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LangGraph

Graph-based orchestration framework for long-running, stateful, multi-step agent workflows.

Resource overview Useful for durable agent workflows where state, branches, retries, checkpoints, and explicit flow control matter more than free-form autonomy.

Why use this

What it helps you do

Use this for stateful agent workflows where branches, checkpoints, retries, memory, human review, and explicit control flow matter.

Who can use this

Best fit users

AI application engineers, workflow automation teams, backend developers, and teams building durable multi-step agents.

Prerequisites

What to know first

Python or JavaScript experience, graph/workflow thinking, LLM API knowledge, and an understanding of the state each step must preserve.

System requirements

Environment needed

Python or Node environment depending on implementation, package manager, LLM provider access, storage/checkpoint backend when persistence is required, and deployment infrastructure for long-running workflows.

Community

Signals and discussion

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