Thoth Oracle System

A sophisticated arbitrage and trading system for the XRPL DEX, featuring flash loans, automated market making, and risk management.

Features

Core Components

1. Flash Loan Agent

   • Execute flash loans on XRPL
   • Manage loan lifecycle and repayment
   • Calculate optimal loan sizes and profits

2. XRPL AMM Agent

   • Monitor liquidity pools
   • Calculate exchange rates
   • Find arbitrage paths
   • Execute optimal trades

3. Risk Management Agent

   • Assess trade risks
   • Track positions and P&L
   • Calculate risk metrics
   • Monitor market conditions

4. Monitoring Agent

   • Track system health
   • Log performance metrics
   • Monitor errors and issues
   • Export system metrics

Key Features

• Real-time DEX monitoring
• Direct and triangular arbitrage detection
• Flash loan integration
• Risk assessment and management
• Performance tracking and reporting
• Comprehensive error handling
• Extensive logging

Installation

1. Clone the repository:

git clone https://github.com/Hobie1Kenobi/Thoth-Oracle.git
cd Thoth-Oracle

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate     # Windows

3. Install dependencies:

pip install -e .

Configuration

1. Set up your XRPL testnet wallet:

   • Replace TEST_WALLET_SEED in examples/live_arbitrage_test.py
   • Ensure your wallet has sufficient XRP for testing

2. Configure trading pairs:

   • Edit TRADING_PAIRS in examples/live_arbitrage_test.py
   • Add or remove pairs based on your strategy

3. Adjust risk parameters:

   • Modify thresholds in agents/risk_management_agent/risk_management_agent.py
   • Set position limits and profit targets

Usage

Live Testing

Run the live arbitrage test script:

python examples/live_arbitrage_test.py

This will:

1. Initialize all agents
2. Monitor specified trading pairs
3. Detect arbitrage opportunities
4. Execute trades when profitable
5. Log performance and results

Monitoring

The system provides extensive monitoring through:

• Real-time logging
• Performance metrics
• Health checks
• Error tracking

Logs are stored in the logs directory.

Architecture

Agent System

The system uses a multi-agent architecture:

1. Each agent handles specific functionality
2. Agents communicate asynchronously
3. Central coordination through the ArbitrageTrader

Risk Management

Multiple layers of risk control:

1. Pre-trade risk assessment
2. Position monitoring
3. P&L tracking
4. System health checks

Performance Optimization

• Asynchronous operations
• Efficient path finding
• Smart order routing
• Optimal trade sizing

Development

Testing

Run the test suite:

pytest tests/

Adding New Features

1. Create new agent in agents/ directory
2. Update main trading loop in examples/live_arbitrage_test.py
3. Add tests in tests/ directory

License

MIT License - See LICENSE file for details

Contributing

1. Fork the repository
2. Create feature branch
3. Submit pull request

Support

Open an issue for:

• Bug reports
• Feature requests
• Documentation improvements