diff --git a/README.md b/README.md index 4ac88ce..b1fafac 100644 --- a/README.md +++ b/README.md @@ -41,30 +41,53 @@ Store any data type an LLM can process: text, JSON, images, and files. All data - **Templates**: Enable dynamic value resolution with circular reference protection ### Automatic Tool Generation -Tools are automatically generated for each writable key, allowing agents to read and write memory without manual tool definitions. Tools integrate seamlessly with Vercel AI SDK. +Tools are automatically generated for each writable key, allowing agents to read and write memory without manual tool definitions. Tools integrate seamlessly with Vercel AI SDK and other AI frameworks. + +### Custom Types (v3.6+) +Define structured data schemas using human-readable Markdown, then assign types to keys for consistent LLM output: + +```typescript +// Define a custom type with Markdown schema +mc.registerType('Contact', ` +#Contact +* name: full name of the contact +* email: email address +* phone: phone number +* notes: any additional context +`); + +// Create a key with this type +mc.set_value('contact_alice', JSON.stringify({ name: 'Alice', email: 'alice@example.com' })); +mc.setType('contact_alice', 'Contact'); + +// LLM tools will enforce the schema +const tools = mc.create_vercel_ai_tools(); // For Vercel AI SDK +// or +const rawTools = mc.create_tools(); // For other frameworks (OpenAI, Anthropic, etc.) +``` ## Quick Start ```typescript -import { mindcache } from 'mindcache'; +import { MindCache } from 'mindcache'; + +const mc = new MindCache(); // Store values -mindcache.set_value('userName', 'Alice'); -mindcache.set_value('favoriteColor', 'blue'); +mc.set_value('userName', 'Alice'); +mc.set_value('favoriteColor', 'blue'); // Generate system prompt for your AI agent -const systemPrompt = mindcache.get_system_prompt(); -// "userName: Alice. You can rewrite \"userName\" by using the write_userName tool..." +const systemPrompt = mc.get_system_prompt(); // Generate tools for Vercel AI SDK -const tools = mindcache.get_aisdk_tools(); -// { write_userName: {...}, write_favoriteColor: {...} } +const tools = mc.create_vercel_ai_tools(); // Use with AI SDK import { generateText } from 'ai'; const { text } = await generateText({ model: openai('gpt-4'), - tools: tools, + tools, system: systemPrompt, prompt: 'Remember that I love green now, not blue.' }); @@ -145,19 +168,40 @@ mindcache.withContext({ includeTags: ['admin'] }, () => { ### Vercel AI SDK ```typescript import { streamText } from 'ai'; -import { mindcache } from 'mindcache'; +import { MindCache } from 'mindcache'; + +const mc = new MindCache(); +mc.set_value('userName', 'Alice', { systemTags: ['SystemPrompt', 'LLMRead', 'LLMWrite'] }); -const tools = mindcache.get_aisdk_tools(); -const systemPrompt = mindcache.get_system_prompt(); +const tools = mc.create_vercel_ai_tools(); +const systemPrompt = mc.get_system_prompt(); const result = await streamText({ model: openai('gpt-4'), - tools: tools, + tools, system: systemPrompt, prompt: userMessage }); ``` +### Other AI Frameworks (OpenAI, Anthropic, LangChain) +```typescript +import { MindCache } from 'mindcache'; + +const mc = new MindCache(); +const tools = mc.create_tools(); // Raw JSON Schema tools + +// Use with OpenAI SDK +const response = await openai.chat.completions.create({ + model: 'gpt-4', + tools: Object.values(tools).map(t => ({ + type: 'function', + function: { name: t.name, description: t.description, parameters: t.parameters } + })), + messages: [{ role: 'user', content: userMessage }] +}); +``` + ### Next.js See the [Next.js example](./examples/nextjs_demo) for a complete integration. @@ -256,13 +300,24 @@ export class MyDurableObject { ### Core Methods - `set_value(key, value, attributes?)` - Store a value with optional attributes - `get_value(key)` - Retrieve a value (supports template processing) -- `delete(key)` - Remove a key-value pair +- `delete_key(key)` - Remove a key-value pair - `has(key)` - Check if a key exists - `clear()` - Clear all memory +- `keys()` - Get all key names + +### Custom Types (v3.6+) +- `registerType(name, markdownSchema)` - Register a custom type with Markdown schema +- `setType(key, typeName)` - Assign a custom type to a key (also sets type to 'json') +- `getKeyType(key)` - Get the custom type name for a key +- `getTypeSchema(typeName)` - Get the parsed schema definition +- `getRegisteredTypes()` - List all registered type names + +### LLM Tool Generation +- `create_vercel_ai_tools()` - Generate Zod-based tools for Vercel AI SDK v5 +- `create_tools()` - Generate raw JSON Schema tools (OpenAI, Anthropic, LangChain) +- `get_system_prompt()` - Generate system prompt from visible keys ### Memory Management -- `get_system_prompt()` - Generate system prompt from visible keys -- `get_aisdk_tools()` - Generate tools for Vercel AI SDK - `injectSTM(template)` - Inject memory values into template strings - `getSTM()` - Get formatted string of all visible entries @@ -297,6 +352,7 @@ export class MyDurableObject { ## Examples See the [examples directory](./examples) for complete implementations: +- **[Contact Extractor](./examples/contact_extractor)** - AI-powered contact extraction using custom types - Form management with AI assistant - Image processing workflows - Multi-step workflows with memory persistence diff --git a/docs/llms-full.md b/docs/llms-full.md index 0c5d62e..5380d4e 100644 --- a/docs/llms-full.md +++ b/docs/llms-full.md @@ -338,6 +338,140 @@ const history = mc.getGlobalHistory(); --- +## Custom Types (v3.6+) + +Define structured data schemas using human-readable Markdown. Custom types guide LLM output to follow consistent schemas. + +### Registering a Type + +```typescript +import { MindCache } from 'mindcache'; + +const mc = new MindCache(); + +// Define a Contact type with Markdown schema +mc.registerType('Contact', ` +#Contact +* name: full name of the contact +* email: email address (primary) +* phone: phone number (mobile preferred) +* company: company or organization name +* role: job title or role +* notes: any additional context about this person +`); +``` + +### Assigning Types to Keys + +```typescript +// Create a key and assign the type +mc.set_value('contact_alice', JSON.stringify({ + name: 'Alice Smith', + email: 'alice@example.com', + company: 'Acme Corp', + role: 'Engineer' +}), { + systemTags: ['SystemPrompt', 'LLMRead', 'LLMWrite'] +}); + +// Assign the custom type (also sets underlying type to 'json') +mc.setType('contact_alice', 'Contact'); +``` + +### Querying Types + +```typescript +// Get the custom type for a key +const typeName = mc.getKeyType('contact_alice'); +// Returns: 'Contact' + +// Get the schema definition +const schema = mc.getTypeSchema('Contact'); +// Returns: { name: 'Contact', fields: [...], rawSchema: '...' } + +// List all registered types +const types = mc.getRegisteredTypes(); +// Returns: ['Contact'] +``` + +### LLM Tool Integration + +When a key has a custom type, the generated tools include schema guidance: + +```typescript +// Generate tools - schema is embedded in tool descriptions +const tools = mc.create_vercel_ai_tools(); + +// The write_contact_alice tool description includes: +// - The Contact schema fields +// - Example JSON format +// - Guidance for the LLM to follow the schema +``` + +### System Prompt with Types + +The system prompt automatically includes type information: + +```typescript +const systemPrompt = mc.get_system_prompt(); +// Includes: +// - Available types (Contact) +// - Keys with their types +// - Schema definitions for each typed key +``` + +### Framework-Agnostic Tools + +```typescript +// For Vercel AI SDK v5 (uses Zod schemas + tool() helper) +const vercelTools = mc.create_vercel_ai_tools(); + +// For other frameworks (raw JSON Schema) +const rawTools = mc.create_tools(); +// Works with: OpenAI SDK, Anthropic SDK, LangChain, etc. +``` + +### Complete Example: Contact Manager + +```typescript +import { MindCache } from 'mindcache'; +import { generateText } from 'ai'; +import { openai } from '@ai-sdk/openai'; + +const mc = new MindCache(); + +// Register Contact type +mc.registerType('Contact', ` +#Contact +* name: full name +* email: email address +* phone: phone number +* notes: additional context +`); + +// Create initial contact +mc.set_value('contact_bob', JSON.stringify({ + name: 'Bob Jones', + email: 'bob@example.com' +}), { systemTags: ['SystemPrompt', 'LLMRead', 'LLMWrite'] }); +mc.setType('contact_bob', 'Contact'); + +// Let LLM update contact +const tools = mc.create_vercel_ai_tools(); +const { text } = await generateText({ + model: openai('gpt-4'), + tools, + system: mc.get_system_prompt(), + prompt: 'Add phone number 555-1234 to Bob' +}); + +// Contact is updated with proper schema +console.log(mc.get_value('contact_bob')); +// { name: 'Bob Jones', email: 'bob@example.com', phone: '555-1234' } +``` + +--- + ## Attributes & Metadata ### Available Attributes @@ -601,13 +735,13 @@ const userEntries = Object.entries(mindcache.getAll()) ## LLM Tool Generation -MindCache automatically generates tools for Vercel AI SDK. +MindCache automatically generates tools for AI frameworks. -### Generating Tools +### Generating Tools for Vercel AI SDK ```typescript -// Signature -get_aisdk_tools(): Record +// For Vercel AI SDK v5 (uses Zod schemas + tool() helper) +const tools = mc.create_vercel_ai_tools(); // Setup mindcache.set_value('userName', 'Alice'); @@ -1902,9 +2036,15 @@ const all = mindcache.getAll(); const result = mindcache.injectSTM('Hello {{name}}!'); // LLM tools -const tools = mindcache.get_aisdk_tools(); +const tools = mindcache.create_vercel_ai_tools(); // For Vercel AI SDK +const rawTools = mindcache.create_tools(); // For other frameworks const prompt = mindcache.get_system_prompt(); +// Custom types (v3.6+) +mindcache.registerType('Contact', '#Contact\n* name: full name\n* email: email'); +mindcache.setType('contact_alice', 'Contact'); +const typeName = mindcache.getKeyType('contact_alice'); + // Tags mindcache.addTag('key', 'tagName'); const tagged = mindcache.getTagged('tagName'); diff --git a/examples/contact_extractor/README.md b/examples/contact_extractor/README.md new file mode 100644 index 0000000..4dbfa36 --- /dev/null +++ b/examples/contact_extractor/README.md @@ -0,0 +1,82 @@ +# Contact Extractor + +A simple example demonstrating MindCache's custom type system with AI-powered contact extraction. + +## Features + +- **Drop Zone**: Drag and drop text files or paste content directly +- **AI Extraction**: Uses OpenAI to extract contact information from any content +- **Custom Types**: Contacts are stored using MindCache's new `registerType()` feature +- **Real-time Updates**: Contact cards update instantly via MindCache subscriptions + +## MindCache Custom Type + +This example registers a `Contact` type with the following schema: + +```markdown +#Contact +* name: full name of the contact +* email: email address +* phone: phone number +* company: company or organization +* role: job title or role +* notes: any additional notes +``` + +## Setup + +1. Copy the environment file: + ```bash + cp env.example .env.local + ``` + +2. Add your OpenAI API key to `.env.local` + +3. Install dependencies: + ```bash + npm install + ``` + +4. Run the development server: + ```bash + npm run dev + ``` + +5. Open [http://localhost:3000](http://localhost:3000) + +## Usage + +1. Paste or drop any content containing contact information: + - Email signatures + - Business cards (text) + - Contact lists + - Meeting notes + - Any text with names, emails, phones, etc. + +2. Click "Extract Contacts" or drop content directly + +3. View extracted contacts as cards on the right panel + +## How It Works + +```typescript +// Register the Contact type +mc.registerType('Contact', ` +#Contact +* name: full name of the contact +* email: email address +... +`); + +// Create a contact and assign the type +mc.set_value('contact_123', JSON.stringify(contact), { systemTags: ['LLMWrite'] }); +mc.setType('contact_123', 'Contact'); + +// Query contacts by type +for (const key of mc.keys()) { + if (mc.getKeyType(key) === 'Contact') { + const contact = JSON.parse(mc.get_value(key)); + // ... + } +} +``` diff --git a/examples/contact_extractor/env.example b/examples/contact_extractor/env.example new file mode 100644 index 0000000..8772d73 --- /dev/null +++ b/examples/contact_extractor/env.example @@ -0,0 +1,2 @@ +# OpenAI API Key for contact extraction +OPENAI_API_KEY=sk-... diff --git a/examples/contact_extractor/next-env.d.ts b/examples/contact_extractor/next-env.d.ts new file mode 100644 index 0000000..830fb59 --- /dev/null +++ b/examples/contact_extractor/next-env.d.ts @@ -0,0 +1,6 @@ +/// +/// +/// + +// NOTE: This file should not be edited +// see https://nextjs.org/docs/app/api-reference/config/typescript for more information. diff --git a/examples/contact_extractor/next.config.js b/examples/contact_extractor/next.config.js new file mode 100644 index 0000000..1713e9d --- /dev/null +++ b/examples/contact_extractor/next.config.js @@ -0,0 +1,9 @@ +/** @type {import('next').NextConfig} */ +const path = require('path'); + +const nextConfig = { + reactStrictMode: true, + outputFileTracingRoot: path.join(__dirname), +} + +module.exports = nextConfig diff --git a/examples/contact_extractor/package-lock.json b/examples/contact_extractor/package-lock.json new file mode 100644 index 0000000..d6243ee --- /dev/null +++ b/examples/contact_extractor/package-lock.json @@ -0,0 +1,2262 @@ +{ + "name": "contact-extractor", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": 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"lint": "next lint" + }, + "dependencies": { + "@ai-sdk/openai": "^2.0.30", + "ai": "^5.0.45", + "lucide-react": "^0.511.0", + "mindcache": "file:../../packages/mindcache", + "next": "^15.5.7", + "react": "^19", + "react-dom": "^19", + "zod": "^4.1.9" + }, + "devDependencies": { + "@types/node": "^20", + "@types/react": "^19", + "@types/react-dom": "^19", + "autoprefixer": "^10.0.1", + "postcss": "^8", + "tailwindcss": "^3.3.0", + "typescript": "^5.3.0" + } +} diff --git a/examples/contact_extractor/postcss.config.js b/examples/contact_extractor/postcss.config.js new file mode 100644 index 0000000..33ad091 --- /dev/null +++ b/examples/contact_extractor/postcss.config.js @@ -0,0 +1,6 @@ +module.exports = { + plugins: { + tailwindcss: {}, + autoprefixer: {}, + }, +} diff --git a/examples/contact_extractor/src/app/api/extract/route.ts b/examples/contact_extractor/src/app/api/extract/route.ts new file mode 100644 index 0000000..ee2ed03 --- /dev/null +++ b/examples/contact_extractor/src/app/api/extract/route.ts @@ -0,0 +1,101 @@ +import { openai } from '@ai-sdk/openai'; +import { generateText } from 'ai'; +import { MindCache } from 'mindcache/server'; + +// Contact type schema +const CONTACT_SCHEMA = ` +#Contact +* name: full name of the contact +* email: email address (primary) +* phone: phone number (mobile preferred) +* company: company or organization name +* role: job title or role +* address: physical address +* linkedin: LinkedIn profile URL +* twitter: Twitter/X handle +* birthday: birthday in YYYY-MM-DD format +* notes: any additional notes or context about this person +`; + +export async function POST(request: Request) { + try { + const { content, existingContacts } = await request.json(); + + if (!content || typeof content !== 'string') { + return Response.json({ error: 'Content is required' }, { status: 400 }); + } + + // Create a temporary MindCache with existing contacts + const mc = new MindCache(); + mc.registerType('Contact', CONTACT_SCHEMA); + + // Hydrate with existing contacts + if (existingContacts) { + for (const [key, contact] of Object.entries(existingContacts)) { + mc.set_value(key, JSON.stringify(contact), { + systemTags: ['SystemPrompt', 'LLMRead', 'LLMWrite'] + }); + mc.setType(key, 'Contact'); + } + } + + // Get system prompt and tools from MindCache + const systemPrompt = mc.get_system_prompt(); + const tools = mc.create_vercel_ai_tools(); + + // Run agent with tools + const result = await generateText({ + model: openai('gpt-4o-mini'), + tools, + toolChoice: 'required' as const, + system: `You are a contact management assistant. You manage contacts using MindCache tools. + +EXISTING DATA: +${systemPrompt || '(no contacts yet)'} + +TOOLS: +- create_key: Create a NEW contact. Use key like "contact_john_doe", value is JSON string, type is "Contact" +- write_: Update an existing contact (rewrite with FULL merged JSON) + +RULES: +1. ALWAYS prefer UPDATING existing contacts over creating new ones +2. If a person already exists, use write_ to UPDATE with merged data +3. Only use create_key for people NOT already in the database +4. When updating, MERGE new info with existing - don't lose existing fields! +5. Value must be a JSON string with fields: name, email, phone, company, role, address, linkedin, twitter, birthday, notes +6. When creating, always set type to "Contact" +7. If the information is in CSV format, you have to process it and create a new contact for each row. +8. If the information is about a contact, you have to create a new contact or update the existing one. +9. More generally, do what seems more appropriate.`, + prompt: content, + }); + + // Collect all the contacts that were modified + const updatedContacts: Array<{ key: string; contact: any }> = []; + + for (const key of mc.keys()) { + if (mc.getKeyType(key) === 'Contact') { + const value = mc.get_value(key); + if (value) { + try { + const contact = typeof value === 'string' ? JSON.parse(value) : value; + updatedContacts.push({ key, contact }); + } catch { + // Skip invalid + } + } + } + } + + return Response.json({ + contacts: updatedContacts, + message: result.text + }); + } catch (error) { + console.error('Agent error:', error); + return Response.json( + { error: 'Failed to process contacts' }, + { status: 500 } + ); + } +} diff --git a/examples/contact_extractor/src/app/globals.css b/examples/contact_extractor/src/app/globals.css new file mode 100644 index 0000000..20bd83d --- /dev/null +++ b/examples/contact_extractor/src/app/globals.css @@ -0,0 +1,69 @@ +@tailwind base; +@tailwind components; +@tailwind utilities; + +@import url('https://fonts.googleapis.com/css2?family=JetBrains+Mono:wght@400;500&display=swap'); + +:root { + --bg-primary: #0a0a0f; + --bg-secondary: #12121a; + --bg-card: #1a1a24; + --accent: #6366f1; + --accent-glow: rgba(99, 102, 241, 0.3); + --text-primary: #f8fafc; + --text-secondary: #94a3b8; + --border: #2a2a3a; +} + +body { + background: var(--bg-primary); + color: var(--text-primary); +} + +.drop-zone { + border: 2px dashed var(--border); + transition: all 0.3s ease; +} + +.drop-zone.drag-over { + border-color: var(--accent); + background: var(--accent-glow); +} + +.contact-card { + background: var(--bg-card); + border: 1px solid var(--border); + transition: all 0.2s ease; +} + +.contact-card:hover { + border-color: var(--accent); + transform: translateY(-2px); + box-shadow: 0 8px 32px rgba(99, 102, 241, 0.15); +} + +.scrollbar-thin::-webkit-scrollbar { + width: 6px; +} + +.scrollbar-thin::-webkit-scrollbar-track { + background: var(--bg-secondary); +} + +.scrollbar-thin::-webkit-scrollbar-thumb { + background: var(--border); + border-radius: 3px; +} + +.scrollbar-thin::-webkit-scrollbar-thumb:hover { + background: var(--accent); +} + +@keyframes pulse-glow { + 0%, 100% { box-shadow: 0 0 20px var(--accent-glow); } + 50% { box-shadow: 0 0 40px var(--accent-glow); } +} + +.processing { + animation: pulse-glow 2s ease-in-out infinite; +} diff --git a/examples/contact_extractor/src/app/layout.tsx b/examples/contact_extractor/src/app/layout.tsx new file mode 100644 index 0000000..07c2d73 --- /dev/null +++ b/examples/contact_extractor/src/app/layout.tsx @@ -0,0 +1,21 @@ +import type { Metadata } from 'next' +import './globals.css' + +export const metadata: Metadata = { + title: 'Contact Extractor - MindCache', + description: 'Extract contacts from any content using AI and MindCache custom types', +} + +export default function RootLayout({ + children, +}: { + children: React.ReactNode +}) { + return ( + + + {children} + + + ) +} diff --git a/examples/contact_extractor/src/app/page.tsx b/examples/contact_extractor/src/app/page.tsx new file mode 100644 index 0000000..527764d --- /dev/null +++ b/examples/contact_extractor/src/app/page.tsx @@ -0,0 +1,407 @@ +"use client"; + +import { useState, useEffect, useRef, useCallback } from 'react'; +import { MindCache } from 'mindcache'; +import { Upload, User, Mail, Phone, Building, FileText, Trash2, Sparkles, MapPin, Linkedin, Twitter, Calendar, ArrowDownAZ, Download } from 'lucide-react'; + +// Contact type schema (matching our MindCache custom type) +const CONTACT_SCHEMA = ` +#Contact +* name: full name of the contact +* email: email address (primary) +* phone: phone number (mobile preferred) +* company: company or organization name +* role: job title or role +* address: physical address +* linkedin: LinkedIn profile URL +* twitter: Twitter/X handle +* birthday: birthday in YYYY-MM-DD format +* notes: any additional notes or context about this person +`; + +interface Contact { + name: string; + email?: string; + phone?: string; + company?: string; + role?: string; + address?: string; + linkedin?: string; + twitter?: string; + birthday?: string; + notes?: string; +} + +export default function Home() { + const [contacts, setContacts] = useState>(new Map()); + const [isDragOver, setIsDragOver] = useState(false); + const [isProcessing, setIsProcessing] = useState(false); + const [inputText, setInputText] = useState(''); + const mindCacheRef = useRef(null); + + // Initialize MindCache with Contact type and IndexedDB persistence + useEffect(() => { + const mc = new MindCache({ + indexedDB: { dbName: 'contact_extractor' } + }); + mc.registerType('Contact', CONTACT_SCHEMA); + mindCacheRef.current = mc; + + // Subscribe to all changes - use getSortedKeys() for zIndex ordering + const unsubscribe = mc.subscribeToAll(() => { + const newContacts = new Map(); + // getSortedKeys() returns keys sorted by zIndex (ascending) + for (const key of mc.getSortedKeys()) { + if (mc.getKeyType(key) === 'Contact') { + const value = mc.get_value(key); + if (value) { + try { + const parsed = typeof value === 'string' ? JSON.parse(value) : value; + newContacts.set(key, parsed); + } catch { + // Skip invalid entries + } + } + } + } + setContacts(newContacts); + }); + + return () => unsubscribe(); + }, []); + + const processContent = async (content: string) => { + if (!content.trim()) return; + + setIsProcessing(true); + try { + const mc = mindCacheRef.current; + if (!mc) return; + + // Collect existing contacts to send to the agent + const existingContacts: Record = {}; + for (const key of mc.keys()) { + if (mc.getKeyType(key) === 'Contact') { + const value = mc.get_value(key); + if (value) { + try { + existingContacts[key] = typeof value === 'string' ? JSON.parse(value) : value; + } catch { + // Skip invalid entries + } + } + } + } + + const response = await fetch('/api/extract', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ content, existingContacts }), + }); + + if (!response.ok) throw new Error('Processing failed'); + + const { contacts: updatedContacts } = await response.json(); + + // Agent has already processed - sync results to local MindCache + if (updatedContacts?.length) { + for (const { key, contact } of updatedContacts) { + mc.set_value(key, JSON.stringify(contact), { + type: 'json', + systemTags: ['SystemPrompt', 'LLMRead', 'LLMWrite'] + }); + mc.setType(key, 'Contact'); + } + } + + // Sort contacts alphabetically after processing + sortContacts(); + + setInputText(''); + } catch (error) { + console.error('Failed to process:', error); + alert('Failed to process. Check console for details.'); + } finally { + setIsProcessing(false); + } + }; + + const handleDrop = useCallback(async (e: React.DragEvent) => { + e.preventDefault(); + setIsDragOver(false); + + const files = Array.from(e.dataTransfer.files); + const textFile = files.find(f => f.type.startsWith('text/') || f.name.endsWith('.txt') || f.name.endsWith('.md')); + + if (textFile) { + const text = await textFile.text(); + processContent(text); + } else if (e.dataTransfer.getData('text')) { + processContent(e.dataTransfer.getData('text')); + } + }, []); + + const handlePaste = useCallback((e: React.ClipboardEvent) => { + const text = e.clipboardData.getData('text'); + if (text) { + setInputText(text); + } + }, []); + + const deleteContact = (key: string) => { + mindCacheRef.current?.delete_key(key); + }; + + const clearAll = () => { + const mc = mindCacheRef.current; + if (!mc) return; + const keysToDelete = mc.keys().filter(key => mc.getKeyType(key) === 'Contact'); + keysToDelete.forEach(key => mc.delete_key(key)); + }; + + // Export contacts to Markdown file + const exportContacts = () => { + const mc = mindCacheRef.current; + if (!mc) return; + + const markdown = mc.toMarkdown(); + const blob = new Blob([markdown], { type: 'text/markdown' }); + const url = URL.createObjectURL(blob); + const a = document.createElement('a'); + a.href = url; + a.download = `contacts_${new Date().toISOString().split('T')[0]}.md`; + document.body.appendChild(a); + a.click(); + document.body.removeChild(a); + URL.revokeObjectURL(url); + }; + + // Sort contacts alphabetically by name using MindCache zIndex + const sortContacts = () => { + const mc = mindCacheRef.current; + if (!mc) return; + + // Get all contact keys with their names + const contactEntries: { key: string; name: string }[] = []; + for (const key of mc.keys()) { + if (mc.getKeyType(key) === 'Contact') { + const value = mc.get_value(key); + if (value) { + try { + const parsed = typeof value === 'string' ? JSON.parse(value) : value; + contactEntries.push({ key, name: parsed.name || '' }); + } catch { + contactEntries.push({ key, name: '' }); + } + } + } + } + + // Sort alphabetically by name + contactEntries.sort((a, b) => a.name.localeCompare(b.name)); + + // Update zIndex for each contact + contactEntries.forEach((entry, index) => { + mc.set_attributes(entry.key, { zIndex: index }); + }); + }; + + return ( +
+ {/* Left Panel - Drop Zone */} +
+
+

+ + Contact Extractor +

+

+ Drop or paste any content to extract contacts using AI +

+
+ +
{ e.preventDefault(); setIsDragOver(true); }} + onDragLeave={() => setIsDragOver(false)} + onDrop={handleDrop} + > + {isProcessing ? ( +
+
+

Agent processing...

+
+ ) : ( + <> + +

Drop files or paste content here

+

+ Supports text files, emails, business cards, etc. +

+ + )} +
+ +
+