GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
TradingAgents is a Python-based framework for developing multi-agent systems for financial trading using LLMs, licensed under Apache-2.0.
Good fit when
- Use TradingAgents when you need a framework that supports the development of multi-agent systems specifically for financial trading scenarios.
- Consider TradingAgents if you are working with local models and require support for Ollama, as it provides a specific profile for running local models.
Avoid when
- Avoid TradingAgents if your project does not involve financial trading or if you do not require a multi-agent system.
- Do not use TradingAgents if you are looking for a framework that does not support local models with Ollama, as this is a specific feature of TradingAgents.
Observed Sep 18, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 18, 2026
- Security (OSV)
- No criticals
- As of Sep 18, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install TradingAgentsHow it fits your stack(32)
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A framework for developing multi-agent systems for financial trading using LLMs.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Sep 18, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Sep 18, 2026
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Sep 18, 2026
- Languages
- python
Source: github.language+pyproject.toml · Sep 18, 2026
Categories
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Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 18, 2026)
conda create -n tradingagents python=3.12Source link
Tags
README
Installation Clone TradingAgents: Create a virtual environment in any of your favorite environment managers: Or with uv: Install the package and its dependencies ( with uv): Docker Alternatively, run with Docker: After updating the repository, rebuild the image with . For local m...
For agents
This page has a .md twin and JSON over the API.