TradingAgents
An open-source multi-agent LLM framework that simulates a trading firm with analyst, trader, and risk-management agents for research purposes.
Last release May 11, 2026 · Last commit May 31, 2026 · ★ 81,001
Overview
TradingAgents (by Tauric Research) is an open-source, LangGraph-based multi-agent framework that mirrors a real trading firm using specialized LLM agents (fundamental, sentiment, technical analysts, trader, risk team). It supports many LLM providers (OpenAI, Google, Anthropic, xAI, DeepSeek, and more) and works with markets covered by Yahoo Finance. The maintainers explicitly state it is for research purposes. It is a TradFi/markets research tool, not an onchain trading product; no live trading or profitability is claimed or implied.
Details
- Chains
- Unknown
- Agent types
- Agent Framework, Research
- Open source
- Yes
- Pricing
- Free (open source); LLM/API costs apply
- Last checked
- 2026-06-10
Marketplace Signals
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Verification status reflects evidence reviewed by Sato Hub. Self-reported claims are never presented as verified.
Recent Activity
All news →Releases and posts from TradingAgents, pulled from its GitHub and X.
TradingAgents v0.2.5
Summary TradingAgents v0.2.5 ships the grounded Sentiment Analyst, Qwen/GLM/MiniMax dual-region support, `TRADINGAGENTS_*` env-var configurability with API-key auto-detection, remote Ollama support, configurable alpha benchmarks for non-US tickers, and a ticker path-traversal fix. Sentiment Analyst The renamed Sentiment Analyst now reads real Yahoo News, StockTwits, and Reddit data before generati
TradingAgents v0.2.4
Summary TradingAgents v0.2.4 ships structured-output decision agents, opt-in checkpoint resume, a persistent decision log with outcome-grounded reflections, four new LLM providers, and a Docker image. Structured-Output Decision Agents Research Manager, Trader, and Portfolio Manager use llm.with_structured_output(Schema) on their primary call and return typed Pydantic instances. Each provider's nat
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