langgraph-human-in-the-loop

Implement human-in-the-loop patterns in LangGraph with interrupt() and Command(resume=...).

Updated Apr 12, 2026
One-click install
npx skills add https://github.com/dotlab-hq/torque --skill langgraph-human-in-the-loop-dotlab-hq
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: langgraph-human-in-the-loop
Source: https://github.com/dotlab-hq/torque/tree/main/.agents/skills/langgraph-human-in-the-loop
Command: npx skills add https://github.com/dotlab-hq/torque --skill langgraph-human-in-the-loop-dotlab-hq

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enables building robust human-in-the-loop patterns in LangGraph by allowing graphs to pause for human input, surface context to operators, and resume execution with a structured Command after approval or feedback.

Core Features & Use Cases

  • Interrupt/Resume workflow to pause and continue workflows with human input
  • Checkpointer integration and thread_id propagation for reliable resumption
  • Support for multi-interrupts, subgraph re-execution on resume, and idempotent side effects
  • Validation loops and approval routing patterns for common decision tasks

Quick Start

Pause graph execution with interrupt() to await human input, then resume using Command(resume=...) to continue.

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 execution to wait for human approval?

Pausing a LangGraph workflow for human approval requires calling the interrupt() function to halt execution and surface context to operators. You then resume the graph by passing a structured Command(resume=...) after the human input is provided.

What is the best way to resume a LangGraph workflow after an interrupt?

Resuming a LangGraph workflow after an interrupt is done using Command(resume=...). This structured command continues execution from the checkpoint, ensuring proper thread_id propagation and passing the human feedback back into the graph.

Does LangGraph support multiple interrupts and subgraph re-execution during human-in-the-loop?

Yes, LangGraph supports multiple interrupts, subgraph re-execution on resume, and idempotent side effects. Ensuring proper checkpointer compatibility and thread_id propagation is required to manage these complex parallel or subgraph workflows reliably.

How do I handle errors during a human-in-the-loop validation loop in LangGraph?

Error handling during a LangGraph human-in-the-loop validation loop is managed using a 4-tier strategy. This approach ensures robust recovery by addressing failures while maintaining checkpointer compatibility and JSON-serializable payloads for state persistence.

Why does my LangGraph interrupt fail to resume in a parallel subgraph?

A LangGraph interrupt may fail to resume in a parallel subgraph if thread_id propagation is incorrect or the checkpointer is incompatible. The workflow requires proper thread IDs and JSON-serializable payloads to successfully resume execution via Command(resume=...).