SableAI is a comprehensive Domain-Driven Design (DDD) framework for translating TradingView Pine Script strategies into Python code and running professional-grade backtests across multiple data sources. This framework implements the RBI method (Research, Backtest, Implement) with enterprise-grade architecture.

• Pine Script Translation - Convert TradingView Pine Script to Python
• Multi-Data Source Testing - Test across 25+ data sources and timeframes
• AI-Powered Strategy Generation - Natural language to code conversion
• Professional Data Access - OpenBB integration for enhanced financial data
• Concurrent Session Management - Cipher-BT integration for advanced trading
• Technical Analysis - BTA-Lib integration with 100+ indicators
• Domain-Driven Design - Clean, maintainable, enterprise-grade architecture
• Risk Management - Advanced risk controls and position sizing
• Performance Analysis - Comprehensive metrics and reporting

 SableAI/
├── domain_models.py              # Core domain models and value objects
├── domain_services.py            # Domain services for business logic
├── technical_analysis_service.py # BTA-Lib technical analysis service
├── bta_integration.py            # BTA-Lib integration
├── bta_launcher.py              # BTA-Lib command-line interface
├── pinescript_translator.py      # Pine Script to Python translator
├── multi_data_backtester.py     # Multi-data source backtesting framework
├── tsa_enhanced_strategy.py     # TSA Enhanced Strategy implementation
├── strategy_launcher.py         # Main launcher and orchestration
├── results_analyzer.py          # Results analysis and visualization
├── openbb_integration.py        # OpenBB integration for enhanced data
├── openbb_launcher.py           # Enhanced launcher with OpenBB
├── openbb_example.py            # OpenBB integration examples
├── cipher_integration.py        # Cipher-BT integration for concurrent sessions
├── cipher_launcher.py           # Enhanced launcher with Cipher-BT
├── cipher_example.py            # Cipher-BT integration examples
├── backtestsh_integration.py    # Backtest.sh AI integration
├── backtestsh_launcher.py       # AI-powered strategy launcher
├── backtestsh_example.py        # AI strategy generation examples
├── example_usage.py             # Comprehensive usage examples
├── test_system.py               # System testing
├── requirements.txt             # Python dependencies
├── .gitignore                   # Git ignore file
├── LICENSE                      # MIT License
├── OPENBB_SETUP.md              # OpenBB integration setup guide
├── CIPHER_SETUP.md              # Cipher-BT integration setup guide
├── BACKTESTSH_SETUP.md          # Backtest.sh AI integration setup guide
├── SYSTEM_SUMMARY.md            # Complete system summary
└── README.md                    # This file

git clone https://github.com/yourusername/ScypherAI.git
cd  SableAI

pip install -r requirements.txt

# On Windows
pip install TA-Lib

# On macOS
brew install ta-lib
pip install TA-Lib

# On Linux
sudo apt-get install libta-lib-dev
pip install TA-Lib

pip install openbb
# Or with all extensions
pip install "openbb[all]"

pip install cipher-bt
# Or with all extensions
pip install "cipher-bt[finplot,talib]"

pip install openai
# Set OpenAI API key
export OPENAI_API_KEY="your-api-key-here"

from pinescript_translator import PineScriptTranslator

translator = PineScriptTranslator()
python_code = translator.translate_to_python(pinescript_code)

from strategy_launcher import StrategyLauncher

launcher = StrategyLauncher()
results = launcher.run_tsa_enhanced_backtest(
    symbol="BTC-USD",
    timeframe="1d",
    start_date="2020-01-01",
    end_date="2024-01-01"
)

results = launcher.run_comprehensive_backtest(
    strategy_params={'atr_length': 14, 'atr_multiplier': 3.0},
    max_workers=4
)

from backtestsh_launcher import BacktestSHAILauncher

ai_launcher = BacktestSHAILauncher()
result = ai_launcher.run_ai_strategy_generation(
    description="Buy when RSI < 30, sell when RSI > 70",
    symbol="BTC-USD",
    strategy_type="mean_reversion"
)

from bta_launcher import BTALauncher

bta_launcher = BTALauncher()
results = bta_launcher.run_enhanced_backtest(
    strategy, market_data, Money(Decimal('10000'), "USD")
)

# Run comprehensive backtest
python strategy_launcher.py --mode comprehensive --workers 4

# Run single backtest
python strategy_launcher.py --mode single --symbol BTC-USD --timeframe 1d

# Translate Pine Script
python strategy_launcher.py --mode translate --pinescript-file strategy.pine

# Run OpenBB demo
python openbb_launcher.py --mode demo

# Single enhanced backtest
python openbb_launcher.py --mode single --symbol AAPL --market-type equity

# Comprehensive enhanced backtest
python openbb_launcher.py --mode comprehensive

# Run Cipher-BT demo
python cipher_launcher.py --mode demo

# Single backtest with concurrent sessions
python cipher_launcher.py --mode single --symbol BTCUSDT --interval 1h

# Multi-symbol backtest
python cipher_launcher.py --mode multi --symbols BTCUSDT ETHUSDT ADAUSDT

# Run AI demo
python backtestsh_launcher.py --mode demo

# Generate strategy from description
python backtestsh_launcher.py --mode generate --description "Your strategy here" --symbol BTC-USD

# Run AI backtest
python backtestsh_launcher.py --mode backtest --description "Moving average crossover" --symbol AAPL

# Run BTA-Lib demo
python bta_launcher.py --mode demo

# Enhanced backtest with technical analysis
python bta_launcher.py --mode backtest --strategy tsa_enhanced --symbol BTC-USD

# Compare strategies
python bta_launcher.py --mode compare --symbol BTC-USD

• Strategy - Trading strategy entities
• Trade - Individual trade execution
• Portfolio - Portfolio management
• MarketData - Market data entities
• BacktestResults - Backtest results

• Money - Monetary amounts with currency
• Price - Price with currency validation
• Quantity - Trade quantities
• Percentage - Percentage calculations
• Timeframe - Time frame validation

• RiskManager - Risk management logic
• StrategyAnalyzer - Strategy analysis
• BacktestExecutor - Backtest execution
• TechnicalIndicatorService - Technical analysis

• Professional-grade financial data
• Technical indicators (RSI, MACD, Bollinger Bands, ATR, ADX)
• Market sentiment analysis
• Fundamental data access
• Real-time data integration

• Multiple concurrent trading sessions
• Sophisticated exit strategies
• Multi-exchange data sources
• Built-in visualization
• Advanced session management

• AI-powered strategy generation
• Natural language to code conversion
• OpenAI GPT-3.5-turbo integration
• Batch strategy generation
• Strategy enhancement

• Comprehensive technical analysis
• 100+ technical indicators
• Pandas-based calculations
• Performance optimized
• Backtrader ecosystem integration

• 25+ Data Sources across multiple timeframes
• Parallel Processing for fast execution
• Comprehensive Results collection
• Statistical Analysis across markets

• Position Sizing based on risk parameters
• Stop Loss and Take Profit mechanisms
• Portfolio Risk analysis
• Correlation Analysis between positions
• Drawdown Protection

• Net Profit and Total Return
• Win Rate and Profit Factor
• Sharpe Ratio and Sortino Ratio
• Maximum Drawdown analysis
• Expectancy calculations
• Trade Analysis and statistics

• Convert Pine Script strategies to Python
• Test across multiple data sources
• Analyze performance metrics
• Compare strategy variations

• Generate strategies from natural language
• Enhance existing strategies with AI
• Batch process multiple strategies
• Automated strategy optimization

• Enterprise-grade backtesting
• Risk management systems
• Portfolio optimization
• Performance monitoring

• Learn algorithmic trading
• Understand strategy development
• Study market behavior
• Practice risk management

• README.md - This file
• OPENBB_SETUP.md - OpenBB integration setup
• CIPHER_SETUP.md - Cipher-BT integration setup
• BACKTESTSH_SETUP.md - Backtest.sh AI setup
• SYSTEM_SUMMARY.md - Complete system overview

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

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

• TradingView for Pine Script platform
• OpenBB for professional financial data
• Cipher-BT for concurrent session management
• BTA-Lib for technical analysis
• Backtest.sh for AI-powered strategy generation

1. Install the framework - Follow the installation guide
2. Run tests - python test_system.py
3. Try examples - python example_usage.py
4. Translate your Pine Script - Use the translator
5. Run comprehensive backtests - Test across multiple data sources
6. Analyze results - Use the analysis tools
7. Deploy professionally - Use OpenBB and Cipher-BT for production

This framework transforms your Pine Script strategies into a professional-grade Python backtesting system with access to the best financial data and analysis tools available! 🚀