LangGraph

LangGraph is a stateful, graph-based orchestration framework for building, managing, and deploying long-running agentic LLM applications and workflows.

AI AgentsOrchestrationGraphStatefulLangChainLLMAgentic Workflows

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About LangGraph

LangGraph is built by the LangChain team as a low-level orchestration foundation for agentic systems. It provides primitives to define nodes, edges, and shared state; supports persistent execution (checkpointing), streaming outputs, human-in-the-loop integration, branching, loops, and multi-agent architectures. Unlike purely linear chains, LangGraph enables complex control flows in AI agent workflows and is designed for production reliability, context persistence, and observability.

Key Features

Graph of nodes / edges (directed, conditional, loops)

Shared state (typed, persistent) across nodes and graph execution

Checkpointing and durable execution (resuming after failure)

Support for streaming (token by token, node updates)

Human-in-the-loop / approval hooks and interruptibility

Multi-agent orchestration (agents as nodes, coordination)

Integration with LangSmith (for debugging, visualization, evaluation)

Support for declarative graph API + imperative (functional / event) APIs

Production deployment via LangGraph Platform (self-hosted, hybrid, or cloud)

Pros

Powerful control over complex agentic workflows (branching, loops, conditional logic)

Built-in persistence and resilience (checkpointing) relieve you from re-writing state logic

Streaming support helps build responsive UI / real-time agent behavior

Flexibility: can operate both declaratively and imperatively, mix and match styles

Strong integration with the LangChain ecosystem (chains, tools, agents)

Scalable agent deployment via LangGraph Platform with features like versioning, registry, observability

Cons

Relatively new: ecosystem and tooling are still maturing

Steeper learning curve: understanding graphs, state, edges, branching, and persistence

Debugging complex graphs of agents and state transitions can be nontrivial

Operational overhead for self-hosting before using the Platform: managing infrastructure, persistence, scaling

Some features (like those in LangGraph Platform) may be behind managed / paid offerings

Tool Information

Language: Python / JavaScript (APIs for both)
License: MIT
Maintainer: LangChain / community

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See how LangGraph stacks up against other workflow orchestration engines, feature by feature.