AI Agents for Trading in Python

This repository offers open-source AI agents for algorithmic trading in Python. It democratizes AI-driven trading tools for quantitative traders and developers integrating AI into financial markets. Provides a modular framework for building diverse trading strategies.

How It Works

Core approach uses specialized AI agents for specific trading functions. Agents leverage LLMs for market analysis, strategy execution, risk management, sentiment monitoring, and arbitrage. Modular architecture allows agent customization and combination for bespoke systems.

Quick Start & Requirements

• Primary Execution: Run via main.py, allowing agent toggling.
• Prerequisites: Python 3.10.9, API keys (e.g., Anthropic, trading platforms) via .env.
• Recommended IDEs: Cursor, Windsurfer.
• Key Links:
  • Docs Video: https://www.youtube.com/playlist?list=PLXrNVMjRZUJg4M4uz52iGd1LhXXGVbIFz
  • Discord: https://discord.gg/XAw8US9aHT
  • Roadmap/Info: moondev.com
  • Education: algotradecamp.com

Highlighted Details

• Features diverse AI agents: live trading, strategy management, risk control, sentiment analysis (Twitter, YouTube), listing arbitrage (Solana), chart analysis, funding rate arbitrage, and research-based strategy generation (RBI Agent).
• Agents perform advanced, real-time analysis: identifying pre-listing Solana tokens, analyzing crypto charts for buy/sell signals, monitoring liquidation events with AI alerts.
• Includes agents for content creation (tweets, videos) and social media data extraction (TikTok).
• Supports LLM prompt customization and user-defined strategy integration in /strategies.

Maintenance & Community

Project updates and discussions are primarily channeled through Discord. A YouTube playlist offers video updates and training materials. The project maintains a public roadmap.

Licensing & Compatibility

The project is described as "100% open sourced," but a specific software license is not provided in the README. This lack of explicit licensing details may pose compatibility concerns for commercial use or integration into proprietary systems.

Limitations & Caveats

This project is an experimental research initiative, not a production trading system. No profitability guarantees are offered; trading carries substantial risk of loss. User success depends on their own strategy, risk management, research, and rigorous testing.