🎮 Tic Tac Toe

A modern, colorful web-based Tic-Tac-Toe game featuring an unbeatable AI opponent powered by the minimax algorithm. Built with Flask backend and vanilla JavaScript frontend.

✨ Features

• 🤖 Unbeatable AI - Minimax algorithm ensures perfect play
• 🎯 Player Choice - Choose to play as X or O
• 📊 Statistics Tracking - Win/loss/draw record with win rate
• 📱 Responsive Design - Works on desktop and mobile devices
• 🔄 Quick Restart - Multiple restart options after game ends

🚀 Quick Start

Prerequisites

• Python 3.11 or higher
• pip (Python package manager)

Local Development

1. Clone the repository

   git clone https://github.com/steve-jr/tic-tac-toe-ai.git
   cd tic-tac-toe-ai

2. Create virtual environment

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

3. Install dependencies

   pip install -r requirements.txt

4. Run the application

   python app.py

5. Open in browser

   http://localhost:5000
   

🔧 API Endpoints

Endpoint	Method	Description
/	GET	Serve main game page
/state	GET	Get current game state
/select-player	POST	Choose X or O
/move	POST	Make a move
/reset	POST	Reset game

Sample API Response

{
  "board": [["X", null, "O"], [null, "X", null], ["O", null, null]],
  "currentPlayer": "X",
  "humanPlayer": "X",
  "isHumanTurn": true,
  "isTerminal": false,
  "winner": null,
  "isDraw": false,
  "needsPlayerSelection": false
}

🧠 Technical

Minimax Algorithm

The AI uses the minimax algorithm with alpha-beta pruning to evaluate all possible game states and choose the optimal move. This makes the AI unbeatable - the best you can do is draw! Game state stored in Flask sessions (cookies). Each player gets their own game instance

🤝 Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/amazing-feature)
3. Commit changes (git commit -m 'Add amazing feature')
4. Push to branch (git push origin feature/amazing-feature)
5. Open Pull Request

📄 License

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

🙏 Acknowledgments

• Minimax algorithm implementation inspired by CS50 AI course at UMich
• UI design inspired by modern glassmorphism trends
• Built with Flask and pure JavaScript for simplicity

📞 Support

• Create an issue for bug reports
• Start a discussion for feature requests
• Email: [email protected]
• Visit URL https://tic-tac-toe-ai-production-faf0.up.railway.app

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Made with ❤️ and ☕ by Steve Junior