Build stateful, multi-actor AI agents with graph-based workflows. From LangChain, the most popular LLM framework.
LangGraph is worth checking the docs before setup with strong trust signals. Check agent compatibility and use-case fit before adding it to your workflow.
gh repo view langchain-ai/langgraph --webOpen the official repository or website.
Check the README for package manager, auth, and platform requirements.
Try it in a small test task inside your agent workflow.
LangGraph is a framework for building stateful agent workflows as directed graphs. Each node is an action, each edge is a condition. Build complex agent loops, human-in-the-loop workflows, and multi-agent systems that maintain state across interactions.
LangGraph is a framework for building stateful agent workflows as directed graphs. Each node is an action, each edge is a condition. Build complex agent loops, human-in-the-loop workflows, and multi-agent systems that maintain state across interactions.
Strong trust signals; still review the README and permissions before production use.
Last commit was about 7 days ago.
9000 GitHub stars indicate community interest.
110 open issues signal maintenance load.
MIT license detected.
Stateful agent workflows
Multi-step reasoning systems
Agent orchestration
Python-based, full control over execution
Graph topology determines agent safety boundaries
9,000
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MIT
License
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2 security/trust notes recorded.
Setup difficulty is 3/5.