                    title="Preview"
+                                <MultiTablePreview
                                     loading={filePreviewLoading}
                                     error={filePreviewError}
                                     tables={filePreviewTables}
                                     emptyLabel="Select a file to preview."
-                                    meta={filePreviewTables && filePreviewTables.length > 0 ? `${filePreviewTables.length} table${filePreviewTables.length > 1 ? 's' : ''} previewed${hasMultipleFileTables ? ' • Multiple sheets detected' : ''}` : undefined}
                                     onRemoveTable={handleRemoveFilePreviewTable}
                                     activeIndex={filePreviewActiveIndex}
                                     onActiveIndexChange={setFilePreviewActiveIndex}
@@ -1103,23 +1111,21 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                         )}
 
                         {filePreviewTables && filePreviewTables.length > 0 && (
-                            <Box sx={{ display: 'flex', justifyContent: 'flex-end', gap: 1, alignItems: 'center' }}>
+                            <Box sx={{ display: 'flex', justifyContent: 'center', gap: 1, alignItems: 'center' }}>
                                 <Button
                                     variant="outlined"
-                                    size="small"
                                     onClick={handleFileLoadSingleTable}
                                     disabled={filePreviewLoading}
-                                    sx={{ textTransform: 'none' }}
+                                    sx={{ textTransform: 'none', width: 240 }}
                                 >
                                     Load Table
                                 </Button>
                                 {hasMultipleFileTables && (
                                     <Button
                                         variant="contained"
-                                        size="small"
                                         onClick={handleFileLoadAllTables}
                                         disabled={filePreviewLoading}
-                                        sx={{ textTransform: 'none' }}
+                                        sx={{ textTransform: 'none', width: 240 }}
                                     >
                                         Load All Tables
                                     </Button>
@@ -1142,69 +1148,45 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                     }}>
                         <Box sx={{ width: '100%', maxWidth: showUrlPreview ? '80%' : 760, alignSelf: 'center', display: 'flex', flexDirection: 'column', gap: 2 }}>
                             {/* URL Input */}
-                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1 }}>
-                                <TextField
-                                    fullWidth
-                                    placeholder="Enter URL: https://example.com/data.json or /api/data"
-                                    value={tableURL}
-                                    onChange={(e) => setTableURL(e.target.value.trim())}
-                                    error={tableURL !== "" && !hasValidUrl}
-                                    helperText={tableURL !== "" && !hasValidUrl ? "Enter a valid URL starting with http://, https://, or /" : undefined}
-                                    size="small"
-                                    sx={{ 
-                                        flex: 1,
-                                        '& .MuiInputBase-input': {
-                                            fontSize: '0.875rem',
-                                        },
-                                        '& .MuiInputBase-input::placeholder': {
-                                            fontSize: '0.875rem',
-                                        },
-                                    }}
-                                />
-                                <Button
-                                    variant="outlined"
-                                    size="small"
-                                    onClick={handleURLPreview}
-                                    disabled={!hasValidUrl || urlPreviewLoading}
-                                    sx={{ textTransform: 'none', whiteSpace: 'nowrap' }}
-                                >
-                                    Preview
-                                </Button>
-                            </Box>
-
-                            {/* Example APIs */}
-                            <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, flexWrap: 'wrap' }}>
-                                <Typography variant="caption" color="text.secondary" sx={{ mr: 0.5 }}>
-                                    Try examples:
-                                </Typography>
-                                {[
-                                    { label: 'USGS Earthquakes', url: '/api/demo-stream/earthquakes?timeframe=day&min_magnitude=2.5', description: 'Recent earthquakes worldwide' },
-                                    { label: 'US Weather', url: '/api/demo-stream/weather', description: 'Current weather for major US cities' },
-                                    { label: 'Stock Prices (yahoo finance)', url: '/api/demo-stream/yfinance?symbols=AAPL,MSFT,GOOGL,NVDA', description: 'Stock prices with historical + intraday data' },
-                                ].map((example) => (
-                                    <Chip
-                                        key={example.label}
-                                        label={example.label}
+                            <Box sx={{ display: 'flex', flexDirection: 'column', gap: 0.5 }}>
+                                <Box sx={{ display: 'flex', alignItems: 'center', gap: 1 }}>
+                                    <TextField
+                                        fullWidth
+                                        placeholder="Enter URL: https://example.com/data.json or /api/data"
+                                        value={tableURL || ''}
+                                        onChange={(e) => setTableURL((e.target.value || '').trim())}
+                                        inputRef={urlInputRef}
+                                        error={tableURL !== "" && !hasValidUrl}
+                                        helperText={tableURL !== "" && !hasValidUrl ? "Enter a valid URL starting with http://, https://, or /" : undefined}
                                         size="small"
-                                        variant="outlined"
-                                        onClick={() => setTableURL(example.url)}
-                                        title={example.description}
                                         sx={{ 
-                                            cursor: 'pointer',
-                                            fontSize: '0.75rem',
-                                            height: 24,
-                                            '&:hover': {
-                                                backgroundColor: alpha(theme.palette.primary.main, 0.08),
-                                                borderColor: 'primary.main',
-                                            }
+                                            flex: 1,
+                                            '& .MuiInputBase-input': {
+                                                fontSize: '0.875rem',
+                                            },
+                                            '& .MuiInputBase-input::placeholder': {
+                                                fontSize: '0.875rem',
+                                            },
                                         }}
                                     />
-                                ))}
+                                    <Button
+                                        variant="outlined"
+                                        size="small"
+                                        onClick={() => handleURLPreview(tableURL || '')}
+                                        disabled={!hasValidUrl || urlPreviewLoading}
+                                        sx={{ textTransform: 'none', whiteSpace: 'nowrap' }}
+                                    >
+                                        Preview
+                                    </Button>
+                                </Box>
+                                <Typography variant="caption" color="text.secondary" sx={{ fontSize: '0.75rem', ml: 0.5 }}>
+                                    The URL must point to data in CSV, JSON, or JSONL format
+                                </Typography>
                             </Box>
                             
                             {/* Watch/Auto-refresh options - always visible */}
                             <Paper variant="outlined" sx={{ p: 2, borderRadius: 1 }}>
-                                <Box sx={{ display: 'flex', flexDirection: 'column', gap: 1.5 }}>
+                                <Box sx={{ display: 'flex', flexDirection: 'row', gap: 1, alignItems: 'center', height: 24 }}>
                                     <FormControlLabel
                                         control={
                                             <Switch
@@ -1214,63 +1196,114 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                             />
                                         }
                                         label={
-                                            <Box sx={{ height: 24, display: 'flex', flexDirection: 'row', gap: 1, alignItems: 'center' }}>
-                                                <Typography component="span" variant="body2" sx={{ fontWeight: 500 }}>
-                                                    Watch Mode:
-                                                </Typography>
-                                                
-                                                {urlAutoRefresh ? (
-                                                    <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, }}>
-                                                        <Typography variant="body2" color="text.secondary" sx={{ fontSize: '0.8rem' }}>
-                                                            refresh interval
-                                                        </Typography>
-                                                        {[
-                                                            { seconds: 5, label: '5s' },
-                                                            { seconds: 15, label: '15s' },
-                                                            { seconds: 30, label: '30s' },
-                                                            { seconds: 60, label: '1m' },
-                                                            { seconds: 300, label: '5m' },
-                                                            { seconds: 600, label: '10m' },
-                                                            { seconds: 1800, label: '30m' },
-                                                            { seconds: 3600, label: '1h' },
-                                                        ].map((opt) => (
-                                                            <Chip
-                                                                key={opt.seconds}
-                                                                label={opt.label}
-                                                                size="small"
-                                                                variant={urlRefreshInterval === opt.seconds ? 'filled' : 'outlined'}
-                                                                color={urlRefreshInterval === opt.seconds ? 'primary' : 'default'}
-                                                                onClick={() => setUrlRefreshInterval(opt.seconds)}
-                                                                sx={{ 
-                                                                    cursor: 'pointer', 
-                                                                    fontSize: '0.7rem',
-                                                                    height: 24,
-                                                                }}
-                                                            />
-                                                        ))}
-                                                    </Box>
-                                                ) : <Typography sx={{ ml: 'auto' }} component="span" variant="caption" color="text.secondary">
-                                                    automatically check and refresh data from the URL at regular intervals
-                                                </Typography>}
-                                            </Box>
+                                            <Typography component="span" variant="body2" sx={{ fontWeight: 500 }}>
+                                                Watch Mode
+                                            </Typography>
                                         }
-                                        sx={{ alignItems: 'flex-start', ml: 0 }}
                                     />
-                                    
+                                    {urlAutoRefresh ? (
+                                        <Box sx={{ display: 'flex', alignItems: 'center', gap: 1, }}>
+                                            <Typography variant="body2" color="text.secondary" sx={{ fontSize: '0.8rem' }}>
+                                                check data updates every
+                                            </Typography>
+                                            {[
+                                                { seconds: 5, label: '5s' },
+                                                { seconds: 15, label: '15s' },
+                                                { seconds: 30, label: '30s' },
+                                                { seconds: 60, label: '1m' },
+                                                { seconds: 300, label: '5m' },
+                                                { seconds: 600, label: '10m' },
+                                                { seconds: 1800, label: '30m' },
+                                                { seconds: 3600, label: '1h' },
+                                                { seconds: 86400, label: '24h' },
+                                            ].map((opt) => (
+                                                <Chip
+                                                    key={opt.seconds}
+                                                    label={opt.label}
+                                                    size="small"
+                                                    variant={urlRefreshInterval === opt.seconds ? 'filled' : 'outlined'}
+                                                    color={urlRefreshInterval === opt.seconds ? 'primary' : 'default'}
+                                                    onClick={() => setUrlRefreshInterval(opt.seconds)}
+                                                    sx={{ 
+                                                        cursor: 'pointer', 
+                                                        fontSize: '0.7rem',
+                                                        height: 24,
+                                                    }}
+                                                />
+                                            ))}
+                                        </Box>
+                                    ) : <Typography component="span" variant="caption" color="text.secondary">
+                                        automatically check and refresh data from the URL at regular intervals
+                                    </Typography>}
                                     
                                 </Box>
                             </Paper>
+
+                            {/* Example APIs - Compact List */}
+                            {(!urlPreviewTables || urlPreviewTables.length === 0) && !urlPreviewLoading && (
+                                <Box sx={{ display: 'flex', flexDirection: 'column', gap: 0.5 }}>
+                                    <Typography variant="caption" color="text.secondary" sx={{ mb: 0.5 }}>
+                                        Try examples:
+                                    </Typography>
+                                    <Box component="ul" sx={{ 
+                                        listStyle: 'none', 
+                                        padding: 0, 
+                                        margin: 0,
+                                        display: 'flex',
+                                        flexDirection: 'column',
+                                        gap: 0.25,
+                                    }}>
+                                        {exampleUrls.map((example) => (
+                                            <Box
+                                                component="li"
+                                                key={example.url}
+                                                onClick={() => {
+                                                    console.log('example', example);
+                                                    if (example.url) {
+                                                        
+                                                        setTableURL(example.url);
+                                                        setUrlAutoRefresh(true);
+                                                        setUrlRefreshInterval(example.refreshSeconds || 60);
+                                                        handleURLPreview(example.url);
+                                                    }
+                                                }}
+                                                sx={{
+                                                    cursor: 'pointer',
+                                                    '&::before': {
+                                                        content: '"• "',
+                                                        color: 'text.secondary',
+                                                        marginRight: 0.5,
+                                                    }
+                                                }}
+                                            >
+                                                <Typography 
+                                                    component="span"
+                                                    variant="caption" 
+                                                    sx={{ 
+                                                        fontSize: '0.75rem',
+                                                        color: 'primary.main',
+                                                        textDecoration: 'none',
+                                                        '&:hover': {
+                                                            textDecoration: 'underline',
+                                                        }
+                                                    }}
+                                                >
+                                                    {example.label}
+                                                </Typography>
+                                            </Box>
+                                        ))}
+                                    </Box>
+                                </Box>
+                            )}
                         </Box>
 
                         {showUrlPreview && (
                             <Box sx={{ width: '90%', alignSelf: 'center' }}>
-                                <PreviewPanel
-                                    title="Preview"
+                                <MultiTablePreview
                                     loading={urlPreviewLoading}
                                     error={urlPreviewError}
                                     tables={urlPreviewTables}
                                     emptyLabel="Enter a URL and click Preview to see data."
-                                    meta={urlPreviewTables && urlPreviewTables.length > 0 ? `${urlPreviewTables.length} table${urlPreviewTables.length > 1 ? 's' : ''} previewed` : undefined}
                                     onRemoveTable={handleRemoveUrlPreviewTable}
                                     activeIndex={urlPreviewActiveIndex}
                                     onActiveIndexChange={setUrlPreviewActiveIndex}
@@ -1279,7 +1312,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                         )}
 
                         {urlPreviewTables && urlPreviewTables.length > 0 && (
-                            <Box sx={{ display: 'flex', justifyContent: 'flex-end', gap: 1, alignItems: 'center' }}>
+                            <Box sx={{ display: 'flex', justifyContent: 'center', gap: 1, alignItems: 'center' }}>
                                 {urlAutoRefresh && (
                                     <Typography variant="caption" color="success.main" sx={{ mr: 1 }}>
                                         <StreamIcon sx={{ fontSize: 14, verticalAlign: 'middle', mr: 0.5 }} />
@@ -1287,11 +1320,10 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                     </Typography>
                                 )}
                                 <Button
-                                    variant="outlined"
-                                    size="small"
+                                    variant="contained"
                                     onClick={handleURLLoadSingleTable}
                                     disabled={urlPreviewLoading}
-                                    sx={{ textTransform: 'none' }}
+                                    sx={{ textTransform: 'none', width: 240 }}
                                 >
                                     Load Table
                                 </Button>
@@ -1392,7 +1424,7 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                             <Button
                                 variant="contained"
                                 onClick={handlePasteSubmit}
-                                disabled={pasteContent.trim() === '' || isOverSizeLimit}
+                                disabled={(pasteContent || '').trim() === '' || isOverSizeLimit}
                                 sx={{ textTransform: 'none' }}
                             >
                                 Upload Data
diff --git a/src/views/VisualizationView.tsx b/src/views/VisualizationView.tsx
index fa55183..20641a1 100644
--- a/src/views/VisualizationView.tsx
+++ b/src/views/VisualizationView.tsx
@@ -300,6 +300,7 @@ const VegaChartRenderer: FC<{
             return;
         }
 
+
         const assembledChart = assembleVegaChart(
             chart.chartType, 
             chart.encodingMap, 
@@ -453,8 +454,8 @@ export const ChartEditorFC: FC<{}> = function ChartEditorFC({}) {
     const processedData = createVisTableRowsLocal(table.rows);
 
     const [visTableRows, setVisTableRows] = useState<any[]>(processedData);
+
     const [visTableTotalRowCount, setVisTableTotalRowCount] = useState<number>(table.virtual?.rowCount || table.rows.length);
-    
 
     let { aggregateFields, groupByFields } = extractFieldsFromEncodingMap(focusedChart.encodingMap, conceptShelfItems);
     let sortedVisDataFields = [...aggregateFields.map(f => `${f[0]}_${f[1]}`), ...groupByFields].sort();

From 1529493735edf58d6dfdceef22b243d0dc008713 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Sun, 25 Jan 2026 18:11:58 -0800
Subject: [PATCH 14/21] prep for new updtes

---
 README.md      | 21 ++++++---------------
 pyproject.toml |  6 ++++--
 2 files changed, 10 insertions(+), 17 deletions(-)

diff --git a/README.md b/README.md
index 992f666..a4c25ba 100644
--- a/README.md
+++ b/README.md
@@ -32,25 +32,16 @@ https://github.com/user-attachments/assets/8ca57b68-4d7a-42cb-bcce-43f8b1681ce2
 
 
 ## News 🔥🔥🔥
-[12-08-2025] **Data Formulator 0.5.1** — Connect more, visualize more, move faster
-- 🔌 **Community data loaders**: Google BigQuery, MySQL, Postgres, MongoDB
-- 📊 **New chart types**: US Map & Pie Chart (more to be added soon)
-- ✏️ **Editable reports**: Refine generated reports with [Chartifact](https://github.com/microsoft/chartifact) in markdown style. [demo](https://github.com/microsoft/data-formulator/pull/200#issue-3635408217)
-- ⚡ **Snappier UI**: Noticeably faster interactions across the board
-
-[11-07-2025] Data Formulator 0.5: Vibe with your data, in control
-
-- 📊 **Load (almost) any data**: load structured data, extract data from screenshots, from messy text blocks, or connect to databases.
-- 🤖 **Explore data with AI agents**: 
-  - In agent mode, provide a high-level goal and ask agents to explore data for you.
-  - To stay in control, directly interact with agents: ask for recommendations or specify chart designs with UI + NL inputs, and AI agents will formulate data to realize your design.
-  - Use data threads to control branching exploration paths: backtrack, branch, or follow up.
-- ✅ **Verify AI generated results**: interact with charts and inspect data, formulas, explanations, and code.
-- 📝 **Create reports to share insights**: choose charts you want to share, and ask agents to create reports grounded in data formulated throughout exploration.
+[01-25-2025] **Data Formulator 0.6** — Connect to your live data
+-  📡 **Live Data** Explore live data source with real-time insights
+  - Set refresh interval when connecting to data from URLs and databases
+  - When data updates, visualizations are refreshed automatically with new insights
 
 ## Previous Updates
 
 Here are milestones that lead to the current design:
+- **v0.5.1** ([Demo](https://github.com/microsoft/data-formulator/pull/200#issue-3635408217)): Community data loaders (Google BigQuery, MySQL, Postgres, MongoDB), new chart types (US Map & Pie Chart), editable reports with Chartifact
+- **v0.5**: Agent mode for data analysis; create reports to share insights.
 - **v0.2.2** ([Demo](https://github.com/microsoft/data-formulator/pull/176)): Goal-driven exploration with agent recommendations and performance improvements
 - **v0.2.1.3/4** ([Readme](https://github.com/microsoft/data-formulator/tree/main/py-src/data_formulator/data_loader) | [Demo](https://github.com/microsoft/data-formulator/pull/155)): External data loaders (MySQL, PostgreSQL, MSSQL, Azure Data Explorer, S3, Azure Blob)
 - **v0.2** ([Demos](https://github.com/microsoft/data-formulator/releases/tag/0.2)): Large data support with DuckDB integration
diff --git a/pyproject.toml b/pyproject.toml
index 37c8b16..49ed802 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "data_formulator"
-version = "0.5.1.1"
+version = "0.6"
 
 requires-python = ">=3.9"
 authors = [
@@ -25,6 +25,7 @@ dependencies = [
     "pandas",  
     "flask",  
     "flask-cors",  
+    "flask-limiter",
     "openai",  
     "python-dotenv",  
     "vega_datasets",
@@ -46,7 +47,8 @@ dependencies = [
     "boto3",
     "pymysql",
     "pyodbc",
-    "pymongo"
+    "pymongo",
+    "yfinance"
 ]
 
 [project.urls]

From a2149735ba1f3e3688dd569a6e6bd484f17e2134 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Sun, 25 Jan 2026 20:52:06 -0800
Subject: [PATCH 15/21] readme updates

---
 README.md | 24 ++++++++++++++++++------
 1 file changed, 18 insertions(+), 6 deletions(-)

diff --git a/README.md b/README.md
index a4c25ba..1238c6e 100644
--- a/README.md
+++ b/README.md
@@ -32,16 +32,28 @@ https://github.com/user-attachments/assets/8ca57b68-4d7a-42cb-bcce-43f8b1681ce2
 
 
 ## News 🔥🔥🔥
-[01-25-2025] **Data Formulator 0.6** — Connect to your live data
--  📡 **Live Data** Explore live data source with real-time insights
-  - Set refresh interval when connecting to data from URLs and databases
-  - When data updates, visualizations are refreshed automatically with new insights
+[01-25-2025] **Data Formulator 0.6** — Explore live data with real-time insights
+-  ⚡ **Connect to live data**: Connect to URLs and databases with automatic refresh intervals. Visualizations update automatically as your data changes to provide you live insights. [Example: Stock market data from Yahoo Finance](https://github.com/microsoft/data-formulator/pull/200#issue-3635408217)
+
+[12-08-2025] **Data Formulator 0.5.1** — Connect more, visualize more, move faster
+- 🔌 **Community data loaders**: Google BigQuery, MySQL, Postgres, MongoDB
+- 📊 **New chart types**: US Map & Pie Chart (more to be added soon)
+- ✏️ **Editable reports**: Refine generated reports with [Chartifact](https://github.com/microsoft/chartifact) in markdown style. [demo](https://github.com/microsoft/data-formulator/pull/200#issue-3635408217)
+- ⚡ **Snappier UI**: Noticeably faster interactions across the board
+
+[11-07-2025] Data Formulator 0.5: Vibe with your data, in control
+
+- 📊 **Load (almost) any data**: load structured data, extract data from screenshots, from messy text blocks, or connect to databases.
+- 🤖 **Explore data with AI agents**: 
+  - In agent mode, provide a high-level goal and ask agents to explore data for you.
+  - To stay in control, directly interact with agents: ask for recommendations or specify chart designs with UI + NL inputs, and AI agents will formulate data to realize your design.
+  - Use data threads to control branching exploration paths: backtrack, branch, or follow up.
+- ✅ **Verify AI generated results**: interact with charts and inspect data, formulas, explanations, and code.
+- 📝 **Create reports to share insights**: choose charts you want to share, and ask agents to create reports grounded in data formulated throughout exploration.
 
 ## Previous Updates
 
 Here are milestones that lead to the current design:
-- **v0.5.1** ([Demo](https://github.com/microsoft/data-formulator/pull/200#issue-3635408217)): Community data loaders (Google BigQuery, MySQL, Postgres, MongoDB), new chart types (US Map & Pie Chart), editable reports with Chartifact
-- **v0.5**: Agent mode for data analysis; create reports to share insights.
 - **v0.2.2** ([Demo](https://github.com/microsoft/data-formulator/pull/176)): Goal-driven exploration with agent recommendations and performance improvements
 - **v0.2.1.3/4** ([Readme](https://github.com/microsoft/data-formulator/tree/main/py-src/data_formulator/data_loader) | [Demo](https://github.com/microsoft/data-formulator/pull/155)): External data loaders (MySQL, PostgreSQL, MSSQL, Azure Data Explorer, S3, Azure Blob)
 - **v0.2** ([Demos](https://github.com/microsoft/data-formulator/releases/tag/0.2)): Large data support with DuckDB integration

From 0017aad57a8038a39098c9b11ddb71a9a8cecdba Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Mon, 26 Jan 2026 13:26:47 -0800
Subject: [PATCH 16/21] fixes and improvements: agent context, db table import

---
 README.md                                     |   1 +
 py-src/data_formulator/agent_routes.py        |  21 -
 .../agents/agent_exploration.py               |   8 +-
 .../agents/agent_interactive_explore.py       |  73 +--
 .../agents/agent_py_data_rec.py               |   2 +
 .../agents/agent_py_data_transform.py         |   2 +
 .../agents/agent_query_completion.py          |  83 ----
 .../agents/agent_report_gen.py                |  13 +-
 .../agents/agent_sql_data_rec.py              |  13 +-
 .../agents/agent_sql_data_transform.py        | 262 +++++++----
 py-src/data_formulator/agents/agent_utils.py  |  38 +-
 .../data_loader/azure_blob_data_loader.py     |  12 +-
 .../data_loader/bigquery_data_loader.py       |  12 +-
 .../data_loader/external_data_loader.py       |  11 +-
 .../data_loader/kusto_data_loader.py          |  13 +-
 .../data_loader/mongodb_data_loader.py        |  13 +-
 .../data_loader/mssql_data_loader.py          |  12 +-
 .../data_loader/mysql_data_loader.py          |  14 +-
 .../data_loader/postgresql_data_loader.py     |  11 +-
 .../data_loader/s3_data_loader.py             |  12 +-
 py-src/data_formulator/tables_routes.py       |  10 +-
 src/app/utils.tsx                             |  70 ++-
 src/components/ChartTemplates.tsx             | 122 +++--
 src/views/DBTableManager.tsx                  | 435 ++++++++++++++----
 src/views/EncodingShelfCard.tsx               |  22 +-
 src/views/ReportView.tsx                      |  11 +-
 26 files changed, 831 insertions(+), 465 deletions(-)
 delete mode 100644 py-src/data_formulator/agents/agent_query_completion.py

diff --git a/README.md b/README.md
index 1238c6e..c42d2be 100644
--- a/README.md
+++ b/README.md
@@ -34,6 +34,7 @@ https://github.com/user-attachments/assets/8ca57b68-4d7a-42cb-bcce-43f8b1681ce2
 ## News 🔥🔥🔥
 [01-25-2025] **Data Formulator 0.6** — Explore live data with real-time insights
 -  ⚡ **Connect to live data**: Connect to URLs and databases with automatic refresh intervals. Visualizations update automatically as your data changes to provide you live insights. [Example: Stock market data from Yahoo Finance](https://github.com/microsoft/data-formulator/pull/200#issue-3635408217)
+-  🎨 **UI Updates**: Directly drag-and-drop fields from the data table to update visualization designs.
 
 [12-08-2025] **Data Formulator 0.5.1** — Connect more, visualize more, move faster
 - 🔌 **Community data loaders**: Google BigQuery, MySQL, Postgres, MongoDB
diff --git a/py-src/data_formulator/agent_routes.py b/py-src/data_formulator/agent_routes.py
index b54755c..6b0fa94 100644
--- a/py-src/data_formulator/agent_routes.py
+++ b/py-src/data_formulator/agent_routes.py
@@ -31,7 +31,6 @@
 from data_formulator.agents.agent_data_clean import DataCleanAgent
 from data_formulator.agents.agent_data_clean_stream import DataCleanAgentStream
 from data_formulator.agents.agent_code_explanation import CodeExplanationAgent
-from data_formulator.agents.agent_query_completion import QueryCompletionAgent
 from data_formulator.agents.agent_interactive_explore import InteractiveExploreAgent
 from data_formulator.agents.agent_report_gen import ReportGenAgent
 from data_formulator.agents.client_utils import Client
@@ -614,26 +613,6 @@ def request_code_expl():
     else:
         return jsonify({'error': 'Invalid request format'}), 400
 
-@agent_bp.route('/query-completion', methods=['POST'])
-def query_completion():
-    if request.is_json:
-        logger.info("# request data: ")
-        content = request.get_json()        
-
-        client = get_client(content['model'])
-
-        data_source_metadata = content["data_source_metadata"]
-        query = content["query"]
-
-        query_completion_agent = QueryCompletionAgent(client=client)
-        reasoning, query = query_completion_agent.run(data_source_metadata, query)
-        response = flask.jsonify({ "token": "", "status": "ok", "reasoning": reasoning, "query": query })
-    else:
-        response = flask.jsonify({ "token": "", "status": "error", "reasoning": "unable to complete query", "query": "" })
-
-    response.headers.add('Access-Control-Allow-Origin', '*')
-    return response
-
 @agent_bp.route('/get-recommendation-questions', methods=['GET', 'POST'])
 def get_recommendation_questions():
     def generate():
diff --git a/py-src/data_formulator/agents/agent_exploration.py b/py-src/data_formulator/agents/agent_exploration.py
index 9865ca5..73515c2 100644
--- a/py-src/data_formulator/agents/agent_exploration.py
+++ b/py-src/data_formulator/agents/agent_exploration.py
@@ -6,7 +6,7 @@
 import base64
 
 from data_formulator.agents.agent_utils import extract_json_objects, generate_data_summary
-from data_formulator.agents.agent_sql_data_transform import get_sql_table_statistics_str, sanitize_table_name
+from data_formulator.agents.agent_sql_data_transform import generate_sql_data_summary
 
 logger = logging.getLogger(__name__)
 
@@ -151,11 +151,7 @@ def get_chart_message(self, visualization):
 
     def get_data_summary(self, input_tables):
         if self.db_conn:
-            data_summary = ""
-            for table in input_tables:
-                table_name = sanitize_table_name(table['name'])
-                table_summary_str = get_sql_table_statistics_str(self.db_conn, table_name)
-                data_summary += f"[TABLE {table_name}]\n\n{table_summary_str}\n\n"
+            data_summary = generate_sql_data_summary(self.db_conn, input_tables)
         else:
             data_summary = generate_data_summary(input_tables)
         return data_summary
diff --git a/py-src/data_formulator/agents/agent_interactive_explore.py b/py-src/data_formulator/agents/agent_interactive_explore.py
index e1c4f2b..c9151db 100644
--- a/py-src/data_formulator/agents/agent_interactive_explore.py
+++ b/py-src/data_formulator/agents/agent_interactive_explore.py
@@ -6,31 +6,35 @@
 import pandas as pd
 
 from data_formulator.agents.agent_utils import extract_json_objects, generate_data_summary
-from data_formulator.agents.agent_sql_data_transform import get_sql_table_statistics_str, sanitize_table_name
+from data_formulator.agents.agent_sql_data_transform import generate_sql_data_summary
 
 logger = logging.getLogger(__name__)
 
 SYSTEM_PROMPT = '''You are a data exploration expert who suggests interesting questions to help users explore their datasets.
 
-Given a dataset (or a thread of datasets that have been explored), your task is to suggest 4 exploration questions (unless the user explicitly asks for the number of questions), that users can follow to gain insights from their data.
-* the user may provide you current explorations they have done, including:
-    - a thread of exploration questions they have explored
-    - the latest data sample they are viewing
-    - the current chart they are viewing
-* when the exploration context is provided, make your suggestion based on the context as well as the original dataset; otherwise leverage the original dataset to suggest questions.
+This prompt contains the following sections:
+- [DATASETS] section: available datasets the user is working with.
+- [EXPLORATION THREAD] section (optional): sequence of datasets that have been explored in the order they were created, and what questions are asked to create them. These tables are all created from tables in the [DATASETS] section.
+- [CURRENT DATA] section (optional): latest data sample the user is viewing, and the visualization they are looking at at the moment.
+- [START QUESTION] section (optional): start question from previous exploration steps for context
+
+Your task is to suggest 4 exploration questions (unless the user explicitly asks for the number of questions), that users can follow to gain insights from their data.
+When the exploration context is provided, make your suggestion based on the context as well as the original datasets; otherwise leverage the original datasets to suggest questions.
 
 Guidelines for question suggestions:
-1. Suggest interesting analytical questions that are not obvious that can uncover nontrivial insights
-2. Use a diverse language style to display the questions (can be questions, statements etc)
-3. If there are multiple datasets in a thread, consider relationships between them
+1. Suggest interesting analytical questions that can uncover new insights from the data.
+2. Use a diverse language style to display the questions (can be questions, statements etc).
+3. If there are multiple datasets in a thread, consider relationships between them.
 4. CONCISENESS: the questions should be concise and to the point
-5. QUESTION: the question should be a new question based on the thread of exploration:
-    - either a followup question, or a new question that is related to the thread
+5. QUESTION: the question should be a new question based on the exploration thread:
+    - if no exploration thread is provided, start with a high-level overview question that directly visualizes the data to give the user a sense of the data.
+    - either a followup question, or a new question that is related to the exploration thread
         - if the current data is rich, you can ask a followup question to further explore the dataset;
         - if the current data is already specialized to answer the previous question, you can ask a new question that is related to the thread but not related to the previous question in the thread, leverage earlier exploration data to ask questions that can expand the exploration horizon
     - do not repeat questions that have already been explored in the thread
     - do not suggest questions that are not related to the thread (e.g. questions that are completely unrelated to the exploration direction in the thread)
     - do not naively follow up if the question is already too low-level when previous iterations have already come into a small subset of the data (suggest new related areas related to the metric / attributes etc)
+    - leverage other datasets in the [DATASETS] section to suggest questions that are related to the exploration thread.
 6. DIVERSITY: the questions should be diverse in difficulty (easy / medium / hard) and the four questions should cover different aspects of the data analysis to expand the user's horizon
     - simple questions should be short -- single sentence exploratory questions
     - medium questions can be 1-2 sentences exploratory questions
@@ -59,15 +63,17 @@
 
 SYSTEM_PROMPT_AGENT = '''You are a data exploration expert to help users explore their datasets.
 
+This prompt contains the following sections:
+- [DATASETS] section: available datasets the user is working with.
+- [EXPLORATION THREAD] section (optional): sequence of datasets that have been explored in the order they were created, and what questions are asked to create them. These tables are all created from tables in the [DATASETS] section.
+- [CURRENT DATA] section (optional): latest data sample the user is viewing, and the visualization they are looking at at the moment.
+- [START QUESTION] section (optional): start question from previous exploration steps for context
+
 Given a dataset (or a thread of datasets that have been explored), your task is to suggest 4 exploration questions (unless the user explicitly asks for the number of questions), that users can follow to gain insights from their data.
-* the user may provide you current explorations they have done, including:
-    - a thread of exploration questions they have explored
-    - the latest data sample they are viewing
-    - the current chart they are viewing
-* when the exploration context is provided, make your suggestion based on the context as well as the original dataset; otherwise leverage the original dataset to suggest questions.
+When the exploration context is provided, make your suggestion based on the context as well as the original datasets; otherwise leverage the original datasets to suggest questions.
 
 Guidelines for question suggestions:
-1. Suggest a list of question_groups of interesting analytical questions that are not obvious that can uncover nontrivial insights.
+1. Suggest a list of question_groups of interesting analytical questions that can uncover new insights from the data.
 2. Use a diverse language style to display the questions (can be questions, statements etc)
 3. If there are multiple datasets in a thread, consider relationships between them
 4. CONCISENESS: the questions should be concise and to the point
@@ -80,6 +86,7 @@
         - hard questions should introduce some new analysis concept but still make it concise
     - if suitable, include a group of questions that are related to statistical analysis: forecasting, regression, or clustering.
 6. QUESTIONS WITHIN A QUESTION GROUP:
+    - if the user doesn't provide an exploration thread, start with a high-level overview question that directly visualizes the data to give the user a sense of the data.
     - raise new questions that are related to the user's goal, do not repeat questions that have already been explored in the context provided to you.
     - if the user provides a start question, suggested questions should be related to the start question.
     - the questions should progressively dive deeper into the data, building on top of the previous question.
@@ -113,15 +120,11 @@ def __init__(self, client, agent_exploration_rules="", db_conn=None):
         self.agent_exploration_rules = agent_exploration_rules
         self.db_conn = db_conn
 
-    def get_data_summary(self, input_tables):
+    def get_data_summary(self, input_tables, table_name_prefix="Table"):
         if self.db_conn:
-            data_summary = ""
-            for table in input_tables:
-                table_name = sanitize_table_name(table['name'])
-                table_summary_str = get_sql_table_statistics_str(self.db_conn, table_name)
-                data_summary += f"[TABLE {table_name}]\n\n{table_summary_str}\n\n"
+            data_summary = generate_sql_data_summary(self.db_conn, input_tables, table_name_prefix=table_name_prefix)
         else:
-            data_summary = generate_data_summary(input_tables, include_data_samples=False)
+            data_summary = generate_data_summary(input_tables, include_data_samples=False, table_name_prefix=table_name_prefix)
         return data_summary
 
     def run(self, input_tables, start_question=None, exploration_thread=None, 
@@ -144,19 +147,21 @@ def run(self, input_tables, start_question=None, exploration_thread=None,
         data_summary = self.get_data_summary(input_tables)
         
         # Build context including exploration thread if available
-        context = f"[DATASET]\n\n{data_summary}"
+        context = f"[DATASETS] These are the datasets the user is working with:\n\n{data_summary}"
         
         if exploration_thread:
-            thread_summary = "Tables in this exploration thread:\n"
-            for i, table in enumerate(exploration_thread, 1):
-                table_name = table.get('name', f'Table {i}')
-                data_summary = self.get_data_summary([{'name': table_name, 'rows': table.get('rows', [])}])
-                table_description = table.get('description', 'No description available')
-                thread_summary += f"{i}. {table_name}: {table_description} \n\n{data_summary}\n\n"
-            context += f"\n\n[EXPLORATION THREAD]\n\n{thread_summary}"
+            thread_summary = self.get_data_summary(
+                [{
+                    'name': table.get('name', f'Table {i}'), 
+                    'rows': table.get('rows', []), 
+                    'attached_metadata': table.get('description', ''),
+                } for i, table in enumerate(exploration_thread, 1)],
+                table_name_prefix="Thread Table"
+            )
+            context += f"\n\n[EXPLORATION THREAD] These are the sequence of tables the user created in this exploration thread, in the order they were created, and what questions are asked to create them:\n\n{thread_summary}"
 
         if current_data_sample:
-            context += f"\n\n[CURRENT DATA SAMPLE]\n\n{pd.DataFrame(current_data_sample).head(10).to_string()}"
+            context += f"\n\n[CURRENT DATA SAMPLE] This is the current data sample the user is viewing, and the visualization they are looking at at the moment is shown below:\n\n{pd.DataFrame(current_data_sample).head(10).to_string()}"
 
         if start_question:
             context += f"\n\n[START QUESTION]\n\n{start_question}"
diff --git a/py-src/data_formulator/agents/agent_py_data_rec.py b/py-src/data_formulator/agents/agent_py_data_rec.py
index 1ff67b0..f943db3 100644
--- a/py-src/data_formulator/agents/agent_py_data_rec.py
+++ b/py-src/data_formulator/agents/agent_py_data_rec.py
@@ -67,6 +67,8 @@
             * the column can either be a column in the input data, or a new column that will be computed in the output data.
             * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned "average score" in the text while the column to be computed is "Avg_Score", you should still highlight "**average score**" in the text.
     - determine "input_tables", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.
+        - Note that the first table is the table the user is currently viewing, it should take precedence if the user asks for visualization of the "current table".
+        - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.
     - "chart_type" must be one of "point", "bar", "line", "area", "heatmap", "group_bar", "boxplot"
     - "chart_encodings" should specify which fields should be used to create the visualization
         - decide which visual channels should be used to create the visualization appropriate for the chart type.
diff --git a/py-src/data_formulator/agents/agent_py_data_transform.py b/py-src/data_formulator/agents/agent_py_data_transform.py
index 5b86b9e..cd0b6b5 100644
--- a/py-src/data_formulator/agents/agent_py_data_transform.py
+++ b/py-src/data_formulator/agents/agent_py_data_transform.py
@@ -35,6 +35,8 @@
                 * the column can either be a column in the input data, or a new column that will be computed in the output data.
                 * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned "average score" in the text while the column to be computed is "Avg_Score", you should still highlight "**average score**" in the text.
         - determine "input_tables", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.
+            - **IMPORTANT** Note that the Table 1 in [CONTEXT] section is the table the user is currently viewing, it should take precedence if the user refers to insights about the "current table".
+            - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.
         - determine "output_fields", the desired fields that the output data should have to achieve the user's goal, it's a good idea to include intermediate fields here.
         - then decide "chart_encodings", which maps visualization channels (x, y, color, size, opacity, facet, etc.) to a subset of "output_fields" that will be visualized, 
             - the "chart_encodings" should be created to support the user's "chart_type".
diff --git a/py-src/data_formulator/agents/agent_query_completion.py b/py-src/data_formulator/agents/agent_query_completion.py
deleted file mode 100644
index 5e82f38..0000000
--- a/py-src/data_formulator/agents/agent_query_completion.py
+++ /dev/null
@@ -1,83 +0,0 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
-
-import json
-
-from data_formulator.agents.agent_utils import extract_json_objects
-import re
-import logging
-
-
-logger = logging.getLogger(__name__)
-
-
-SYSTEM_PROMPT = '''You are a data scientist to help with data queries. 
-The user will provide you with a description of the data source and tables available in the [DATA SOURCE] section and a query in the [USER INPUTS] section. 
-You will need to help the user complete the query and provide reasoning for the query you generated in the [OUTPUT] section.
-
-Input format:
-* The data source description is a json object with the following fields:
-    * `data_source`: the name of the data source
-    * `tables`: a list of tables in the data source, which maps the table name to the list of columns available in the table.
-* The user input is a natural language description of the query or a partial query you need to complete.
-
-Steps:
-* Based on data source description and user input, you should first decide on what language should be used to query the data. 
-* Then, describe the logic for the query you generated in a json object in a block ```json``` with the following fields:
-    * `language`: the language of the query you generated
-    * `tables`: the names of the tables you will use in the query
-    * `logic`: the reasoning behind why you chose the tables and the logic for the query you generated
-* Finally, generate the complete query in the language specified in a code block ```{language}```.
-
-Output format:
-* The output should be in the following format, no other text should be included:
-
-[REASONING]
-```json
-{
-    "language": {language},
-    "tables": {tables},
-    "logic": {logic}
-}
-```
-
-[QUERY]
-```{language}   
-{query}
-```
-'''
-
-class QueryCompletionAgent(object):
-
-    def __init__(self, client):
-        self.client = client
-
-    def run(self, data_source_metadata, query):
-
-        # For MongoDB, treat it as a SQL-like data source for query generation
-        if data_source_metadata['data_loader_type'] == "mongodb":
-            data_source_metadata['data_loader_type'] = "SQL"
-
-        user_query = f"[DATA SOURCE]\n\n{json.dumps(data_source_metadata, indent=2)}\n\n[USER INPUTS]\n\n{query}\n\n"
-
-        logger.info(user_query)
-
-        messages = [{"role":"system", "content": SYSTEM_PROMPT},
-                    {"role":"user","content": user_query}]
-        
-        ###### the part that calls open_ai
-        response = self.client.get_completion(messages = messages)
-        response_content = response.choices[0].message.content
-        
-        logger.info(f"=== query completion output ===>\n{response_content}\n")
-
-        reasoning = extract_json_objects(response_content.split("[QUERY]")[0].strip())[0]
-        output_query = response_content.split("[QUERY]")[1].strip()
-        
-        # Extract the query by removing the language markers
-        language_pattern = r"```(\w+)\s+(.*?)```"
-        match = re.search(language_pattern, output_query, re.DOTALL)
-        if match:
-            output_query = match.group(2).strip()
-
-        return reasoning, output_query
diff --git a/py-src/data_formulator/agents/agent_report_gen.py b/py-src/data_formulator/agents/agent_report_gen.py
index eabcf81..f1dac08 100644
--- a/py-src/data_formulator/agents/agent_report_gen.py
+++ b/py-src/data_formulator/agents/agent_report_gen.py
@@ -4,7 +4,7 @@
 import json
 
 from data_formulator.agents.agent_utils import extract_json_objects, generate_data_summary
-from data_formulator.agents.agent_sql_data_transform import  sanitize_table_name, get_sql_table_statistics_str
+from data_formulator.agents.agent_sql_data_transform import generate_sql_data_summary
 
 import logging
 
@@ -45,8 +45,7 @@
     - "blog post": "blog post", -- a blogpost that is published on a blog platform
     - "social post": "social post", -- a social post that is published on a social media platform (should be shorter than a blog post)
     - "executive summary": "executive summary", -- a summary of the report for executives, with more formal language and more details, and more bullet points
-    - "short note": "short note", -- a short note that is published on a social media platform, with no more than 300 characters in total, and there should be no more than 3 short sentences.
-
+    - "live report": "live report", -- a live report is designed for user to monitor the data and visualization live (like a dashboard), thus, don't interpret the visualization as of now since data will change, instead describe what each chart is designed for and hint what the user should look for as data get updated.
 The report should be lightweight, and respect facts in the data. Do not make up any facts or make judgements about the data.
 The report should be based off the data and visualizations provided by the user, do not make up any facts or make judgements about the data.
 Output markdown directly, do not need to include any other text.
@@ -60,11 +59,7 @@ def __init__(self, client, conn):
 
     def get_data_summary(self, input_tables):
         if self.conn:
-            data_summary = ""
-            for table in input_tables:
-                table_name = sanitize_table_name(table['name'])
-                table_summary_str = get_sql_table_statistics_str(self.conn, table_name)
-                data_summary += f"[TABLE {table_name}]\n\n{table_summary_str}\n\n"
+            data_summary = generate_sql_data_summary(self.conn, input_tables)
         else:
             data_summary = generate_data_summary(input_tables)
         return data_summary
@@ -82,7 +77,7 @@ def stream(self, input_tables, charts=[], style="blog post"):
                     "chart_url": ... // base64 encoded image
                 }
             ]
-            - style (str): the style of the report, can be "blog post" or "social post" or "executive summary" or "short note"
+            - style (str): the style of the report, can be "blog post" or "social post" or "executive summary" or "live report"
         Returns:
             generator: the result of the agent
         """
diff --git a/py-src/data_formulator/agents/agent_sql_data_rec.py b/py-src/data_formulator/agents/agent_sql_data_rec.py
index 835bfd9..bc48c05 100644
--- a/py-src/data_formulator/agents/agent_sql_data_rec.py
+++ b/py-src/data_formulator/agents/agent_sql_data_rec.py
@@ -4,7 +4,7 @@
 import json
 
 from data_formulator.agents.agent_utils import extract_json_objects, extract_code_from_gpt_response
-from data_formulator.agents.agent_sql_data_transform import get_sql_table_statistics_str, sanitize_table_name
+from data_formulator.agents.agent_sql_data_transform import generate_sql_data_summary
 
 import random
 import string
@@ -37,6 +37,7 @@
     "recap": "..." // string, a short summary of the user's goal.
     "display_instruction": "..." // string, the even shorter verb phrase describing the users' goal.
     "recommendation": "..." // string, explain why this recommendation is made
+    "input_tables": [...] // string[], describe names of the input tables that will be used in the transformation.
     "output_fields": [...] // string[], describe the desired output fields that the output data should have (i.e., the goal of transformed data), it's a good idea to preseve intermediate fields here
     "chart_type": "" // string, one of "point", "bar", "line", "area", "heatmap", "group_bar". "chart_type" should either be inferred from user instruction, or recommend if the user didn't specify any.
     "chart_encodings": {
@@ -69,6 +70,9 @@
         - if you mention column names from the input or the output data, highlight the text in **bold**.
             * the column can either be a column in the input data, or a new column that will be computed in the output data.
             * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned "average score" in the text while the column to be computed is "Avg_Score", you should still highlight "**average score**" in the text.
+    - determine "input_tables", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.
+        - **IMPORTANT** Note that the Table 1 in [CONTEXT] section is the table the user is currently viewing, it should take precedence if the user refers to insights about the "current table".
+        - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.
     - "chart_type" must be one of "point", "bar", "line", "area", "heatmap", "group_bar"
     - "chart_encodings" should specify which fields should be used to create the visualization
         - decide which visual channels should be used to create the visualization appropriate for the chart type.
@@ -188,6 +192,7 @@
 
 ```json
 {  
+    "input_tables": ["student_exam"],
     "recap": "Rank students based on their average scores",
     "display_instruction": "Rank students by **average scores**",
     "mode": "infer",
@@ -318,11 +323,7 @@ def process_gpt_response(self, input_tables, messages, response):
     
 
     def run(self, input_tables, description, n=1, prev_messages: list[dict] = []):
-        data_summary = ""
-        for table in input_tables:
-            table_name = sanitize_table_name(table['name'])
-            table_summary_str = get_sql_table_statistics_str(self.conn, table_name)
-            data_summary += f"[TABLE {table_name}]\n\n{table_summary_str}\n\n"
+        data_summary = generate_sql_data_summary(self.conn, input_tables)
 
         user_query = f"[CONTEXT]\n\n{data_summary}\n\n[GOAL]\n\n{description}"
         if len(prev_messages) > 0:
diff --git a/py-src/data_formulator/agents/agent_sql_data_transform.py b/py-src/data_formulator/agents/agent_sql_data_transform.py
index 32340c6..89f158e 100644
--- a/py-src/data_formulator/agents/agent_sql_data_transform.py
+++ b/py-src/data_formulator/agents/agent_sql_data_transform.py
@@ -26,6 +26,9 @@
 
     1. First, refine users' [GOAL]. The main objective in this step is to check if "chart_type" and "chart_encodings" provided by the user are sufficient to achieve their "goal". Concretely:
         - based on the user's "goal" and "chart_type" and "chart_encodings", elaborate the goal into a "detailed_instruction".
+        - determine "input_tables", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.
+            - **IMPORTANT** Note that the Table 1 in [CONTEXT] section is the table the user is currently viewing, it should take precedence if the user refers to insights about the "current table".
+            - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.
         - "display_instruction" is a short verb phrase describing the users' goal. 
             - it would be a short verbal description of user intent as a verb phrase (<12 words).
             - generate it based on detailed_instruction and the suggested chart_type and chart_encodings, but don't need to mention the chart details.
@@ -52,6 +55,7 @@
 
 ```
 {
+    "input_tables": ["student_exam"],
     "detailed_instruction": "..." // string, elaborate user instruction with details if the user
     "display_instruction": "..." // string, the short verb phrase describing the users' goal.
     "output_fields": [...] // string[], describe the desired output fields that the output data should have based on the user's goal, it's a good idea to preserve intermediate fields here (i.e., the goal of transformed data)
@@ -100,22 +104,23 @@
 EXAMPLE='''
 [CONTEXT]
 
-Here are our datasets, here are their field summaries and samples:
+Here are 1 dataset with their summaries:
 
-table_0 (weather_seattle_atlanta) fields:
-	Date -- type: object, values: 1/1/2020, 1/10/2020, 1/11/2020, ..., 9/6/2020, 9/7/2020, 9/8/2020, 9/9/2020
-	City -- type: object, values: Atlanta, Seattle
-	Temperature -- type: int64, values: 30, 31, 32, ..., 83, 84, 85, 86
+## Table 1: weather_seattle_atlanta (548 rows × 3 columns)
 
-table_0 (weather_seattle_atlanta) sample:
+### Schema (3 fields)
+  - Date -- type: VARCHAR, values: 1/1/2020, 1/10/2020, 1/11/2020, ..., 9/7/2020, 9/8/2020, 9/9/2020
+  - City -- type: VARCHAR, values: Atlanta, Seattle
+  - Temperature -- type: INTEGER, range: [30, 86]
+
+### Sample Data (first 5 rows)
 ```
-|Date|City|Temperature
-0|1/1/2020|Seattle|51
-1|1/1/2020|Atlanta|45
-2|1/2/2020|Seattle|45
-3|1/2/2020|Atlanta|47
-4|1/3/2020|Seattle|48
-......
+        Date    City  Temperature
+0   1/1/2020  Seattle           51
+1   1/1/2020  Atlanta           45
+2   1/2/2020  Seattle           45
+3   1/2/2020  Atlanta           47
+4   1/3/2020  Seattle           48
 ```
 
 [GOAL]
@@ -129,6 +134,7 @@
 [OUTPUT]
 
 {  
+    "input_tables": ["weather_seattle_atlanta"],
     "detailed_instruction": "Create a scatter plot to compare Seattle and Atlanta temperatures with Seattle temperatures on the x-axis and Atlanta temperatures on the y-axis. Color the points by which city is warmer.",  
     "display_instruction": "Create a scatter plot to compare Seattle and Atlanta temperatures",
     "output_fields": ["Date", "Seattle Temperature", "Atlanta Temperature", "Warmer City"],  
@@ -137,15 +143,20 @@
 }
 
 ```sql
-WITH MovingAverage AS (  
-    SELECT   
-        Date,  
-        Cases,  
-        AVG(Cases) OVER (ORDER BY Date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS "7-day average cases"  
-    FROM us_covid_cases  
-)  
-SELECT Date, "7-day average cases"  
-FROM MovingAverage;  
+WITH pivoted AS (
+    SELECT 
+        Date,
+        MAX(CASE WHEN City = 'Seattle' THEN Temperature END) AS "Seattle Temperature",
+        MAX(CASE WHEN City = 'Atlanta' THEN Temperature END) AS "Atlanta Temperature"
+    FROM weather_seattle_atlanta
+    GROUP BY Date
+)
+SELECT 
+    Date,
+    "Seattle Temperature",
+    "Atlanta Temperature",
+    CASE WHEN "Seattle Temperature" > "Atlanta Temperature" THEN 'Seattle' ELSE 'Atlanta' END AS "Warmer City"
+FROM pivoted;
 ```
 '''
 
@@ -290,11 +301,7 @@ def run(self, input_tables, description, chart_type: str, chart_encodings: dict,
                 logger.info(f"Created table {table_name} from dataframe")
 
 
-        data_summary = ""
-        for table in input_tables:
-            table_name = sanitize_table_name(table['name'])
-            table_summary_str = get_sql_table_statistics_str(self.conn, table_name)
-            data_summary += f"[TABLE {table_name}]\n\n{table_summary_str}\n\n"
+        data_summary = generate_sql_data_summary(self.conn, input_tables)
 
         goal = {
             "instruction": description,
@@ -352,26 +359,96 @@ def followup(self, input_tables, dialog, latest_data_sample, chart_type: str, ch
         return self.process_gpt_sql_response(response, messages)
         
 
+def generate_sql_data_summary(conn, input_tables: list[dict], 
+        row_sample_size: int = 5,
+        field_sample_size: int = 7,
+        max_val_chars: int = 140,
+        table_name_prefix: str = "Table"
+    ) -> str:
+    """
+    Generate a natural, well-organized summary of SQL input tables.
+    This is the SQL equivalent of generate_data_summary for pandas DataFrames.
+    
+    Organization approach:
+    - Each table is clearly separated with a header
+    - Information flows logically: Overview → Schema → Examples
+    - Consistent section ordering for better readability
+    
+    Args:
+        conn: DuckDB connection
+        input_tables: list of dicts, each containing 'name' key for the table name
+        row_sample_size: number of rows to sample in the data preview
+        field_sample_size: number of example values for each field
+        max_val_chars: max characters to show for each value
+        table_name_prefix: prefix for table headers (default "Table")
+    
+    Returns:
+        A formatted string summary of all tables
+    """
+    table_summaries = []
+    
+    for idx, table in enumerate(input_tables):
+        table_name = sanitize_table_name(table['name'])
+        description = table.get("attached_metadata", "")
+        table_summary_str = get_sql_table_statistics_str(
+            conn, table_name, 
+            row_sample_size=row_sample_size,
+            field_sample_size=field_sample_size,
+            max_val_chars=max_val_chars,
+            table_name_prefix=table_name_prefix,
+            table_idx=idx,
+            description=description
+        )
+        table_summaries.append(table_summary_str)
+    
+    # Add visual separator between tables (except for the last one)
+    separator = "\n" + "─" * 60 + "\n\n"
+    joined_summaries = separator.join(table_summaries)
+    
+    return joined_summaries
+
+
 def get_sql_table_statistics_str(conn, table_name: str, 
         row_sample_size: int = 5, # number of rows to be sampled in the sample data part
         field_sample_size: int = 7, # number of example values for each field to be sampled
-        max_val_chars: int = 140 # max number of characters to be shown for each example value
+        max_val_chars: int = 140, # max number of characters to be shown for each example value
+        table_name_prefix: str = "Table",
+        table_idx: int = 0,
+        description: str = ""
     ) -> str:
-    """Get a string representation of the table statistics"""
+    """
+    Get a string representation of the table statistics in markdown format.
+    
+    Organization:
+    - Header with table name and dimensions
+    - Description (if available)
+    - Schema section with field summaries
+    - Sample data section with code block
+    """
 
     table_name = sanitize_table_name(table_name)
 
-    # Get column information
+    # Get column information and row count
     columns = conn.execute(f"DESCRIBE {table_name}").fetchall()
-    sample_data = conn.execute(f"SELECT * FROM {table_name} LIMIT {row_sample_size}").fetchall()
+    row_count = conn.execute(f"SELECT COUNT(*) FROM {table_name}").fetchone()[0]
+    num_cols = len(columns)
+    
+    # Build sections in logical order: Overview → Description → Schema → Examples
+    sections = []
     
-    # Format sample data as pipe-separated string
-    col_names = [col[0] for col in columns]
-    formatted_sample_data = "| " + " | ".join(col_names) + " |\n"
-    for i, row in enumerate(sample_data):
-        formatted_sample_data += f"{i}| " + " | ".join(str(val)[:max_val_chars]+ "..." if len(str(val)) > max_val_chars else str(val) for val in row) + " |\n"
+    # 1. Table Header with basic stats
+    header = f"## {table_name_prefix} {table_idx + 1}: {table_name}"
+    if row_count > 0:
+        header += f" ({row_count:,} rows × {num_cols} columns)"
+    sections.append(header)
+    sections.append("")  # Empty line for spacing
     
-    col_metadata_list = []
+    # 2. Description (if available) - provides context first
+    if description:
+        sections.append(f"### Description\n{description}\n")
+    
+    # 3. Schema/Fields - core structure information
+    field_summaries = []
     for col in columns:
         col_name = col[0]
         col_type = col[1]
@@ -379,68 +456,61 @@ def get_sql_table_statistics_str(conn, table_name: str,
         # Properly quote column names to avoid SQL keywords issues
         quoted_col_name = f'"{col_name}"'
         
-        # Basic stats query
-        stats_query = f"""
-        SELECT 
-            COUNT(*) as count,
-            COUNT(DISTINCT {quoted_col_name}) as unique_count,
-            COUNT(*) - COUNT({quoted_col_name}) as null_count
-        FROM {table_name}
-        """
-        
-        # Add numeric stats if applicable
-        if col_type in ['INTEGER', 'DOUBLE', 'DECIMAL']:
-            stats_query = f"""
-            SELECT 
-                COUNT(*) as count,
-                COUNT(DISTINCT {quoted_col_name}) as unique_count,
-                COUNT(*) - COUNT({quoted_col_name}) as null_count,
-                MIN({quoted_col_name}) as min_value,
-                MAX({quoted_col_name}) as max_value,
-                AVG({quoted_col_name}) as avg_value
+        # Get sample values for the field
+        if col_type in ['INTEGER', 'BIGINT', 'DOUBLE', 'DECIMAL', 'FLOAT', 'REAL']:
+            # For numeric types, get min/max as value range indicator
+            range_query = f"""
+            SELECT MIN({quoted_col_name}), MAX({quoted_col_name})
             FROM {table_name}
+            WHERE {quoted_col_name} IS NOT NULL
             """
-        
-        col_stats = conn.execute(stats_query).fetchone()
-        
-        # Create a dictionary with appropriate keys based on column type
-        if col_type in ['INTEGER', 'DOUBLE', 'DECIMAL']:
-            stats_dict = dict(zip(
-                ["count", "unique_count", "null_count", "min", "max", "avg"],
-                col_stats
-            ))
+            range_result = conn.execute(range_query).fetchone()
+            if range_result[0] is not None:
+                min_val, max_val = range_result
+                val_str = f"range: [{min_val}, {max_val}]"
+            else:
+                val_str = "all null"
         else:
-            stats_dict = dict(zip(
-                ["count", "unique_count", "null_count"],
-                col_stats
-            ))
-
-            # Combined query for top 4 and bottom 3 values using UNION ALL
+            # For non-numeric types, get sample values similar to Python version
             query_for_sample_values = f"""
-            (SELECT DISTINCT {quoted_col_name}
-                FROM {table_name} 
-                WHERE {quoted_col_name} IS NOT NULL 
-                LIMIT {field_sample_size})
+            SELECT DISTINCT {quoted_col_name}
+            FROM {table_name} 
+            WHERE {quoted_col_name} IS NOT NULL 
+            ORDER BY {quoted_col_name}
+            LIMIT {field_sample_size * 2}
             """
             
-            sample_values = conn.execute(query_for_sample_values).fetchall()
-            
-            stats_dict['sample_values'] = [str(val)[:max_val_chars]+ "..." if len(str(val)) > max_val_chars else str(val) for val in sample_values]
-
-        col_metadata_list.append({
-            "column": col_name,
-            "type": col_type,
-            "statistics": stats_dict,
-        })
-
-    table_metadata = {
-        "column_metadata": col_metadata_list,
-        "sample_data_str": formatted_sample_data
-    }
-
-    table_summary_str = f"Column metadata:\n\n"
-    for col_metadata in table_metadata['column_metadata']:
-        table_summary_str += f"\t{col_metadata['column']} ({col_metadata['type']}) ---- {col_metadata['statistics']}\n"
-    table_summary_str += f"\n\nSample data:\n\n{table_metadata['sample_data_str']}\n"
-
-    return table_summary_str
+            try:
+                sample_values_result = conn.execute(query_for_sample_values).fetchall()
+                sample_values = [row[0] for row in sample_values_result]
+                
+                # Format values similar to Python version
+                def sample_val_cap(val):
+                    s = str(val)
+                    if len(s) > max_val_chars:
+                        s = s[:max_val_chars] + "..."
+                    if ',' in s:
+                        s = f'"{s}"'
+                    return s
+                
+                if len(sample_values) <= field_sample_size:
+                    val_sample = sample_values
+                else:
+                    half = field_sample_size // 2
+                    val_sample = sample_values[:half] + ["..."] + sample_values[-(field_sample_size - half):]
+                
+                val_str = "values: " + ', '.join([sample_val_cap(v) for v in val_sample])
+            except Exception:
+                val_str = "values: N/A"
+        
+        field_summaries.append(f"  - {col_name} -- type: {col_type}, {val_str}")
+    
+    fields_summary = '\n'.join(field_summaries)
+    sections.append(f"### Schema ({num_cols} fields)\n{fields_summary}\n")
+    
+    # 4. Sample data - concrete examples last
+    if row_count > 0:
+        sample_data = conn.execute(f"SELECT * FROM {table_name} LIMIT {row_sample_size}").fetch_df()
+        sections.append(f"### Sample Data (first {min(row_sample_size, row_count)} rows)\n```\n{sample_data.to_string()}\n```\n")
+    
+    return '\n'.join(sections)
diff --git a/py-src/data_formulator/agents/agent_utils.py b/py-src/data_formulator/agents/agent_utils.py
index 87a3a14..1d53d03 100644
--- a/py-src/data_formulator/agents/agent_utils.py
+++ b/py-src/data_formulator/agents/agent_utils.py
@@ -149,34 +149,6 @@ def extract_json_objects(text):
     return json_objects  
 
 
-def insert_candidates(code, table, dialog, candidate_groups):
-    """ Try to insert a candidate into existing candidate groups
-    Args:
-        code: code candidate
-        table: json records table
-        candidate_groups: current candidate group
-    Returns:
-        a boolean flag incidate whether new_group_created
-    """
-    table_headers = sorted(table[0].keys())
-    t_hash = table_hash([{c: r[c] for c in table_headers} for r in table])
-    if t_hash in candidate_groups:
-        candidate_groups[t_hash].append({"code": code, "content": table, "dialog": dialog})
-        new_group_created = False
-    else:
-        candidate_groups[t_hash] = [{"code": code, "content": table, "dialog": dialog}]
-        new_group_created = True
-    return new_group_created
-
-def dedup_data_transform_candidates(candidates):
-    """each candidate is a tuple of {status: ..., code: ..., data: ..., dialog: ...},
-    this function extracts candidates that are 'ok', and removes uncessary duplicates"""
-    candidate_groups = {}
-    for candidate in candidates:
-        insert_candidates(candidate["code"], candidate['data'], candidate['dialog'], candidate_groups)
-    return [items[0] for _, items in candidate_groups.items()]
-
-
 def get_field_summary(field_name, df, field_sample_size, max_val_chars=100):
     # Convert lists to strings to make them hashable
     def make_hashable(val):
@@ -215,7 +187,7 @@ def sample_val_cap(val):
 
     return f"{field_name} -- type: {df[field_name].dtype}, values: {val_str}"
 
-def generate_data_summary(input_tables, include_data_samples=True, field_sample_size=7, max_val_chars=140):
+def generate_data_summary(input_tables, include_data_samples=True, field_sample_size=7, max_val_chars=140, table_name_prefix="Table"):
     """
     Generate a natural, well-organized summary of input tables.
     
@@ -238,7 +210,7 @@ def assemble_table_summary(input_table, idx):
         sections = []
         
         # 1. Table Header with basic stats
-        header = f"## Table {idx + 1}: {name}"
+        header = f"## {table_name_prefix} {idx + 1}: {name}"
         if num_rows > 0:
             header += f" ({num_rows:,} rows × {num_cols} columns)"
         sections.append(header)
@@ -267,10 +239,6 @@ def assemble_table_summary(input_table, idx):
     separator = "\n" + "─" * 60 + "\n\n"
     joined_summaries = separator.join(table_summaries)
     
-    # Natural introduction
-    num_tables = len(input_tables)
-    intro = f"Here are {num_tables} dataset{'s' if num_tables != 1 else ''} with their summaries:\n\n"
-    
-    full_summary = intro + joined_summaries
+    full_summary = joined_summaries
     return full_summary
 
diff --git a/py-src/data_formulator/data_loader/azure_blob_data_loader.py b/py-src/data_formulator/data_loader/azure_blob_data_loader.py
index da97a3b..1206f4e 100644
--- a/py-src/data_formulator/data_loader/azure_blob_data_loader.py
+++ b/py-src/data_formulator/data_loader/azure_blob_data_loader.py
@@ -348,29 +348,39 @@ def _estimate_by_row_sampling(self, azure_url: str, file_extension: str) -> int:
             print(f"Error in row sampling for {azure_url}: {e}")
             return 0
 
-    def ingest_data(self, table_name: str, name_as: str = None, size: int = 1000000):
+    def ingest_data(self, table_name: str, name_as: str = None, size: int = 1000000, sort_columns: List[str] = None, sort_order: str = 'asc'):
         if name_as is None:
             name_as = table_name.split('/')[-1].split('.')[0]
         
         name_as = sanitize_table_name(name_as)
         
+        # Build ORDER BY clause if sort_columns are specified
+        order_by_clause = ""
+        if sort_columns and len(sort_columns) > 0:
+            order_direction = "DESC" if sort_order == 'desc' else "ASC"
+            sanitized_cols = [f'"{col}" {order_direction}' for col in sort_columns]
+            order_by_clause = f"ORDER BY {', '.join(sanitized_cols)}"
+        
         # Determine file type and use appropriate DuckDB function
         if table_name.lower().endswith('.csv'):
             self.duck_db_conn.execute(f"""
                 CREATE OR REPLACE TABLE main.{name_as} AS 
                 SELECT * FROM read_csv_auto('{table_name}')
+                {order_by_clause}
                 LIMIT {size}
             """)
         elif table_name.lower().endswith('.parquet'):
             self.duck_db_conn.execute(f"""
                 CREATE OR REPLACE TABLE main.{name_as} AS 
                 SELECT * FROM read_parquet('{table_name}')
+                {order_by_clause}
                 LIMIT {size}
             """)
         elif table_name.lower().endswith('.json') or table_name.lower().endswith('.jsonl'):
             self.duck_db_conn.execute(f"""
                 CREATE OR REPLACE TABLE main.{name_as} AS 
                 SELECT * FROM read_json_auto('{table_name}')
+                {order_by_clause}
                 LIMIT {size}
             """)
         else:
diff --git a/py-src/data_formulator/data_loader/bigquery_data_loader.py b/py-src/data_formulator/data_loader/bigquery_data_loader.py
index c0383e8..cd3c1cf 100644
--- a/py-src/data_formulator/data_loader/bigquery_data_loader.py
+++ b/py-src/data_formulator/data_loader/bigquery_data_loader.py
@@ -204,7 +204,7 @@ def safe_convert(x):
 
         return df
 
-    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 1000000):
+    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 1000000, sort_columns: List[str] = None, sort_order: str = 'asc'):
             """Ingest data from BigQuery table into DuckDB with stable, de-duplicated column aliases."""
             if name_as is None:
                 name_as = table_name.split('.')[-1]
@@ -272,7 +272,15 @@ def process_field(field, parent_path: str = ""):
             if not select_parts:
                 raise ValueError(f"No fields found for table {table_name}")
 
-            query = f"SELECT {', '.join(select_parts)} FROM `{table_name}` LIMIT {size}"
+            # Build ORDER BY clause if sort_columns are specified
+            order_by_clause = ""
+            if sort_columns and len(sort_columns) > 0:
+                # Use backticks for BigQuery column quoting
+                order_direction = "DESC" if sort_order == 'desc' else "ASC"
+                sanitized_cols = [f'`{col}` {order_direction}' for col in sort_columns]
+                order_by_clause = f"ORDER BY {', '.join(sanitized_cols)}"
+
+            query = f"SELECT {', '.join(select_parts)} FROM `{table_name}` {order_by_clause} LIMIT {size}"
 
             df = self.client.query(query).to_dataframe()
 
diff --git a/py-src/data_formulator/data_loader/external_data_loader.py b/py-src/data_formulator/data_loader/external_data_loader.py
index 8048085..41060d8 100644
--- a/py-src/data_formulator/data_loader/external_data_loader.py
+++ b/py-src/data_formulator/data_loader/external_data_loader.py
@@ -93,7 +93,16 @@ def list_tables(self, table_filter: str = None) -> List[Dict[str, Any]]:
         pass
 
     @abstractmethod
-    def ingest_data(self, table_name: str, name_as: str = None, size: int = 1000000):
+    def ingest_data(self, table_name: str, name_as: str = None, size: int = 1000000, sort_columns: List[str] = None, sort_order: str = 'asc'):
+        """Ingest data from a table into DuckDB.
+        
+        Args:
+            table_name: The source table name
+            name_as: Optional name for the destination table
+            size: Maximum number of rows to import (row limit)
+            sort_columns: Optional list of columns to sort by before applying the limit
+            sort_order: Sort direction, 'asc' for ascending or 'desc' for descending
+        """
         pass
 
     @abstractmethod
diff --git a/py-src/data_formulator/data_loader/kusto_data_loader.py b/py-src/data_formulator/data_loader/kusto_data_loader.py
index 8801621..6ed6d60 100644
--- a/py-src/data_formulator/data_loader/kusto_data_loader.py
+++ b/py-src/data_formulator/data_loader/kusto_data_loader.py
@@ -197,10 +197,18 @@ def list_tables(self, table_filter: str = None) -> List[Dict[str, Any]]:
 
         return tables
     
-    def ingest_data(self, table_name: str, name_as: str = None, size: int = 5000000) -> pd.DataFrame:
+    def ingest_data(self, table_name: str, name_as: str = None, size: int = 5000000, sort_columns: List[str] = None, sort_order: str = 'asc') -> pd.DataFrame:
         if name_as is None:
             name_as = table_name
         
+        # Build sort clause for Kusto (KQL syntax)
+        sort_clause = ""
+        if sort_columns and len(sort_columns) > 0:
+            # Kusto uses | sort by col1 asc/desc syntax
+            order_direction = "desc" if sort_order == 'desc' else "asc"
+            sort_cols_with_order = [f"{col} {order_direction}" for col in sort_columns]
+            sort_clause = f" | sort by {', '.join(sort_cols_with_order)}"
+        
         # Create a subquery that applies random ordering once with a fixed seed
         total_rows_ingested = 0
         first_chunk = True
@@ -216,7 +224,8 @@ def ingest_data(self, table_name: str, name_as: str = None, size: int = 5000000)
 
         while total_rows_ingested < size:
             try:
-                query = f"['{table_name}'] | serialize | extend rn=row_number() | where rn >= {total_rows_ingested} and rn < {total_rows_ingested + chunk_size} | project-away rn"
+                # Apply sort if specified, then apply row numbering for pagination
+                query = f"['{table_name}']{sort_clause} | serialize | extend rn=row_number() | where rn >= {total_rows_ingested} and rn < {total_rows_ingested + chunk_size} | project-away rn"
                 chunk_df = self.query(query)
             except Exception as e:
                 chunk_size = int(chunk_size * 0.8)
diff --git a/py-src/data_formulator/data_loader/mongodb_data_loader.py b/py-src/data_formulator/data_loader/mongodb_data_loader.py
index 32ad8cd..6b46035 100644
--- a/py-src/data_formulator/data_loader/mongodb_data_loader.py
+++ b/py-src/data_formulator/data_loader/mongodb_data_loader.py
@@ -240,7 +240,7 @@ def list_tables(self, table_filter: str = None):
         
         return results
     
-    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 100000):
+    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 100000, sort_columns: List[str] = None, sort_order: str = 'asc'):
         """
         Import MongoDB collection data into DuckDB
         """
@@ -256,7 +256,16 @@ def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int
 
         # Get and process data from MongoDB (limit rows)
         collection = self.db[collection_name]
-        data_cursor = collection.find().limit(size)
+        
+        # Build cursor with optional sorting
+        data_cursor = collection.find()
+        if sort_columns and len(sort_columns) > 0:
+            # MongoDB sort format: 1 for ascending, -1 for descending
+            sort_direction = -1 if sort_order == 'desc' else 1
+            sort_spec = [(col, sort_direction) for col in sort_columns]
+            data_cursor = data_cursor.sort(sort_spec)
+        data_cursor = data_cursor.limit(size)
+        
         data_list = list(data_cursor)
         if not data_list:
             raise Exception(f"No data found in MongoDB collection '{collection_name}'.")
diff --git a/py-src/data_formulator/data_loader/mssql_data_loader.py b/py-src/data_formulator/data_loader/mssql_data_loader.py
index eeb8c4f..1f18a79 100644
--- a/py-src/data_formulator/data_loader/mssql_data_loader.py
+++ b/py-src/data_formulator/data_loader/mssql_data_loader.py
@@ -387,7 +387,7 @@ def list_tables(self):
 
         return results
 
-    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 1000000):
+    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 1000000, sort_columns: List[str] = None, sort_order: str = 'asc'):
         """Ingest data from SQL Server table into DuckDB"""
         # Parse table name (assuming format: schema.table)
         if "." in table_name:
@@ -402,8 +402,16 @@ def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int
         name_as = sanitize_table_name(name_as)
 
         try:
+            # Build ORDER BY clause if sort_columns are specified
+            order_by_clause = ""
+            if sort_columns and len(sort_columns) > 0:
+                # Use square brackets for SQL Server column quoting
+                order_direction = "DESC" if sort_order == 'desc' else "ASC"
+                sanitized_cols = [f'[{col}] {order_direction}' for col in sort_columns]
+                order_by_clause = f"ORDER BY {', '.join(sanitized_cols)}"
+
             # Query data from SQL Server with limit
-            query = f"SELECT TOP {size} * FROM [{schema}].[{table}]"
+            query = f"SELECT TOP {size} * FROM [{schema}].[{table}] {order_by_clause}"
             df = self._execute_query(query)
 
             # Use the base class method to ingest DataFrame into DuckDB
diff --git a/py-src/data_formulator/data_loader/mysql_data_loader.py b/py-src/data_formulator/data_loader/mysql_data_loader.py
index 9e29f3b..0430a57 100644
--- a/py-src/data_formulator/data_loader/mysql_data_loader.py
+++ b/py-src/data_formulator/data_loader/mysql_data_loader.py
@@ -220,7 +220,7 @@ def list_tables(self, table_filter: str = None) -> List[Dict[str, Any]]:
             
         return results
 
-    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 1000000):
+    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 1000000, sort_columns: List[str] = None, sort_order: str = 'asc'):
         """Fetch data from MySQL and ingest into DuckDB."""
         if name_as is None:
             name_as = table_name.split('.')[-1]
@@ -236,14 +236,22 @@ def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int
         except Exception:
             raise ValueError("Size parameter must be a positive integer.")
 
+        # Build ORDER BY clause if sort_columns are specified
+        order_by_clause = ""
+        if sort_columns and len(sort_columns) > 0:
+            # Use backticks for MySQL column quoting
+            order_direction = "DESC" if sort_order == 'desc' else "ASC"
+            sanitized_cols = [f'`{col}` {order_direction}' for col in sort_columns]
+            order_by_clause = f"ORDER BY {', '.join(sanitized_cols)}"
+
         if '.' in table_name:
             parts = table_name.split('.')
             schema = sanitize_table_name(parts[0])
             tbl = sanitize_table_name(parts[1])
-            query = f"SELECT * FROM `{schema}`.`{tbl}` LIMIT {sanitized_size}"
+            query = f"SELECT * FROM `{schema}`.`{tbl}` {order_by_clause} LIMIT {sanitized_size}"
         else:
             sanitized_table_name = sanitize_table_name(table_name)
-            query = f"SELECT * FROM `{sanitized_table_name}` LIMIT {sanitized_size}"
+            query = f"SELECT * FROM `{sanitized_table_name}` {order_by_clause} LIMIT {sanitized_size}"
 
         # Fetch data from MySQL
         df = self._execute_query(query)
diff --git a/py-src/data_formulator/data_loader/postgresql_data_loader.py b/py-src/data_formulator/data_loader/postgresql_data_loader.py
index b045376..b327a73 100644
--- a/py-src/data_formulator/data_loader/postgresql_data_loader.py
+++ b/py-src/data_formulator/data_loader/postgresql_data_loader.py
@@ -130,16 +130,25 @@ def list_tables(self):
             print(f"Error listing tables: {e}")
             return []
 
-    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 1000000):
+    def ingest_data(self, table_name: str, name_as: Optional[str] = None, size: int = 1000000, sort_columns: List[str] = None, sort_order: str = 'asc'):
         # Create table in the main DuckDB database from Postgres data
         if name_as is None:
             name_as = table_name.split('.')[-1]
 
         name_as = sanitize_table_name(name_as)
 
+        # Build ORDER BY clause if sort_columns are specified
+        order_by_clause = ""
+        if sort_columns and len(sort_columns) > 0:
+            # Sanitize column names to prevent SQL injection
+            order_direction = "DESC" if sort_order == 'desc' else "ASC"
+            sanitized_cols = [f'"{col}" {order_direction}' for col in sort_columns]
+            order_by_clause = f"ORDER BY {', '.join(sanitized_cols)}"
+
         self.duck_db_conn.execute(f"""
             CREATE OR REPLACE TABLE main.{name_as} AS 
             SELECT * FROM {table_name} 
+            {order_by_clause}
             LIMIT {size}
         """)
 
diff --git a/py-src/data_formulator/data_loader/s3_data_loader.py b/py-src/data_formulator/data_loader/s3_data_loader.py
index 074172a..d92b7c4 100644
--- a/py-src/data_formulator/data_loader/s3_data_loader.py
+++ b/py-src/data_formulator/data_loader/s3_data_loader.py
@@ -181,29 +181,39 @@ def _estimate_row_count(self, s3_url: str) -> int:
             print(f"Error estimating row count for {s3_url}: {e}")
             return 0
 
-    def ingest_data(self, table_name: str, name_as: str = None, size: int = 1000000):
+    def ingest_data(self, table_name: str, name_as: str = None, size: int = 1000000, sort_columns: List[str] = None, sort_order: str = 'asc'):
         if name_as is None:
             name_as = table_name.split('/')[-1].split('.')[0]
         
         name_as = sanitize_table_name(name_as)
         
+        # Build ORDER BY clause if sort_columns are specified
+        order_by_clause = ""
+        if sort_columns and len(sort_columns) > 0:
+            order_direction = "DESC" if sort_order == 'desc' else "ASC"
+            sanitized_cols = [f'"{col}" {order_direction}' for col in sort_columns]
+            order_by_clause = f"ORDER BY {', '.join(sanitized_cols)}"
+        
         # Determine file type and use appropriate DuckDB function
         if table_name.lower().endswith('.csv'):
             self.duck_db_conn.execute(f"""
                 CREATE OR REPLACE TABLE main.{name_as} AS 
                 SELECT * FROM read_csv_auto('{table_name}')
+                {order_by_clause}
                 LIMIT {size}
             """)
         elif table_name.lower().endswith('.parquet'):
             self.duck_db_conn.execute(f"""
                 CREATE OR REPLACE TABLE main.{name_as} AS 
                 SELECT * FROM read_parquet('{table_name}')
+                {order_by_clause}
                 LIMIT {size}
             """)
         elif table_name.lower().endswith('.json') or table_name.lower().endswith('.jsonl'):
             self.duck_db_conn.execute(f"""
                 CREATE OR REPLACE TABLE main.{name_as} AS 
                 SELECT * FROM read_json_auto('{table_name}')
+                {order_by_clause}
                 LIMIT {size}
             """)
         else:
diff --git a/py-src/data_formulator/tables_routes.py b/py-src/data_formulator/tables_routes.py
index 66a32ce..a66eb16 100644
--- a/py-src/data_formulator/tables_routes.py
+++ b/py-src/data_formulator/tables_routes.py
@@ -922,18 +922,24 @@ def data_loader_ingest_data():
         data_loader_type = data.get('data_loader_type')
         data_loader_params = data.get('data_loader_params')
         table_name = data.get('table_name')
+        import_options = data.get('import_options', {})
+        
+        # Extract import options
+        row_limit = import_options.get('row_limit', 1000000) if import_options else 1000000
+        sort_columns = import_options.get('sort_columns', None) if import_options else None
+        sort_order = import_options.get('sort_order', 'asc') if import_options else 'asc'
 
         if data_loader_type not in DATA_LOADERS:
             return jsonify({"status": "error", "message": f"Invalid data loader type. Must be one of: {', '.join(DATA_LOADERS.keys())}"}), 400
 
         with db_manager.connection(session['session_id']) as duck_db_conn:
             data_loader = DATA_LOADERS[data_loader_type](data_loader_params, duck_db_conn)
-            data_loader.ingest_data(table_name)
+            data_loader.ingest_data(table_name, size=row_limit, sort_columns=sort_columns, sort_order=sort_order)
             
             # Get the actual table name that was created (may be sanitized)
             sanitized_name = table_name.split('.')[-1]  # Base name
             
-            # Store metadata for refresh capability
+            # Store metadata for refresh capability (include import options for future refresh)
             save_table_metadata(
                 duck_db_conn, 
                 sanitized_name, 
diff --git a/src/app/utils.tsx b/src/app/utils.tsx
index 3412b06..b6c82b6 100644
--- a/src/app/utils.tsx
+++ b/src/app/utils.tsx
@@ -56,7 +56,6 @@ export function getUrls() {
         DATA_LOADER_GET_TABLE_METADATA: `/api/tables/data-loader/get-table-metadata`,
         DATA_LOADER_LIST_TABLE_METADATA: `/api/tables/data-loader/list-table-metadata`,
 
-        QUERY_COMPLETION: `/api/agent/query-completion`,
         GET_RECOMMENDATION_QUESTIONS: `/api/agent/get-recommendation-questions`,
         GENERATE_REPORT_STREAM: `/api/agent/generate-report-stream`,
 
@@ -355,7 +354,38 @@ export function extractFieldsFromEncodingMap(encodingMap: EncodingMap, allFields
     }
 
     return { aggregateFields, groupByFields };
-}   
+}
+
+/**
+ * Check if a numeric value is likely a Unix timestamp (seconds or milliseconds since epoch).
+ * Returns false for values that look like years or other small numbers.
+ */
+function isLikelyTimestamp(val: number): boolean {
+    // Unix timestamps in seconds: typically 10 digits (starts from ~1970)
+    // Unix timestamps in milliseconds: typically 13 digits
+    // Reasonable timestamp range: 1970 (0) to 2100 (~4102444800 seconds)
+    
+    // Milliseconds range: 1970 to 2100
+    const minTimestampMs = 0;  // Jan 1, 1970
+    const maxTimestampMs = 4102444800000;  // ~year 2100
+    
+    // Seconds range: 1970 to 2100
+    const minTimestampSec = 0;
+    const maxTimestampSec = 4102444800;  // ~year 2100
+    
+    // Check if it looks like milliseconds (13 digits, typically > 1e12)
+    if (val >= 1e12 && val <= maxTimestampMs) {
+        return true;
+    }
+    
+    // Check if it looks like seconds (10 digits, typically > 1e9)
+    // Must be > 1e9 to avoid confusion with years (1000-9999)
+    if (val >= 1e9 && val <= maxTimestampSec) {
+        return true;
+    }
+    
+    return false;
+}
 
 export function prepVisTable(table: any[], allFields: FieldItem[], encodingMap: EncodingMap) {
     let { aggregateFields, groupByFields } = extractFieldsFromEncodingMap(encodingMap, allFields);
@@ -454,7 +484,9 @@ export const assembleVegaChart = (
             let fieldMetadata = tableMetadata[field.name];
 
             if (fieldMetadata != undefined) {
-                encodingObj["type"] = getDType(fieldMetadata.type, workingTable.map(r => r[field.name]));
+                let fieldValues = workingTable.map(r => r[field.name]);
+                encodingObj["type"] = getDType(fieldMetadata.type, fieldValues);
+
                 if (fieldMetadata.semanticType == "Date" || fieldMetadata.semanticType == "DateTime" || fieldMetadata.semanticType == "YearMonth" || fieldMetadata.semanticType == "Year" || fieldMetadata.semanticType == "Decade") {
                     if (['color', 'size', 'column', 'row'].includes(channel)) {
                         encodingObj["type"] = "nominal";
@@ -495,6 +527,17 @@ export const assembleVegaChart = (
                 // if the column or row channel and no dtype is specified, use nominal
                 encodingObj["type"] = 'nominal';
             }
+
+            if (field && encodingObj["type"] == "quantitative") {
+                // TODO: special hack: if the field values are all valid temporal values, set the type to temporal
+                let sampleValues = workingTable.slice(0, 15).filter(r => r[field.name] != undefined).map(r => r[field.name]);
+                // ISO 8601 format: YYYY-MM-DDTHH:mm:ss.sss with optional timezone (Z or +/-HH:mm)
+                const isoDateRegex = /^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}(\.\d+)?(Z|[+-]\d{2}:\d{2})?$/;
+                if (sampleValues.length > 0 && sampleValues.every((val: any) => isoDateRegex.test(`${val}`.trim()))) {
+                    encodingObj["type"] = "temporal";
+                }
+            }
+            
             
             if (aggrPreprocessed) {
                 if (encoding.aggregate) {
@@ -689,11 +732,24 @@ export const assembleVegaChart = (
             values = values.map((r: any) => { 
                 for (let temporalKey of temporalKeys) {
                     const val = r[temporalKey];
-                    // Convert numeric timestamps to ISO date strings for Vega-Lite compatibility
+                    const fieldMeta = tableMetadata[temporalKey];
+                    const semanticType = fieldMeta?.semanticType;
+                    
+                    // Convert to ISO date strings for Vega-Lite compatibility
                     if (typeof val === 'number') {
-                        // Detect if timestamp is in seconds (10 digits) or milliseconds (13 digits)
-                        const timestamp = val < 1e12 ? val * 1000 : val;
-                        r[temporalKey] = new Date(timestamp).toISOString();
+                        // Handle Year/Decade semantic types - these are year numbers, not timestamps
+                        if (semanticType === 'Year' || semanticType === 'Decade') {
+                            // Year values like 2018 should become "2018-01-01"
+                            r[temporalKey] = `${Math.floor(val)}`;
+                        } else if (isLikelyTimestamp(val)) {
+                            // Detect if timestamp is in seconds (10 digits) or milliseconds (13 digits)
+                            const timestamp = val < 1e12 ? val * 1000 : val;
+                            r[temporalKey] = new Date(timestamp).toISOString();
+                        } else {
+                            // Small numbers that aren't Year/Decade and don't look like timestamps
+                            // If it looks like a year (1000-9999), format as a date for consistency
+                            r[temporalKey] = String(val);
+                        }
                     } else if (val instanceof Date) {
                         r[temporalKey] = val.toISOString();
                     } else {
diff --git a/src/components/ChartTemplates.tsx b/src/components/ChartTemplates.tsx
index c26575e..2c09b71 100644
--- a/src/components/ChartTemplates.tsx
+++ b/src/components/ChartTemplates.tsx
@@ -47,6 +47,69 @@ export const CHANNEL_LIST =  ["x", "y", "x2", "y2", "id", "color", "opacity", "s
                               "row", "latitude", "longitude", "theta", "radius", "detail", "group",
                               "field 1", "field 2", "field 3", "field 4", "field 5", 'field 6'] as const;
 
+/**
+ * Ensures one axis (x or y) is nominal based on the spec and data cardinality.
+ * If neither axis is nominal, converts the one with lower cardinality to nominal.
+ * Returns "x" or "y" indicating which channel is nominal, or null if undetermined.
+ */
+const ensureNominalAxis = (vgSpec: any, table: any[], defaultToX: boolean = true): "x" | "y" | null => {
+    if (vgSpec.encoding.x?.type === "nominal") {
+        return "x";
+    } else if (vgSpec.encoding.y?.type === "nominal") {
+        return "y";
+    } else if (vgSpec.encoding.x && vgSpec.encoding.y) {
+        // Neither are nominal, determine based on cardinality
+        if (table && table.length > 0) {
+            const xField = vgSpec.encoding.x?.field;
+            const yField = vgSpec.encoding.y?.field;
+            
+            let xCardinality = Infinity;
+            let yCardinality = Infinity;
+            
+            if (xField) {
+                const xValues = [...new Set(table.map(r => r[xField]))];
+                xCardinality = xValues.length;
+            }
+            
+            if (yField) {
+                const yValues = [...new Set(table.map(r => r[yField]))];
+                yCardinality = yValues.length;
+            }
+            
+            // The axis with lower cardinality should be nominal (categories)
+            if (xCardinality <= yCardinality) {
+                vgSpec.encoding.x.type = "nominal";
+                return "x";
+            } else {
+                vgSpec.encoding.y.type = "nominal";
+                return "y";
+            }
+        } else {
+            // Default based on parameter
+            if (defaultToX) {
+                vgSpec.encoding.x.type = "nominal";
+                return "x";
+            } else {
+                vgSpec.encoding.y.type = "nominal";
+                return "y";
+            }
+        }
+    } else if (vgSpec.encoding.x) {
+        // Only x is defined
+        if (vgSpec.encoding.x.type !== "nominal") {
+            vgSpec.encoding.x.type = "nominal";
+        }
+        return "x";
+    } else if (vgSpec.encoding.y) {
+        // Only y is defined
+        if (vgSpec.encoding.y.type !== "nominal") {
+            vgSpec.encoding.y.type = "nominal";
+        }
+        return "y";
+    }
+    return null;
+};
+
 export const ChannelGroups = {
         "": ["x", "y", "x2", "y2", "latitude", "longitude", "id", "radius", "theta", "detail"],
         "legends": ["color", "group", "size", "shape", "text", "opacity" ],
@@ -175,9 +238,16 @@ const scatterPlots: ChartTemplate[] = [
         "channels": ["x", "y", "color", "opacity", "column", "row"],
         "paths": Object.fromEntries(["x", "y", "color", "opacity", "column", "row"].map(channel => [channel, ["encoding", channel]])),
         "postProcessor": (vgSpec: any,  table: any[]) => {
-            if (vgSpec.encoding.x && vgSpec.encoding.x.type != "nominal") {
-                vgSpec.encoding.x.type = "nominal";
-            } 
+            const hasX = vgSpec.encoding.x?.field;
+            const hasY = vgSpec.encoding.y?.field;
+            
+            // If only one axis is defined, show a helpful message
+            if (hasX && hasY) {
+                // Both axes defined - determine which should be nominal
+                // Vertical boxplot: x is nominal, y is quantitative
+                // Horizontal boxplot: y is nominal, x is quantitative
+                ensureNominalAxis(vgSpec, table, true);
+            }
             return vgSpec;
         }
     }
@@ -275,50 +345,8 @@ const barCharts: ChartTemplate[] = [
         "postProcessor": (vgSpec: any, table: any[]) => {
             if (!vgSpec.encoding.color?.field) return vgSpec;
             
-            let nominalChannel: "x" | "y" | null = null;
-            let offsetChannel: "xOffset" | "yOffset" | null = null;
-            
-            if (vgSpec.encoding.x?.type === "nominal") {
-                nominalChannel = "x";
-                offsetChannel = "xOffset";
-            } else if (vgSpec.encoding.y?.type === "nominal") {
-                nominalChannel = "y";
-                offsetChannel = "yOffset";
-            } else if (vgSpec.encoding.x && vgSpec.encoding.y) {
-                // Neither are nominal, convert the one with lower cardinality to nominal
-                if (table && table.length > 0) {
-                    const xField = vgSpec.encoding.x?.field;
-                    const yField = vgSpec.encoding.y?.field;
-                    
-                    let xCardinality = Infinity;
-                    let yCardinality = Infinity;
-                    
-                    if (xField) {
-                        const xValues = [...new Set(table.map(r => r[xField]))];
-                        xCardinality = xValues.length;
-                    }
-                    
-                    if (yField) {
-                        const yValues = [...new Set(table.map(r => r[yField]))];
-                        yCardinality = yValues.length;
-                    }
-                    
-                    if (xCardinality <= yCardinality) {
-                        nominalChannel = "x";
-                        offsetChannel = "xOffset";
-                        vgSpec.encoding.x.type = "nominal";
-                    } else {
-                        nominalChannel = "y";
-                        offsetChannel = "yOffset";
-                        vgSpec.encoding.y.type = "nominal";
-                    }
-                } else {
-                    // Default: convert x to nominal and use xOffset if no table data
-                    nominalChannel = "x";
-                    offsetChannel = "xOffset";
-                    vgSpec.encoding.x.type = "nominal";
-                }
-            }
+            const nominalChannel = ensureNominalAxis(vgSpec, table, true);
+            const offsetChannel = nominalChannel === "x" ? "xOffset" : nominalChannel === "y" ? "yOffset" : null;
             
             if (nominalChannel && offsetChannel) {
                 if (!vgSpec.encoding[offsetChannel]) {
diff --git a/src/views/DBTableManager.tsx b/src/views/DBTableManager.tsx
index 64662a9..542d1f8 100644
--- a/src/views/DBTableManager.tsx
+++ b/src/views/DBTableManager.tsx
@@ -30,7 +30,6 @@ import {
   styled,
   useTheme,
   Link,
-  Checkbox,
   Popover,
   Switch,
   Slider,
@@ -45,6 +44,13 @@ import TableRowsIcon from '@mui/icons-material/TableRows';
 import RefreshIcon from '@mui/icons-material/Refresh';
 import SearchIcon from '@mui/icons-material/Search';
 import StreamIcon from '@mui/icons-material/Stream';
+import Autocomplete from '@mui/material/Autocomplete';
+
+// Type for table import configuration
+type TableImportConfig = 
+    | { mode: 'none' }
+    | { mode: 'full' }
+    | { mode: 'subset'; rowLimit: number; sortColumns: string[]; sortOrder: 'asc' | 'desc' };
 
 import { getUrls, fetchWithSession } from '../app/utils';
 import { CustomReactTable } from './ReactTable';
@@ -1151,7 +1157,23 @@ export const DataLoaderForm: React.FC<{
     const [tableMetadata, setTableMetadata] = useState<Record<string, any>>({});
     let [displaySamples, setDisplaySamples] = useState<Record<string, boolean>>({});
     let [tableFilter, setTableFilter] = useState<string>("");
-    const [selectedTables, setSelectedTables] = useState<Set<string>>(new Set());
+    const [tableImportConfigs, setTableImportConfigs] = useState<Record<string, TableImportConfig>>({});
+    const [subsetConfigAnchor, setSubsetConfigAnchor] = useState<{element: HTMLElement, tableName: string} | null>(null);
+    
+    // Helper to get import config for a table (defaults to 'none')
+    const getTableConfig = (tableName: string): TableImportConfig => {
+        return tableImportConfigs[tableName] ?? { mode: 'none' };
+    };
+    
+    // Helper to update config for a specific table
+    const updateTableConfig = (tableName: string, config: TableImportConfig) => {
+        setTableImportConfigs(prev => ({ ...prev, [tableName]: config }));
+    };
+    
+    // Get selected tables (those with mode !== 'none')
+    const selectedTables = Object.entries(tableImportConfigs)
+        .filter(([_, config]) => config.mode !== 'none')
+        .map(([tableName, _]) => tableName);
 
     let [isConnecting, setIsConnecting] = useState(false);
 
@@ -1162,92 +1184,336 @@ export const DataLoaderForm: React.FC<{
     let tableMetadataBox = [
         <TableContainer component={Box} sx={{borderTop: '1px solid rgba(0, 0, 0, 0.1)', maxHeight: 340, overflowY: "auto"}} >
             <Table sx={{ minWidth: 650 }} size="small" aria-label="simple table">
-            <TableBody>
-                {Object.entries(tableMetadata).map(([tableName, metadata]) => {
-                    return [
-                    <TableRow
-                        key={tableName}
-                        sx={{ 
-                            '&:last-child td, &:last-child th': { border: 0 }, 
-                            '& .MuiTableCell-root': { 
-                                borderBottom: displaySamples[tableName] ? 'none' : '1px solid rgba(0, 0, 0, 0.1)',
-                                padding: 0.25, wordWrap: 'break-word', whiteSpace: 'normal'},
-                            backgroundColor: selectedTables.has(tableName) ? 'action.selected' : 'inherit',
-                            '&:hover': { backgroundColor: selectedTables.has(tableName) ? 'action.selected' : 'action.hover' },
-                            cursor: 'pointer',
-                        }}
-                        onClick={() => {
-                            const newSelected = new Set(selectedTables);
-                            if (newSelected.has(tableName)) {
-                                newSelected.delete(tableName);
-                            } else {
-                                newSelected.add(tableName);
-                            }
-                            setSelectedTables(newSelected);
-                        }}
-                    >
-                        <TableCell>
-                            <IconButton size="small" onClick={(e) => {
-                                e.stopPropagation();
-                                toggleDisplaySamples(tableName);
-                            }}>
-                                {displaySamples[tableName] ? <ExpandLessIcon /> : <ExpandMoreIcon />}
-                            </IconButton>
-                        </TableCell>
-                        <TableCell sx={{maxWidth: 240}} component="th" scope="row">
-                            {tableName} <Typography variant="caption" sx={{color: "text.secondary"}} fontSize={10}>
-                                ({metadata.row_count > 0 ? `${metadata.row_count} rows × ` : ""}{metadata.columns.length} cols)
-                            </Typography>
-                        </TableCell>
-                        <TableCell sx={{maxWidth: 500}}>
-                            {metadata.columns.map((column: any) => (
-                                <Chip key={column.name} label={column.name} sx={{fontSize: 11, margin: 0.25, height: 20}} size="small" />
-                            ))}
-                        </TableCell>
-                        <TableCell sx={{width: 40}}>
-                            <Checkbox
-                                size="small"
-                                checked={selectedTables.has(tableName)}
-                            />
-                        </TableCell>
-                    </TableRow>,
-                    <TableRow key={`${tableName}-sample`}>
-                        <TableCell colSpan={4} sx={{ paddingBottom: 0, paddingTop: 0, px: 0, maxWidth: 800, overflowX: "auto", 
-                                         borderBottom: displaySamples[tableName] ? '1px solid rgba(0, 0, 0, 0.1)' : 'none' }}>
-                        <Collapse in={displaySamples[tableName]} timeout="auto" unmountOnExit>
-                            <Card variant="outlined" sx={{ ml: 5, my: 1}}>
-                                <CustomReactTable rows={metadata.sample_rows.slice(0, 9).map((row: any) => {
-                                    return Object.fromEntries(Object.entries(row).map(([key, value]: [string, any]) => {
-                                        return [key, String(value)];
-                                    }));
-                                })} 
-                                columnDefs={metadata.columns.map((column: any) => ({id: column.name, label: column.name}))} 
-                                rowsPerPageNum={-1} 
-                                compact={false} 
-                                isIncompleteTable={metadata.row_count > 10}
-                                />
-                            </Card>
-                        </Collapse>
-                        </TableCell>
-                    </TableRow>]
-                })}
-                </TableBody>
+                <TableHead>
+                    <TableRow sx={{ '& .MuiTableCell-root': { fontSize: 12 } }}>
+                        <TableCell> </TableCell>
+                        <TableCell>Table Name</TableCell>
+                        <TableCell>Columns</TableCell>
+                        <TableCell align="right">Import Options</TableCell>
+                    </TableRow>
+                </TableHead>
+                <TableBody>
+                    {Object.entries(tableMetadata).map(([tableName, metadata]) => {
+                        return [
+                        <TableRow
+                            key={tableName}
+                            sx={{ 
+                                '&:last-child td, &:last-child th': { border: 0 }, 
+                                '& .MuiTableCell-root': { 
+                                    borderBottom: displaySamples[tableName] ? 'none' : '1px solid rgba(0, 0, 0, 0.1)',
+                                    padding: 0.25, wordWrap: 'break-word', whiteSpace: 'normal'},
+                                backgroundColor: getTableConfig(tableName).mode !== 'none' ? 'action.selected' : 'inherit',
+                                '&:hover': { backgroundColor: getTableConfig(tableName).mode !== 'none' ? 'action.selected' : 'action.hover' },
+                            }}
+                        >
+                            <TableCell>
+                                <IconButton size="small" onClick={(e) => {
+                                    e.stopPropagation();
+                                    toggleDisplaySamples(tableName);
+                                }}>
+                                    {displaySamples[tableName] ? <ExpandLessIcon /> : <ExpandMoreIcon />}
+                                </IconButton>
+                            </TableCell>
+                            <TableCell sx={{maxWidth: 240}} component="th" scope="row">
+                                {tableName} <Typography variant="caption" sx={{color: "text.secondary"}} fontSize={10}>
+                                    ({metadata.row_count > 0 ? `${metadata.row_count} rows × ` : ""}{metadata.columns.length} cols)
+                                </Typography>
+                            </TableCell>
+                            <TableCell sx={{maxWidth: 400}}>
+                                {metadata.columns.map((column: any) => (
+                                    <Chip key={column.name} label={column.name} sx={{fontSize: 11, margin: 0.25, height: 20}} size="small" />
+                                ))}
+                            </TableCell>
+                            <TableCell sx={{width: 220}} align="right">
+                                <Box sx={{ display: 'flex', alignItems: 'flex-end', flexDirection: 'column', mx: 1 }}>
+                                    <Box sx={{ display: 'flex', alignItems: 'center', my: 1, gap: 0.5, flexDirection: 'row', justifyContent: 'flex-end' }}>
+                                        <ToggleButtonGroup
+                                            size="small"
+                                            value={getTableConfig(tableName).mode}
+                                            exclusive
+                                            onChange={(e, newMode) => {
+                                                if (newMode === null) return; // Prevent deselecting all
+                                                if (newMode === 'none') {
+                                                    updateTableConfig(tableName, { mode: 'none' });
+                                                } else if (newMode === 'full') {
+                                                    updateTableConfig(tableName, { mode: 'full' });
+                                                } else if (newMode === 'subset') {
+                                                    // Initialize with default values
+                                                    updateTableConfig(tableName, { 
+                                                        mode: 'subset', 
+                                                        rowLimit: Math.min(1000, metadata.row_count || 1000),
+                                                        sortColumns: [],
+                                                        sortOrder: 'asc'
+                                                    });
+                                                }
+                                            }}
+                                        >
+                                            <ToggleButton value="none" sx={{ 
+                                                px: 1, py: 0, fontSize: 11, textTransform: 'none',
+                                                '&.Mui-selected': { backgroundColor: 'grey.400', color: 'white' },
+                                                '&.Mui-selected:hover': { backgroundColor: 'grey.500' }
+                                            }}>
+                                                <Tooltip title="Don't import this table">
+                                                    <span>Skip</span>
+                                                </Tooltip>
+                                            </ToggleButton>
+                                            <ToggleButton value="full" sx={{ 
+                                                px: 1, py: 0, fontSize: 11, textTransform: 'none',
+                                                '&.Mui-selected': { backgroundColor: 'secondary.main', color: 'white' },
+                                                '&.Mui-selected:hover': { backgroundColor: 'secondary.dark' }
+                                            }}>
+                                                <Tooltip title="Import entire table">
+                                                    <span>Full</span>
+                                                </Tooltip>
+                                            </ToggleButton>
+                                            <ToggleButton value="subset" onClick={(e) => {
+                                                e.stopPropagation();
+                                                setSubsetConfigAnchor({ element: e.currentTarget, tableName });
+                                            }} sx={{ 
+                                                px: 1, py: 0, fontSize: 11, textTransform: 'none',
+                                                '&.Mui-selected': { backgroundColor: '#f9a825', color: 'white' },
+                                                '&.Mui-selected:hover': { backgroundColor: '#f57f17' }
+                                            }}>
+                                                <Tooltip title="Import first K rows (with optional sorting)">
+                                                    <span>Subset</span>
+                                                </Tooltip>
+                                            </ToggleButton>
+                                        </ToggleButtonGroup>
+                                    </Box>
+                                    {getTableConfig(tableName).mode === 'subset' && (
+                                        <Box sx={{ display: 'flex', alignItems: 'center', gap: 0.5, flexDirection: 'row', justifyContent: 'flex-end' }}>
+                                            <Button
+                                                size="small"
+                                                startIcon={<SettingsIcon sx={{ fontSize: 12 }} />}
+                                                onClick={(e) => {
+                                                    e.stopPropagation();
+                                                    setSubsetConfigAnchor({ element: e.currentTarget, tableName });
+                                                }}
+                                                sx={{ 
+                                                    fontSize: 11,
+                                                    textTransform: 'none',
+                                                    minWidth: 'auto',
+                                                    padding: '2px 4px',
+                                                }}
+                                            >
+                                                {(() => {
+                                                    const config = getTableConfig(tableName);
+                                                    if (config.mode === 'subset') {
+                                                        const sortInfo = config.sortColumns.length > 0 
+                                                            ? `, ${config.sortOrder === 'asc' ? '↑' : '↓'} by ${config.sortColumns.join(', ')} ` 
+                                                            : '';
+                                                        return `first ${config.rowLimit} rows${sortInfo}`;
+                                                    }
+                                                    return '';
+                                                })()}
+                                            </Button>
+                                        </Box>
+                                    )}
+                                </Box>
+                            </TableCell>
+                        </TableRow>,
+                        <TableRow key={`${tableName}-sample`}>
+                            <TableCell colSpan={4} sx={{ paddingBottom: 0, paddingTop: 0, px: 0, maxWidth: 800, overflowX: "auto", 
+                                            borderBottom: displaySamples[tableName] ? '1px solid rgba(0, 0, 0, 0.1)' : 'none' }}>
+                            <Collapse in={displaySamples[tableName]} timeout="auto" unmountOnExit>
+                                <Card variant="outlined" sx={{ ml: 5, my: 1}}>
+                                    <CustomReactTable rows={metadata.sample_rows.slice(0, 5).map((row: any) => {
+                                        return Object.fromEntries(Object.entries(row).map(([key, value]: [string, any]) => {
+                                            return [key, String(value)];
+                                        }));
+                                    })} 
+                                    columnDefs={metadata.columns.map((column: any) => ({id: column.name, label: column.name}))} 
+                                    rowsPerPageNum={-1} 
+                                    compact={false} 
+                                    isIncompleteTable={metadata.row_count > 10}
+                                    />
+                                </Card>
+                            </Collapse>
+                            </TableCell>
+                        </TableRow>]
+                    })}
+                    </TableBody>
                 </Table>
             </TableContainer>,
-        Object.keys(tableMetadata).length > 0 && <Box sx={{ display: 'flex', justifyContent: 'center', mt: 1 }}>
+        // Subset configuration popover
+        <Popover
+            key="subset-config-popover"
+            open={subsetConfigAnchor !== null}
+            anchorEl={subsetConfigAnchor?.element}
+            onClose={() => setSubsetConfigAnchor(null)}
+            anchorOrigin={{
+                vertical: 'bottom',
+                horizontal: 'left',
+            }}
+            transformOrigin={{
+                vertical: 'top',
+                horizontal: 'left',
+            }}
+        >
+            {subsetConfigAnchor && (() => {
+                const tableName = subsetConfigAnchor.tableName;
+                const config = getTableConfig(tableName);
+                const metadata = tableMetadata[tableName];
+                if (config.mode !== 'subset' || !metadata) return null;
+                
+                return (
+                    <Box sx={{ fontSize: 12, p: 1.5, minWidth: 280, maxWidth: 360 }}>
+                        <Typography variant="body2" sx={{ mb: 1.5, fontSize: 14, fontWeight: 600 }}>
+                            Create a subset of "{tableName}"
+                        </Typography>
+                        <Typography variant="caption" sx={{  display: 'block', mb: 0.75, fontSize: 12, fontWeight: 500 }}>
+                            Row Limit (max: {metadata.row_count || 'unknown'} rows)
+                        </Typography>
+                        <Box sx={{ my: 2, ml: 2 }}>
+                            <TextField
+                                size="small"
+                                type="number"
+                                value={config.rowLimit}
+                                onChange={(e) => {
+                                    const value = parseInt(e.target.value) || 1;
+                                    const maxRows = metadata.row_count || 100000;
+                                    updateTableConfig(tableName, {
+                                        ...config,
+                                        rowLimit: Math.min(Math.max(1, value), maxRows)
+                                    });
+                                }}
+                                slotProps={{ 
+                                    input: {
+                                        inputProps: { 
+                                            min: 1, 
+                                            max: metadata.row_count || 100000,
+                                            step: 100
+                                        }
+                                    }
+                                }}
+                                fullWidth
+                                sx={{ mb: 1, '& .MuiInputBase-root': { fontSize: 12 } }}
+                            />
+                            <Slider
+                                size="small"
+                                value={config.rowLimit}
+                                onChange={(_, value) => {
+                                    updateTableConfig(tableName, {
+                                        ...config,
+                                        rowLimit: value as number
+                                    });
+                                }}
+                                min={1}
+                                max={metadata.row_count || 10000}
+                                step={Math.max(1, Math.floor((metadata.row_count || 10000) / 100))}
+                                valueLabelDisplay="auto"
+                            />
+                        </Box>
+                        
+                        <Typography variant="caption" sx={{  display: 'block', my: 1, fontSize: 12, fontWeight: 500 }}>
+                            Sort By <span style={{ fontWeight: 400, color: 'rgba(0, 0, 0, 0.6)' }}>(optional)</span>
+                        </Typography>
+                        <Box sx={{ my: 2, ml: 2 }}>
+                            <Autocomplete
+                                multiple
+                                size="small"
+                                options={metadata.columns.map((col: any) => col.name)}
+                                value={config.sortColumns}
+                                onChange={(_, newValue) => {
+                                    updateTableConfig(tableName, {
+                                        ...config,
+                                        sortColumns: newValue
+                                    });
+                                }}
+                                renderInput={(params) => (
+                                    <TextField 
+                                        {...params} 
+                                        placeholder="Select columns..."
+                                        size="small"
+                                        sx={{ '& .MuiInputBase-root': { fontSize: 12 } }}
+                                    />
+                                )}
+                                renderTags={(value, getTagProps) =>
+                                    value.map((option, index) => (
+                                        <Chip
+                                            {...getTagProps({ index })}
+                                            key={option}
+                                            label={option}
+                                            size="small"
+                                            sx={{ height: 20, fontSize: 11 }}
+                                        />
+                                    ))
+                                }
+                            />
+                            {config.sortColumns.length > 0 && (
+                                <Box sx={{ mt: 1, display: 'flex', alignItems: 'center', gap: 1 }}>
+                                    <ToggleButtonGroup
+                                        value={config.sortOrder}
+                                        exclusive
+                                        onChange={(_, newValue) => {
+                                            if (newValue) {
+                                                updateTableConfig(tableName, {
+                                                    ...config,
+                                                    sortOrder: newValue
+                                                });
+                                            }
+                                        }}
+                                        size="small"
+                                        sx={{ height: 24 }}
+                                    >
+                                        <ToggleButton value="asc" sx={{ 
+                                            px: 1.5, py: 0, fontSize: 11, textTransform: 'none',
+                                            '&.Mui-selected': { backgroundColor: 'primary.main', color: 'white' },
+                                            '&.Mui-selected:hover': { backgroundColor: 'primary.dark' }
+                                        }}>
+                                            ↑ Asc
+                                        </ToggleButton>
+                                        <ToggleButton value="desc" sx={{ 
+                                            px: 1.5, py: 0, fontSize: 11, textTransform: 'none',
+                                            '&.Mui-selected': { backgroundColor: 'primary.main', color: 'white' },
+                                            '&.Mui-selected:hover': { backgroundColor: 'primary.dark' }
+                                        }}>
+                                            ↓ Desc
+                                        </ToggleButton>
+                                    </ToggleButtonGroup>
+                                </Box>
+                            )}
+                        </Box>
+                        
+                        <Box sx={{ display: 'flex', justifyContent: 'flex-end', mt: 2 }}>
+                            <Button 
+                                size="small" 
+                                variant="contained" 
+                                onClick={() => setSubsetConfigAnchor(null)}
+                                sx={{ textTransform: 'none', fontSize: 11, height: 28 }}
+                            >
+                                Done
+                            </Button>
+                        </Box>
+                    </Box>
+                );
+            })()}
+        </Popover>,
+        Object.keys(tableMetadata).length > 0 && <Box sx={{ display: 'flex', justifyContent: 'center', mt: 2}}>
             <Button 
-                variant="outlined" 
+                variant="contained" 
                 color="secondary"
-                size="small"
-                disabled={selectedTables.size === 0}
+                disabled={selectedTables.length === 0}
                 sx={{ textTransform: 'none' }}
                 onClick={() => {
-                    const tablesToImport = Array.from(selectedTables);
+                    const tablesToImport = selectedTables;
                     onImport();
                     
                     // Import all selected tables sequentially
-                    const importPromises = tablesToImport.map(tableName => 
-                        fetchWithSession(getUrls().DATA_LOADER_INGEST_DATA, {
+                    const importPromises = tablesToImport.map(tableName => {
+                        const config = getTableConfig(tableName);
+                        
+                        // Build import options based on config
+                        const importOptions: any = {};
+                        if (config.mode === 'subset') {
+                            importOptions.row_limit = config.rowLimit;
+                            if (config.sortColumns.length > 0) {
+                                importOptions.sort_columns = config.sortColumns;
+                                importOptions.sort_order = config.sortOrder;
+                            }
+                        }
+                        
+                        return fetchWithSession(getUrls().DATA_LOADER_INGEST_DATA, {
                             method: 'POST',
                             headers: {
                                 'Content-Type': 'application/json',
@@ -1255,16 +1521,17 @@ export const DataLoaderForm: React.FC<{
                             body: JSON.stringify({
                                 data_loader_type: dataLoaderType, 
                                 data_loader_params: params, 
-                                table_name: tableName
+                                table_name: tableName,
+                                import_options: Object.keys(importOptions).length > 0 ? importOptions : undefined
                             })
-                        }, dispatch).then((response: Response) => response.json())
-                    );
+                        }, dispatch).then((response: Response) => response.json());
+                    });
                     
                     Promise.all(importPromises)
                         .then(results => {
                             const errors = results.filter(r => r.status !== "success");
                             if (errors.length === 0) {
-                                setSelectedTables(new Set());
+                                setTableImportConfigs({});
                                 // Get the actual table names that were created (may be sanitized)
                                 const actualTableNames = results
                                     .filter(r => r.status === "success" && r.table_name)
@@ -1284,7 +1551,7 @@ export const DataLoaderForm: React.FC<{
                         });
                 }}
             >
-                Import Selected Tables ({selectedTables.size})
+                Import Selected Tables to Local DuckDB ({selectedTables.length})
             </Button>
         </Box>
     ]
diff --git a/src/views/EncodingShelfCard.tsx b/src/views/EncodingShelfCard.tsx
index 449b631..cba27b6 100644
--- a/src/views/EncodingShelfCard.tsx
+++ b/src/views/EncodingShelfCard.tsx
@@ -330,10 +330,6 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
         }));
     };
     
-    // Add state for developer message dialog
-    const [devMessageOpen, setDevMessageOpen] = useState<boolean>(false);
-
-
     let encodingBoxGroups = Object.entries(ChannelGroups)
         .filter(([group, channelList]) => channelList.some(ch => Object.keys(encodingMap).includes(ch)))
         .map(([group, channelList]) => {
@@ -395,24 +391,20 @@ export const EncodingShelfCard: FC<EncodingShelfCardProps> = function ({ chartId
                     }));
             }
 
-            // Get the root table (first table in actionTableIds)
-            const rootTable = tables.find(t => t.id === actionTableIds[0]);
-            if (!rootTable) {
-                throw new Error('No root table found');
-            }
-
             let chartAvailable = checkChartAvailability(chart, conceptShelfItems, currentTable.rows);
             let currentChartPng = chartAvailable ? await vegaLiteSpecToPng(assembleVegaChart(chart.chartType, chart.encodingMap, activeFields, currentTable.rows, currentTable.metadata, 20)) : undefined;
 
+            let actionTables = actionTableIds.map(id => tables.find(t => t.id == id) as DictTable);
+
             const token = String(Date.now());
             const messageBody = JSON.stringify({
                 token: token,
                 model: activeModel,
-                input_tables: [{
-                    name: rootTable.virtual?.tableId || rootTable.id.replace(/\.[^/.]+$/, ""),
-                    rows: rootTable.rows,
-                    attached_metadata: rootTable.attachedMetadata
-                }],
+                input_tables: actionTables.map(t => ({
+                    name: t.virtual?.tableId || t.id.replace(/\.[^/.]+$/, ""),
+                    rows: t.rows,
+                    attached_metadata: t.attachedMetadata
+                })),
                 language: currentTable.virtual ? "sql" : "python",
                 exploration_thread: explorationThread,
                 current_data_sample: currentTable.rows.slice(0, 10),
diff --git a/src/views/ReportView.tsx b/src/views/ReportView.tsx
index a7ac149..bd07078 100644
--- a/src/views/ReportView.tsx
+++ b/src/views/ReportView.tsx
@@ -51,6 +51,7 @@ import { Collapse } from '@mui/material';
 import ExpandMoreIcon from '@mui/icons-material/ExpandMore';
 import ExpandLessIcon from '@mui/icons-material/ExpandLess';
 import { convertToChartifact, openChartifactViewer } from './ChartifactDialog';
+import StreamIcon from '@mui/icons-material/Stream';
 
 // Typography constants
 const FONT_FAMILY_SYSTEM = '-apple-system, BlinkMacSystemFont, "Segoe UI", Helvetica, "Apple Color Emoji", Arial, sans-serif, "Segoe UI Emoji", "Segoe UI Symbol"';
@@ -231,13 +232,13 @@ export const ReportView: FC = () => {
     const [isLoadingPreviews, setIsLoadingPreviews] = useState(false);
     const [isGenerating, setIsGenerating] = useState(false);
     const [error, setError] = useState<string>('');
-    const [style, setStyle] = useState<string>('short note');
+    const [style, setStyle] = useState<string>('social post');
     const [mode, setMode] = useState<'compose' | 'post'>(allGeneratedReports.length > 0 ? 'post' : 'compose');
 
     // Local state for current report
     const [currentReportId, setCurrentReportId] = useState<string | undefined>(undefined);
     const [generatedReport, setGeneratedReport] = useState<string>('');
-    const [generatedStyle, setGeneratedStyle] = useState<string>('short note');
+    const [generatedStyle, setGeneratedStyle] = useState<string>('social post');
     const [cachedReportImages, setCachedReportImages] = useState<Record<string, { url: string; width: number; height: number }>>({});
     const [shareButtonSuccess, setShareButtonSuccess] = useState(false);
     const [hideTableOfContents, setHideTableOfContents] = useState(false);
@@ -798,7 +799,7 @@ export const ReportView: FC = () => {
                 // No reports left, clear the view and go back to compose mode
                 setCurrentReportId(undefined);
                 setGeneratedReport('');
-                setGeneratedStyle('short note');
+                setGeneratedStyle('social post');
                 setMode('compose');
             }
         }
@@ -896,7 +897,7 @@ export const ReportView: FC = () => {
                                 }}
                             >
                                 {[
-                                    { value: 'short note', label: 'short note' },
+                                    { value: 'live report', label: 'live report' },
                                     { value: 'blog post', label: 'blog post' },
                                     { value: 'social post', label: 'social post' },
                                     { value: 'executive summary', label: 'executive summary' },
@@ -912,7 +913,7 @@ export const ReportView: FC = () => {
                                             minWidth: 'auto'
                                         }}
                                     >
-                                        {option.label}
+                                        {option.value === 'live report' ? <StreamIcon sx={{ fontSize: 16, mr: 1 }} /> : <></>} {option.label}
                                     </ToggleButton>
                                 ))}
                             </ToggleButtonGroup>

From 10398c1189db896bfa4a4a8900b8a3b521745022 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Mon, 26 Jan 2026 13:37:43 -0800
Subject: [PATCH 17/21] small

---
 src/views/DBTableManager.tsx | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/src/views/DBTableManager.tsx b/src/views/DBTableManager.tsx
index 542d1f8..b0da233 100644
--- a/src/views/DBTableManager.tsx
+++ b/src/views/DBTableManager.tsx
@@ -1753,10 +1753,11 @@ export const DataLoaderForm: React.FC<{
                                 onChange={(event) => setTableFilter(event.target.value)}
                             />
                         </Box>
-                        {paramDefs.length > 0 && <ButtonGroup sx={{height: 32, mt: 'auto'}} size="small" 
-                         variant="contained" color="primary">
+                        {paramDefs.length > 0 && 
                             <Button 
-                                sx={{textTransform: "none"}}
+                                variant="contained"
+                                color="primary"
+                                sx={{textTransform: "none", minWidth: 120}}
                                 onClick={() => {
                                     setIsConnecting(true);
                                     fetchWithSession(getUrls().DATA_LOADER_LIST_TABLES, {
@@ -1787,9 +1788,8 @@ export const DataLoaderForm: React.FC<{
                                     setIsConnecting(false);
                                 });
                             }}>
-                                connect {tableFilter.trim() ? "with filter" : ""}
-                            </Button>
-                        </ButtonGroup>}
+                                Connect {tableFilter.trim() ? "with filter" : ""}
+                            </Button>}
                     </Box>
                     <Box  sx={{display: "flex", flexDirection: "row", alignItems: "center", gap: 1, ml: 4, mt: 4}}>
                         

From 79555d9755643378412c5d17399d707c1ed6cd67 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Mon, 26 Jan 2026 14:55:48 -0800
Subject: [PATCH 18/21] some quick fixes

---
 src/views/RefreshDataDialog.tsx       | 11 ++-----
 src/views/ReportView.tsx              |  9 ++---
 src/views/UnifiedDataUploadDialog.tsx | 47 +++++++++++++++------------
 3 files changed, 33 insertions(+), 34 deletions(-)

diff --git a/src/views/RefreshDataDialog.tsx b/src/views/RefreshDataDialog.tsx
index a650cc8..3a51f63 100644
--- a/src/views/RefreshDataDialog.tsx
+++ b/src/views/RefreshDataDialog.tsx
@@ -16,20 +16,16 @@ import {
     Tab,
     LinearProgress,
     Input,
-    Alert,
-    Tooltip,
     Link,
     alpha,
     useTheme,
 } from '@mui/material';
 import CloseIcon from '@mui/icons-material/Close';
 import UploadFileIcon from '@mui/icons-material/UploadFile';
-import { useDispatch, useSelector } from 'react-redux';
-import { AppDispatch } from '../app/store';
-import { DataFormulatorState, dfActions, dfSelectors, fetchFieldSemanticType } from '../app/dfSlice';
+import { useSelector } from 'react-redux';
+import { DataFormulatorState } from '../app/dfSlice';
 import { DictTable } from '../components/ComponentType';
-import { createTableFromFromObjectArray, createTableFromText, loadTextDataWrapper, loadBinaryDataWrapper } from '../data/utils';
-import { getUrls } from '../app/utils';
+import { createTableFromText, loadTextDataWrapper, loadBinaryDataWrapper } from '../data/utils';
 
 interface TabPanelProps {
     children?: React.ReactNode;
@@ -66,7 +62,6 @@ export const RefreshDataDialog: React.FC<RefreshDataDialogProps> = ({
     onRefreshComplete,
 }) => {
     const theme = useTheme();
-    const dispatch = useDispatch<AppDispatch>();
     const [tabValue, setTabValue] = useState(0);
     const [pasteContent, setPasteContent] = useState('');
     const [urlContent, setUrlContent] = useState('');
diff --git a/src/views/ReportView.tsx b/src/views/ReportView.tsx
index bd07078..e1ef738 100644
--- a/src/views/ReportView.tsx
+++ b/src/views/ReportView.tsx
@@ -395,11 +395,9 @@ export const ReportView: FC = () => {
         affectedTableIds.forEach(tableId => {
             const table = tables.find(t => t.id === tableId);
             if (table) {
-                // Create a signature for the table data
-                const rowCount = table.rows.length;
-                const firstRows = JSON.stringify(table.rows.slice(0, 3));
-                const lastRows = JSON.stringify(table.rows.slice(-2));
-                const signature = `${rowCount}:${firstRows}:${lastRows}`;
+                // Use contentHash if available (set by state management), otherwise fallback to lightweight rowCount
+                // This avoids expensive JSON.stringify operations on every table change during streaming updates
+                const signature = table.contentHash || `${table.rows.length}`;
                 
                 const prevSignature = tableRowSignaturesRef.current.get(tableId);
                 if (prevSignature && prevSignature !== signature) {
@@ -411,7 +409,6 @@ export const ReportView: FC = () => {
         
         // If data changed, regenerate chart images for the report
         if (hasChanges) {
-            console.log('[ReportView] Table data changed, refreshing chart images...');
             
             reportChartIds.forEach(chartId => {
                 const chart = charts.find(c => c.id === chartId);
diff --git a/src/views/UnifiedDataUploadDialog.tsx b/src/views/UnifiedDataUploadDialog.tsx
index 96ab382..ecb8093 100644
--- a/src/views/UnifiedDataUploadDialog.tsx
+++ b/src/views/UnifiedDataUploadDialog.tsx
@@ -473,7 +473,6 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
 
     // Paste tab state
     const [pasteContent, setPasteContent] = useState<string>("");
-    const [displayContent, setDisplayContent] = useState<string>("");
     const [isLargeContent, setIsLargeContent] = useState<boolean>(false);
     const [showFullContent, setShowFullContent] = useState<boolean>(false);
     const [isOverSizeLimit, setIsOverSizeLimit] = useState<boolean>(false);
@@ -595,7 +594,6 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
     const handleClose = useCallback(() => {
         // Reset state when closing
         setPasteContent("");
-        setDisplayContent("");
         setIsLargeContent(false);
         setIsOverSizeLimit(false);
         setShowFullContent(false);
@@ -753,27 +751,15 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
         const isLarge = newContent.length > LARGE_CONTENT_THRESHOLD;
         setIsLargeContent(isLarge);
         
-        if (isLarge && !showFullContent) {
-            const lines = newContent.split('\n');
-            const previewLines = lines.slice(0, MAX_DISPLAY_LINES);
-            const preview = previewLines.join('\n') + (lines.length > MAX_DISPLAY_LINES ? '\n... (truncated for performance)' : '');
-            setDisplayContent(preview);
-        } else {
-            setDisplayContent(newContent);
+        // If switching from large to small content, ensure full content is shown
+        if (!isLarge) {
+            setShowFullContent(true);
         }
-    }, [showFullContent, MAX_CONTENT_SIZE]);
+    }, []);
 
     const toggleFullContent = useCallback(() => {
         setShowFullContent(!showFullContent);
-        if (!showFullContent) {
-            setDisplayContent(pasteContent);
-        } else {
-            const lines = pasteContent.split('\n');
-            const previewLines = lines.slice(0, MAX_DISPLAY_LINES);
-            const preview = previewLines.join('\n') + (lines.length > MAX_DISPLAY_LINES ? '\n... (truncated for performance)' : '');
-            setDisplayContent(preview);
-        }
-    }, [showFullContent, pasteContent]);
+    }, [showFullContent]);
 
     const handlePasteSubmit = (): void => {
         let table: undefined | DictTable = undefined;
@@ -1401,9 +1387,12 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                 autoFocus
                                 multiline
                                 fullWidth
-                                value={displayContent}
+                                value={pasteContent}
                                 onChange={handleContentChange}
                                 placeholder="Paste your data here (CSV, TSV, or JSON format)"
+                                InputProps={{
+                                    readOnly: isLargeContent && !showFullContent,
+                                }}
                                 sx={{
                                     flex: hasPasteContent ? 1 : 'none',
                                     '& .MuiInputBase-root': {
@@ -1415,9 +1404,27 @@ export const UnifiedDataUploadDialog: React.FC<UnifiedDataUploadDialogProps> = (
                                         fontFamily: 'monospace',
                                         height: hasPasteContent ? '100% !important' : 'auto !important',
                                         overflow: 'auto !important',
+                                    },
+                                    '& .MuiInputBase-input[readonly]': {
+                                        cursor: 'not-allowed',
                                     }
                                 }}
                             />
+                            {/* Show preview indicator when in preview mode */}
+                            {isLargeContent && !showFullContent && (
+                                <Box sx={{ 
+                                    mt: 0.5, 
+                                    px: 1, 
+                                    py: 0.5, 
+                                    backgroundColor: alpha(theme.palette.info.main, 0.08),
+                                    borderRadius: 0.5,
+                                    border: `1px solid ${alpha(theme.palette.info.main, 0.2)}`
+                                }}>
+                                    <Typography variant="caption" color="text.secondary" sx={{ fontSize: '0.7rem' }}>
+                                        Preview mode: Editing disabled. Click "Show Full" to enable editing.
+                                    </Typography>
+                                </Box>
+                            )}
                         </Box>
 
                         <Box sx={{ display: 'flex', justifyContent: 'flex-end', mt: 2, gap: 1 }}>

From e460804f5f8366e48eb91f69ff78abbaf57295f5 Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Mon, 26 Jan 2026 16:14:59 -0800
Subject: [PATCH 19/21] add examples

---
 public/df_stock_prices_live.json              |   1 +
 ...screenshot-stock-price-live-thumbnail.webp | Bin 0 -> 9682 bytes
 .../agents/agent_py_data_rec.py               |   2 +-
 .../agents/agent_py_data_transform.py         |   3 +-
 src/app/useDataRefresh.tsx                    |  46 +++++++++++++-----
 src/views/DataFormulator.tsx                  |   3 --
 src/views/ExampleSessions.tsx                 |  20 ++++++--
 7 files changed, 56 insertions(+), 19 deletions(-)
 create mode 100644 public/df_stock_prices_live.json
 create mode 100644 public/screenshot-stock-price-live-thumbnail.webp

diff --git a/public/df_stock_prices_live.json b/public/df_stock_prices_live.json
new file mode 100644
index 0000000..59d6d63
--- /dev/null
+++ b/public/df_stock_prices_live.json
@@ -0,0 +1 @@
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pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Select only needed columns\n    cols = [\"date\", \"symbol\", \"close\"]\n    df = df_history[cols].copy()\n\n    # Ensure date is a string in YYYY-MM-DD format (no datetime objects)\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper line plotting\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    transformed_df = df\n    return transformed_df\n","source":["history"],"dialog":[{"role":"system","content":"You are a data scientist to help user to recommend data that will be used for visualization.\nThe user will provide you information about what visualization they would like to create, and your job is to recommend a transformed data that can be used to create the visualization and write a python function to transform the data.\nThe recommendation and transformation function should be based on the [CONTEXT] and [GOAL] provided by the user. \nThe [CONTEXT] shows what the current dataset is, and the [GOAL] describes what the user wants the data for.\n\n**Important:**\n- NEVER make assumptions or judgments about a person's gender, biological sex, sexuality, religion, race, nationality, ethnicity, political stance, socioeconomic status, mental health, invisible disabilities, medical conditions, personality type, social impressions, emotional state, and cognitive state.\n- NEVER create formulas that could be used to discriminate based on age. Ageism of any form (explicit and implicit) is strictly prohibited.\n- If above issue occurs, generate columns with np.nan.\n\nConcretely, you should infer the appropriate data and create in the output section a python function based off the [CONTEXT] and [GOAL] in two steps:\n\n1. First, based on users' [GOAL]. Create a json object that represents the inferred user intent. The json object should have the following format:\n\n{\n    \"mode\": \"\" // string, one of \"infer\", \"overview\", \"distribution\", \"summary\", \"forecast\"\n    \"recap\": \"...\" // string, a short summary of the user's goal.\n    \"display_instruction\": \"...\" // string, the even shorter verb phrase describing the users' goal.\n    \"recommendation\": \"...\" // string, explain why this recommendation is made\n    \"input_tables\": [...] // string[], describe names of the input tables that will be used in the transformation.\n    \"output_fields\": [...] // string[], describe the desired output fields that the output data should have (i.e., the goal of transformed data), it's a good idea to preseve intermediate fields here\n    \"chart_type\": \"\" // string, one of \"point\", \"bar\", \"line\", \"area\", \"heatmap\", \"group_bar\", 'boxplot'. \"chart_type\" should either be inferred from user instruction, or recommend if the user didn't specify any.\n    \"chart_encodings\": {\n        \"x\": \"\",\n        \"y\": \"\",\n        \"color\": \"\",\n        \"size\": \"\",\n        \"opacity\": \"\",\n        \"facet\": \"\",\n    } // object: map visualization channels (x, y, color, size, opacity, facet, etc.) to a subset of output fields, appropriate visual channels for different chart types are defined below.\n}\n\nConcretely:\n    - recap what the user's goal is in a short summary in \"recap\".\n    - If the user's [GOAL] is clear already, simply infer what the user mean. Set \"mode\" as \"infer\" and create \"output_fields\" and \"chart_encodings\" based off user description.\n    - If the user's [GOAL] is not clear, make recommendations to the user:\n        - choose one of \"distribution\", \"overview\", \"summary\", \"forecast\" in \"mode\":\n            * if it is \"overview\" and the data is in wide format, reshape it into long format.\n            * if it is \"distribution\", select a few fields that would be interesting to visualize together.\n            * if it is \"summary\", calculate some aggregated statistics to show intresting facts of the data.\n            * if it is \"forecast\", concretize the x,y fields that will be used for forecasting and decide if it is about regression or forecasting.\n        - describe the recommendation reason in \"recommendation\"\n        - based on the recommendation, determine what is an ideal output data. Note, the output data must be in tidy format.\n        - then suggest recommendations of chart encoding that should be used to create the visualization.\n    - \"display_instruction\" should be a short verb phrase describing the users' goal, it should be even shorter than \"recap\". \n        - it would be a short verbal description of user intent as a verb phrase (<12 words).\n        - generate based on \"recap\" and the suggested visualization, but don't need to mention the visualization details.\n        - should capture key computation ideas: by reading the display, the user can understand the purpose and what's derived from the data.\n        - if the user instruction builds up the previous instruction, the 'display_instruction' should only describe how it builds up the previous instruction without repeating information from previous steps.\n        - the phrase can be presented in different styles, e.g., question (what's xxx), instruction (show xxx), description, etc.\n        - if you mention column names from the input or the output data, highlight the text in **bold**.\n            * the column can either be a column in the input data, or a new column that will be computed in the output data.\n            * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned \"average score\" in the text while the column to be computed is \"Avg_Score\", you should still highlight \"**average score**\" in the text.\n    - determine \"input_tables\", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.\n        - **IMPORTANT** Note that the Table 1 in [CONTEXT] section is the table the user is currently viewing, it should take precedence if the user refers to insights about the \"current table\".\n        - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.\n    - \"chart_type\" must be one of \"point\", \"bar\", \"line\", \"area\", \"heatmap\", \"group_bar\", \"boxplot\"\n    - \"chart_encodings\" should specify which fields should be used to create the visualization\n        - decide which visual channels should be used to create the visualization appropriate for the chart type.\n            - point: x, y, color, size, facet\n            - histogram: x, color, facet\n            - bar: x, y, color, facet\n            - line: x, y, color, facet\n            - area: x, y, color, facet\n            - heatmap: x, y, color, facet\n            - group_bar: x, y, color, facet\n            - boxplot: x, y, color, facet\n        - note that all fields used in \"chart_encodings\" should be included in \"output_fields\".\n            - all fields you need for visualizations should be transformed into the output fields!\n            - \"output_fields\" should include important intermediate fields that are not used in visualization but are used for data transformation.\n        - typically only 2-3 fields should be used to create the visualization (x, y, color/size), facet use be added if it's a faceted visualization (totally 4 fields used).\n    - Guidelines for choosing chart type and visualization fields:\n        - Consider chart types as follows:\n            - (point) Scatter Plots: x,y: Quantitative/Categorical, color: Categorical (optional), size: Quantitative (optional for creating bubble chart), \n                - best for: Relationships, correlations, distributions, forecasting, regression analysis\n                - scatter plots are good default way to visualize data when other chart types are not applicable.\n                - use color to visualize points from different categories.\n                - use size to visualize data points with an additional quantitative dimension of the data points.\n            - (histogram) Histograms: x: Quantitative/Categorical, color: Categorical (optional for creating grouped histogram), \n                - best for: Distribution of a quantitative field\n                - use x values directly if x values are categorical, and transform the data into bins if the field values are quantitative.\n                - when color is specified, the histogram will be grouped automatically (items with the same x values will be grouped).\n            - (bar) Bar Charts: x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical/Quantitative (for stacked bar chart / showing additional quantitative dimension), \n                - best for: Comparisons across categories\n                - use (bar) for simple bar chart or stacked bar chart (when it makes sense to add up Y values for each category with the same X value), \n                    - when color is specified, the bar will be stacked automatically (items with the same x values will be stacked).\n                    - note that when there are multiple rows in the data with same x values, the bar will be stacked automatically.\n                        - 1. consider to use an aggregated field for y values if the value is not suitable for stacking.\n                        - 2. consider to introduce facets so that each group is visualized in a separate bar.\n            - (group_bar) for grouped bar chart, x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical\n                - when color is specifed, bars from different groups will be grouped automatically.\n                - only use facet if the cardinality of color field is small (less than 5).\n            - (line) Line Charts: x: Temporal (preferred) or ordinal, y: Quantitative, color: Categorical (optional for creating multiple lines), \n                - best for: Trends over time, continuous data, forecasting, regression analysis\n                - note that when there are multiple rows in the data belong to the same group (same x and color values) but different y values, the line will not look correct.\n                - consider to use an aggregated field for y values, or introduce facets so that each group is visualized in a separate line.\n            - (area) Area Charts: x: Temporal (preferred) or ordinal, y: Quantitative, color: Categorical (optional for creating stacked areas), \n                - best for: Trends over time, continuous data\n            - (heatmap) Heatmaps: x,y: Categorical (you need to convert quantitative to nominal), color: Quantitative intensity, \n                - best for: Pattern discovery in matrix data\n            - (boxplot) Box plots: x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical (optional for creating grouped boxplots), \n                - best for: Distribution of a quantitative field\n                - use x values directly if x values are categorical, and transform the data into bins if the field values are quantitative.\n                - when color is specified, the boxplot will be grouped automatically (items with the same x values will be grouped).\n        - facet channel is available for all chart types, it supports a categorical field with small cardinality to visualize the data in different facets.\n        - if you really need additional legend fields:\n            - you can use opacity for legend (support Quantitative and Categorical).\n    - visualization fields require tidy data. \n        - similar to VegaLite and ggplot2 so that each field is mapped to a visualization axis or legend. \n        - consider data transformations if you want to visualize multiple fields together:\n            - exapmle 1: suggest reshaping the data into long format in data transformation description (if these fields are all of the same type, e.g., they are all about sales, price, two columns about min/max-values, etc. don't mix different types of fields in reshaping) so we can visualize multiple fields as categories or in different facets.\n            - exapmle 2: calculate some derived fields from these fields(e.g., correlation, difference, profit etc.) in data transformation description to visualize them in one visualization.\n            - example 3: create a visualization only with a subset of the fields, you don't have to visualize all of them in one chart, you can later create a visualization with the rest of the fields. With the subset of charts, you can also consider reshaping or calculate some derived value.\n            - again, it does not make sense to have five fields like [item, A, B, C, D, E] in visualization fields, you should consider data transformation to reduce the number of fields.\n            - when reshaping data to long format, only fields of the same semantic type should be rehaped into the same column.\n    - guide on statistical analysis:\n        - when the user asks for forecasting or regression analysis, you should consider the following:\n            - the output should be a long format table where actual x, y pairs and predicted x, y pairs are included in the X, Y columns, they are differentiated with a third column \"is_predicted\" that is a boolean field.\n            - i.e., if the user ask for forecasting based on two columns T and Y, the output should be three columns: T, Y, is_predicted, where\n                - T, Y columns contain BOTH original values from the data and predicted values from the data.\n                - is_predicted is a boolean field to indicate whether the x, y pairs are original values from the data or predicted / regression values from the data.\n            - the recommended chart should be line chart (time series) or scatter plot (quantitative x, y)\n            - if the user asks for forecasting, it's good to include predicted x, y pairs for both x in the original data and future x values (i.e., combine regression and forecasting results)\n                - in this case, is_predicted should be of three values 'original', 'regression', 'forecasting'\n                - put is_predicted field in 'opacity' channel to distinguish them.\n        - when the user asks for clustering:\n            - the output should be a long format table where actual x, y pairs with a third column \"cluster_id\" that indicates the cluster id of the data point.\n            - the recommended chart should be scatter plot (quantitative x, y)\n            \n    2. Then, write a python function based on the inferred goal, the function input is a dataframe \"df\" (or multiple dataframes based on tables presented in the [CONTEXT] section) and the output is the transformed dataframe \"transformed_df\". \n\"transformed_df\" should contain all \"output_fields\" from the refined user intent in the json object.\nThe python function must follow the template provided in [TEMPLATE]. The function should be as simple as possible and easily readable. \nIf there is no data transformation needed based on \"output_fields\", the transformation function can simply \"return df\".\n\n[TEMPLATE]\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n# from sklearn import ... # import from sklearn if you need it.\n\ndef transform_data(df1, df2, ...): \n    # complete the template here\n    return transformed_df\n```\n\nnote: \n- decide the function signature based on the number of tables you decided in the previous step \"input_tables\":\n    - if you decide there will only be one input table, then function signature should be `def transform_data(df1)`\n    - if you decided there will be k input tables, then function signature should be `def transform_data(df_1, df_2, ..., df_k)`.\n    - instead of using generic names like df1, df2, ..., try to use intuitive table names for function arguments, for example, if you have input_tables: [\"City\", \"Weather\"]`, you can use `transform_data(df_city, df_weather)` to refer to the two dataframes.\n    - **VERY IMPORTANT** the number of arguments in the function signature must be the same as the number of tables provided in \"input_tables\", and the order of arguments must match the order of tables provided in \"input_tables\".\n- datetime objects handling:\n    - if the output field is year, convert it to number, if it is year-month / year-month-day, convert it to string object (e.g., \"2020-01\" / \"2020-01-01\").\n    - if the output is time only: convert hour to number if it's just the hour (e.g., 10), but convert hour:min or h:m:s to string object (e.g., \"10:30\", \"10:30:45\")\n    - never return datetime object directly, convert it to either number (if it only contains year) or string so it's readable.\n    \n    3. The output must only contain a json object representing inferred user intent and a python code block representing the transformation code, do not add any extra text explanation.\n"},{"role":"user","content":"[CONTEXT]\n\n## Table 1: history (738 rows × 8 columns)\n\n### Schema (8 fields)\n  - symbol -- type: object, values: AAPL, AMZN, GOOGL, META, MSFT, NVDA\n  - date -- type: object, values: 2025-07-30, 2025-07-31, 2025-08-01, ..., 2026-01-20, 2026-01-21, 2026-01-22, 2026-01-23\n  - open -- type: float64, values: 167.53, 168.01, 169.07, ..., 781.21, 782.98, 785.25, 789.97\n  - high -- type: float64, values: 169.01, 170.94, 170.96, ..., 789.62, 792.49, 794.28, 795.06\n  - low -- type: float64, values: 164.05, 166.72, 167.2, ..., 771.36, 772.21, 777.07, 779.66\n  - close -- type: float64, values: 167.0, 168.29, 170.28, ..., 779.09, 780.97, 784.06, 788.82\n  - volume -- type: int64, values: 5627500, 5855900, 6861200, ..., 320600300, 324925900, 343504800, 346926200\n  - fetched_at -- type: object, values: 2026-01-26T23:46:42.347312Z\n\n### Sample Data (first 5 rows)\n```\n  symbol        date    open    high     low   close     volume                   fetched_at\n0   AAPL  2025-07-30  211.45  211.94  207.28  208.61   45512500  2026-01-26T23:46:42.347312Z\n1   AAPL  2025-07-31  208.05  209.40  206.72  207.13   80698400  2026-01-26T23:46:42.347312Z\n2   AAPL  2025-08-01  210.43  213.13  201.08  201.95  104434500  2026-01-26T23:46:42.347312Z\n3   AAPL  2025-08-04  204.08  207.44  201.26  202.92   75109300  2026-01-26T23:46:42.347312Z\n4   AAPL  2025-08-05  202.97  204.91  201.74  202.49   44155100  2026-01-26T23:46:42.347312Z\n```\n\n\n[GOAL]\n\n1) First, plot the overall **closing price** trends for each **symbol** over **time** on a single line chart to compare their broad trajectories and volatility."},{"role":"assistant","content":"{\n  \"mode\": \"infer\",\n  \"recap\": \"Compare overall closing price trends and volatility over time for each stock symbol on a single line chart.\",\n  \"display_instruction\": \"Visualize **closing price** trends by **symbol** over **date**\",\n  \"recommendation\": \"A line chart with time on the x-axis and closing price on the y-axis, colored by symbol, best shows comparative trajectories and volatility over time. The data only needs column selection, date normalization, and sorting to be visualization-ready.\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"close\"],\n  \"chart_type\": \"line\",\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"close\",\n    \"color\": \"symbol\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"\"\n  }\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Select only needed columns\n    cols = [\"date\", \"symbol\", \"close\"]\n    df = df_history[cols].copy()\n\n    # Ensure date is a string in YYYY-MM-DD format (no datetime objects)\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper line plotting\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    transformed_df = df\n    return transformed_df\n```"}],"trigger":{"tableId":"history","sourceTableIds":["history"],"instruction":"1) First, plot the overall **closing price** trends for each **symbol** over **time** on a single line chart to compare their broad trajectories and volatility.","displayInstruction":"Visualize **closing price** trends by **symbol** over **date**","chart":{"id":"chart-1769471233291","chartType":"Auto","encodingMap":{},"tableRef":"history","saved":false,"source":"trigger","unread":true},"resultTableId":"table-233476"},"explanation":{"status":"ok","concepts":[],"code":"- **Keep only the key fields**: selects the columns **`\"date\"`**, **`\"symbol\"`**, and **`\"close\"`** from the input data and **drops all other columns**.\n- **Standardize the date format**: converts **`date`** into a **string** in the **`\"YYYY-MM-DD\"`** format to ensure consistency (no time component, no different date formats).\n- **Order the data for time-series use**: **sorts** the rows first by **`symbol`** and then by **`date`** so that each stock’s closing prices are in **chronological order**, which is important for **line charts** or time-based analysis.\n- **Return the cleaned dataset**: outputs this **simplified and ordered** table as the final transformed data.","dialog":[{"role":"system","content":"You are a data scientist to help user explain code, \nso that a non-code can clearly understand what the code is doing, you are provided with a summary of the input data, and the transformation code.\n\nYour goal:\n1. You should generate a good itemized explanation of the code so that the reader can understand high-level steps of what the data transformation is doing.\n    - Be very concise, and stay at a high-level. The reader doesn't understand code and does not want to learn exactly what the code is doing. They just want to learn what have been done from a logical level.\n    - The explanation should be a markdown string that is a list of bullet points (with new lines), highlight constants, data fields, and important verbs.\n2. Generate a list of explanations for new fields (fields not from the input data) that introduce metrics/concepts that are not obvious from the code.\n    - provide a declarative definition that explains the new field, use a mathematical notation if applicable.\n    - only include new fields explanation of new metrics that are involved in computation (e.g., ROI, commerical_success_score)\n    - *DO NOT* explain trivial new fields like \"Decade\" or \"Avg_Rating\", \"US_Sales\" that are self-explanatory.\n        - Avoid explaining fields that are simple aggregate of fields in the original data (min_score, avg_value, count, etc.)\n    - When a field involves mathematical computation, you can use LaTeX math notation in the explanation. Format mathematical expressions using:\n        - Inline math: `\\( ... \\)` for formulas within text\n        - Block math: `\\[ ... \\]` for standalone formulas\n        - Examples: `\\( \\frac{\\text{Revenue}}{\\text{Cost}} \\)` for ratios, `\\[ \\text{Score} = \\text{Rating} \\times \\text{Worldwide\\_Gross} \\]` for formulas\n        - note: when using underscores as part of the text, you need to escape them with a backslash, e.g., `\\_`\n    - Note: don't use math notation for fields whose computation is trivial (use plain english), it will likely be confusing to the reader. \n      Only use math notation for fields that can not be easilyexplained in plain english. Use it sparingly.\n3. If there are multiple fields that have the similar computation, you can explain them together in one explanation.\n    - in \"field\", you can provide a list of fields in format of \"field1, field2, ...\"\n    - in \"explanation\", you can provide a single explanation for the computation of the fields.\n    - for example, if you have fields like \"Norm_Rating\", \"Norm_Gross\", \"Critical_Commercial_Score\", you can explain Norm_Rating, Norm_Gross together in one explanation and explain Critical_Commercial_Score in another explanation.\n4. If the code is about statistical analysis, you should explain the statistical analysis in the explanation as a concept named \"Statistical Analysis\" in the [CONCEPTS EXPLANATION] section.\n    - explain how you model the data, which fields are used, how data processing is done, and what models are used.\n    - suggest some other modeling approaches that can be used to analyze the data in the explanation as well.\n    \nThe focus is to explain how new fields are computed, don't generate explanation for low-level actions like \"return\", \"load data\" etc. \n\nProvide the result in the following two sections:\n    - first section is the code explanation that should be a markdown block explaining the code, in the [CODE EXPLANATION] section.\n        - remember to highlight constants, data fields, and important verbs in the code explanation.\n    - second section is the concepts explanation that should be a json block (start with ```json) in the [CONCEPTS EXPLANATION] section.\n\n[CODE EXPLANATION]\n\n...(explanation of the code)\n\n[CONCEPTS EXPLANATION]\n\n```json\n[\n    {\n        \"field\": \"...\",\n        \"explanation\": \"...\"\n    }\n]\n\n```\n"},{"role":"user","content":"[CONTEXT]\n\n## Table 1: history (738 rows × 8 columns)\n\n### Schema (8 fields)\n  - symbol -- type: object, values: AAPL, AMZN, GOOGL, META, MSFT, NVDA\n  - date -- type: object, values: 2025-07-30, 2025-07-31, 2025-08-01, ..., 2026-01-20, 2026-01-21, 2026-01-22, 2026-01-23\n  - open -- type: float64, values: 167.53, 168.01, 169.07, ..., 781.21, 782.98, 785.25, 789.97\n  - high -- type: float64, values: 169.01, 170.94, 170.96, ..., 789.62, 792.49, 794.28, 795.06\n  - low -- type: float64, values: 164.05, 166.72, 167.2, ..., 771.36, 772.21, 777.07, 779.66\n  - close -- type: float64, values: 167.0, 168.29, 170.28, ..., 779.09, 780.97, 784.06, 788.82\n  - volume -- type: int64, values: 5627500, 5855900, 6861200, ..., 320600300, 324925900, 343504800, 346926200\n  - fetched_at -- type: object, values: 2026-01-26T23:46:42.347312Z\n\n### Sample Data (first 5 rows)\n```\n  symbol        date    open    high     low   close     volume                   fetched_at\n0   AAPL  2025-07-30  211.45  211.94  207.28  208.61   45512500  2026-01-26T23:46:42.347312Z\n1   AAPL  2025-07-31  208.05  209.40  206.72  207.13   80698400  2026-01-26T23:46:42.347312Z\n2   AAPL  2025-08-01  210.43  213.13  201.08  201.95  104434500  2026-01-26T23:46:42.347312Z\n3   AAPL  2025-08-04  204.08  207.44  201.26  202.92   75109300  2026-01-26T23:46:42.347312Z\n4   AAPL  2025-08-05  202.97  204.91  201.74  202.49   44155100  2026-01-26T23:46:42.347312Z\n```\n\n\n[CODE]\n\nhere is the transformation code: \nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Select only needed columns\n    cols = [\"date\", \"symbol\", \"close\"]\n    df = df_history[cols].copy()\n\n    # Ensure date is a string in YYYY-MM-DD format (no datetime objects)\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper line plotting\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    transformed_df = df\n    return transformed_df\n\n\n[EXPLANATION]\n"},{"role":"assistant","content":"[CODE EXPLANATION]\n\n- **Keep only the key fields**: selects the columns **`\"date\"`**, **`\"symbol\"`**, and **`\"close\"`** from the input data and **drops all other columns**.\n- **Standardize the date format**: converts **`date`** into a **string** in the **`\"YYYY-MM-DD\"`** format to ensure consistency (no time component, no different date formats).\n- **Order the data for time-series use**: **sorts** the rows first by **`symbol`** and then by **`date`** so that each stock’s closing prices are in **chronological order**, which is important for **line charts** or time-based analysis.\n- **Return the cleaned dataset**: outputs this **simplified and ordered** table as the final transformed data.\n\n[CONCEPTS EXPLANATION]\n\n```json\n[]\n```"}],"agent":"CodeExplanationAgent"}},"anchored":false,"createdBy":"user","attachedMetadata":""},{"id":"table-265247","displayId":"stock-ma","names":["date","symbol","close","value","ma_window"],"rows":[{"date":"2025-07-30","symbol":"AAPL","close":208.61,"value":208.61,"ma_window":20},{"date":"2025-07-31","symbol":"AAPL","close":207.13,"value":207.87,"ma_window":20},{"date":"2025-08-01","symbol":"AAPL","close":201.95,"value":205.8966666667,"ma_window":20},{"date":"2025-08-04","symbol":"AAPL","close":202.92,"value":205.1525,"ma_window":20},{"date":"2025-08-05","symbol":"AAPL","close":202.49,"value":204.62,"ma_window":20},{"date":"2025-08-06","symbol":"AAPL","close":212.8,"value":205.9833333333,"ma_window":20},{"date":"2025-08-07","symbol":"AAPL","close":219.57,"value":207.9242857143,"ma_window":20},{"date":"2025-08-08","symbol":"AAPL","close":228.87,"value":210.5425,"ma_window":20},{"date":"2025-08-11","symbol":"AAPL","close":226.96,"value":212.3666666667,"ma_window":20},{"date":"2025-08-12","symbol":"AAPL","close":229.43,"value":214.073,"ma_window":20},{"date":"2025-08-13","symbol":"AAPL","close":233.1,"value":215.8027272727,"ma_window":20},{"date":"2025-08-14","symbol":"AAPL","close":232.55,"value":217.1983333333,"ma_window":20},{"date":"2025-08-15","symbol":"AAPL","close":231.37,"value":218.2884615385,"ma_window":20},{"date":"2025-08-18","symbol":"AAPL","close":230.67,"value":219.1728571429,"ma_window":20},{"date":"2025-08-19","symbol":"AAPL","close":230.34,"value":219.9173333333,"ma_window":20},{"date":"2025-08-20","symbol":"AAPL","close":225.79,"value":220.284375,"ma_window":20},{"date":"2025-08-21","symbol":"AAPL","close":224.68,"value":220.5429411765,"ma_window":20},{"date":"2025-08-22","symbol":"AAPL","close":227.54,"value":220.9316666667,"ma_window":20},{"date":"2025-08-25","symbol":"AAPL","close":226.94,"value":221.2478947368,"ma_window":20},{"date":"2025-08-26","symbol":"AAPL","close":229.09,"value":221.64,"ma_window":20},{"date":"2025-08-27","symbol":"AAPL","close":230.27,"value":222.723,"ma_window":20},{"date":"2025-08-28","symbol":"AAPL","close":232.33,"value":223.983,"ma_window":20},{"date":"2025-08-29","symbol":"AAPL","close":231.92,"value":225.4815,"ma_window":20},{"date":"2025-09-02","symbol":"AAPL","close":229.5,"value":226.8105,"ma_window":20},{"date":"2025-09-03","symbol":"AAPL","close":238.24,"value":228.598,"ma_window":20},{"date":"2025-09-04","symbol":"AAPL","close":239.55,"value":229.9355,"ma_window":20},{"date":"2025-09-05","symbol":"AAPL","close":239.46,"value":230.93,"ma_window":20},{"date":"2025-09-08","symbol":"AAPL","close":237.65,"value":231.369,"ma_window":20},{"date":"2025-09-09","symbol":"AAPL","close":234.12,"value":231.727,"ma_window":20},{"date":"2025-09-10","symbol":"AAPL","close":226.57,"value":231.584,"ma_window":20},{"date":"2025-09-11","symbol":"AAPL","close":229.81,"value":231.4195,"ma_window":20},{"date":"2025-09-12","symbol":"AAPL","close":233.84,"value":231.484,"ma_window":20},{"date":"2025-09-15","symbol":"AAPL","close":236.47,"value":231.739,"ma_window":20},{"date":"2025-09-16","symbol":"AAPL","close":237.92,"value":232.1015,"ma_window":20},{"date":"2025-09-17","symbol":"AAPL","close":238.76,"value":232.5225,"ma_window":20},{"date":"2025-09-18","symbol":"AAPL","close":237.65,"value":233.1155,"ma_window":20},{"date":"2025-09-19","symbol":"AAPL","close":245.26,"value":234.1445,"ma_window":20},{"date":"2025-09-22","symbol":"AAPL","close":255.83,"value":235.559,"ma_window":20},{"date":"2025-09-23","symbol":"AAPL","close":254.18,"value":236.921,"ma_window":20},{"date":"2025-09-24","symbol":"AAPL","close":252.07,"value":238.07,"ma_window":20},{"date":"2025-09-25","symbol":"AAPL","close":256.62,"value":239.3875,"ma_window":20},{"date":"2025-09-26","symbol":"AAPL","close":255.21,"value":240.5315,"ma_window":20},{"date":"2025-09-29","symbol":"AAPL","close":254.18,"value":241.6445,"ma_window":20},{"date":"2025-09-30","symbol":"AAPL","close":254.38,"value":242.8885,"ma_window":20},{"date":"2025-10-01","symbol":"AAPL","close":255.2,"value":243.7365,"ma_window":20},{"date":"2025-10-02","symbol":"AAPL","close":256.88,"value":244.603,"ma_window":20},{"date":"2025-10-03","symbol":"AAPL","close":257.77,"value":245.5185,"ma_window":20},{"date":"2025-10-06","symbol":"AAPL","close":256.44,"value":246.458,"ma_window":20},{"date":"2025-10-07","symbol":"AAPL","close":256.23,"value":247.5635,"ma_window":20},{"date":"2025-10-08","symbol":"AAPL","close":257.81,"value":249.1255,"ma_window":20},{"date":"2025-10-09","symbol":"AAPL","close":253.79,"value":250.3245,"ma_window":20},{"date":"2025-10-10","symbol":"AAPL","close":245.03,"value":250.884,"ma_window":20},{"date":"2025-10-13","symbol":"AAPL","close":247.42,"value":251.4315,"ma_window":20},{"date":"2025-10-14","symbol":"AAPL","close":247.53,"value":251.912,"ma_window":20},{"date":"2025-10-15","symbol":"AAPL","close":249.1,"value":252.429,"ma_window":20},{"date":"2025-10-16","symbol":"AAPL","close":247.2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pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Work on a copy and keep only needed columns if present\n    base_cols = [c for c in [\"date\", \"symbol\", \"close\"] if c in df_history.columns]\n    df = df_history[base_cols].copy()\n\n    # Normalize date to string YYYY-MM-DD\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper rolling computation\n    df = df.sort_values([\"symbol\", \"date\"])\n\n    # Ensure we have a clean, simple index to avoid alignment issues\n    df = df.reset_index(drop=True)\n\n    # Compute rolling means using transform to preserve index alignment\n    df[\"ma_20\"] = (\n        df.groupby(\"symbol\")[\"close\"]\n          .transform(lambda s: s.rolling(window=20, min_periods=1).mean())\n    )\n    df[\"ma_60\"] = (\n        df.groupby(\"symbol\")[\"close\"]\n          .transform(lambda s: s.rolling(window=60, min_periods=1).mean())\n    )\n\n    # Reshape to long format for the moving averages\n    df_long = df.melt(\n        id_vars=[\"date\", \"symbol\", \"close\"],\n        value_vars=[\"ma_20\", \"ma_60\"],\n        var_name=\"ma_window\",\n        value_name=\"value\",\n    )\n\n    # Map ma_window to numeric window size (20 or 60)\n    window_map = {\"ma_20\": 20, \"ma_60\": 60}\n    df_long[\"ma_window\"] = df_long[\"ma_window\"].map(window_map).astype(int)\n\n    # Final tidy output\n    transformed_df = df_long[[\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"]].reset_index(drop=True)\n    return transformed_df\n","source":["history"],"dialog":[{"role":"system","content":"You are a data scientist to help user to recommend data that will be used for visualization.\nThe user will provide you information about what visualization they would like to create, and your job is to recommend a transformed data that can be used to create the visualization and write a python function to transform the data.\nThe recommendation and transformation function should be based on the [CONTEXT] and [GOAL] provided by the user. \nThe [CONTEXT] shows what the current dataset is, and the [GOAL] describes what the user wants the data for.\n\n**Important:**\n- NEVER make assumptions or judgments about a person's gender, biological sex, sexuality, religion, race, nationality, ethnicity, political stance, socioeconomic status, mental health, invisible disabilities, medical conditions, personality type, social impressions, emotional state, and cognitive state.\n- NEVER create formulas that could be used to discriminate based on age. Ageism of any form (explicit and implicit) is strictly prohibited.\n- If above issue occurs, generate columns with np.nan.\n\nConcretely, you should infer the appropriate data and create in the output section a python function based off the [CONTEXT] and [GOAL] in two steps:\n\n1. First, based on users' [GOAL]. Create a json object that represents the inferred user intent. The json object should have the following format:\n\n{\n    \"mode\": \"\" // string, one of \"infer\", \"overview\", \"distribution\", \"summary\", \"forecast\"\n    \"recap\": \"...\" // string, a short summary of the user's goal.\n    \"display_instruction\": \"...\" // string, the even shorter verb phrase describing the users' goal.\n    \"recommendation\": \"...\" // string, explain why this recommendation is made\n    \"input_tables\": [...] // string[], describe names of the input tables that will be used in the transformation.\n    \"output_fields\": [...] // string[], describe the desired output fields that the output data should have (i.e., the goal of transformed data), it's a good idea to preseve intermediate fields here\n    \"chart_type\": \"\" // string, one of \"point\", \"bar\", \"line\", \"area\", \"heatmap\", \"group_bar\", 'boxplot'. \"chart_type\" should either be inferred from user instruction, or recommend if the user didn't specify any.\n    \"chart_encodings\": {\n        \"x\": \"\",\n        \"y\": \"\",\n        \"color\": \"\",\n        \"size\": \"\",\n        \"opacity\": \"\",\n        \"facet\": \"\",\n    } // object: map visualization channels (x, y, color, size, opacity, facet, etc.) to a subset of output fields, appropriate visual channels for different chart types are defined below.\n}\n\nConcretely:\n    - recap what the user's goal is in a short summary in \"recap\".\n    - If the user's [GOAL] is clear already, simply infer what the user mean. Set \"mode\" as \"infer\" and create \"output_fields\" and \"chart_encodings\" based off user description.\n    - If the user's [GOAL] is not clear, make recommendations to the user:\n        - choose one of \"distribution\", \"overview\", \"summary\", \"forecast\" in \"mode\":\n            * if it is \"overview\" and the data is in wide format, reshape it into long format.\n            * if it is \"distribution\", select a few fields that would be interesting to visualize together.\n            * if it is \"summary\", calculate some aggregated statistics to show intresting facts of the data.\n            * if it is \"forecast\", concretize the x,y fields that will be used for forecasting and decide if it is about regression or forecasting.\n        - describe the recommendation reason in \"recommendation\"\n        - based on the recommendation, determine what is an ideal output data. Note, the output data must be in tidy format.\n        - then suggest recommendations of chart encoding that should be used to create the visualization.\n    - \"display_instruction\" should be a short verb phrase describing the users' goal, it should be even shorter than \"recap\". \n        - it would be a short verbal description of user intent as a verb phrase (<12 words).\n        - generate based on \"recap\" and the suggested visualization, but don't need to mention the visualization details.\n        - should capture key computation ideas: by reading the display, the user can understand the purpose and what's derived from the data.\n        - if the user instruction builds up the previous instruction, the 'display_instruction' should only describe how it builds up the previous instruction without repeating information from previous steps.\n        - the phrase can be presented in different styles, e.g., question (what's xxx), instruction (show xxx), description, etc.\n        - if you mention column names from the input or the output data, highlight the text in **bold**.\n            * the column can either be a column in the input data, or a new column that will be computed in the output data.\n            * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned \"average score\" in the text while the column to be computed is \"Avg_Score\", you should still highlight \"**average score**\" in the text.\n    - determine \"input_tables\", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.\n        - **IMPORTANT** Note that the Table 1 in [CONTEXT] section is the table the user is currently viewing, it should take precedence if the user refers to insights about the \"current table\".\n        - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.\n    - \"chart_type\" must be one of \"point\", \"bar\", \"line\", \"area\", \"heatmap\", \"group_bar\", \"boxplot\"\n    - \"chart_encodings\" should specify which fields should be used to create the visualization\n        - decide which visual channels should be used to create the visualization appropriate for the chart type.\n            - point: x, y, color, size, facet\n            - histogram: x, color, facet\n            - bar: x, y, color, facet\n            - line: x, y, color, facet\n            - area: x, y, color, facet\n            - heatmap: x, y, color, facet\n            - group_bar: x, y, color, facet\n            - boxplot: x, y, color, facet\n        - note that all fields used in \"chart_encodings\" should be included in \"output_fields\".\n            - all fields you need for visualizations should be transformed into the output fields!\n            - \"output_fields\" should include important intermediate fields that are not used in visualization but are used for data transformation.\n        - typically only 2-3 fields should be used to create the visualization (x, y, color/size), facet use be added if it's a faceted visualization (totally 4 fields used).\n    - Guidelines for choosing chart type and visualization fields:\n        - Consider chart types as follows:\n            - (point) Scatter Plots: x,y: Quantitative/Categorical, color: Categorical (optional), size: Quantitative (optional for creating bubble chart), \n                - best for: Relationships, correlations, distributions, forecasting, regression analysis\n                - scatter plots are good default way to visualize data when other chart types are not applicable.\n                - use color to visualize points from different categories.\n                - use size to visualize data points with an additional quantitative dimension of the data points.\n            - (histogram) Histograms: x: Quantitative/Categorical, color: Categorical (optional for creating grouped histogram), \n                - best for: Distribution of a quantitative field\n                - use x values directly if x values are categorical, and transform the data into bins if the field values are quantitative.\n                - when color is specified, the histogram will be grouped automatically (items with the same x values will be grouped).\n            - (bar) Bar Charts: x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical/Quantitative (for stacked bar chart / showing additional quantitative dimension), \n                - best for: Comparisons across categories\n                - use (bar) for simple bar chart or stacked bar chart (when it makes sense to add up Y values for each category with the same X value), \n                    - when color is specified, the bar will be stacked automatically (items with the same x values will be stacked).\n                    - note that when there are multiple rows in the data with same x values, the bar will be stacked automatically.\n                        - 1. consider to use an aggregated field for y values if the value is not suitable for stacking.\n                        - 2. consider to introduce facets so that each group is visualized in a separate bar.\n            - (group_bar) for grouped bar chart, x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical\n                - when color is specifed, bars from different groups will be grouped automatically.\n                - only use facet if the cardinality of color field is small (less than 5).\n            - (line) Line Charts: x: Temporal (preferred) or ordinal, y: Quantitative, color: Categorical (optional for creating multiple lines), \n                - best for: Trends over time, continuous data, forecasting, regression analysis\n                - note that when there are multiple rows in the data belong to the same group (same x and color values) but different y values, the line will not look correct.\n                - consider to use an aggregated field for y values, or introduce facets so that each group is visualized in a separate line.\n            - (area) Area Charts: x: Temporal (preferred) or ordinal, y: Quantitative, color: Categorical (optional for creating stacked areas), \n                - best for: Trends over time, continuous data\n            - (heatmap) Heatmaps: x,y: Categorical (you need to convert quantitative to nominal), color: Quantitative intensity, \n                - best for: Pattern discovery in matrix data\n            - (boxplot) Box plots: x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical (optional for creating grouped boxplots), \n                - best for: Distribution of a quantitative field\n                - use x values directly if x values are categorical, and transform the data into bins if the field values are quantitative.\n                - when color is specified, the boxplot will be grouped automatically (items with the same x values will be grouped).\n        - facet channel is available for all chart types, it supports a categorical field with small cardinality to visualize the data in different facets.\n        - if you really need additional legend fields:\n            - you can use opacity for legend (support Quantitative and Categorical).\n    - visualization fields require tidy data. \n        - similar to VegaLite and ggplot2 so that each field is mapped to a visualization axis or legend. \n        - consider data transformations if you want to visualize multiple fields together:\n            - exapmle 1: suggest reshaping the data into long format in data transformation description (if these fields are all of the same type, e.g., they are all about sales, price, two columns about min/max-values, etc. don't mix different types of fields in reshaping) so we can visualize multiple fields as categories or in different facets.\n            - exapmle 2: calculate some derived fields from these fields(e.g., correlation, difference, profit etc.) in data transformation description to visualize them in one visualization.\n            - example 3: create a visualization only with a subset of the fields, you don't have to visualize all of them in one chart, you can later create a visualization with the rest of the fields. With the subset of charts, you can also consider reshaping or calculate some derived value.\n            - again, it does not make sense to have five fields like [item, A, B, C, D, E] in visualization fields, you should consider data transformation to reduce the number of fields.\n            - when reshaping data to long format, only fields of the same semantic type should be rehaped into the same column.\n    - guide on statistical analysis:\n        - when the user asks for forecasting or regression analysis, you should consider the following:\n            - the output should be a long format table where actual x, y pairs and predicted x, y pairs are included in the X, Y columns, they are differentiated with a third column \"is_predicted\" that is a boolean field.\n            - i.e., if the user ask for forecasting based on two columns T and Y, the output should be three columns: T, Y, is_predicted, where\n                - T, Y columns contain BOTH original values from the data and predicted values from the data.\n                - is_predicted is a boolean field to indicate whether the x, y pairs are original values from the data or predicted / regression values from the data.\n            - the recommended chart should be line chart (time series) or scatter plot (quantitative x, y)\n            - if the user asks for forecasting, it's good to include predicted x, y pairs for both x in the original data and future x values (i.e., combine regression and forecasting results)\n                - in this case, is_predicted should be of three values 'original', 'regression', 'forecasting'\n                - put is_predicted field in 'opacity' channel to distinguish them.\n        - when the user asks for clustering:\n            - the output should be a long format table where actual x, y pairs with a third column \"cluster_id\" that indicates the cluster id of the data point.\n            - the recommended chart should be scatter plot (quantitative x, y)\n            \n    2. Then, write a python function based on the inferred goal, the function input is a dataframe \"df\" (or multiple dataframes based on tables presented in the [CONTEXT] section) and the output is the transformed dataframe \"transformed_df\". \n\"transformed_df\" should contain all \"output_fields\" from the refined user intent in the json object.\nThe python function must follow the template provided in [TEMPLATE]. The function should be as simple as possible and easily readable. \nIf there is no data transformation needed based on \"output_fields\", the transformation function can simply \"return df\".\n\n[TEMPLATE]\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n# from sklearn import ... # import from sklearn if you need it.\n\ndef transform_data(df1, df2, ...): \n    # complete the template here\n    return transformed_df\n```\n\nnote: \n- decide the function signature based on the number of tables you decided in the previous step \"input_tables\":\n    - if you decide there will only be one input table, then function signature should be `def transform_data(df1)`\n    - if you decided there will be k input tables, then function signature should be `def transform_data(df_1, df_2, ..., df_k)`.\n    - instead of using generic names like df1, df2, ..., try to use intuitive table names for function arguments, for example, if you have input_tables: [\"City\", \"Weather\"]`, you can use `transform_data(df_city, df_weather)` to refer to the two dataframes.\n    - **VERY IMPORTANT** the number of arguments in the function signature must be the same as the number of tables provided in \"input_tables\", and the order of arguments must match the order of tables provided in \"input_tables\".\n- datetime objects handling:\n    - if the output field is year, convert it to number, if it is year-month / year-month-day, convert it to string object (e.g., \"2020-01\" / \"2020-01-01\").\n    - if the output is time only: convert hour to number if it's just the hour (e.g., 10), but convert hour:min or h:m:s to string object (e.g., \"10:30\", \"10:30:45\")\n    - never return datetime object directly, convert it to either number (if it only contains year) or string so it's readable.\n    \n    3. The output must only contain a json object representing inferred user intent and a python code block representing the transformation code, do not add any extra text explanation.\n"},{"role":"user","content":"[CONTEXT]\n\n## Table 1: history (738 rows × 8 columns)\n\n### Schema (8 fields)\n  - symbol -- type: object, values: AAPL, AMZN, GOOGL, META, MSFT, NVDA\n  - date -- type: object, values: 2025-07-30, 2025-07-31, 2025-08-01, ..., 2026-01-20, 2026-01-21, 2026-01-22, 2026-01-23\n  - open -- type: float64, values: 167.53, 168.01, 169.07, ..., 781.21, 782.98, 785.25, 789.97\n  - high -- type: float64, values: 169.01, 170.94, 170.96, ..., 789.62, 792.49, 794.28, 795.06\n  - low -- type: float64, values: 164.05, 166.72, 167.2, ..., 771.36, 772.21, 777.07, 779.66\n  - close -- type: float64, values: 167.0, 168.29, 170.28, ..., 779.09, 780.97, 784.06, 788.82\n  - volume -- type: int64, values: 5627500, 5855900, 6861200, ..., 320600300, 324925900, 343504800, 346926200\n  - fetched_at -- type: object, values: 2026-01-26T23:46:42.347312Z\n\n### Sample Data (first 5 rows)\n```\n  symbol        date    open    high     low   close     volume                   fetched_at\n0   AAPL  2025-07-30  211.45  211.94  207.28  208.61   45512500  2026-01-26T23:46:42.347312Z\n1   AAPL  2025-07-31  208.05  209.40  206.72  207.13   80698400  2026-01-26T23:46:42.347312Z\n2   AAPL  2025-08-01  210.43  213.13  201.08  201.95  104434500  2026-01-26T23:46:42.347312Z\n3   AAPL  2025-08-04  204.08  207.44  201.26  202.92   75109300  2026-01-26T23:46:42.347312Z\n4   AAPL  2025-08-05  202.97  204.91  201.74  202.49   44155100  2026-01-26T23:46:42.347312Z\n```\n\n\n[GOAL]\n\n1) First, plot the overall **closing price** trends for each **symbol** over **time** on a single line chart to compare their broad trajectories and volatility."},{"role":"assistant","content":"{\n  \"mode\": \"infer\",\n  \"recap\": \"Compare overall closing price trends and volatility over time for each stock symbol on a single line chart.\",\n  \"display_instruction\": \"Visualize **closing price** trends by **symbol** over **date**\",\n  \"recommendation\": \"A line chart with time on the x-axis and closing price on the y-axis, colored by symbol, best shows comparative trajectories and volatility over time. The data only needs column selection, date normalization, and sorting to be visualization-ready.\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"close\"],\n  \"chart_type\": \"line\",\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"close\",\n    \"color\": \"symbol\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"\"\n  }\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Select only needed columns\n    cols = [\"date\", \"symbol\", \"close\"]\n    df = df_history[cols].copy()\n\n    # Ensure date is a string in YYYY-MM-DD format (no datetime objects)\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper line plotting\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    transformed_df = df\n    return transformed_df\n```"},{"role":"user","content":"This is the result from the latest python code:\n\n         date symbol   close\n0  2025-07-30   AAPL  208.61\n1  2025-07-31   AAPL  207.13\n2  2025-08-01   AAPL  201.95\n3  2025-08-04   AAPL  202.92\n4  2025-08-05   AAPL  202.49\n5  2025-08-06   AAPL  212.80\n6  2025-08-07   AAPL  219.57\n7  2025-08-08   AAPL  228.87\n8  2025-08-11   AAPL  226.96\n9  2025-08-12   AAPL  229.43\n......\n\nUpdate the code above based on the following instruction:\n\n2) For each symbol, compute 20-day and 60-day rolling averages of close price (columns: date, symbol, value, ma_window with values 20 or 60) and plot them over time alongside the actual close to compare short- vs long-term trends and reversals."},{"role":"assistant","content":"{\n  \"mode\": \"infer\",\n  \"recap\": \"Compute 20-day and 60-day rolling averages of closing prices for each symbol in tidy format for plotting alongside actual closes over time.\",\n  \"display_instruction\": \"Add **20/60-day moving averages** of **close** by **symbol** over **date**\",\n  \"recommendation\": \"To compare short- and long-term trends per symbol, compute 20- and 60-day rolling means of close, reshape them into a long format with one row per date-symbol-window, and keep the original close for plotting alongside the moving averages.\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"],\n  \"chart_type\": \"line\",\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"value\",\n    \"color\": \"ma_window\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"symbol\"\n  }\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Work on a copy\n    df = df_history.copy()\n\n    # Normalize date to string YYYY-MM-DD\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper rolling computation\n    df = df.sort_values([\"symbol\", \"date\"])\n\n    # Group by symbol and compute rolling means on close\n    group = df.groupby(\"symbol\", group_keys=False)[\"close\"]\n    df[\"ma_20\"] = group.rolling(20, min_periods=1).mean()\n    df[\"ma_60\"] = group.rolling(60, min_periods=1).mean()\n\n    # Reshape to long format for the moving averages\n    df_long = df.melt(\n        id_vars=[\"date\", \"symbol\", \"close\"],\n        value_vars=[\"ma_20\", \"ma_60\"],\n        var_name=\"ma_window\",\n        value_name=\"value\",\n    )\n\n    # Map ma_window to numeric window size (20 or 60)\n    window_map = {\"ma_20\": 20, \"ma_60\": 60}\n    df_long[\"ma_window\"] = df_long[\"ma_window\"].map(window_map)\n\n    # Ensure correct column order and types\n    df_long[\"ma_window\"] = df_long[\"ma_window\"].astype(int)\n\n    transformed_df = df_long[[\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"]].reset_index(drop=True)\n    return transformed_df\n```"},{"role":"user","content":"This is the result from the latest python code:\n\nEmpty DataFrame\nColumns: []\nIndex: []\n......\n\nUpdate the code above based on the following instruction:\n\nWe run into the following problem executing the code, please fix it:\n\nError: TypeError - incompatible index of inserted column with frame index\n\nPlease think step by step, reflect why the error happens and fix the code so that no more errors would occur."},{"role":"assistant","content":"{\n  \"mode\": \"infer\",\n  \"recap\": \"Compute 20-day and 60-day rolling averages of closing prices for each symbol in tidy format for plotting alongside actual closes over time.\",\n  \"display_instruction\": \"Compute **20/60-day moving averages** of **close** by **symbol** over **date**\",\n  \"recommendation\": \"The previous implementation used groupby().rolling() and assigned the result directly to new columns, which can create an index mismatch and raise a TypeError. Using groupby().transform(...) with an inner rolling mean keeps the index aligned with the original DataFrame, avoiding incompatible index issues. After computing the moving averages, reshape to long format for visualization.\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"],\n  \"chart_type\": \"line\",\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"value\",\n    \"color\": \"ma_window\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"symbol\"\n  }\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Work on a copy and keep only needed columns if present\n    base_cols = [c for c in [\"date\", \"symbol\", \"close\"] if c in df_history.columns]\n    df = df_history[base_cols].copy()\n\n    # Normalize date to string YYYY-MM-DD\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper rolling computation\n    df = df.sort_values([\"symbol\", \"date\"])\n\n    # Ensure we have a clean, simple index to avoid alignment issues\n    df = df.reset_index(drop=True)\n\n    # Compute rolling means using transform to preserve index alignment\n    df[\"ma_20\"] = (\n        df.groupby(\"symbol\")[\"close\"]\n          .transform(lambda s: s.rolling(window=20, min_periods=1).mean())\n    )\n    df[\"ma_60\"] = (\n        df.groupby(\"symbol\")[\"close\"]\n          .transform(lambda s: s.rolling(window=60, min_periods=1).mean())\n    )\n\n    # Reshape to long format for the moving averages\n    df_long = df.melt(\n        id_vars=[\"date\", \"symbol\", \"close\"],\n        value_vars=[\"ma_20\", \"ma_60\"],\n        var_name=\"ma_window\",\n        value_name=\"value\",\n    )\n\n    # Map ma_window to numeric window size (20 or 60)\n    window_map = {\"ma_20\": 20, \"ma_60\": 60}\n    df_long[\"ma_window\"] = df_long[\"ma_window\"].map(window_map).astype(int)\n\n    # Final tidy output\n    transformed_df = df_long[[\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"]].reset_index(drop=True)\n    return transformed_df\n```"}],"trigger":{"tableId":"table-233476","sourceTableIds":["history"],"instruction":"2) For each symbol, compute 20-day and 60-day rolling averages of close price (columns: date, symbol, value, ma_window with values 20 or 60) and plot them over time alongside the actual close to compare short- vs long-term trends and reversals.","displayInstruction":"Compute **20/60-day moving averages** of **close** by **symbol** over **date**","chart":{"id":"chart-1769471261112","chartType":"Auto","encodingMap":{},"tableRef":"history","saved":false,"source":"trigger","unread":true},"resultTableId":"table-265247"},"explanation":{"status":"ok","concepts":[{"field":"ma_20, ma_60, value","explanation":"These fields represent a rolling (moving) average of the closing price over a fixed number of recent trading days for each stock symbol. For a window of N days (N = 20 or 60), the moving average on a given date is the average of the last N closing prices up to that date. Mathematically, if close_t is the closing price on day t, then the N-day moving average MA_N(t) is: MA_N(t) = (close_t + close_{t-1} + ... + close_{t-N+1}) / N. At the start of the series, when fewer than N days are available, the average is taken over all available past days instead."},{"field":"ma_window","explanation":"This field indicates the length of the moving-average window, in days. A value of 20 means the corresponding 'value' is a 20-day moving average; a value of 60 means it is a 60-day moving average."}],"code":"- Start from the original **history** table but keep only the **`date`**, **`symbol`**, and **`close`** fields to simplify the data.\n- Convert **`date`** into a standardized text format **`YYYY-MM-DD`** so all dates look consistent.\n- **Sort** the data by **`symbol`** and then by **`date`** to ensure the time series for each stock is in the correct order.\n- For each **`symbol`**, **compute**:\n  - **`ma_20`**: a **20-day moving average** of the **`close`** price (uses up to the last **20** days; for the first few days it uses all available past days).\n  - **`ma_60`**: a **60-day moving average** of the **`close`** price (uses up to the last **60** days; similarly relaxed at the start).\n- **Reshape** the data so that instead of having separate columns **`ma_20`** and **`ma_60`**, each row represents **one moving-average value**:\n  - Keep **`date`**, **`symbol`**, and **`close`**.\n  - Put the moving-average values into a single column **`value`**.\n  - Use a column **`ma_window`** to indicate whether **`value`** is for **20** days or **60** days.\n- **Map** the labels **`ma_20`** and **`ma_60`** into numeric values **20** and **60** in **`ma_window`**, and keep only:\n  - **`date`**, **`symbol`**, **`close`**, **`value`** (moving average), **`ma_window`** (window length in days).","dialog":[{"role":"system","content":"You are a data scientist to help user explain code, \nso that a non-code can clearly understand what the code is doing, you are provided with a summary of the input data, and the transformation code.\n\nYour goal:\n1. You should generate a good itemized explanation of the code so that the reader can understand high-level steps of what the data transformation is doing.\n    - Be very concise, and stay at a high-level. The reader doesn't understand code and does not want to learn exactly what the code is doing. They just want to learn what have been done from a logical level.\n    - The explanation should be a markdown string that is a list of bullet points (with new lines), highlight constants, data fields, and important verbs.\n2. Generate a list of explanations for new fields (fields not from the input data) that introduce metrics/concepts that are not obvious from the code.\n    - provide a declarative definition that explains the new field, use a mathematical notation if applicable.\n    - only include new fields explanation of new metrics that are involved in computation (e.g., ROI, commerical_success_score)\n    - *DO NOT* explain trivial new fields like \"Decade\" or \"Avg_Rating\", \"US_Sales\" that are self-explanatory.\n        - Avoid explaining fields that are simple aggregate of fields in the original data (min_score, avg_value, count, etc.)\n    - When a field involves mathematical computation, you can use LaTeX math notation in the explanation. Format mathematical expressions using:\n        - Inline math: `\\( ... \\)` for formulas within text\n        - Block math: `\\[ ... \\]` for standalone formulas\n        - Examples: `\\( \\frac{\\text{Revenue}}{\\text{Cost}} \\)` for ratios, `\\[ \\text{Score} = \\text{Rating} \\times \\text{Worldwide\\_Gross} \\]` for formulas\n        - note: when using underscores as part of the text, you need to escape them with a backslash, e.g., `\\_`\n    - Note: don't use math notation for fields whose computation is trivial (use plain english), it will likely be confusing to the reader. \n      Only use math notation for fields that can not be easilyexplained in plain english. Use it sparingly.\n3. If there are multiple fields that have the similar computation, you can explain them together in one explanation.\n    - in \"field\", you can provide a list of fields in format of \"field1, field2, ...\"\n    - in \"explanation\", you can provide a single explanation for the computation of the fields.\n    - for example, if you have fields like \"Norm_Rating\", \"Norm_Gross\", \"Critical_Commercial_Score\", you can explain Norm_Rating, Norm_Gross together in one explanation and explain Critical_Commercial_Score in another explanation.\n4. If the code is about statistical analysis, you should explain the statistical analysis in the explanation as a concept named \"Statistical Analysis\" in the [CONCEPTS EXPLANATION] section.\n    - explain how you model the data, which fields are used, how data processing is done, and what models are used.\n    - suggest some other modeling approaches that can be used to analyze the data in the explanation as well.\n    \nThe focus is to explain how new fields are computed, don't generate explanation for low-level actions like \"return\", \"load data\" etc. \n\nProvide the result in the following two sections:\n    - first section is the code explanation that should be a markdown block explaining the code, in the [CODE EXPLANATION] section.\n        - remember to highlight constants, data fields, and important verbs in the code explanation.\n    - second section is the concepts explanation that should be a json block (start with ```json) in the [CONCEPTS EXPLANATION] section.\n\n[CODE EXPLANATION]\n\n...(explanation of the code)\n\n[CONCEPTS EXPLANATION]\n\n```json\n[\n    {\n        \"field\": \"...\",\n        \"explanation\": \"...\"\n    }\n]\n\n```\n"},{"role":"user","content":"[CONTEXT]\n\n## Table 1: history (738 rows × 8 columns)\n\n### Schema (8 fields)\n  - symbol -- type: object, values: AAPL, AMZN, GOOGL, META, MSFT, NVDA\n  - date -- type: object, values: 2025-07-30, 2025-07-31, 2025-08-01, ..., 2026-01-20, 2026-01-21, 2026-01-22, 2026-01-23\n  - open -- type: float64, values: 167.53, 168.01, 169.07, ..., 781.21, 782.98, 785.25, 789.97\n  - high -- type: float64, values: 169.01, 170.94, 170.96, ..., 789.62, 792.49, 794.28, 795.06\n  - low -- type: float64, values: 164.05, 166.72, 167.2, ..., 771.36, 772.21, 777.07, 779.66\n  - close -- type: float64, values: 167.0, 168.29, 170.28, ..., 779.09, 780.97, 784.06, 788.82\n  - volume -- type: int64, values: 5627500, 5855900, 6861200, ..., 320600300, 324925900, 343504800, 346926200\n  - fetched_at -- type: object, values: 2026-01-26T23:46:42.347312Z\n\n### Sample Data (first 5 rows)\n```\n  symbol        date    open    high     low   close     volume                   fetched_at\n0   AAPL  2025-07-30  211.45  211.94  207.28  208.61   45512500  2026-01-26T23:46:42.347312Z\n1   AAPL  2025-07-31  208.05  209.40  206.72  207.13   80698400  2026-01-26T23:46:42.347312Z\n2   AAPL  2025-08-01  210.43  213.13  201.08  201.95  104434500  2026-01-26T23:46:42.347312Z\n3   AAPL  2025-08-04  204.08  207.44  201.26  202.92   75109300  2026-01-26T23:46:42.347312Z\n4   AAPL  2025-08-05  202.97  204.91  201.74  202.49   44155100  2026-01-26T23:46:42.347312Z\n```\n\n\n[CODE]\n\nhere is the transformation code: \nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Work on a copy and keep only needed columns if present\n    base_cols = [c for c in [\"date\", \"symbol\", \"close\"] if c in df_history.columns]\n    df = df_history[base_cols].copy()\n\n    # Normalize date to string YYYY-MM-DD\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper rolling computation\n    df = df.sort_values([\"symbol\", \"date\"])\n\n    # Ensure we have a clean, simple index to avoid alignment issues\n    df = df.reset_index(drop=True)\n\n    # Compute rolling means using transform to preserve index alignment\n    df[\"ma_20\"] = (\n        df.groupby(\"symbol\")[\"close\"]\n          .transform(lambda s: s.rolling(window=20, min_periods=1).mean())\n    )\n    df[\"ma_60\"] = (\n        df.groupby(\"symbol\")[\"close\"]\n          .transform(lambda s: s.rolling(window=60, min_periods=1).mean())\n    )\n\n    # Reshape to long format for the moving averages\n    df_long = df.melt(\n        id_vars=[\"date\", \"symbol\", \"close\"],\n        value_vars=[\"ma_20\", \"ma_60\"],\n        var_name=\"ma_window\",\n        value_name=\"value\",\n    )\n\n    # Map ma_window to numeric window size (20 or 60)\n    window_map = {\"ma_20\": 20, \"ma_60\": 60}\n    df_long[\"ma_window\"] = df_long[\"ma_window\"].map(window_map).astype(int)\n\n    # Final tidy output\n    transformed_df = df_long[[\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"]].reset_index(drop=True)\n    return transformed_df\n\n\n[EXPLANATION]\n"},{"role":"assistant","content":"[CODE EXPLANATION]\n\n- Start from the original **history** table but keep only the **`date`**, **`symbol`**, and **`close`** fields to simplify the data.\n- Convert **`date`** into a standardized text format **`YYYY-MM-DD`** so all dates look consistent.\n- **Sort** the data by **`symbol`** and then by **`date`** to ensure the time series for each stock is in the correct order.\n- For each **`symbol`**, **compute**:\n  - **`ma_20`**: a **20-day moving average** of the **`close`** price (uses up to the last **20** days; for the first few days it uses all available past days).\n  - **`ma_60`**: a **60-day moving average** of the **`close`** price (uses up to the last **60** days; similarly relaxed at the start).\n- **Reshape** the data so that instead of having separate columns **`ma_20`** and **`ma_60`**, each row represents **one moving-average value**:\n  - Keep **`date`**, **`symbol`**, and **`close`**.\n  - Put the moving-average values into a single column **`value`**.\n  - Use a column **`ma_window`** to indicate whether **`value`** is for **20** days or **60** days.\n- **Map** the labels **`ma_20`** and **`ma_60`** into numeric values **20** and **60** in **`ma_window`**, and keep only:\n  - **`date`**, **`symbol`**, **`close`**, **`value`** (moving average), **`ma_window`** (window length in days).\n\n\n[CONCEPTS EXPLANATION]\n\n```json\n[\n  {\n    \"field\": \"ma_20, ma_60, value\",\n    \"explanation\": \"These fields represent a rolling (moving) average of the closing price over a fixed number of recent trading days for each stock symbol. For a window of N days (N = 20 or 60), the moving average on a given date is the average of the last N closing prices up to that date. Mathematically, if close_t is the closing price on day t, then the N-day moving average MA_N(t) is: MA_N(t) = (close_t + close_{t-1} + ... + close_{t-N+1}) / N. At the start of the series, when fewer than N days are available, the average is taken over all available past days instead.\"\n  },\n  {\n    \"field\": \"ma_window\",\n    \"explanation\": \"This field indicates the length of the moving-average window, in days. A value of 20 means the corresponding 'value' is a 20-day moving average; a value of 60 means it is a 60-day moving average.\"\n  }\n]\n```"}],"agent":"CodeExplanationAgent"}},"anchored":false,"createdBy":"user","attachedMetadata":""},{"id":"table-277926","displayId":"stock-metr","names":["date","symbol","metric","value"],"rows":[{"date":"2025-07-30","symbol":"AAPL","metric":"return","value":null},{"date":"2025-07-31","symbol":"AAPL","metric":"return","value":-0.0070945784},{"date":"2025-08-01","symbol":"AAPL","metric":"return","value":-0.0250084488},{"date":"2025-08-04","symbol":"AAPL","metric":"return","value":0.0048031691},{"date":"2025-08-05","symbol":"AAPL","metric":"return","value":-0.0021190617},{"date":"2025-08-06","symbol":"AAPL","metric":"return","value":0.0509160946},{"date":"2025-08-07","symbol":"AAPL","metric":"return","value":0.0318139098},{"date":"2025-08-08","symbol":"AAPL","metric":"return","value":0.042355513},{"date":"2025-08-11","symbol":"AAPL","metric":"return","value":-0.0083453489},{"date":"2025-08-12","symbol":"AAPL","metric":"return","value":0.010882975},{"date":"2025-08-13","symbol":"AAPL","metric":"return","value":0.0159961644},{"date":"2025-08-14","symbol":"AAPL","metric":"return","value":-0.0023595024},{"date":"2025-08-15","symbol":"AAPL","metric":"return","value":-0.0050741776},{"date":"2025-08-18","symbol":"AAPL","metric":"return","value":-0.0030254571},{"date":"2025-08-19","symbol":"AAPL","metric":"return","value":-0.0014306152},{"date":"2025-08-20","symbol":"AAPL","metric":"return","value":-0.019753408},{"date":"2025-08-21","symbol":"AAPL","metric":"return","value":-0.0049160725},{"date":"2025-08-22","symbol":"AAPL","metric":"return","value":0.0127292149},{"date":"2025-08-25","symbol":"AAPL","metric":"return","value":-0.002636899},{"date":"2025-08-26","symbol":"AAPL","metric":"return","value":0.0094738697},{"date":"2025-08-27","symbol":"AAPL","metric":"return","value":0.0051508141},{"date":"2025-08-28","symbol":"AAPL","metric":"return","value":0.0089460199},{"date":"2025-08-29","symbol":"AAPL","metric":"return","value":-0.0017647312},{"date":"2025-09-02","symbol":"AAPL","metric":"return","value":-0.0104346326},{"date":"2025-09-03","symbol":"AAPL","metric":"return","value":0.0380827887},{"date":"2025-09-04","symbol":"AAPL","metric":"return","value":0.0054986568},{"date":"2025-09-05","symbol":"AAPL","metric":"return","value":-0.0003757044},{"date":"2025-09-08","symbol":"AAPL","metric":"return","value":-0.0075586737},{"date":"2025-09-09","symbol":"AAPL","metric":"return","value":-0.0148537766},{"date":"2025-09-10","symbol":"AAPL","metric":"return","value":-0.0322484196},{"date":"2025-09-11","symbol":"AAPL","metric":"return","value":0.0143002163},{"date":"2025-09-12","symbol":"AAPL","metric":"return","value":0.0175362256},{"date":"2025-09-15","symbol":"AAPL","metric":"return","value":0.0112470065},{"date":"2025-09-16","symbol":"AAPL","metric":"return","value":0.006131856},{"date":"2025-09-17","symbol":"AAPL","metric":"return","value":0.0035305985},{"date":"2025-09-18","symbol":"AAPL","metric":"return","value":-0.0046490199},{"date":"2025-09-19","symbol":"AAPL","metric":"return","value":0.0320218809},{"date":"2025-09-22","symbol":"AAPL","metric":"return","value":0.0430971214},{"date":"2025-09-23","symbol":"AAPL","metric":"return","value":-0.0064495954},{"date":"2025-09-24","symbol":"AAPL","metric":"return","value":-0.0083012039},{"date":"2025-09-25","symbol":"AAPL","metric":"return","value":0.0180505415},{"date":"2025-09-26","symbol":"AAPL","metric":"return","value":-0.0054945055},{"date":"2025-09-29","symbol":"AAPL","metric":"return","value":-0.004035892},{"date":"2025-09-30","symbol":"AAPL","metric":"return","value":0.000786844},{"date":"2025-10-01","symbol":"AAPL","metric":"return","value":0.0032235239},{"date":"2025-10-02","symbol":"AAPL","metric":"return","value":0.0065830721},{"date":"2025-10-03","symbol":"AAPL","metric":"return","value":0.0034646528},{"date":"2025-10-06","symbol":"AAPL","metric":"return","value":-0.0051596384},{"date":"2025-10-07","symbol":"AAPL","metric":"return","value":-0.000818905},{"date":"2025-10-08","symbol":"AAPL","metric":"return","value":0.0061663349},{"date":"2025-10-09","symbol":"AAPL","metric":"return","value":-0.0155928785},{"date":"2025-10-10","symbol":"AAPL","metric":"return","value":-0.0345167264},{"date":"2025-10-13","symbol":"AAPL","metric":"return","value":0.0097539077},{"date":"2025-10-14","symbol":"AAPL","metric":"return","value":0.0004445881},{"date":"2025-10-15","symbol":"AAPL","metric":"return","value":0.0063426655},{"date":"2025-10-16","symbol":"AAPL","metric":"return","value":-0.0075873143},{"date":"2025-10-17","symbol":"AAPL","metric":"return","value":0.019578496},{"date":"2025-10-20","symbol":"AAPL","metric":"return","value":0.0394366197},{"date":"2025-10-21","symbol":"AAPL","metric":"return","value":0.002022978},{"date":"2025-10-22","symbol":"AAPL","metric":"return","value":-0.0164558891},{"date":"2025-10-23","symbol":"AAPL","metric":"return","value":0.0043764524},{"date":"2025-10-24","symbol":"AAPL","metric":"return","value":0.0124937339},{"date":"2025-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pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Keep only necessary columns\n    cols = [c for c in [\"date\", \"symbol\", \"close\", \"volume\"] if c in df_history.columns]\n    df = df_history[cols].copy()\n\n    # Normalize date to string YYYY-MM-DD\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for time-series operations\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    # Compute daily returns as pct_change of close within each symbol\n    df[\"return\"] = df.groupby(\"symbol\")[\"close\"].pct_change()\n\n    # Compute 20-day rolling volatility (std of returns) within each symbol\n    df[\"vol20\"] = (\n        df.groupby(\"symbol\")[\"return\"]\n          .transform(lambda s: s.rolling(window=20, min_periods=1).std())\n    )\n\n    # Reshape to long format: metrics = return, vol20, volume\n    df_long = df.melt(\n        id_vars=[\"date\", \"symbol\"],\n        value_vars=[\"return\", \"vol20\", \"volume\"],\n        var_name=\"metric\",\n        value_name=\"value\",\n    )\n\n    # Final tidy output\n    transformed_df = df_long[[\"date\", \"symbol\", \"metric\", \"value\"]].reset_index(drop=True)\n    return transformed_df\n","source":["history"],"dialog":[{"role":"system","content":"You are a data scientist to help user to recommend data that will be used for visualization.\nThe user will provide you information about what visualization they would like to create, and your job is to recommend a transformed data that can be used to create the visualization and write a python function to transform the data.\nThe recommendation and transformation function should be based on the [CONTEXT] and [GOAL] provided by the user. \nThe [CONTEXT] shows what the current dataset is, and the [GOAL] describes what the user wants the data for.\n\n**Important:**\n- NEVER make assumptions or judgments about a person's gender, biological sex, sexuality, religion, race, nationality, ethnicity, political stance, socioeconomic status, mental health, invisible disabilities, medical conditions, personality type, social impressions, emotional state, and cognitive state.\n- NEVER create formulas that could be used to discriminate based on age. Ageism of any form (explicit and implicit) is strictly prohibited.\n- If above issue occurs, generate columns with np.nan.\n\nConcretely, you should infer the appropriate data and create in the output section a python function based off the [CONTEXT] and [GOAL] in two steps:\n\n1. First, based on users' [GOAL]. Create a json object that represents the inferred user intent. The json object should have the following format:\n\n{\n    \"mode\": \"\" // string, one of \"infer\", \"overview\", \"distribution\", \"summary\", \"forecast\"\n    \"recap\": \"...\" // string, a short summary of the user's goal.\n    \"display_instruction\": \"...\" // string, the even shorter verb phrase describing the users' goal.\n    \"recommendation\": \"...\" // string, explain why this recommendation is made\n    \"input_tables\": [...] // string[], describe names of the input tables that will be used in the transformation.\n    \"output_fields\": [...] // string[], describe the desired output fields that the output data should have (i.e., the goal of transformed data), it's a good idea to preseve intermediate fields here\n    \"chart_type\": \"\" // string, one of \"point\", \"bar\", \"line\", \"area\", \"heatmap\", \"group_bar\", 'boxplot'. \"chart_type\" should either be inferred from user instruction, or recommend if the user didn't specify any.\n    \"chart_encodings\": {\n        \"x\": \"\",\n        \"y\": \"\",\n        \"color\": \"\",\n        \"size\": \"\",\n        \"opacity\": \"\",\n        \"facet\": \"\",\n    } // object: map visualization channels (x, y, color, size, opacity, facet, etc.) to a subset of output fields, appropriate visual channels for different chart types are defined below.\n}\n\nConcretely:\n    - recap what the user's goal is in a short summary in \"recap\".\n    - If the user's [GOAL] is clear already, simply infer what the user mean. Set \"mode\" as \"infer\" and create \"output_fields\" and \"chart_encodings\" based off user description.\n    - If the user's [GOAL] is not clear, make recommendations to the user:\n        - choose one of \"distribution\", \"overview\", \"summary\", \"forecast\" in \"mode\":\n            * if it is \"overview\" and the data is in wide format, reshape it into long format.\n            * if it is \"distribution\", select a few fields that would be interesting to visualize together.\n            * if it is \"summary\", calculate some aggregated statistics to show intresting facts of the data.\n            * if it is \"forecast\", concretize the x,y fields that will be used for forecasting and decide if it is about regression or forecasting.\n        - describe the recommendation reason in \"recommendation\"\n        - based on the recommendation, determine what is an ideal output data. Note, the output data must be in tidy format.\n        - then suggest recommendations of chart encoding that should be used to create the visualization.\n    - \"display_instruction\" should be a short verb phrase describing the users' goal, it should be even shorter than \"recap\". \n        - it would be a short verbal description of user intent as a verb phrase (<12 words).\n        - generate based on \"recap\" and the suggested visualization, but don't need to mention the visualization details.\n        - should capture key computation ideas: by reading the display, the user can understand the purpose and what's derived from the data.\n        - if the user instruction builds up the previous instruction, the 'display_instruction' should only describe how it builds up the previous instruction without repeating information from previous steps.\n        - the phrase can be presented in different styles, e.g., question (what's xxx), instruction (show xxx), description, etc.\n        - if you mention column names from the input or the output data, highlight the text in **bold**.\n            * the column can either be a column in the input data, or a new column that will be computed in the output data.\n            * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned \"average score\" in the text while the column to be computed is \"Avg_Score\", you should still highlight \"**average score**\" in the text.\n    - determine \"input_tables\", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.\n        - **IMPORTANT** Note that the Table 1 in [CONTEXT] section is the table the user is currently viewing, it should take precedence if the user refers to insights about the \"current table\".\n        - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.\n    - \"chart_type\" must be one of \"point\", \"bar\", \"line\", \"area\", \"heatmap\", \"group_bar\", \"boxplot\"\n    - \"chart_encodings\" should specify which fields should be used to create the visualization\n        - decide which visual channels should be used to create the visualization appropriate for the chart type.\n            - point: x, y, color, size, facet\n            - histogram: x, color, facet\n            - bar: x, y, color, facet\n            - line: x, y, color, facet\n            - area: x, y, color, facet\n            - heatmap: x, y, color, facet\n            - group_bar: x, y, color, facet\n            - boxplot: x, y, color, facet\n        - note that all fields used in \"chart_encodings\" should be included in \"output_fields\".\n            - all fields you need for visualizations should be transformed into the output fields!\n            - \"output_fields\" should include important intermediate fields that are not used in visualization but are used for data transformation.\n        - typically only 2-3 fields should be used to create the visualization (x, y, color/size), facet use be added if it's a faceted visualization (totally 4 fields used).\n    - Guidelines for choosing chart type and visualization fields:\n        - Consider chart types as follows:\n            - (point) Scatter Plots: x,y: Quantitative/Categorical, color: Categorical (optional), size: Quantitative (optional for creating bubble chart), \n                - best for: Relationships, correlations, distributions, forecasting, regression analysis\n                - scatter plots are good default way to visualize data when other chart types are not applicable.\n                - use color to visualize points from different categories.\n                - use size to visualize data points with an additional quantitative dimension of the data points.\n            - (histogram) Histograms: x: Quantitative/Categorical, color: Categorical (optional for creating grouped histogram), \n                - best for: Distribution of a quantitative field\n                - use x values directly if x values are categorical, and transform the data into bins if the field values are quantitative.\n                - when color is specified, the histogram will be grouped automatically (items with the same x values will be grouped).\n            - (bar) Bar Charts: x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical/Quantitative (for stacked bar chart / showing additional quantitative dimension), \n                - best for: Comparisons across categories\n                - use (bar) for simple bar chart or stacked bar chart (when it makes sense to add up Y values for each category with the same X value), \n                    - when color is specified, the bar will be stacked automatically (items with the same x values will be stacked).\n                    - note that when there are multiple rows in the data with same x values, the bar will be stacked automatically.\n                        - 1. consider to use an aggregated field for y values if the value is not suitable for stacking.\n                        - 2. consider to introduce facets so that each group is visualized in a separate bar.\n            - (group_bar) for grouped bar chart, x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical\n                - when color is specifed, bars from different groups will be grouped automatically.\n                - only use facet if the cardinality of color field is small (less than 5).\n            - (line) Line Charts: x: Temporal (preferred) or ordinal, y: Quantitative, color: Categorical (optional for creating multiple lines), \n                - best for: Trends over time, continuous data, forecasting, regression analysis\n                - note that when there are multiple rows in the data belong to the same group (same x and color values) but different y values, the line will not look correct.\n                - consider to use an aggregated field for y values, or introduce facets so that each group is visualized in a separate line.\n            - (area) Area Charts: x: Temporal (preferred) or ordinal, y: Quantitative, color: Categorical (optional for creating stacked areas), \n                - best for: Trends over time, continuous data\n            - (heatmap) Heatmaps: x,y: Categorical (you need to convert quantitative to nominal), color: Quantitative intensity, \n                - best for: Pattern discovery in matrix data\n            - (boxplot) Box plots: x: Categorical (nominal/ordinal), y: Quantitative, color: Categorical (optional for creating grouped boxplots), \n                - best for: Distribution of a quantitative field\n                - use x values directly if x values are categorical, and transform the data into bins if the field values are quantitative.\n                - when color is specified, the boxplot will be grouped automatically (items with the same x values will be grouped).\n        - facet channel is available for all chart types, it supports a categorical field with small cardinality to visualize the data in different facets.\n        - if you really need additional legend fields:\n            - you can use opacity for legend (support Quantitative and Categorical).\n    - visualization fields require tidy data. \n        - similar to VegaLite and ggplot2 so that each field is mapped to a visualization axis or legend. \n        - consider data transformations if you want to visualize multiple fields together:\n            - exapmle 1: suggest reshaping the data into long format in data transformation description (if these fields are all of the same type, e.g., they are all about sales, price, two columns about min/max-values, etc. don't mix different types of fields in reshaping) so we can visualize multiple fields as categories or in different facets.\n            - exapmle 2: calculate some derived fields from these fields(e.g., correlation, difference, profit etc.) in data transformation description to visualize them in one visualization.\n            - example 3: create a visualization only with a subset of the fields, you don't have to visualize all of them in one chart, you can later create a visualization with the rest of the fields. With the subset of charts, you can also consider reshaping or calculate some derived value.\n            - again, it does not make sense to have five fields like [item, A, B, C, D, E] in visualization fields, you should consider data transformation to reduce the number of fields.\n            - when reshaping data to long format, only fields of the same semantic type should be rehaped into the same column.\n    - guide on statistical analysis:\n        - when the user asks for forecasting or regression analysis, you should consider the following:\n            - the output should be a long format table where actual x, y pairs and predicted x, y pairs are included in the X, Y columns, they are differentiated with a third column \"is_predicted\" that is a boolean field.\n            - i.e., if the user ask for forecasting based on two columns T and Y, the output should be three columns: T, Y, is_predicted, where\n                - T, Y columns contain BOTH original values from the data and predicted values from the data.\n                - is_predicted is a boolean field to indicate whether the x, y pairs are original values from the data or predicted / regression values from the data.\n            - the recommended chart should be line chart (time series) or scatter plot (quantitative x, y)\n            - if the user asks for forecasting, it's good to include predicted x, y pairs for both x in the original data and future x values (i.e., combine regression and forecasting results)\n                - in this case, is_predicted should be of three values 'original', 'regression', 'forecasting'\n                - put is_predicted field in 'opacity' channel to distinguish them.\n        - when the user asks for clustering:\n            - the output should be a long format table where actual x, y pairs with a third column \"cluster_id\" that indicates the cluster id of the data point.\n            - the recommended chart should be scatter plot (quantitative x, y)\n            \n    2. Then, write a python function based on the inferred goal, the function input is a dataframe \"df\" (or multiple dataframes based on tables presented in the [CONTEXT] section) and the output is the transformed dataframe \"transformed_df\". \n\"transformed_df\" should contain all \"output_fields\" from the refined user intent in the json object.\nThe python function must follow the template provided in [TEMPLATE]. The function should be as simple as possible and easily readable. \nIf there is no data transformation needed based on \"output_fields\", the transformation function can simply \"return df\".\n\n[TEMPLATE]\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n# from sklearn import ... # import from sklearn if you need it.\n\ndef transform_data(df1, df2, ...): \n    # complete the template here\n    return transformed_df\n```\n\nnote: \n- decide the function signature based on the number of tables you decided in the previous step \"input_tables\":\n    - if you decide there will only be one input table, then function signature should be `def transform_data(df1)`\n    - if you decided there will be k input tables, then function signature should be `def transform_data(df_1, df_2, ..., df_k)`.\n    - instead of using generic names like df1, df2, ..., try to use intuitive table names for function arguments, for example, if you have input_tables: [\"City\", \"Weather\"]`, you can use `transform_data(df_city, df_weather)` to refer to the two dataframes.\n    - **VERY IMPORTANT** the number of arguments in the function signature must be the same as the number of tables provided in \"input_tables\", and the order of arguments must match the order of tables provided in \"input_tables\".\n- datetime objects handling:\n    - if the output field is year, convert it to number, if it is year-month / year-month-day, convert it to string object (e.g., \"2020-01\" / \"2020-01-01\").\n    - if the output is time only: convert hour to number if it's just the hour (e.g., 10), but convert hour:min or h:m:s to string object (e.g., \"10:30\", \"10:30:45\")\n    - never return datetime object directly, convert it to either number (if it only contains year) or string so it's readable.\n    \n    3. The output must only contain a json object representing inferred user intent and a python code block representing the transformation code, do not add any extra text explanation.\n"},{"role":"user","content":"[CONTEXT]\n\n## Table 1: history (738 rows × 8 columns)\n\n### Schema (8 fields)\n  - symbol -- type: object, values: AAPL, AMZN, GOOGL, META, MSFT, NVDA\n  - date -- type: object, values: 2025-07-30, 2025-07-31, 2025-08-01, ..., 2026-01-20, 2026-01-21, 2026-01-22, 2026-01-23\n  - open -- type: float64, values: 167.53, 168.01, 169.07, ..., 781.21, 782.98, 785.25, 789.97\n  - high -- type: float64, values: 169.01, 170.94, 170.96, ..., 789.62, 792.49, 794.28, 795.06\n  - low -- type: float64, values: 164.05, 166.72, 167.2, ..., 771.36, 772.21, 777.07, 779.66\n  - close -- type: float64, values: 167.0, 168.29, 170.28, ..., 779.09, 780.97, 784.06, 788.82\n  - volume -- type: int64, values: 5627500, 5855900, 6861200, ..., 320600300, 324925900, 343504800, 346926200\n  - fetched_at -- type: object, values: 2026-01-26T23:46:42.347312Z\n\n### Sample Data (first 5 rows)\n```\n  symbol        date    open    high     low   close     volume                   fetched_at\n0   AAPL  2025-07-30  211.45  211.94  207.28  208.61   45512500  2026-01-26T23:46:42.347312Z\n1   AAPL  2025-07-31  208.05  209.40  206.72  207.13   80698400  2026-01-26T23:46:42.347312Z\n2   AAPL  2025-08-01  210.43  213.13  201.08  201.95  104434500  2026-01-26T23:46:42.347312Z\n3   AAPL  2025-08-04  204.08  207.44  201.26  202.92   75109300  2026-01-26T23:46:42.347312Z\n4   AAPL  2025-08-05  202.97  204.91  201.74  202.49   44155100  2026-01-26T23:46:42.347312Z\n```\n\n\n[GOAL]\n\n1) First, plot the overall **closing price** trends for each **symbol** over **time** on a single line chart to compare their broad trajectories and volatility."},{"role":"assistant","content":"{\n  \"mode\": \"infer\",\n  \"recap\": \"Compare overall closing price trends and volatility over time for each stock symbol on a single line chart.\",\n  \"display_instruction\": \"Visualize **closing price** trends by **symbol** over **date**\",\n  \"recommendation\": \"A line chart with time on the x-axis and closing price on the y-axis, colored by symbol, best shows comparative trajectories and volatility over time. The data only needs column selection, date normalization, and sorting to be visualization-ready.\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"close\"],\n  \"chart_type\": \"line\",\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"close\",\n    \"color\": \"symbol\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"\"\n  }\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Select only needed columns\n    cols = [\"date\", \"symbol\", \"close\"]\n    df = df_history[cols].copy()\n\n    # Ensure date is a string in YYYY-MM-DD format (no datetime objects)\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper line plotting\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    transformed_df = df\n    return transformed_df\n```"},{"role":"user","content":"This is the result from the latest python code:\n\n         date symbol   close\n0  2025-07-30   AAPL  208.61\n1  2025-07-31   AAPL  207.13\n2  2025-08-01   AAPL  201.95\n3  2025-08-04   AAPL  202.92\n4  2025-08-05   AAPL  202.49\n5  2025-08-06   AAPL  212.80\n6  2025-08-07   AAPL  219.57\n7  2025-08-08   AAPL  228.87\n8  2025-08-11   AAPL  226.96\n9  2025-08-12   AAPL  229.43\n......\n\nUpdate the code above based on the following instruction:\n\n2) For each symbol, compute 20-day and 60-day rolling averages of close price (columns: date, symbol, value, ma_window with values 20 or 60) and plot them over time alongside the actual close to compare short- vs long-term trends and reversals."},{"role":"assistant","content":"{\n  \"mode\": \"infer\",\n  \"recap\": \"Compute 20-day and 60-day rolling averages of closing prices for each symbol in tidy format for plotting alongside actual closes over time.\",\n  \"display_instruction\": \"Add **20/60-day moving averages** of **close** by **symbol** over **date**\",\n  \"recommendation\": \"To compare short- and long-term trends per symbol, compute 20- and 60-day rolling means of close, reshape them into a long format with one row per date-symbol-window, and keep the original close for plotting alongside the moving averages.\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"],\n  \"chart_type\": \"line\",\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"value\",\n    \"color\": \"ma_window\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"symbol\"\n  }\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Work on a copy\n    df = df_history.copy()\n\n    # Normalize date to string YYYY-MM-DD\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper rolling computation\n    df = df.sort_values([\"symbol\", \"date\"])\n\n    # Group by symbol and compute rolling means on close\n    group = df.groupby(\"symbol\", group_keys=False)[\"close\"]\n    df[\"ma_20\"] = group.rolling(20, min_periods=1).mean()\n    df[\"ma_60\"] = group.rolling(60, min_periods=1).mean()\n\n    # Reshape to long format for the moving averages\n    df_long = df.melt(\n        id_vars=[\"date\", \"symbol\", \"close\"],\n        value_vars=[\"ma_20\", \"ma_60\"],\n        var_name=\"ma_window\",\n        value_name=\"value\",\n    )\n\n    # Map ma_window to numeric window size (20 or 60)\n    window_map = {\"ma_20\": 20, \"ma_60\": 60}\n    df_long[\"ma_window\"] = df_long[\"ma_window\"].map(window_map)\n\n    # Ensure correct column order and types\n    df_long[\"ma_window\"] = df_long[\"ma_window\"].astype(int)\n\n    transformed_df = df_long[[\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"]].reset_index(drop=True)\n    return transformed_df\n```"},{"role":"user","content":"This is the result from the latest python code:\n\nEmpty DataFrame\nColumns: []\nIndex: []\n......\n\nUpdate the code above based on the following instruction:\n\nWe run into the following problem executing the code, please fix it:\n\nError: TypeError - incompatible index of inserted column with frame index\n\nPlease think step by step, reflect why the error happens and fix the code so that no more errors would occur."},{"role":"assistant","content":"{\n  \"mode\": \"infer\",\n  \"recap\": \"Compute 20-day and 60-day rolling averages of closing prices for each symbol in tidy format for plotting alongside actual closes over time.\",\n  \"display_instruction\": \"Compute **20/60-day moving averages** of **close** by **symbol** over **date**\",\n  \"recommendation\": \"The previous implementation used groupby().rolling() and assigned the result directly to new columns, which can create an index mismatch and raise a TypeError. Using groupby().transform(...) with an inner rolling mean keeps the index aligned with the original DataFrame, avoiding incompatible index issues. After computing the moving averages, reshape to long format for visualization.\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"],\n  \"chart_type\": \"line\",\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"value\",\n    \"color\": \"ma_window\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"symbol\"\n  }\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Work on a copy and keep only needed columns if present\n    base_cols = [c for c in [\"date\", \"symbol\", \"close\"] if c in df_history.columns]\n    df = df_history[base_cols].copy()\n\n    # Normalize date to string YYYY-MM-DD\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper rolling computation\n    df = df.sort_values([\"symbol\", \"date\"])\n\n    # Ensure we have a clean, simple index to avoid alignment issues\n    df = df.reset_index(drop=True)\n\n    # Compute rolling means using transform to preserve index alignment\n    df[\"ma_20\"] = (\n        df.groupby(\"symbol\")[\"close\"]\n          .transform(lambda s: s.rolling(window=20, min_periods=1).mean())\n    )\n    df[\"ma_60\"] = (\n        df.groupby(\"symbol\")[\"close\"]\n          .transform(lambda s: s.rolling(window=60, min_periods=1).mean())\n    )\n\n    # Reshape to long format for the moving averages\n    df_long = df.melt(\n        id_vars=[\"date\", \"symbol\", \"close\"],\n        value_vars=[\"ma_20\", \"ma_60\"],\n        var_name=\"ma_window\",\n        value_name=\"value\",\n    )\n\n    # Map ma_window to numeric window size (20 or 60)\n    window_map = {\"ma_20\": 20, \"ma_60\": 60}\n    df_long[\"ma_window\"] = df_long[\"ma_window\"].map(window_map).astype(int)\n\n    # Final tidy output\n    transformed_df = df_long[[\"date\", \"symbol\", \"close\", \"value\", \"ma_window\"]].reset_index(drop=True)\n    return transformed_df\n```"},{"role":"user","content":"This is the result from the latest python code:\n\n         date symbol   close       value  ma_window\n0  2025-07-30   AAPL  208.61  208.610000         20\n1  2025-07-31   AAPL  207.13  207.870000         20\n2  2025-08-01   AAPL  201.95  205.896667         20\n3  2025-08-04   AAPL  202.92  205.152500         20\n4  2025-08-05   AAPL  202.49  204.620000         20\n5  2025-08-06   AAPL  212.80  205.983333         20\n6  2025-08-07   AAPL  219.57  207.924286         20\n7  2025-08-08   AAPL  228.87  210.542500         20\n8  2025-08-11   AAPL  226.96  212.366667         20\n9  2025-08-12   AAPL  229.43  214.073000         20\n......\n\nUpdate the code above based on the following instruction:\n\n3) For each symbol, compute daily returns as pct_change of close, then 20-day rolling volatility as the rolling std of these returns; keep volume. Reshape to long format with columns [date, symbol, metric, value], where metric ∈ {\"return\", \"vol20\", \"volume\"}, and visualize over time (e.g., faceted by symbol with separate lines for each metric) to highlight periods of strong trends with elevated volatility or volume."},{"role":"assistant","content":"{\n  \"mode\": \"infer\",\n  \"recap\": \"Compute daily returns and 20-day rolling volatility for each symbol, keep volume, and reshape to a long format for multi-metric time-series visualization.\",\n  \"display_instruction\": \"Show **daily return**, **20-day volatility**, and **volume** by **symbol** over **date**\",\n  \"recommendation\": \"To highlight periods of strong trends with elevated volatility or volume, compute per-symbol daily returns as pct_change of close and 20-day rolling volatility as the rolling standard deviation of those returns. Keep volume, then reshape into a long table with one metric per row so time-series lines for return, volatility, and volume can be plotted and compared per symbol.\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"metric\", \"value\"],\n  \"chart_type\": \"line\",\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"value\",\n    \"color\": \"metric\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"symbol\"\n  }\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Keep only necessary columns\n    cols = [c for c in [\"date\", \"symbol\", \"close\", \"volume\"] if c in df_history.columns]\n    df = df_history[cols].copy()\n\n    # Normalize date to string YYYY-MM-DD\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for time-series operations\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    # Compute daily returns as pct_change of close within each symbol\n    df[\"return\"] = df.groupby(\"symbol\")[\"close\"].pct_change()\n\n    # Compute 20-day rolling volatility (std of returns) within each symbol\n    df[\"vol20\"] = (\n        df.groupby(\"symbol\")[\"return\"]\n          .transform(lambda s: s.rolling(window=20, min_periods=1).std())\n    )\n\n    # Reshape to long format: metrics = return, vol20, volume\n    df_long = df.melt(\n        id_vars=[\"date\", \"symbol\"],\n        value_vars=[\"return\", \"vol20\", \"volume\"],\n        var_name=\"metric\",\n        value_name=\"value\",\n    )\n\n    # Final tidy output\n    transformed_df = df_long[[\"date\", \"symbol\", \"metric\", \"value\"]].reset_index(drop=True)\n    return transformed_df\n```"}],"trigger":{"tableId":"table-265247","sourceTableIds":["history"],"instruction":"3) For each symbol, compute daily returns as pct_change of close, then 20-day rolling volatility as the rolling std of these returns; keep volume. Reshape to long format with columns [date, symbol, metric, value], where metric ∈ {\"return\", \"vol20\", \"volume\"}, and visualize over time (e.g., faceted by symbol with separate lines for each metric) to highlight periods of strong trends with elevated volatility or volume.","displayInstruction":"Show **daily return**, **20-day volatility**, and **volume** by **symbol** over **date**","chart":{"id":"chart-1769471280073","chartType":"Auto","encodingMap":{},"tableRef":"history","saved":false,"source":"trigger","unread":true},"resultTableId":"table-277926"},"explanation":{"status":"ok","concepts":[{"field":"return","explanation":"Daily return measures how much the closing price changes in percentage terms from one trading day to the next for the same symbol. For day t, return_t = (Close_t - Close_{t-1}) / Close_{t-1}."},{"field":"vol20","explanation":"20-day rolling volatility is a short-term risk measure that summarizes how much the daily returns have fluctuated over roughly the past month. For each date, vol20 is the standard deviation of the last up-to-20 'return' values for that symbol; higher vol20 indicates more unstable (more volatile) recent price movements."},{"field":"metric, value","explanation":"These two fields reorganize different measures into a single tidy structure: 'metric' tells you which quantity is being reported (return, vol20, or volume), and 'value' stores the corresponding number. This makes it easy to filter and compare different metrics in the same table."},{"field":"Statistical Analysis","explanation":"The transformation introduces two statistical concepts: (1) daily returns, which quantify relative price changes over time, and (2) rolling volatility, which applies a moving standard deviation to recent returns to estimate short-term risk. The model is implicit: for each symbol, returns are treated as a time series, and volatility is computed over a 20-day rolling window. Other possible analyses on this data could include moving averages of price or volume, exponential moving volatility, correlation between different symbols' returns, or time-series models such as ARIMA or GARCH to forecast returns and volatility."}],"code":"- **Selects** only the key fields from the original data: **\"date\"**, **\"symbol\"**, **\"close\"**, and **\"volume\"**.\n- **Standardizes** the **\"date\"** format to **\"YYYY-MM-DD\"** so all dates are consistent.\n- **Sorts** the data by **\"symbol\"** and then by **\"date\"** to put each stock’s prices in correct time order.\n- For each **symbol**, **calculates daily price change**:\n  - Adds a new field **\"return\"** = the **percentage change of the closing price** from the previous trading day for that same symbol.\n- For each **symbol**, **measures recent risk/variability**:\n  - Adds a new field **\"vol20\"** = the **20‑day rolling volatility**, i.e., the **standard deviation of the last up-to-20 daily returns** (a larger value means the stock has been more volatile recently).\n- **Restructures** the data into a “long” tidy format:\n  - Keeps **\"date\"** and **\"symbol\"**.\n  - Converts the three measures **\"return\"**, **\"vol20\"**, and **\"volume\"** into rows under a single **\"metric\"** column, with their numbers stored in a **\"value\"** column.\n- **Outputs** a clean table with columns **\"date\"**, **\"symbol\"**, **\"metric\"**, and **\"value\"**, where each row represents **one metric for one stock on one date**.","dialog":[{"role":"system","content":"You are a data scientist to help user explain code, \nso that a non-code can clearly understand what the code is doing, you are provided with a summary of the input data, and the transformation code.\n\nYour goal:\n1. You should generate a good itemized explanation of the code so that the reader can understand high-level steps of what the data transformation is doing.\n    - Be very concise, and stay at a high-level. The reader doesn't understand code and does not want to learn exactly what the code is doing. They just want to learn what have been done from a logical level.\n    - The explanation should be a markdown string that is a list of bullet points (with new lines), highlight constants, data fields, and important verbs.\n2. Generate a list of explanations for new fields (fields not from the input data) that introduce metrics/concepts that are not obvious from the code.\n    - provide a declarative definition that explains the new field, use a mathematical notation if applicable.\n    - only include new fields explanation of new metrics that are involved in computation (e.g., ROI, commerical_success_score)\n    - *DO NOT* explain trivial new fields like \"Decade\" or \"Avg_Rating\", \"US_Sales\" that are self-explanatory.\n        - Avoid explaining fields that are simple aggregate of fields in the original data (min_score, avg_value, count, etc.)\n    - When a field involves mathematical computation, you can use LaTeX math notation in the explanation. Format mathematical expressions using:\n        - Inline math: `\\( ... \\)` for formulas within text\n        - Block math: `\\[ ... \\]` for standalone formulas\n        - Examples: `\\( \\frac{\\text{Revenue}}{\\text{Cost}} \\)` for ratios, `\\[ \\text{Score} = \\text{Rating} \\times \\text{Worldwide\\_Gross} \\]` for formulas\n        - note: when using underscores as part of the text, you need to escape them with a backslash, e.g., `\\_`\n    - Note: don't use math notation for fields whose computation is trivial (use plain english), it will likely be confusing to the reader. \n      Only use math notation for fields that can not be easilyexplained in plain english. Use it sparingly.\n3. If there are multiple fields that have the similar computation, you can explain them together in one explanation.\n    - in \"field\", you can provide a list of fields in format of \"field1, field2, ...\"\n    - in \"explanation\", you can provide a single explanation for the computation of the fields.\n    - for example, if you have fields like \"Norm_Rating\", \"Norm_Gross\", \"Critical_Commercial_Score\", you can explain Norm_Rating, Norm_Gross together in one explanation and explain Critical_Commercial_Score in another explanation.\n4. If the code is about statistical analysis, you should explain the statistical analysis in the explanation as a concept named \"Statistical Analysis\" in the [CONCEPTS EXPLANATION] section.\n    - explain how you model the data, which fields are used, how data processing is done, and what models are used.\n    - suggest some other modeling approaches that can be used to analyze the data in the explanation as well.\n    \nThe focus is to explain how new fields are computed, don't generate explanation for low-level actions like \"return\", \"load data\" etc. \n\nProvide the result in the following two sections:\n    - first section is the code explanation that should be a markdown block explaining the code, in the [CODE EXPLANATION] section.\n        - remember to highlight constants, data fields, and important verbs in the code explanation.\n    - second section is the concepts explanation that should be a json block (start with ```json) in the [CONCEPTS EXPLANATION] section.\n\n[CODE EXPLANATION]\n\n...(explanation of the code)\n\n[CONCEPTS EXPLANATION]\n\n```json\n[\n    {\n        \"field\": \"...\",\n        \"explanation\": \"...\"\n    }\n]\n\n```\n"},{"role":"user","content":"[CONTEXT]\n\n## Table 1: history (738 rows × 8 columns)\n\n### Schema (8 fields)\n  - symbol -- type: object, values: AAPL, AMZN, GOOGL, META, MSFT, NVDA\n  - date -- type: object, values: 2025-07-30, 2025-07-31, 2025-08-01, ..., 2026-01-20, 2026-01-21, 2026-01-22, 2026-01-23\n  - open -- type: float64, values: 167.53, 168.01, 169.07, ..., 781.21, 782.98, 785.25, 789.97\n  - high -- type: float64, values: 169.01, 170.94, 170.96, ..., 789.62, 792.49, 794.28, 795.06\n  - low -- type: float64, values: 164.05, 166.72, 167.2, ..., 771.36, 772.21, 777.07, 779.66\n  - close -- type: float64, values: 167.0, 168.29, 170.28, ..., 779.09, 780.97, 784.06, 788.82\n  - volume -- type: int64, values: 5627500, 5855900, 6861200, ..., 320600300, 324925900, 343504800, 346926200\n  - fetched_at -- type: object, values: 2026-01-26T23:46:42.347312Z\n\n### Sample Data (first 5 rows)\n```\n  symbol        date    open    high     low   close     volume                   fetched_at\n0   AAPL  2025-07-30  211.45  211.94  207.28  208.61   45512500  2026-01-26T23:46:42.347312Z\n1   AAPL  2025-07-31  208.05  209.40  206.72  207.13   80698400  2026-01-26T23:46:42.347312Z\n2   AAPL  2025-08-01  210.43  213.13  201.08  201.95  104434500  2026-01-26T23:46:42.347312Z\n3   AAPL  2025-08-04  204.08  207.44  201.26  202.92   75109300  2026-01-26T23:46:42.347312Z\n4   AAPL  2025-08-05  202.97  204.91  201.74  202.49   44155100  2026-01-26T23:46:42.347312Z\n```\n\n\n[CODE]\n\nhere is the transformation code: \nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Keep only necessary columns\n    cols = [c for c in [\"date\", \"symbol\", \"close\", \"volume\"] if c in df_history.columns]\n    df = df_history[cols].copy()\n\n    # Normalize date to string YYYY-MM-DD\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for time-series operations\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    # Compute daily returns as pct_change of close within each symbol\n    df[\"return\"] = df.groupby(\"symbol\")[\"close\"].pct_change()\n\n    # Compute 20-day rolling volatility (std of returns) within each symbol\n    df[\"vol20\"] = (\n        df.groupby(\"symbol\")[\"return\"]\n          .transform(lambda s: s.rolling(window=20, min_periods=1).std())\n    )\n\n    # Reshape to long format: metrics = return, vol20, volume\n    df_long = df.melt(\n        id_vars=[\"date\", \"symbol\"],\n        value_vars=[\"return\", \"vol20\", \"volume\"],\n        var_name=\"metric\",\n        value_name=\"value\",\n    )\n\n    # Final tidy output\n    transformed_df = df_long[[\"date\", \"symbol\", \"metric\", \"value\"]].reset_index(drop=True)\n    return transformed_df\n\n\n[EXPLANATION]\n"},{"role":"assistant","content":"[CODE EXPLANATION]\n\n- **Selects** only the key fields from the original data: **\"date\"**, **\"symbol\"**, **\"close\"**, and **\"volume\"**.\n- **Standardizes** the **\"date\"** format to **\"YYYY-MM-DD\"** so all dates are consistent.\n- **Sorts** the data by **\"symbol\"** and then by **\"date\"** to put each stock’s prices in correct time order.\n- For each **symbol**, **calculates daily price change**:\n  - Adds a new field **\"return\"** = the **percentage change of the closing price** from the previous trading day for that same symbol.\n- For each **symbol**, **measures recent risk/variability**:\n  - Adds a new field **\"vol20\"** = the **20‑day rolling volatility**, i.e., the **standard deviation of the last up-to-20 daily returns** (a larger value means the stock has been more volatile recently).\n- **Restructures** the data into a “long” tidy format:\n  - Keeps **\"date\"** and **\"symbol\"**.\n  - Converts the three measures **\"return\"**, **\"vol20\"**, and **\"volume\"** into rows under a single **\"metric\"** column, with their numbers stored in a **\"value\"** column.\n- **Outputs** a clean table with columns **\"date\"**, **\"symbol\"**, **\"metric\"**, and **\"value\"**, where each row represents **one metric for one stock on one date**.\n\n\n[CONCEPTS EXPLANATION]\n\n```json\n[\n  {\n    \"field\": \"return\",\n    \"explanation\": \"Daily return measures how much the closing price changes in percentage terms from one trading day to the next for the same symbol. For day t, return_t = (Close_t - Close_{t-1}) / Close_{t-1}.\"\n  },\n  {\n    \"field\": \"vol20\",\n    \"explanation\": \"20-day rolling volatility is a short-term risk measure that summarizes how much the daily returns have fluctuated over roughly the past month. For each date, vol20 is the standard deviation of the last up-to-20 'return' values for that symbol; higher vol20 indicates more unstable (more volatile) recent price movements.\"\n  },\n  {\n    \"field\": \"metric, value\",\n    \"explanation\": \"These two fields reorganize different measures into a single tidy structure: 'metric' tells you which quantity is being reported (return, vol20, or volume), and 'value' stores the corresponding number. This makes it easy to filter and compare different metrics in the same table.\"\n  },\n  {\n    \"field\": \"Statistical Analysis\",\n    \"explanation\": \"The transformation introduces two statistical concepts: (1) daily returns, which quantify relative price changes over time, and (2) rolling volatility, which applies a moving standard deviation to recent returns to estimate short-term risk. The model is implicit: for each symbol, returns are treated as a time series, and volatility is computed over a 20-day rolling window. Other possible analyses on this data could include moving averages of price or volume, exponential moving volatility, correlation between different symbols' returns, or time-series models such as ARIMA or GARCH to forecast returns and volatility.\"\n  }\n]\n```"}],"agent":"CodeExplanationAgent"}},"anchored":false,"createdBy":"user","attachedMetadata":""},{"id":"table-457008","displayId":"stock-close1","names":["date","symbol","close"],"rows":[{"date":"2025-07-30","symbol":"GOOGL","close":196.23},{"date":"2025-07-31","symbol":"GOOGL","close":191.6},{"date":"2025-08-01","symbol":"GOOGL","close":188.84},{"date":"2025-08-04","symbol":"GOOGL","close":194.74},{"date":"2025-08-05","symbol":"GOOGL","close":194.37},{"date":"2025-08-06","symbol":"GOOGL","close":195.79},{"date":"2025-08-07","symbol":"GOOGL","close":196.22},{"date":"2025-08-08","symbol":"GOOGL","close":201.11},{"date":"2025-08-11","symbol":"GOOGL","close":200.69},{"date":"2025-08-12","symbol":"GOOGL","close":203.03},{"date":"2025-08-13","symbol":"GOOGL","close":201.65},{"date":"2025-08-14","symbol":"GOOGL","close":202.63},{"date":"2025-08-15","symbol":"GOOGL","close":203.58},{"date":"2025-08-18","symbol":"GOOGL","close":203.19},{"date":"2025-08-19","symbol":"GOOGL","close":201.26},{"date":"2025-08-20","symbol":"GOOGL","close":199.01},{"date":"2025-08-21","symbol":"GOOGL","close":199.44},{"date":"2025-08-22","symbol":"GOOGL","close":205.77},{"date":"2025-08-25","symbol":"GOOGL","close":208.17},{"date":"2025-08-26","symbol":"GOOGL","close":206.82},{"date":"2025-08-27","symbol":"GOOGL","close":207.16},{"date":"2025-08-28","symbol":"GOOGL","close":211.31},{"date":"2025-08-29","symbol":"GOOGL","close":212.58},{"date":"2025-09-02","symbol":"GOOGL","close":211.02},{"date":"2025-09-03","symbol":"GOOGL","close":230.3},{"date":"2025-09-04","symbol":"GOOGL","close":231.94},{"date":"2025-09-05","symbol":"GOOGL","close":234.64},{"date":"2025-09-08","symbol":"GOOGL","close":233.89},{"date":"2025-09-09","symbol":"GOOGL","close":239.47},{"date":"2025-09-10","symbol":"GOOGL","close":239.01},{"date":"2025-09-11","symbol":"GOOGL","close":240.21},{"date":"2025-09-12","symbol":"GOOGL","close":240.64},{"date":"2025-09-15","symbol":"GOOGL","close":251.45},{"date":"2025-09-16","symbol":"GOOGL","close":251},{"date":"2025-09-17","symbol":"GOOGL","close":249.37},{"date":"2025-09-18","symbol":"GOOGL","close":251.87},{"date":"2025-09-19","symbol":"GOOGL","close":254.55},{"date":"2025-09-22","symbol":"GOOGL","close":252.36},{"date":"2025-09-23","symbol":"GOOGL","close":251.5},{"date":"2025-09-24","symbol":"GOOGL","close":246.98},{"date":"2025-09-25","symbol":"GOOGL","close":245.63},{"date":"2025-09-26","symbol":"GOOGL","close":246.38},{"date":"2025-09-29","symbol":"GOOGL","close":243.89},{"date":"2025-09-30","symbol":"GOOGL","close":242.94},{"date":"2025-10-01","symbol":"GOOGL","close":244.74},{"date":"2025-10-02","symbol":"GOOGL","close":245.53},{"date":"2025-10-03","symbol":"GOOGL","close":245.19},{"date":"2025-10-06","symbol":"GOOGL","close":250.27},{"date":"2025-10-07","symbol":"GOOGL","close":245.6},{"date":"2025-10-08","symbol":"GOOGL","close":244.46},{"date":"2025-10-09","symbol":"GOOGL","close":241.37},{"date":"2025-10-10","symbol":"GOOGL","close":236.42},{"date":"2025-10-13","symbol":"GOOGL","close":243.99},{"date":"2025-10-14","symbol":"GOOGL","close":245.29},{"date":"2025-10-15","symbol":"GOOGL","close":250.87},{"date":"2025-10-16","symbol":"GOOGL","close":251.3},{"date":"2025-10-17","symbol":"GOOGL","close":253.13},{"date":"2025-10-20","symbol":"GOOGL","close":256.38},{"date":"2025-10-21","symbol":"GOOGL","close":250.3},{"date":"2025-10-22","symbol":"GOOGL","close":251.53},{"date":"2025-10-23","symbol":"GOOGL","close":252.91},{"date":"2025-10-24","symbol":"GOOGL","close":259.75},{"date":"2025-10-27","symbol":"GOOGL","close":269.09},{"date":"2025-10-28","symbol":"GOOGL","close":267.3},{"date":"2025-10-29","symbol":"GOOGL","close":274.39},{"date":"2025-10-30","symbol":"GOOGL","close":281.3},{"date":"2025-10-31","symbol":"GOOGL","close":281.01},{"date":"2025-11-03","symbol":"GOOGL","close":283.53},{"date":"2025-11-04","symbol":"GOOGL","close":277.36},{"date":"2025-11-05","symbol":"GOOGL","close":284.12},{"date":"2025-11-06","symbol":"GOOGL","close":284.56},{"date":"2025-11-07","symbol":"GOOGL","close":278.65},{"date":"2025-11-10","symbol":"GOOGL","close":289.91},{"date":"2025-11-11","symbol":"GOOGL","close":291.12},{"date":"2025-11-12","symbol":"GOOGL","close":286.52},{"date":"2025-11-13","symbol":"GOOGL","close":278.39},{"date":"2025-11-14","symbol":"GOOGL","close":276.23},{"date":"2025-11-17","symbol":"GOOGL","close":284.83},{"date":"2025-11-18","symbol":"GOOGL","close":284.09},{"date":"2025-11-19","symbol":"GOOGL","close":292.62},{"date":"2025-11-20","symbol":"GOOGL","close":289.26},{"date":"2025-11-21","symbol":"GOOGL","close":299.46},{"date":"2025-11-24","symbol":"GOOGL","close":318.37},{"date":"2025-11-25","symbol":"GOOGL","close":323.23},{"date":"2025-11-26","symbol":"GOOGL","close":319.74},{"date":"2025-11-28","symbol":"GOOGL","close":319.97},{"date":"2025-12-01","symbol":"GOOGL","close":314.68},{"date":"2025-12-02","symbol":"GOOGL","close":315.6},{"date":"2025-12-03","symbol":"GOOGL","close":319.42},{"date":"20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pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Select only needed columns\n    cols = [\"date\", \"symbol\", \"close\"]\n    df = df_history[cols].copy()\n\n    # Filter for Microsoft (MSFT) and Google (GOOGL)\n    target_symbols = [\"MSFT\", \"GOOGL\"]\n    df = df[df[\"symbol\"].isin(target_symbols)].copy()\n\n    # Ensure date is a string in YYYY-MM-DD format (no datetime objects)\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper line plotting\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    transformed_df = df\n    return transformed_df\n","source":["history"],"dialog":[{"role":"system","content":"You are a data scientist to help user to transform data that will be used for visualization.\nThe user will provide you information about what data would be needed, and your job is to create a python function based on the input data summary, transformation instruction and expected fields.\nThe users' instruction includes \"chart_type\" and \"chart_encodings\" that describe the visualization they want, and natural language instructions \"goal\" that describe what data is needed.\n\n**Important:**\n- NEVER make assumptions or judgments about a person's gender, biological sex, sexuality, religion, race, nationality, ethnicity, political stance, socioeconomic status, mental health, invisible disabilities, medical conditions, personality type, social impressions, emotional state, and cognitive state.\n- NEVER create formulas that could be used to discriminate based on age. Ageism of any form (explicit and implicit) is strictly prohibited.\n- If above issue occurs, generate columns with np.nan.\n\nConcretely, you should first refine users' goal and then create a python function in the output section based off the [CONTEXT] and [GOAL]:\n\n    1. First, refine users' [GOAL]. The main objective in this step is to check if \"chart_type\" and \"chart_encodings\" provided by the user are sufficient to achieve their \"goal\". Concretely:\n        - based on the user's \"goal\" and \"chart_type\" and \"chart_encodings\", elaborate the goal into a \"detailed_instruction\".\n        - \"display_instruction\" is a short verb phrase describing the users' goal. \n            - it would be a short verbal description of user intent as a verb phrase (<12 words).\n            - generate it based on detailed_instruction and the suggested chart_type and chart_encodings, but don't need to mention the chart details.\n            - should capture key computation ideas: by reading the display, the user can understand the purpose and what's derived from the data.\n            - if the user specification follows up the previous instruction, the 'display_instruction' should only describe how it builds up the previous instruction without repeating information from previous steps.\n            - the phrase can be presented in different styles, e.g., question (what's xxx), instruction (show xxx), description, etc.\n            - if you mention column names from the input or the output data, highlight the text in **bold**.\n                * the column can either be a column in the input data, or a new column that will be computed in the output data.\n                * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned \"average score\" in the text while the column to be computed is \"Avg_Score\", you should still highlight \"**average score**\" in the text.\n        - determine \"input_tables\", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.\n            - **IMPORTANT** Note that the Table 1 in [CONTEXT] section is the table the user is currently viewing, it should take precedence if the user refers to insights about the \"current table\".\n            - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.\n        - determine \"output_fields\", the desired fields that the output data should have to achieve the user's goal, it's a good idea to include intermediate fields here.\n        - then decide \"chart_encodings\", which maps visualization channels (x, y, color, size, opacity, facet, latitude, longitude, etc.) to a subset of \"output_fields\" that will be visualized, \n            - the \"chart_encodings\" should be created to support the user's \"chart_type\".\n            - first, determine whether the user has provided sufficient fields in \"chart_encodings\" that are needed to achieve their goal:\n                - if the user's \"chart_encodings\" are sufficient, simply copy it.\n                - if the user didn't provide sufficient fields in \"chart_encodings\", add missing fields in \"chart_encodings\" (ordered them based on whether the field will be used in x,y axes or legends);\n                    - \"chart_encodings\" should only include fields that will be visualized (do not include other intermediate fields from \"output_fields\")  \n                    - when adding new fields to \"chart_encodings\", be efficient and add only a minimal number of fields that are needed to achive the user's goal. \n                    - generally, the total number of fields in \"chart_encodings\" should be no more than 3 for x,y,legend.\n                - if the user's \"chart_encodings\" is sufficient but can be optimized, you can reorder encodings to visualize the data more effectively.\n            - sometimes, user may provide instruction to update visualizations fields they provided. You should leverage the user's goal to resolve the conflict and decide the final \"chart_encodings\"\n                - e.g., they may mention \"use B metric instead\" while A metric is in provided fields, in this case, you should update \"chart_encodings\" to update A metric with B metric.\n            - if the user provides latitude and longitude as visual channels, use \"latitude\" and \"longitude\" as visual channels in \"chart_encodings\" as opposed to \"x\" and \"y\".\n        - guide on statistical analysis:\n            - when the user asks for forecasting or regression analysis, you should consider the following:\n                - the output should be a long format table where actual x, y pairs and predicted x, y pairs are included in the X, Y columns, they are differentiated with a third column \"is_predicted\".\n                - i.e., if the user ask for forecasting based on two columns T and Y, the output should be three columns: T, Y, is_predicted, where\n                    - T, Y columns contain BOTH original values from the data and predicted values from the data.\n                    - is_predicted is a boolean field to indicate whether the x, y pairs are original values from the data or predicted / regression values from the data.\n                - the recommended chart should be line chart (time series) or scatter plot (quantitative x, y)\n                - if the user asks for forecasting, it's good to include predicted x, y pairs for both x in the original data and future x values (i.e., combine regression and forecasting results)\n                    - in this case, is_predicted should be of three values 'original', 'regression', 'forecasting'\n        - when the user asks for clustering:\n            - the output should be a long format table where actual x, y pairs with a third column \"cluster_id\" that indicates the cluster id of the data point.\n            - the recommended chart should be scatter plot (quantitative x, y)\n    \n    Prepare the result in the following json format:\n\n```\n{\n    \"detailed_instruction\": \"...\" // string, elaborate user instruction with details if the user\n    \"display_instruction\": \"...\" // string, the short verb phrase describing the users' goal.\n    \"input_tables\": [...] // string[], describe names of the input tables that will be used in the transformation.\n    \"output_fields\": [...] // string[], describe the desired output fields that the output data should have based on the user's goal, it's a good idea to preserve intermediate fields here (i.e., the goal of transformed data)\n    \"chart_encodings\": {\n        \"x\": \"\",\n        \"y\": \"\",\n        \"color\": \"\",\n        \"size\": \"\",\n        \"opacity\": \"\",\n        \"facet\": \"\",\n        ... // other visualization channels user used\n    } // object: map visualization channels (x, y, color, size, opacity, facet, etc.) to a subset of \"output_fields\" that will be visualized.\n    \"reason\": \"...\" // string, explain why this refinement is made\n}\n```\n\n    2. Then, write a python function based on the refined goal, the function input is a dataframe \"df\" (or multiple dataframes based on tables described in \"input_tables\") and the output is the transformed dataframe \"transformed_df\". \"transformed_df\" should contain all \"output_fields\" from the refined goal.\nThe python function must follow the template provided in [TEMPLATE], only import libraries allowed in the template, do not modify function name. The function should be as simple as possible and easily readable.\nIf there is no data transformation needed based on \"output_fields\", the transformation function can simply \"return df\".\n\n[TEMPLATE]\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n# from sklearn import ... # import from sklearn if you need it.\n\ndef transform_data(df1, df2, ...): \n    # complete the template here\n    return transformed_df\n```\n\nnote: \n- decide the function signature based on the number of tables you decided in the previous step \"input_tables\":\n    - if you decide there will only be one input table, then function signature should be `def transform_data(df1)`\n    - if you decided there will be k input tables, then function signature should be `def transform_data(df_1, df_2, ..., df_k)`.\n    - instead of using generic names like df1, df2, ..., try to use intuitive table names for function arguments, for example, if you have input_tables: [\"City\", \"Weather\"]`, you can use `transform_data(df_city, df_weather)` to refer to the two dataframes.\n    - **VERY IMPORTANT** the number of arguments in the function signature must be the same as the number of tables provided in \"input_tables\", and the order of arguments must match the order of tables provided in \"input_tables\".\n- datetime objects handling:\n    - if the output field is year, convert it to number, if it is year-month / year-month-day, convert it to string object (e.g., \"2020-01\" / \"2020-01-01\").\n    - if the output is time only: convert hour to number if it's just the hour (e.g., 10), but convert hour:min or h:m:s to string object (e.g., \"10:30\", \"10:30:45\")\n    - never return datetime object directly, convert it to either number (if it only contains year) or string so it's readable.\n\n    3. The output must only contain a json object representing the refined goal and a python code block representing the transformation code, do not add any extra text explanation.\n"},{"role":"user","content":"[CONTEXT]\n\n## Table 1: history (738 rows × 8 columns)\n\n### Schema (8 fields)\n  - symbol -- type: object, values: AAPL, AMZN, GOOGL, META, MSFT, NVDA\n  - date -- type: object, values: 2025-07-30, 2025-07-31, 2025-08-01, ..., 2026-01-20, 2026-01-21, 2026-01-22, 2026-01-23\n  - open -- type: float64, values: 167.53, 168.01, 169.07, ..., 781.21, 782.98, 785.25, 789.97\n  - high -- type: float64, values: 169.01, 170.94, 170.96, ..., 789.62, 792.49, 794.28, 795.06\n  - low -- type: float64, values: 164.05, 166.72, 167.2, ..., 771.36, 772.21, 777.07, 779.66\n  - close -- type: float64, values: 167.0, 168.29, 170.28, ..., 779.09, 780.97, 784.06, 788.82\n  - volume -- type: int64, values: 5627500, 5855900, 6861200, ..., 320600300, 324925900, 343504800, 346926200\n  - fetched_at -- type: object, values: 2026-01-26T23:46:42.347312Z\n\n### Sample Data (first 5 rows)\n```\n  symbol        date    open    high     low   close     volume                   fetched_at\n0   AAPL  2025-07-30  211.45  211.94  207.28  208.61   45512500  2026-01-26T23:46:42.347312Z\n1   AAPL  2025-07-31  208.05  209.40  206.72  207.13   80698400  2026-01-26T23:46:42.347312Z\n2   AAPL  2025-08-01  210.43  213.13  201.08  201.95  104434500  2026-01-26T23:46:42.347312Z\n3   AAPL  2025-08-04  204.08  207.44  201.26  202.92   75109300  2026-01-26T23:46:42.347312Z\n4   AAPL  2025-08-05  202.97  204.91  201.74  202.49   44155100  2026-01-26T23:46:42.347312Z\n```\n\n\n[GOAL]\n\n1) First, plot the overall **closing price** trends for each **symbol** over **time** on a single line chart to compare their broad trajectories and volatility."},{"role":"assistant","content":"{\n  \"mode\": \"infer\",\n  \"recap\": \"Compare overall closing price trends and volatility over time for each stock symbol on a single line chart.\",\n  \"display_instruction\": \"Visualize **closing price** trends by **symbol** over **date**\",\n  \"recommendation\": \"A line chart with time on the x-axis and closing price on the y-axis, colored by symbol, best shows comparative trajectories and volatility over time. The data only needs column selection, date normalization, and sorting to be visualization-ready.\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"close\"],\n  \"chart_type\": \"line\",\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"close\",\n    \"color\": \"symbol\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"\"\n  }\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Select only needed columns\n    cols = [\"date\", \"symbol\", \"close\"]\n    df = df_history[cols].copy()\n\n    # Ensure date is a string in YYYY-MM-DD format (no datetime objects)\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper line plotting\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    transformed_df = df\n    return transformed_df\n```"},{"role":"user","content":"This is the result from the latest python code:\n\n         date symbol   close\n0  2025-07-30   AAPL  208.61\n1  2025-07-31   AAPL  207.13\n2  2025-08-01   AAPL  201.95\n3  2025-08-04   AAPL  202.92\n4  2025-08-05   AAPL  202.49\n5  2025-08-06   AAPL  212.80\n6  2025-08-07   AAPL  219.57\n7  2025-08-08   AAPL  228.87\n8  2025-08-11   AAPL  226.96\n9  2025-08-12   AAPL  229.43\n......\n\nUpdate the code above based on the following instruction:\n\n{\n    \"followup_instruction\": \"compare microsoft and google\",\n    \"chart_type\": \"\",\n    \"chart_encodings\": {}\n}"},{"role":"assistant","content":"{\n  \"detailed_instruction\": \"Filter the historical price data to only include Microsoft (MSFT) and Google (GOOGL) and prepare it for a line chart that compares their closing price trends over time on the same plot.\",\n  \"display_instruction\": \"Compare **closing price** trends of **MSFT** and **GOOGL** over **date**\",\n  \"input_tables\": [\"history\"],\n  \"output_fields\": [\"date\", \"symbol\", \"close\"],\n  \"chart_encodings\": {\n    \"x\": \"date\",\n    \"y\": \"close\",\n    \"color\": \"symbol\",\n    \"size\": \"\",\n    \"opacity\": \"\",\n    \"facet\": \"\"\n  },\n  \"reason\": \"The follow-up focuses the existing trend comparison on only Microsoft and Google. This requires filtering the original prepared data to those two symbols while keeping the same line chart structure: date on x, close on y, and symbol as the color encoding.\"\n}\n\n```python\nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Select only needed columns\n    cols = [\"date\", \"symbol\", \"close\"]\n    df = df_history[cols].copy()\n\n    # Filter for Microsoft (MSFT) and Google (GOOGL)\n    target_symbols = [\"MSFT\", \"GOOGL\"]\n    df = df[df[\"symbol\"].isin(target_symbols)].copy()\n\n    # Ensure date is a string in YYYY-MM-DD format (no datetime objects)\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper line plotting\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    transformed_df = df\n    return transformed_df\n```"}],"trigger":{"tableId":"table-233476","sourceTableIds":["history"],"instruction":"compare microsoft and google","displayInstruction":"Compare **closing price** trends of **MSFT** and **GOOGL** over **date**","chart":{"id":"chart-1769471462237","chartType":"Auto","encodingMap":{},"tableRef":"table-233476","saved":false,"source":"trigger","unread":true},"resultTableId":"table-457008"},"explanation":{"status":"ok","concepts":[],"code":"- **Keep only** the **`date`**, **`symbol`**, and **`close`** price columns from the original data, discarding all others.\n- **Filter rows** to include **only** the two companies: **`MSFT` (Microsoft)** and **`GOOGL` (Google)**.\n- **Standardize the date format** by converting **`date`** into a **string** formatted as **`YYYY-MM-DD`** (year-month-day).\n- **Sort the data** by **`symbol`** and then by **`date`** so that each company’s prices are in **chronological order**, making it ready for **line plotting over time**.\n- **Return** this cleaned and filtered dataset as the final result.","dialog":[{"role":"system","content":"You are a data scientist to help user explain code, \nso that a non-code can clearly understand what the code is doing, you are provided with a summary of the input data, and the transformation code.\n\nYour goal:\n1. You should generate a good itemized explanation of the code so that the reader can understand high-level steps of what the data transformation is doing.\n    - Be very concise, and stay at a high-level. The reader doesn't understand code and does not want to learn exactly what the code is doing. They just want to learn what have been done from a logical level.\n    - The explanation should be a markdown string that is a list of bullet points (with new lines), highlight constants, data fields, and important verbs.\n2. Generate a list of explanations for new fields (fields not from the input data) that introduce metrics/concepts that are not obvious from the code.\n    - provide a declarative definition that explains the new field, use a mathematical notation if applicable.\n    - only include new fields explanation of new metrics that are involved in computation (e.g., ROI, commerical_success_score)\n    - *DO NOT* explain trivial new fields like \"Decade\" or \"Avg_Rating\", \"US_Sales\" that are self-explanatory.\n        - Avoid explaining fields that are simple aggregate of fields in the original data (min_score, avg_value, count, etc.)\n    - When a field involves mathematical computation, you can use LaTeX math notation in the explanation. Format mathematical expressions using:\n        - Inline math: `\\( ... \\)` for formulas within text\n        - Block math: `\\[ ... \\]` for standalone formulas\n        - Examples: `\\( \\frac{\\text{Revenue}}{\\text{Cost}} \\)` for ratios, `\\[ \\text{Score} = \\text{Rating} \\times \\text{Worldwide\\_Gross} \\]` for formulas\n        - note: when using underscores as part of the text, you need to escape them with a backslash, e.g., `\\_`\n    - Note: don't use math notation for fields whose computation is trivial (use plain english), it will likely be confusing to the reader. \n      Only use math notation for fields that can not be easilyexplained in plain english. Use it sparingly.\n3. If there are multiple fields that have the similar computation, you can explain them together in one explanation.\n    - in \"field\", you can provide a list of fields in format of \"field1, field2, ...\"\n    - in \"explanation\", you can provide a single explanation for the computation of the fields.\n    - for example, if you have fields like \"Norm_Rating\", \"Norm_Gross\", \"Critical_Commercial_Score\", you can explain Norm_Rating, Norm_Gross together in one explanation and explain Critical_Commercial_Score in another explanation.\n4. If the code is about statistical analysis, you should explain the statistical analysis in the explanation as a concept named \"Statistical Analysis\" in the [CONCEPTS EXPLANATION] section.\n    - explain how you model the data, which fields are used, how data processing is done, and what models are used.\n    - suggest some other modeling approaches that can be used to analyze the data in the explanation as well.\n    \nThe focus is to explain how new fields are computed, don't generate explanation for low-level actions like \"return\", \"load data\" etc. \n\nProvide the result in the following two sections:\n    - first section is the code explanation that should be a markdown block explaining the code, in the [CODE EXPLANATION] section.\n        - remember to highlight constants, data fields, and important verbs in the code explanation.\n    - second section is the concepts explanation that should be a json block (start with ```json) in the [CONCEPTS EXPLANATION] section.\n\n[CODE EXPLANATION]\n\n...(explanation of the code)\n\n[CONCEPTS EXPLANATION]\n\n```json\n[\n    {\n        \"field\": \"...\",\n        \"explanation\": \"...\"\n    }\n]\n\n```\n"},{"role":"user","content":"[CONTEXT]\n\n## Table 1: history (738 rows × 8 columns)\n\n### Schema (8 fields)\n  - symbol -- type: object, values: AAPL, AMZN, GOOGL, META, MSFT, NVDA\n  - date -- type: object, values: 2025-07-30, 2025-07-31, 2025-08-01, ..., 2026-01-20, 2026-01-21, 2026-01-22, 2026-01-23\n  - open -- type: float64, values: 167.53, 168.01, 169.07, ..., 781.21, 782.98, 785.25, 789.97\n  - high -- type: float64, values: 169.01, 170.94, 170.96, ..., 789.62, 792.49, 794.28, 795.06\n  - low -- type: float64, values: 164.05, 166.72, 167.2, ..., 771.36, 772.21, 777.07, 779.66\n  - close -- type: float64, values: 167.0, 168.29, 170.28, ..., 779.09, 780.97, 784.06, 788.82\n  - volume -- type: int64, values: 5627500, 5855900, 6861200, ..., 320600300, 324925900, 343504800, 346926200\n  - fetched_at -- type: object, values: 2026-01-26T23:46:42.347312Z\n\n### Sample Data (first 5 rows)\n```\n  symbol        date    open    high     low   close     volume                   fetched_at\n0   AAPL  2025-07-30  211.45  211.94  207.28  208.61   45512500  2026-01-26T23:46:42.347312Z\n1   AAPL  2025-07-31  208.05  209.40  206.72  207.13   80698400  2026-01-26T23:46:42.347312Z\n2   AAPL  2025-08-01  210.43  213.13  201.08  201.95  104434500  2026-01-26T23:46:42.347312Z\n3   AAPL  2025-08-04  204.08  207.44  201.26  202.92   75109300  2026-01-26T23:46:42.347312Z\n4   AAPL  2025-08-05  202.97  204.91  201.74  202.49   44155100  2026-01-26T23:46:42.347312Z\n```\n\n\n[CODE]\n\nhere is the transformation code: \nimport pandas as pd\nimport collections\nimport numpy as np\n\ndef transform_data(df_history: pd.DataFrame) -> pd.DataFrame:\n    # Select only needed columns\n    cols = [\"date\", \"symbol\", \"close\"]\n    df = df_history[cols].copy()\n\n    # Filter for Microsoft (MSFT) and Google (GOOGL)\n    target_symbols = [\"MSFT\", \"GOOGL\"]\n    df = df[df[\"symbol\"].isin(target_symbols)].copy()\n\n    # Ensure date is a string in YYYY-MM-DD format (no datetime objects)\n    df[\"date\"] = pd.to_datetime(df[\"date\"]).dt.strftime(\"%Y-%m-%d\")\n\n    # Sort for proper line plotting\n    df = df.sort_values([\"symbol\", \"date\"]).reset_index(drop=True)\n\n    transformed_df = df\n    return transformed_df\n\n\n[EXPLANATION]\n"},{"role":"assistant","content":"[CODE EXPLANATION]\n\n- **Keep only** the **`date`**, **`symbol`**, and **`close`** price columns from the original data, discarding all others.\n- **Filter rows** to include **only** the two companies: **`MSFT` (Microsoft)** and **`GOOGL` (Google)**.\n- **Standardize the date format** by converting **`date`** into a **string** formatted as **`YYYY-MM-DD`** (year-month-day).\n- **Sort the data** by **`symbol`** and then by **`date`** so that each company’s prices are in **chronological order**, making it ready for **line plotting over time**.\n- **Return** this cleaned and filtered dataset as the final result.\n\n[CONCEPTS EXPLANATION]\n\n```json\n[\n]\n```"}],"agent":"CodeExplanationAgent"}},"anchored":false,"createdBy":"user","attachedMetadata":""}],"charts":[{"id":"chart-1769471461230","chartType":"Scatter Plot","encodingMap":{"x":{"fieldID":"original--history--date"},"y":{"fieldID":"original--history--close"},"color":{"fieldID":"original--history--symbol"},"size":{"channel":"size","bin":false},"opacity":{"channel":"opacity","bin":false},"column":{"channel":"column","bin":false},"row":{"channel":"row","bin":false}},"tableRef":"table-457008","saved":false,"source":"user","unread":false},{"id":"chart-1769471279744","chartType":"Line 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help you track six large tech stocks (AAPL, AMZN, GOOGL, META, MSFT, NVDA) across price, trends, and risk. Each chart updates as new rows are added to the `history` table.\n\n[IMAGE(chart-1769471233467)]\n\nThe first chart shows daily closing prices over time for all six symbols. Use it to spot broad moves, compare relative price levels, and see when one stock starts to diverge from the group.\n\n[IMAGE(chart-1769471263442)]\n\nThe second chart adds 20‑day and 60‑day moving averages. Watch how actual prices relate to these smoother trend lines: crossovers, sustained gaps, or trend flattening can signal shifting momentum.\n\n[IMAGE(chart-1769471279744)]\n\nThe third set of panels tracks three risk and activity metrics: daily returns, 20‑day return volatility, and trading volume. Look for periods where volatility or volume spikes, or where returns cluster on one side.\n\n[IMAGE(chart-1769471461230)]\n\nThe final chart zooms in on GOOGL and MSFT closing prices, making it easier to compare their day‑to‑day paths without the distraction of other symbols.\n\n**In summary**, use these views together: price levels and trends, plus returns, volatility, and volume, to monitor how each stock is behaving and how relationships between them evolve over time. Possible follow‑ups: add alerts for threshold moves, overlay events (earnings, macro news), or include benchmark indices for context.","style":"live report","selectedChartIds":["chart-1769471279744","chart-1769471233467","chart-1769471461230","chart-1769471263442"],"createdAt":1769471511269}],"_persist":{"version":-1,"rehydrated":true}}
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z6NvDI2k;<#n0_1iV@DbF&5yUUr?0aI0(NZ|ZsXzSE5pcm?dUK4j?+HC`Cm^6AKqU<
z^V)j2^IgyI3Gnjs{k4r!mA>Xm>NyA4yO}FHyQ7kT@*yiIAj&WOOX2^T`q$-uRL%ZX
z6%rTzAFBVE`roR?KK9;99_}cozOw(`fq(q|ck&-aX};^V|0fr}6a9;e%Cs!DG~eI5
ICX4-l04XBA0{{R3

literal 0
HcmV?d00001

diff --git a/py-src/data_formulator/agents/agent_py_data_rec.py b/py-src/data_formulator/agents/agent_py_data_rec.py
index f943db3..c61cde6 100644
--- a/py-src/data_formulator/agents/agent_py_data_rec.py
+++ b/py-src/data_formulator/agents/agent_py_data_rec.py
@@ -67,7 +67,7 @@
             * the column can either be a column in the input data, or a new column that will be computed in the output data.
             * the mention don't have to be exact match, it can be semantically matching, e.g., if you mentioned "average score" in the text while the column to be computed is "Avg_Score", you should still highlight "**average score**" in the text.
     - determine "input_tables", the names of a subset of input tables from [CONTEXT] section that will be used to achieve the user's goal.
-        - Note that the first table is the table the user is currently viewing, it should take precedence if the user asks for visualization of the "current table".
+        - **IMPORTANT** Note that the Table 1 in [CONTEXT] section is the table the user is currently viewing, it should take precedence if the user refers to insights about the "current table".
         - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.
     - "chart_type" must be one of "point", "bar", "line", "area", "heatmap", "group_bar", "boxplot"
     - "chart_encodings" should specify which fields should be used to create the visualization
diff --git a/py-src/data_formulator/agents/agent_py_data_transform.py b/py-src/data_formulator/agents/agent_py_data_transform.py
index cd0b6b5..a227d10 100644
--- a/py-src/data_formulator/agents/agent_py_data_transform.py
+++ b/py-src/data_formulator/agents/agent_py_data_transform.py
@@ -38,7 +38,7 @@
             - **IMPORTANT** Note that the Table 1 in [CONTEXT] section is the table the user is currently viewing, it should take precedence if the user refers to insights about the "current table".
             - At the same time, leverage table information to determine which tables are relevant to the user's goal and should be used.
         - determine "output_fields", the desired fields that the output data should have to achieve the user's goal, it's a good idea to include intermediate fields here.
-        - then decide "chart_encodings", which maps visualization channels (x, y, color, size, opacity, facet, etc.) to a subset of "output_fields" that will be visualized, 
+        - then decide "chart_encodings", which maps visualization channels (x, y, color, size, opacity, facet, latitude, longitude, etc.) to a subset of "output_fields" that will be visualized, 
             - the "chart_encodings" should be created to support the user's "chart_type".
             - first, determine whether the user has provided sufficient fields in "chart_encodings" that are needed to achieve their goal:
                 - if the user's "chart_encodings" are sufficient, simply copy it.
@@ -49,6 +49,7 @@
                 - if the user's "chart_encodings" is sufficient but can be optimized, you can reorder encodings to visualize the data more effectively.
             - sometimes, user may provide instruction to update visualizations fields they provided. You should leverage the user's goal to resolve the conflict and decide the final "chart_encodings"
                 - e.g., they may mention "use B metric instead" while A metric is in provided fields, in this case, you should update "chart_encodings" to update A metric with B metric.
+            - if the user provides latitude and longitude as visual channels, use "latitude" and "longitude" as visual channels in "chart_encodings" as opposed to "x" and "y".
         - guide on statistical analysis:
             - when the user asks for forecasting or regression analysis, you should consider the following:
                 - the output should be a long format table where actual x, y pairs and predicted x, y pairs are included in the X, Y columns, they are differentiated with a third column "is_predicted".
diff --git a/src/app/useDataRefresh.tsx b/src/app/useDataRefresh.tsx
index d5b8f43..ec53dde 100644
--- a/src/app/useDataRefresh.tsx
+++ b/src/app/useDataRefresh.tsx
@@ -27,6 +27,7 @@ export function useDataRefresh() {
     const timeoutRefs = useRef<Map<string, NodeJS.Timeout>>(new Map());
     const refreshInProgressRef = useRef<Map<string, boolean>>(new Map());
     const isActiveRef = useRef<Map<string, boolean>>(new Map());
+    const initializedTablesRef = useRef<Set<string>>(new Set()); // Track tables that have been initialized
     const lastMessageTimeRef = useRef<number>(0);
     const MESSAGE_THROTTLE_MS = 10000; // 10 seconds
 
@@ -316,6 +317,7 @@ export function useDataRefresh() {
     /**
      * Set up refresh intervals for tables with auto-refresh enabled.
      * Uses recursive setTimeout pattern to ensure updates wait until complete.
+     * Triggers immediate refresh for newly loaded tables.
      */
     useEffect(() => {
         // Clear all existing timeouts
@@ -334,22 +336,44 @@ export function useDataRefresh() {
 
             if (shouldAutoRefresh) {
                 const intervalMs = source.refreshIntervalSeconds! * 1000;
+                const isNewTable = !initializedTablesRef.current.has(table.id);
                 
-                console.log(`[DataRefresh] Setting up auto-refresh for "${table.id}" every ${source.refreshIntervalSeconds}s (waiting for completion)`);
+                console.log(`[DataRefresh] Setting up auto-refresh for "${table.id}" every ${source.refreshIntervalSeconds}s (new=${isNewTable})`);
                 
-                // Mark as active
+                // Mark as active and initialized
                 isActiveRef.current.set(table.id, true);
+                initializedTablesRef.current.add(table.id);
                 
-                // Start the refresh cycle - first refresh happens after interval, then schedules next after completion
-                const initialTimeout = setTimeout(async () => {
-                    if (!isActiveRef.current.get(table.id)) {
-                        return;
-                    }
-                    await performRefresh(table);
-                    scheduleNextRefresh(table.id);
-                }, intervalMs);
+                if (isNewTable) {
+                    // For newly loaded tables, trigger immediate refresh then schedule next
+                    console.log(`[DataRefresh] Triggering immediate first refresh for newly loaded table "${table.id}"`);
+                    (async () => {
+                        if (!isActiveRef.current.get(table.id)) {
+                            return;
+                        }
+                        await performRefresh(table);
+                        scheduleNextRefresh(table.id);
+                    })();
+                } else {
+                    // For existing tables, continue with normal interval
+                    const initialTimeout = setTimeout(async () => {
+                        if (!isActiveRef.current.get(table.id)) {
+                            return;
+                        }
+                        await performRefresh(table);
+                        scheduleNextRefresh(table.id);
+                    }, intervalMs);
+
+                    timeoutRefs.current.set(table.id, initialTimeout);
+                }
+            }
+        });
 
-                timeoutRefs.current.set(table.id, initialTimeout);
+        // Clean up tables that no longer exist from the initialized set
+        const currentTableIds = new Set(tables.map(t => t.id));
+        initializedTablesRef.current.forEach(tableId => {
+            if (!currentTableIds.has(tableId)) {
+                initializedTablesRef.current.delete(tableId);
             }
         });
 
diff --git a/src/views/DataFormulator.tsx b/src/views/DataFormulator.tsx
index 35b9130..f9cea9d 100644
--- a/src/views/DataFormulator.tsx
+++ b/src/views/DataFormulator.tsx
@@ -55,9 +55,6 @@ export const DataFormulatorFC = ({ }) => {
     const theme = useTheme();
 
     const dispatch = useDispatch();
-
-    // Set up auto-refresh for streaming and database tables
-    const { manualRefresh, getRefreshInfo } = useDataRefresh();
     
     // Set up automatic refresh of derived tables when source data changes
     useDerivedTableRefresh();
diff --git a/src/views/ExampleSessions.tsx b/src/views/ExampleSessions.tsx
index f87e0e6..1564253 100644
--- a/src/views/ExampleSessions.tsx
+++ b/src/views/ExampleSessions.tsx
@@ -11,6 +11,7 @@ import {
     alpha,
     useTheme,
 } from '@mui/material';
+import StreamIcon from '@mui/icons-material/Stream';
 
 // Example session data for pre-built sessions
 export interface ExampleSession {
@@ -19,22 +20,33 @@ export interface ExampleSession {
     description: string;
     previewImage: string;
     dataFile: string;
+    live: boolean;
 }
 
 export const exampleSessions: ExampleSession[] = [
+    {
+        id: 'stock-prices-live',
+        title: 'Stock Prices (Live)',
+        description: 'Live stock prices for different companies',
+        previewImage: '/screenshot-stock-price-live-thumbnail.webp',
+        dataFile: '/df_stock_prices_live.json',
+        live: true,
+    },
     {
         id: 'gas-prices',
         title: 'Gas Prices',
         description: 'Weekly gas prices across different grades and formulations',
         previewImage: '/gas_prices-thumbnail.webp',
         dataFile: '/df_gas_prices.json',
+        live: false,
     },
     {
         id: 'global-energy',
         title: 'Global Energy',
         description: 'Explore global energy consumption and CO2 emissions data',
         previewImage: '/global_energy-thumbnail.webp',
-        dataFile: '/df_global_energy.json',
+        dataFile: '/df_global_energy.json', 
+        live: false,
     },
     {
         id: 'movies',
@@ -42,6 +54,7 @@ export const exampleSessions: ExampleSession[] = [
         description: 'Analyze movie performance, budgets, and ratings data',
         previewImage: '/movies-thumbnail.webp',
         dataFile: '/df_movies.json',
+        live: false,
     },
     {
         id: 'unemployment',
@@ -49,6 +62,7 @@ export const exampleSessions: ExampleSession[] = [
         description: 'Unemployment rates across different industries over time',
         previewImage: '/unemployment-thumbnail.webp',
         dataFile: '/df_unemployment.json',
+        live: false,
     }
 ];
 
@@ -66,7 +80,7 @@ export const ExampleSessionCard: React.FC<{
                 cursor: disabled ? 'default' : 'pointer',
                 '&:hover': disabled ? {} : {
                     transform: 'translateY(-2px)',
-                    borderColor: alpha(theme.palette.primary.main, 0.4),
+                    borderColor: session.live ? alpha(theme.palette.secondary.main, 0.4) : alpha(theme.palette.primary.main, 0.4),
                 },
             }}
             onClick={disabled ? undefined : onClick}
@@ -111,7 +125,7 @@ export const ExampleSessionCard: React.FC<{
                             overflow: 'hidden'
                         }}
                     >
-                        <span style={{textDecoration: 'underline'}}>{session.title}:</span> {session.description}
+                        {session.live && <StreamIcon sx={{ fontSize: 10, color: 'success.main' }} />} <span style={{textDecoration: 'underline'}}>{session.title}:</span> {session.description}
                     </Typography>
                 </Box>
             </CardContent>

From bdc231c7cf6d376da7cec90861783f3d75e25cbb Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Mon, 26 Jan 2026 16:56:16 -0800
Subject: [PATCH 20/21] wording

---
 README.md | 11 ++++-------
 1 file changed, 4 insertions(+), 7 deletions(-)

diff --git a/README.md b/README.md
index c42d2be..5b4f9e8 100644
--- a/README.md
+++ b/README.md
@@ -32,9 +32,9 @@ https://github.com/user-attachments/assets/8ca57b68-4d7a-42cb-bcce-43f8b1681ce2
 
 
 ## News 🔥🔥🔥
-[01-25-2025] **Data Formulator 0.6** — Explore live data with real-time insights
--  ⚡ **Connect to live data**: Connect to URLs and databases with automatic refresh intervals. Visualizations update automatically as your data changes to provide you live insights. [Example: Stock market data from Yahoo Finance](https://github.com/microsoft/data-formulator/pull/200#issue-3635408217)
--  🎨 **UI Updates**: Directly drag-and-drop fields from the data table to update visualization designs.
+[01-25-2025] **Data Formulator 0.6** — Real-time insights from live data
+-  ⚡ **Connect to live data**: Connect to URLs and databases with automatic refresh intervals. Visualizations update automatically as your data changes to provide you live insights. [Demo: track international space station position speed live](https://github.com/microsoft/data-formulator/releases/tag/0.6)
+-  🎨 **UI Updates**: Unified UI for data loading; direct drag-and-drop fields from the data table to update visualization designs.
 
 [12-08-2025] **Data Formulator 0.5.1** — Connect more, visualize more, move faster
 - 🔌 **Community data loaders**: Google BigQuery, MySQL, Postgres, MongoDB
@@ -45,10 +45,7 @@ https://github.com/user-attachments/assets/8ca57b68-4d7a-42cb-bcce-43f8b1681ce2
 [11-07-2025] Data Formulator 0.5: Vibe with your data, in control
 
 - 📊 **Load (almost) any data**: load structured data, extract data from screenshots, from messy text blocks, or connect to databases.
-- 🤖 **Explore data with AI agents**: 
-  - In agent mode, provide a high-level goal and ask agents to explore data for you.
-  - To stay in control, directly interact with agents: ask for recommendations or specify chart designs with UI + NL inputs, and AI agents will formulate data to realize your design.
-  - Use data threads to control branching exploration paths: backtrack, branch, or follow up.
+- 🤖 **Explore data with AI agents**: Use agent mode for hands-off exploration, or stay in control in interactive mode.
 - ✅ **Verify AI generated results**: interact with charts and inspect data, formulas, explanations, and code.
 - 📝 **Create reports to share insights**: choose charts you want to share, and ask agents to create reports grounded in data formulated throughout exploration.
 

From 6c3abf347ddc5c41b97314670d38d58916987c8a Mon Sep 17 00:00:00 2001
From: Chenglong Wang <chenglong.wang@microsoft.com>
Date: Mon, 26 Jan 2026 16:58:24 -0800
Subject: [PATCH 21/21] update dev container

---
 .devcontainer/devcontainer.json | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index 0567c8a..4e9cd33 100644
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -17,7 +17,7 @@
 	// "forwardPorts": [],
 
 	// Use 'postCreateCommand' to run commands after the container is created.
-	"postCreateCommand": "python3 -m venv /workspaces/data-formulator/venv && . /workspaces/data-formulator/venv/bin/activate && pip install https://github.com/user-attachments/files/17319752/data_formulator-0.1.0.tar.gz --verbose && data_formulator"
+	"postCreateCommand": "cd /workspaces/data-formulator && npm install && npm run build && python3 -m venv /workspaces/data-formulator/venv && . /workspaces/data-formulator/venv/bin/activate && pip install -e /workspaces/data-formulator --verbose && data_formulator"
 
 	// Configure tool-specific properties.
 	// "customizations": {},