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langgraph-hitl-patterns

Implement human-in-the-loop approval patterns for LangGraph stateful graphs.

Updated Dec 17, 2025
Search Tags:#checkpointing#ai workflow#langgraph#structured output#firestore#hitl#stateful graphs
One-click install
npx skills add https://github.com/ionmidori/SYDBioedilizia --skill langgraph-hitl-patterns
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langgraph-hitl-patterns
Source: https://github.com/ionmidori/SYDBioedilizia/tree/main/.gemini/skills/langgraph-hitl-patterns
Command: npx skills add https://github.com/ionmidori/SYDBioedilizia --skill langgraph-hitl-patterns

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires langgraph-checkpoint-firestore, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the development of complex, multi-turn AI applications by integrating human-in-the-loop (HITL) checkpoints, enabling stateful persistence, and facilitating asynchronous resume capabilities.

Core Features & Use Cases

  • Stateful Graph Persistence: Utilizes Firestore for reliable checkpointing of LangGraph states, allowing workflows to be paused and resumed.
  • Human Review Integration: Implements a "soft interrupt" pattern to pause execution before critical decision points, awaiting human approval or input.
  • Structured Output Agent: Features a Quantity Surveyor agent that uses Gemini Vision and Pydantic for structured data extraction and SKU matching from visual and textual inputs.
  • Use Case: A renovation quoting system where an AI generates a draft quote based on user-provided images and chat history, then pauses for an administrator to review and approve before finalizing.

Quick Start

Initiate the quote generation process for project ID 'proj-12345' by sending a POST request to the /quote/proj-12345/start endpoint.

Frequently Asked Questions about langgraph-hitl-patterns

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

FAQPage Schema
How do I implement human-in-the-loop approval steps in a LangGraph stateful graph?▼

Human-in-the-loop approval in a LangGraph stateful graph is implemented here via a soft interrupt pattern that pauses execution at critical decision points, awaiting human input before resuming the workflow.

How does Firestore checkpointing work for resuming asynchronous AI workflows?▼

Firestore checkpointing persists LangGraph state at pause points, allowing asynchronous AI workflows to securely resume execution from the exact checkpoint once an administrator provides approval.

Can I use structured output with Pydantic for data extraction in LangGraph?▼

Yes, structured output with Pydantic for data extraction in LangGraph is demonstrated here by a Quantity Surveyor agent using Gemini Vision and Pydantic for structured data extraction and SKU matching.

Do I need langgraph-checkpoint-firestore to manage multi-turn stateful graph persistence?▼

Yes, the langgraph-checkpoint-firestore dependency is required to enable reliable stateful graph persistence for pausing multi-turn AI workflows and resuming them from checkpoints.

What is the best way to build a renovation quoting system requiring admin review?▼

Building a renovation quoting system with admin review is achieved here via a multi-turn AI workflow that generates a draft quote from visual inputs, then pauses for administrator approval before finalizing.

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