This project provides a framework for building multi-agent LLM-based financial trading systems. It targets researchers and developers interested in exploring LLM applications in algorithmic trading, offering a structured environment for agent interaction and strategy development.

How It Works

TradingAgents utilizes a multi-agent system architecture where Large Language Models (LLMs) act as decision-making agents within a simulated financial market. This approach allows for emergent trading strategies and complex interactions between agents, leveraging LLMs' natural language understanding and reasoning capabilities for financial tasks.

Quick Start & Requirements

• Primary install / run command: Not yet available. The project states that source code or an API will be released soon.
• Non-default prerequisites and dependencies: Not specified.
• Estimated setup time or resource footprint: Not applicable until release.
• Links: Homepage: https://TradingAgents-AI.github.io/

Highlighted Details

• Framework for multi-agent LLM financial trading.
• Presented at MARW Workshop, AAAI 2025.
• Includes citation for academic referencing.

Maintenance & Community

• No specific contributors, sponsorships, or community channels (Discord/Slack) are mentioned in the README.
• The project is actively under development with a planned release of source code or API.

Licensing & Compatibility

• The license is not specified in the provided README.
• Compatibility for commercial use or closed-source linking is undetermined.

Limitations & Caveats

The project is not yet released, with source code or API access pending. This means the framework's functionality, stability, and practical usability are currently unproven.