Alpha Notice: These docs cover the v1-alpha release. Content is incomplete and subject to change.For the latest stable version, see the current LangGraph Python or LangGraph JavaScript docs.
When working with non-deterministic systems that make model-based decisions (e.g., agents powered by LLMs), it can be useful to examine their decision-making process in detail:
🤔 Understand reasoning: Analyze the steps that led to a successful result.
🐞 Debug mistakes: Identify where and why errors occurred.
🔍 Explore alternatives: Test different paths to uncover better solutions.
LangGraph provides time travel functionality to support these use cases. Specifically, you can resume execution from a prior checkpoint — either replaying the same state or modifying it to explore alternatives. In all cases, resuming past execution produces a new fork in the history.