We believe that every SOTA result is only valid on its own dataset. RAGView provides a unified evaluation platform to benchmark different RAG methods on your specific data.
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Updated
Oct 11, 2025
We believe that every SOTA result is only valid on its own dataset. RAGView provides a unified evaluation platform to benchmark different RAG methods on your specific data.
Generate & Ship UI with minimal effort - Open Source Generative UI with natural language
Modular full-stack ML project leveraging Groq API, Streamlit, Supabase, JSON, SciPy, SciKit-Learn, Plotly & EmailJS, alongside libraries - NumPy, Pandas, Utils, OS, Base64, Re, Pillow & DateTime.
Quickest way to production grade RAG UI.
AI-powered mock interview platform using Next.js, Gemini AI, Drizzle, NeonDB, and Clerk for dynamic questions, feedback & session recording, plus Dockerized microservices bypassing API rate limiting.
A minimal Agentic RAG demo built with LangGraph — learn Retrieval-Augmented Agents in minutes.
Vectrain is a high-performance, modular, plug-and-play RAG pipeline that ingests data, generates vector embeddings, and stores them in vector databases for semantic search, recommendations, and analytics.
Build a RAG preprocessing pipeline
Production-ready Chainlit RAG application with Pinecone pipeline offering all Groq and OpenAI Models, to chat with your documents.
Search for a holiday and get destination advice from an LLM. Observability by Dynatrace.
An intelligent customer support system powered by LangGraph and LangChain that uses Retrieval-Augmented Generation (RAG) to provide accurate, context-aware responses to customer queries. Built with FastAPI, FAISS, and multi-stage validation for production-ready deployment.
When retrieval outperforms generation: Dense evidence retrieval for scalable fake news detection - LDK 2025
Good Memory aims to be a dependable, friendly, intelligent memory layer for agents.
The Audited Context Generation (ACG) Protocol prevents AI hallucinations with a dual-layer system. The UGVP layer links every fact to a precise source for verification. The RSVP layer audits the AI's logical reasoning when combining facts. This creates a fully transparent, machine-auditable trail for both source and logical integrity.
🤖 AI-Powered PDF Chat App | Dual AI Engine (Alchemyst + Gemini) | RAG Pipeline | Vector Search | MERN + TypeScript
Learn Retrieval-Augmented Generation (RAG) from Scratch using LLMs from Hugging Face and Langchain or Python
🛡️ Web3 Guardian is a comprehensive security suite for Web3 that combines browser extension and backend services to provide real-time transaction analysis, smart contract auditing, and risk assessment for decentralized applications (dApps).
This project demonstrates a real-time AI "Meeting Coach" showcasing the use of Confluent Cloud for Apache Flink AI Inference functions to build a real-time Retrieval-Augmented Generation (RAG) pipeline. The demo uses both a static knowledge base of sales documents and real-time simulated meeting data.
This repo is for advanced RAG systems, each branch will represent a project based on RAG.
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