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 ![LangGraph](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_130f89aab1b465273fde317a846f02b6/langgraph.png "LangGraph")
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# LangGraph Discussions

LangGraph, built by LangChain, is a model neutral, low-level orchestration framework for building long-running, stateful agents that handle complex tasks. It uses a graph-based model backed by a durable engine, with human-in-the-loop control, fault tolerance, streaming, and persistence. Key Features and Functionality: ∙Human-in-the-loop: Keep agents on track with moderation and quality controls. Teams can inspect, steer, and approve agent actions at any point. ∙Customizable agent workflows: Low-level primitives provide the flexibility needed to create single-, multi-, and hierarchical agent workflows using one framework. ∙Comprehensive memory: Build stateful agents with short-term working memory for ongoing reasoning and long-term memory across sessions, for rich, personalized interactions. ∙Native streaming: Bridge user expectations and agent capabilities with native token-by-token streaming that show agent reasoning and actions in real time. ∙Durable execution: Build long-running agents that persist through failures and run for extended periods, resuming exactly where they left off. Primary Value and Problem Solving: Developers trust LangGraph to build agents that reliably handle complex tasks. LangGraph enables developers to combine deterministic and agentic steps in a single agent graph. This lets you build bespoke workflows where parts of the logic are fully predictable while other parts benefit from the flexibility of model reasoning, giving you fine-grained control over exactly where and how AI is applied.

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