Chess AI

A chess AI project built with Python and FastAPI, containerized with Docker for easy deployment and development.

🚀 Quick Start with Docker

Prerequisites

• Docker and Docker Compose installed
• Git

Development Setup

1. Clone the repository

   git clone <your-repo-url>
   cd chess-ai

2. Start development environment

   # Start all services (app, Redis, PostgreSQL)
   docker-compose up chess-ai-dev redis postgres
   
   # Or start just the app for development
   docker-compose up chess-ai-dev

3. Access the application

   • API: http://localhost:8000
   • API Documentation: http://localhost:8000/docs

Production Deployment

# Build and start production services
docker-compose up chess-ai-prod redis postgres

# Or run in detached mode
docker-compose up -d chess-ai-prod redis postgres

🛠️ Development

Local Development (without Docker)

1. Create virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies

   pip install -r requirements.txt
   pip install -r requirements-dev.txt

3. Run the application

   uvicorn main:app --reload

Docker Commands

# Build development image
docker-compose build chess-ai-dev

# Build production image
docker-compose build chess-ai-prod

# View logs
docker-compose logs chess-ai-dev

# Execute commands in container
docker-compose exec chess-ai-dev bash

# Stop all services
docker-compose down

# Stop and remove volumes
docker-compose down -v

📁 Project Structure

chess-ai/
├── Dockerfile              # Multi-stage Docker configuration
├── docker-compose.yml      # Development and production services
├── .dockerignore           # Files to exclude from Docker context
├── requirements.txt        # Production dependencies
├── requirements-dev.txt    # Development dependencies
├── main.py                 # FastAPI application (to be created)
└── README.md              # This file

🔧 Services

• chess-ai-dev: Development application with hot reload
• chess-ai-prod: Production application
• redis: Caching service for AI computations
• postgres: Database for storing game data

📝 Next Steps

1. Create the main FastAPI application (main.py)
2. Implement chess engine logic
3. Add AI algorithms (minimax, neural networks, etc.)
4. Create API endpoints for game management
5. Add unit tests and integration tests

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests: docker-compose exec chess-ai-dev pytest
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.