langgraph-human-in-the-loop

Implement human-in-the-loop patterns in LangGraph graphs with interrupts and resume.

113|9|Updated Jan 24, 2026
One-click install
npx skills add https://github.com/langchain-ai/skills-benchmarks --skill langgraph-human-in-the-loop
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: langgraph-human-in-the-loop
Source: https://github.com/langchain-ai/skills-benchmarks/tree/main/skills/main/langgraph-human-in-the-loop
Command: npx skills add https://github.com/langchain-ai/skills-benchmarks --skill langgraph-human-in-the-loop

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables developers to implement human-in-the-loop patterns in LangGraph graphs by pausing execution at strategic points, surfacing data for human review, and resuming with provided input.

Core Features & Use Cases

  • Interrupt and resume flows across Python and TypeScript implementations
  • Approval workflows and routing based on human decisions
  • Handling multiple concurrent interrupts and subgraph re-execution semantics
  • Guidance on idempotent side effects and safe checkpointing prior to interrupts
  • Robust resume semantics with Command(resume=...) to restart from the checkpoint

Quick Start

Pause a running LangGraph graph with interrupt(), review the surfaced context, and resume using Command(resume=...) when a decision is provided.

Frequently Asked Questions about langgraph-human-in-the-loop

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I pause a LangGraph workflow for human approval before resuming?

To pause a LangGraph workflow for human approval, use the interrupt() function to halt execution and surface data, then resume the graph using Command(resume=...) with the user's decision.

Does LangGraph support multiple concurrent interrupts in a single graph execution?

Yes, LangGraph supports handling multiple concurrent interrupts and subgraph re-execution semantics, allowing complex interactive graph workflows to pause and resume at various decision points.

What do I need to set up checkpointer and thread_id tracking for LangGraph interrupts?

You need a checkpointer to save the graph state and a unique thread_id to track the execution thread, ensuring your workflow payloads remain JSON-serializable for safe and resumable operations.

Can I implement human-in-the-loop routing in both Python and TypeScript LangGraph implementations?

Yes, you can implement human-in-the-loop patterns like interrupt and resume flows, approval workflows, and human decision routing across both Python and TypeScript LangGraph implementations.

Why does my LangGraph interrupt fail to resume correctly after pausing execution?

Resuming a LangGraph interrupt fails when side effects are not idempotent or payloads lack JSON-serializable data, so ensure safe checkpointing is configured prior to triggering interrupts.

When should I use the interrupt function versus standard graph execution in LangGraph?

Use the interrupt function in LangGraph when your workflow requires interactive graph validation, approval routing, or human decisions, pausing execution to surface context before resuming with input.