langgraph-error-handling

LangGraph error handling patterns classify failures into transient, LLM-recoverable, and fatal errors to apply appropriate recovery strategies. You can implement ToolNode error handling and LLM-based recovery loops to keep your workflows resilient.

Human-in-the-loop (HITL) interrupts in LangGraph pause graph execution for sensitive actions, allowing deterministic resume flows after user approval. This pattern uses interrupt-based HITL escalation to handle user-fixable errors securely.

A RetryPolicy in LangGraph automatically retries transient failures across nodes during graph execution. By mapping transient errors to this policy, the graph can recover from temporary issues without manual intervention.

Checkpointer integration in LangGraph saves graph state to enable resilient execution and deterministic resume flows. While it helps recover from interruptions and HITL escalations, fatal errors typically require user intervention or reconfiguration.

Yes, these LangGraph error handling patterns provide templates for both Python and TypeScript. They cover error taxonomy mapping, RetryPolicy implementation, and ToolNode error handling across both languages.

Use LLM-based recovery loops in LangGraph when an LLM-recoverable error occurs and the model can correct its own output, whereas a standard RetryPolicy is better suited for transient network or API failures.