PolyTrader: AI-Powered Automated Trading System for Polymarket

An autonomous AI trading agent for Polymarket that identifies market inefficiencies, calculates optimal bet sizes, and executes trades automatically. This system leverages ChatGPT's predictive capabilities against existing market odds to find profitable edges.

🚀 Getting Started

Prerequisites

• Python 3.8+ installed
• A Polygon network wallet with MATIC (for gas) and USDC (for trading)
• API keys for OpenAI and SerpAPI
• Basic understanding of prediction markets and crypto wallets

Installation

1. Clone this repository

   git clone https://github.com/yourusername/PolyTrader.git
   cd PolyTrader

2. Create a virtual environment

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

3. Install dependencies

   pip install -r requirements.txt

4. Set up environment variables

   cp .env.example .env
   # Edit .env with your API keys and configuration

5. Run the application

   python app.py

6. Visit http://127.0.0.1:5000 in your browser

📋 Features

• Market Analysis: Continuously scans Polymarket for opportunities
• AI-Powered Predictions: Uses ChatGPT to analyze various events
• Edge Detection: Compares AI predictions with market consensus to find inefficiencies
• Intelligent Bet Sizing: Implements Kelly Criterion for optimal bankroll management
• Automated Execution: Places trades via Polymarket Agents SDK
• Risk Management: Includes safety features to protect your bankroll

🏗️ Architecture

The system consists of three core modules:

1. Analysis Module

   • Uses ChatGPT to analyze upcoming events
   • Compares predictions with current Polymarket odds
   • Identifies opportunities with significant edge

2. Decision Module

   • Evaluates opportunities based on edge percentage
   • Calculates optimal bet size using Kelly Criterion
   • Manages risk to preserve bankroll

3. Execution Module

   • Connects to Polymarket using their official Agents SDK
   • Places trades automatically with verification
   • Implements safety measures and error handling

⚙️ Configuration

Edit your .env file with the following variables:

# OpenAI API key (required for AI functionality)
OPENAI_API_KEY=your_openai_api_key_here

# Flask app settings
FLASK_SECRET_KEY=your_flask_secret_key_here

# SerpAPI key (required for market data)
SERPAPI_API_KEY=your_serpapi_api_key_here

# Polymarket API credentials
POLYMARKET_API_KEY=your_polymarket_api_key_here

# Wallet information (required for transactions)
POLYGON_WALLET_PRIVATE_KEY=your_private_key_here
POLYMARKET_WALLET_ADDRESS=your_wallet_address_here

# Trading settings
INITIAL_BANKROLL=1000
MAX_BET_PERCENTAGE=0.05
MIN_EDGE_PERCENTAGE=0.15

⚠️ IMPORTANT: Never commit your .env file or hardcode API keys in the source code. The .env file is included in .gitignore to prevent accidental exposure of your credentials.

🚀 Usage

Start the web interface:

python app.py

Run in simulation mode (no real trades):

python app.py --simulation

Analyze specific markets:

python polymarket_ai_search.py --query "NBA games tonight"

⚠️ Risk Warning

Trading involves substantial risk and is not suitable for all investors. Past performance is not indicative of future results. Start with small amounts to test the system before scaling up. Implement proper risk management.

🔍 Main Files

• app.py - Main entry point for the Flask application
• polymarket_ai_search.py - Search and analysis of Polymarket events
• place_polymarket_bet.py - Automated bet execution
• fetch_current_markets.py - Real-time market data retrieval

📝 License

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

👨‍💻 Author

Siraj Raval

🙏 Acknowledgements

• OpenAI for ChatGPT API
• Polymarket team for the Agents SDK
• All contributors and testers

⭐ Star this repo if you find it useful! Join our Discord community to discuss improvements and share results.

Note: This system is for educational purposes. Always do your own research before trading.