LangGraph
Build stateful, multi-step AI agents that loop, branch, and pause for human input — modeled as graphs so you see exactly what your agent does at every step.
LangGraph — the verdict: Developers building agent workflows that need loops, branching, or human-in-the-loop checkpoints LangGraph is the right framework once your agent logic has outgrown a simple sequential pipeline, not the starting point for someone building a first agent. Pricing: Open source / Free (LangGraph Cloud available). Last reviewed: August 2026.
Best For
Developers building agent workflows that need loops, branching, or human-in-the-loop checkpoints
Standout Feature
Graph visualization makes complex agent logic debuggable in a way a purely sequential framework can't match
Verdict
The right tool once your agent logic outgrows a simple pipeline, overkill for a straightforward linear task.
Alternatives
Overview
LangGraph is a graph-based agent orchestration framework from the LangChain team that models complex agent workflows as stateful directed graphs. Each node is an action or decision step; edges define transitions based on state and conditions. This gives you precise control over branching, loops, human-in-the-loop interrupts, and parallel execution — patterns that are impractical to implement reliably with linear chain frameworks.
Our Take
LangGraph is the right framework once your agent logic has outgrown a simple sequential pipeline, not the starting point for someone building a first agent. The graph model gives you precise control over loops, branching conditions, and human-in-the-loop checkpoints, and the visualization makes complex state transitions debuggable in a way a purely linear framework can't match. The steeper learning curve is real: the graph mental model takes time to internalize. From the LangChain team, the open-source core and LangGraph Cloud are both available. If your agent needs to loop or pause for approval, this is the framework to reach for.
Key Features
- Stateful directed graph model for complex multi-step agent workflows
- Human-in-the-loop interrupt support at any graph node
- Parallel node execution for independent agent branches
- Persistent state checkpointing across workflow runs
- Built-in streaming of intermediate steps and reasoning
- LangGraph Cloud for managed deployment with built-in observability
- • Best framework for agents that need loops, branches, and human checkpoints
- • Graph visualization makes complex agent logic debuggable
- • Tightly integrated with LangChain's 600+ integrations and tools
- • Steeper learning curve than simpler sequential frameworks
- • Graph mental model is overkill for straightforward linear pipelines
- • LangGraph Cloud adds cost compared to self-hosted options
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Workflows Using This Tool
Step-by-step playbooks that put LangGraph to work.