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LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application, crucial for creating reliable agents. Additionally, LangGraph includes built-in persistence, enabling advanced human-in-the-loop and memory features.
Features
- Implement loops and conditionals in your apps
- Automatically save state after each step in the graph. Pause and resume the graph execution at any point to support error recovery, human-in-the-loop workflows, time travel and more
- Interrupt graph execution to approve or edit next action planned by the agent
- Stream outputs as they are produced by each node (including token streaming)
- LangGraph integrates seamlessly with LangChain and LangSmith (but does not require them)
- Documentation available
Project Samples
License
MIT LicenseFollow LangGraph
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