Update README.md

README.md

@@ -1,27 +1,55 @@
 ---
-title: SafetyAI
-emoji: 💬
-colorFrom: yellow
-colorTo: purple
-app_file: app.py
+title: YourAI - LightRAG Powered
+emoji: 🔥
+colorFrom: red
+colorTo: yellow
+sdk: docker
 pinned: false
 license: mit
-sdk: docker
-short_description: A FastAPI-based AI application for fire safety, general, and
+app_port: 7860
 ---
 
-# YourAI Multi-Model API
+# YourAI - LightRAG Powered
+
+A sophisticated AI assistant powered by LightRAG (Retrieval-Augmented Generation) with conversation memory and custom AI creation capabilities.
+
+## Features
+
+🔥 **Fire Safety AI** - Specialized AI for fire safety regulations and codes
+🤖 **General AI** - General-purpose conversational AI with memory
+🛠️ **Custom AI Builder** - Create your own AI with uploaded knowledge
+💬 **Conversation Memory** - Maintains context within conversations
+📚 **Knowledge Management** - Advanced GraphRAG for better information retrieval
+
+## How to Use
+
+1. **Chat with Fire Safety AI** - Ask questions about fire safety regulations
+2. **General Chat** - Have conversations with context awareness
+3. **Create Custom AI** - Upload documents to create specialized AI assistants
+4. **Manage Conversations** - View and manage your chat history
+
+## Technology Stack
+
+- **LightRAG**: Advanced retrieval-augmented generation
+- **Cloudflare Workers AI**: LLM and embedding models
+- **FastAPI**: High-performance API framework
+- **NetworkX**: Graph storage for knowledge relationships
+- **NanoVectorDB**: Vector storage for embeddings
+
+## API Endpoints
+
+- `POST /chat/fire-safety` - Chat with fire safety AI
+- `POST /chat/general` - General conversation
+- `POST /chat/custom/{ai_id}` - Chat with custom AI
+- `POST /create-custom-ai` - Create custom AI
+- `POST /upload` - Upload knowledge files
+- `GET /conversations` - Get user conversations
 
-A FastAPI-based AI application for fire safety, general, and custom AI interactions with PostgreSQL, Redis, and Cloudflare Worker integration.
+## Models Used
 
-## Setup
+- **LLM**: `@cf/meta/llama-3.2-3b-instruct`
+- **Embedding**: `@cf/baai/bge-m3`
 
-### App Type
-- **Framework**: FastAPI
-- **Port**: 7860
-- **Command**: `uvicorn app:app --host 0.0.0.0 --port 7860`
+## License
 
-### Dependencies
-Install dependencies from `requirements.txt`:
-```bash
-pip install -r requirements.txt
+MIT License - Feel free to use and modify!