LangGraph
Graph-based agentic orchestration from the LangChain team. State machines for LLM workflows — nodes are functions/agents, edges are transitions (conditional or fixed), state persists across nodes. Designed for the cases where a free-form chat between agents is the wrong abstraction and you actually want a deterministic flow with LLM-driven branch points. Pairs naturally with LangChain's tool + retriever ecosystem. Has first-class support for human-in-the-loop checkpointing, which is rare in this space.
Overview
Graph-based agentic orchestration from the LangChain team. State machines for LLM workflows — nodes are functions/agents, edges are transitions (conditional or fixed), state persists across nodes. Designed for the cases where a free-form chat between agents is the wrong abstraction and you actually want a deterministic flow with LLM-driven branch points. Pairs naturally with LangChain's tool + retriever ecosystem. Has first-class support for human-in-the-loop checkpointing, which is rare in this space.
Pros
- Deterministic flow control — easier to reason about than free-form multi-agent
- Native checkpoint / replay / human-in-the-loop primitives
- Composes with the whole LangChain ecosystem (retrievers, tools, parsers)
- Streaming-first design — partial outputs propagate through the graph
Cons
- Steeper learning curve than CrewAI for the first 'hello world'
- Carries LangChain's surface-area baggage even when you don't need it
- API still evolving; pin versions in production
Compatibility
| Operating systems | linux macos windows |
| GPU backends | cuda rocm metal cpu |
| License | Open source · free |
Runtime health
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Release cadence
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1 days since last refresh · source: lastUpdated
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