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LangGraph

LangGraph is a graph-based agent-orchestration framework from the LangChain ecosystem. It models an agentic workflow as a directed graph of nodes (agent / tool calls) and edges (state transitions), with a shared mutable state object passed between nodes. Used to implement supervisor-routing and multi-agent collaboration shapes that exceed the linear chain abstraction of plain LangChain.

Stub page. First wiki disclosure 2026-05-20 via the Databricks + Virtue Foundation post.

Why graph and not chain

LangChain's original chain abstraction is linear; LangGraph is a graph because realistic agent workflows have:

  • Conditional branching — a supervisor classifies the input and routes to one of several specialist sub-agents.
  • Cycles — a verification step may loop back to a re-planning step until a quality bar is met.
  • Shared mutable state — tool outputs and intermediate reasoning need to flow between nodes without being re-derived.

LangGraph encodes these as a graph spec; the runtime executes the graph step-by-step, calling LLM endpoints / tools at each node.

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