This project implements a chess coaching application with AI agents that can analyze chess positions, suggest moves, and provide strategic advice. The system combines a modern React frontend with a Python-based AI agent backend.
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This project implements a chess coaching application with AI agents that can analyze chess positions, suggest moves, and provide strategic advice. The system combines a modern React frontend with a Python-based AI agent backend.
Purpose: Provides chess analysis, move suggestions, and strategic coaching
Capabilities:
Technical Implementation:
State Schema:
type ChessState = { position: string; // FEN notation of current board position }
# Install frontend dependencies npm install # Install Python agent dependencies npm run install:agent # Set environment variables export OPENAI_API_KEY="your-api-key"
# Start both frontend and agent servers npm run dev # Or run separately npm run dev:ui # Frontend only npm run dev:agent # Agent only
The system uses standard FEN (Forsyth-Edwards Notation) for position representation:
rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1src/ ├── app/ │ ├── page.tsx # Main application component │ └── api/copilotkit/ # CopilotKit API routes ├── components/ │ ├── ChessBoard.tsx # Interactive chess board │ └── WeatherCard.tsx # Example component (legacy) agent/ ├── agent/ │ ├── agent.py # Chess assistant agent │ └── server.py # FastAPI server └── pyproject.toml # Python dependencies