This project implements an AI-powered chess game using multiple agents, natural language processing, and machine learning techniques. The game allows two AI agents to play chess against each other, with moves determined by a combination of chess engine analysis and language model reasoning.

• Multi-agent system with specialized roles:

  • White Player Agent: Aggressive style with sound principles
  • Black Player Agent: Solid positional play focus
  • Board Proxy Agent: Manages game state and move validation
  • Commentator Agent: Provides engaging game analysis

• Advanced Chess Engine:

  • Position evaluation using material and positional factors
  • Opening principles enforcement
  • Tactical awareness
  • King safety evaluation

• Interactive Web Interface:

  • Real-time game visualization
  • Move validation
  • PGN export functionality
  • Game state management via WebSocket
  • Detailed game analysis and commentary

• RAG (Retrieval Augmented Generation):

  • Integrated chess knowledge base
  • Position-specific strategy retrieval
  • Dynamic game analysis

• Backend Framework: Flask with SocketIO

• AI/ML Components:

  • AutoGen for multi-agent orchestration
  • LangChain for RAG implementation
  • OpenAI GPT-4 for strategic decision making
  • Custom Chess Engine for position evaluation

• Libraries:

  • python-chess: Core chess logic
  • ChromaDB: Vector store for chess knowledge
  • PyTorch: Neural network operations
  • Eventlet: Async operations

1. Clone the repository:

git clone <repository-url>
cd chess-ai-project

1. Install dependencies:

pip install -r requirements.txt

1. Set up environment variables:

cp .env.example .env
# Edit .env and add your OpenAI API key

1. Start the server:

python app.py

2. Access the application:

Local: http://localhost:5001
Network: http://0.0.0.0:5001

• White Player Agent:

  • Aggressive style
  • Focuses on tactical opportunities
  • Follows sound opening principles

• Black Player Agent:

  • Positional play style
  • Emphasis on solid pawn structure
  • Strategic piece placement

• Board Proxy Agent:

  • Manages game state
  • Validates moves
  • Tracks game progress

• Commentator Agent:

  • Provides move analysis
  • Offers strategic insights
  • Explains key positions

• Material evaluation
• Positional assessment
• Opening principles enforcement
• King safety evaluation
• Tactical awareness
• Move validation system

• Real-time board updates
• Move validation
• Game state management
• PGN export
• Game analysis display
• WebSocket communication

├── app.py                 # Main application file
├── models/
│   └── base_model.py     # Chess engine implementation
├── static/               # Frontend assets
├── templates/           # HTML templates
└── requirements.txt     # Project dependencies

• /: Main chess interface
• /export_pgn: PGN export endpoint

• connect: Initial connection
• make_move: Handle player moves
• request_ai_move: Request AI move
• reset_game: Reset game state
• get_game_summary: Get game analysis
• get_pgn: Export game in PGN format

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request