Semiconductor Component RAG Search

# Quick Start Guide ## 🚀 Get Started in 3 Steps ### Step 1: Install Dependencies ```bash pip install -r requirements.txt ``` ### Step 2: Create Example Data ```bash python create_example_excel.py ``` ### Step 3: Start the Server ```bash python main.py ``` The API will be available at: **http://localhost:8000** ## 📤 Upload Document Open browser: **http://localhost:8000/docs** Or use curl: ```bash curl -X POST "http://localhost:8000/upload" \ -F "file=@examples/semiconductor_components.xlsx" ``` ## ❓ Ask Questions **Via Browser:** - Go to http://localhost:8000/docs - Click on `/ask` endpoint - Click "Try it out" - Enter question: `"What MOSFET components are available?"` - Click "Execute" **Via curl:** ```bash curl -X POST "http://localhost:8000/ask" \ -H "Content-Type: application/json" \ -d '{"question": "What MOSFET components are available?", "n_results": 3}' ``` ## 🎯 Example Questions - "What MOSFET components are available?" - "Show me voltage regulators" - "What components work with 5V?" - "List components from Texas Instruments" ## 📚 Full Documentation - **README.md** - Overview - **USAGE.md** - Detailed usage - **PROJECT_SUMMARY.md** - Complete project details ## ✅ Verify Setup ```bash # Check API health curl http://localhost:8000/health # Check collection info curl http://localhost:8000/info # Run automated tests python test_api.py ``` ## 🎓 Understanding MCP **MCP Purpose**: Standardized protocol for context retrieval **How it works here:** 1. MCP Server defines tools for ChromaDB access 2. RAG Pipeline uses MCP principles for retrieval 3. Questions trigger MCP tool calls → ChromaDB → LLM → Answer See `PROJECT_SUMMARY.md` for detailed explanation!