langchain-middleware

Orchestrate human approval for LangChain tool calls and structured outputs.

7|1|Updated Mar 15, 2026

Search Tags:#middleware #langchain #resume #human-in-the-loop #agent-design #checkpointer

Ready to run

npx skills add https://github.com/Harmeet10000/skills --skill langchain-middleware-harmeet10000

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: langchain-middleware
Source: https://github.com/Harmeet10000/skills/tree/main/skills/ai-ml/langchain-middleware
Command: npx skills add https://github.com/Harmeet10000/skills --skill langchain-middleware-harmeet10000

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enable controlled, auditable human oversight for AI tool calls and structured outputs by introducing HITL middleware and custom hooks.

Core Features & Use Cases

HumanInTheLoopMiddleware pauses dangerous tool calls for human approval.
Custom middleware intercepts tool calls for error handling, logging, and retry logic
Command resume continues execution after human decisions (approve, edit, reject)
Thread_id/checkpointer requirement ensures state persistence and traceability.

Quick Start

Configure an agent with HITL middleware and a memory checkpointer, then run a task that requires approval and resume after a human decision.

Frequently Asked Questions about langchain-middleware

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

FAQPage Schema

How do I add human-in-the-loop approval for LangChain agent tool calls?▼

Human-in-the-loop approval for LangChain agents is added by applying middleware that pauses tool calls for human decisions. You can configure per-tool policies to intercept, approve, edit, or reject actions before execution proceeds.

What is needed to maintain state persistence when pausing LangChain agents for human review?▼

State persistence when pausing LangChain agents requires a memory checkpointer and a thread_id for tracking. This configuration ensures execution state is saved and traceable across human-in-the-loop interruption and resume cycles.

How do I resume an agent after a human rejects or edits a tool call?▼

You resume an agent after a human decision using command resume functionality. This mechanism continues execution by passing the human's choice—whether to approve, edit, or reject the tool call—back into the LangChain workflow.

Can I use human-in-the-loop middleware with both Python and TypeScript LangChain implementations?▼

Yes, human-in-the-loop middleware supports both Python and TypeScript LangChain implementations. The orchestration applies across production agents in both languages, maintaining consistent interruption and resume flow capabilities.

Does LangChain middleware allow setting separate approval policies for individual tools?▼

Yes, LangChain middleware supports per-tool policies for human-in-the-loop approval. You can configure different interception rules and hooks at both the tool level and the middleware level for granular control over agent actions.