An advanced AI-powered autonomous gambling system that uses cutting-edge machine learning, sophisticated decision-making algorithms, and real-time analytics to play casino games intelligently.
This software is for educational and research purposes only. Gambling involves significant financial risk and can lead to addiction. Please gamble responsibly and within your means. The authors are not responsible for any financial losses incurred through the use of this software.
- DSPy Integration: Leverages DSPy (Declarative Self-improving Python) for intelligent decision making
- Multi-Game Strategies: Specialized algorithms for Blackjack, Roulette, and Poker
- Card Counting: Advanced card counting system for Blackjack with true count calculations
- Pattern Recognition: Sophisticated pattern detection for Roulette wheel bias and trends
- GTO Poker: Game Theory Optimal poker strategies with opponent modeling
- Market Analysis: Real-time market sentiment analysis affecting gambling decisions
- News Sentiment: AI-powered news analysis for market context
- Predictive ML Models: Machine learning models for outcome prediction
- Risk Assessment: Advanced risk management with multiple risk factors
- Multi-Site Support: Adaptable to different gambling websites
- Game Detection: Automatic detection of game types and states
- Element Recognition: Multiple strategies for finding and interacting with game elements
- Screenshot Capture: Automatic screenshot capture for debugging and analysis
- Session Management: Cookie handling and session persistence
- Real-Time Monitoring: Live bankroll tracking and performance metrics
- Interactive Charts: Dynamic charts showing profit/loss, decision distribution, and game performance
- Risk Management: Visual risk indicators and alerts
- Configuration Management: Easy configuration through web interface
- Multi-Page Interface: Separate pages for dashboard, analytics, configuration, and strategy management
- Kelly Criterion: Optimal bet sizing using Kelly Criterion
- Stop Loss/Take Profit: Automatic session termination based on profit/loss thresholds
- Risk Controls: Multiple layers of risk management
- Performance Tracking: Detailed performance analytics and reporting
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Taipy GUI │ │ Main │ │ DSPy Brain │
│ Dashboard │◄──►│ Orchestrator │◄──►│ Decision │
│ │ │ │ │ Engine │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│ │ │
│ ▼ │
│ ┌─────────────────┐ │
│ │ MCP Tools │ │
│ │ Manager │ │
│ └─────────────────┘ │
│ │ │
▼ ▼ ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Browser │ │ Game │ │ Bankroll │
│ Automation │◄──►│ Strategies │◄──►│ Manager │
│ │ │ │ │ │
└─────────────────┘ └─────────────────┘ └─────────────────┘
- Python 3.8+
- Chrome browser
- OpenAI API key (for DSPy)
# Clone the repository
git clone https://github.com/your-username/autonomous-gambling-agent.git
cd autonomous-gambling-agent
# Install dependencies
pip install -r requirements.txt
# Install ChromeDriver (automatic via webdriver-manager)
# No manual installation needed
# Copy and configure settings
cp config.yaml.example config.yaml
# Edit config.yaml with your settings# Create virtual environment
python -m venv gambling_env
source gambling_env/bin/activate # On Windows: gambling_env\Scripts\activate
# Install packages
pip install dspy-ai==2.4.9
pip install selenium==4.15.2
pip install taipy==3.1.1
pip install numpy pandas pyyaml
pip install scikit-learn plotly
pip install beautifulsoup4 requests
pip install webdriver-managerEdit config.yaml with your settings:
# OpenAI API Key for DSPy intelligence
openai_key: "your-openai-api-key-here"
# Initial bankroll amount
initial_bankroll: 100.0
# Website configuration
website:
url: "https://your-casino-site.com"
username: "your-username"
password: "your-password"
# Games to play
games:
- name: "Blackjack"
max_rounds: 30
strategy: "basic"
- name: "Roulette"
max_rounds: 20
strategy: "pattern"
# Risk management
risk_management:
stop_loss_percent: 20
take_profit_percent: 50
max_bet_percent: 10python taipy_dashboard.pyOpen http://localhost:52651 in your browser
python main_orchestrator.py# Test browser automation
python advanced_browser.py
# Test game strategies
python game_strategies.py
# Test MCP tools
python mcp_tools.py- Basic Strategy: Mathematically optimal play
- Card Counting: Hi-Lo counting system with true count
- Bankroll Management: Kelly Criterion bet sizing
- Advanced Features: Splitting, doubling, insurance decisions
- Pattern Recognition: Hot/cold number analysis
- Sector Bias Detection: Wheel bias identification
- Betting Systems: Multiple betting strategies
- Trend Analysis: Color and number pattern analysis
- GTO Strategy: Game Theory Optimal play
- Opponent Modeling: Dynamic opponent analysis
- Position Awareness: Position-based decision making
- Bankroll Management: Tournament and cash game strategies
- Real-time bankroll tracking
- Session statistics
- Risk level indicators
- Agent control (start/stop/pause)
- Market analysis integration
- News sentiment analysis
- ML prediction results
- Risk assessment details
- Bankroll settings
- API key management
- Website credentials
- Game selection
- Strategy performance metrics
- Real-time strategy adjustments
- Game-specific settings
- Market Analysis: Real-time market data integration
- News Analysis: Sentiment analysis of relevant news
- Predictive Models: ML models for outcome prediction
- Risk Assessment: Multi-factor risk analysis
- Adaptive Selectors: Multiple strategies for element detection
- Game State Detection: Automatic game state recognition
- Error Recovery: Robust error handling and recovery
- Session Persistence: Cookie and session management
- Real-time Metrics: Live performance tracking
- Historical Analysis: Session history and trends
- Risk Monitoring: Continuous risk assessment
- Alert System: Automated alerts for risk conditions
- Stop Loss: Automatic session termination on losses
- Take Profit: Profit-taking at predetermined levels
- Bet Sizing: Kelly Criterion and percentage-based sizing
- Time Limits: Maximum session duration controls
- Balance Thresholds: Minimum balance protection
- Volatility Tracking: Bet size and outcome volatility
- Drawdown Analysis: Maximum drawdown monitoring
- Behavioral Analysis: Tilt and emotional decision detection
- Market Correlation: External market factor analysis
# Run unit tests
python -m pytest tests/
# Test individual components
python test_strategies.py
python test_browser.py
python test_mcp_tools.py- Headless browser mode for faster execution
- Parallel processing for analytics
- Efficient data structures
- Optimized database queries
- Automatic cleanup of browser resources
- Session data rotation
- Memory-efficient data structures
- Garbage collection optimization
- Encrypted credential storage
- Secure API key handling
- Session token management
- Local data encryption
- No data transmission to third parties
- Local processing only
- Configurable logging levels
- Automatic log rotation
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
This software is provided for educational purposes only. Users are responsible for ensuring compliance with all applicable laws and regulations in their jurisdiction. Gambling may be illegal in some areas, and users should verify the legality before use.
- Documentation: Check the
/docsfolder for detailed documentation - Issues: Report bugs and feature requests on GitHub Issues
- Discussions: Join discussions on GitHub Discussions
- DSPy Team: For the amazing DSPy framework
- Taipy Team: For the beautiful dashboard framework
- Selenium Team: For robust browser automation
- OpenAI: For powerful language models
- Community: For contributions and feedback
Remember: Gamble responsibly. Never bet more than you can afford to lose.