{"data":{"slug":"tauricresearch-tradingagents","name":"TradingAgents","tagline":"Multi-Agents LLM Financial Trading Framework","github_url":"https://github.com/TauricResearch/TradingAgents","owner":"TauricResearch","repo":"TradingAgents","owner_avatar_url":"https://avatars.githubusercontent.com/u/192884433?v=4","primary_language":"Python","stars":98335,"forks":18953,"topics":["agent","finance","llm","multiagent","trading"],"archived":false,"github_pushed_at":"2026-07-18T15:55:05+00:00","maintenance_label":"Active","stars_delta_30d":5040,"url":"https://www.graphcanon.com/tools/tauricresearch-tradingagents","markdown_url":"https://www.graphcanon.com/tools/tauricresearch-tradingagents.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/tauricresearch-tradingagents","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=tauricresearch-tradingagents","description":"TradingAgents: Multi-Agents LLM Financial Trading Framework","homepage_url":"https://arxiv.org/pdf/2412.20138","license":"Apache-2.0","open_issues":364,"watchers":732,"ai_summary":"TradingAgents is a framework for developing and deploying AI agents focused on financial market trading using Large Language Models (LLMs) in a multi-agent system.","readme_excerpt":"### Installation\n\nClone TradingAgents:\n```bash\ngit clone https://github.com/TauricResearch/TradingAgents.git\ncd TradingAgents\n```\n\nCreate a virtual environment in any of your favorite environment managers:\n```bash\nconda create -n tradingagents python=3.12\nconda activate tradingagents\n```\n\nInstall the package and its dependencies:\n```bash\npip install .\n```\n\n---\n\n### Docker\n\nAlternatively, run with Docker:\n```bash\ncp .env.example .env  # add your API keys\ndocker compose run --rm tradingagents\n```\n\nFor local models with Ollama:\n```bash\ndocker compose --profile ollama run --rm tradingagents-ollama\n```","github_created_at":"2024-12-28T03:31:08+00:00","created_at":"2026-07-07T17:30:32.700932+00:00","updated_at":"2026-08-16T00:01:24.130715+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"agent","name":"agent"},{"slug":"finance","name":"finance"},{"slug":"llm","name":"llm"},{"slug":"multiagent","name":"multiagent"},{"slug":"trading","name":"trading"}],"trust":{"provenance":{"is_fork":false,"github_id":909213664,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-16T00:01:23.354Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":2,"days_since_push":28,"last_release_at":"2026-07-05T14:32:25Z","stars_delta_30d":5040,"open_issues_delta_30d":62},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T10:56:00.021Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-16T00:01:23.804Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-08-16T00:01:23.804Z","managed_saas":false},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-16T00:01:23.804Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-16T00:01:23.804Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-08-16T00:01:23.804Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-16T00:01:23.804Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Python environment setup is required.","Deep understanding of finance and LLMs will enhance the utilization of this framework."],"min_ram_gb":8,"requires_docker":false},"constraints":{"min_ram_gb":8,"requires_docker":false},"when_to_use":["When your project involves complex multi-agent interactions specifically in the finance domain, utilizing LLMs to manage trading strategies.","For developing advanced trading algorithms where human-like language understanding is critical for interpreting market insights and news."],"when_not_to_use":["If simplicity and ease of deployment are prioritized over advanced AI capabilities; TradingAgents' complexity might introduce unnecessary overhead.","When the focus is on non-financial applications or when LLM integration isn't necessary, as this framework specializes in financial market trading with a multi-agent approach."],"source":"enrich:decision_facts","observed_at":"2026-07-11T11:52:07.622Z"},"constraint_facets":{"min_ram_gb":8,"requires_docker":false},"decision_summary":[{"label":"Requirements","value":"Min 8 GB RAM; Python environment setup is required.; Deep understanding of finance and LLMs will enhance the utilization of this framework."},{"label":"Adopt for","value":"Use TradingAgents for projects requiring a sophisticated framework to develop and deploy AI agents in financial market transactions leveraging Large Language Models. Avoid it if you need simpler tools or frameworks thatだ"}]}}