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langchain-middlewares

Provide provider-agnostic middleware for agent summarization and human-in-the-loop workflows.

1|Updated Apr 30, 2026
Search Tags:#security#middleware#compliance#LLM integration#agent enhancement
One-click install
npx skills add https://github.com/wpsadi/stock-agent --skill langchain-middlewares
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langchain-middlewares
Source: https://github.com/wpsadi/stock-agent/tree/main/.agents/skills/langchain-middlewares
Command: npx skills add https://github.com/wpsadi/stock-agent --skill langchain-middlewares

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires langchain, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill Unit provides a collection of middleware solutions to enhance the capabilities of agents, addressing various use cases such as summarization, human-in-the-loop operations, and PII detection.

Core Features & Use Cases

  • Middleware Support: Offers a variety of middleware for common agent use cases, including summarization, human-in-the-loop, model call limits, and more.
  • Provider-Agnostic: Works with any LLM provider, making it versatile for different environments.
  • Use Case: For a stock analysis system, integrate the Summarization middleware to automatically compress and preserve relevant conversation context during long-running sessions.

Quick Start

Use the 'Summarization' middleware to automatically compress conversation context when the token limit is approached.

Frequently Asked Questions about langchain-middlewares

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

FAQPage Schema
How do I add human-in-the-loop approval to a LangChain agent workflow?▼

Human-in-the-loop middleware intercepts LangChain agent execution to add manual approval steps, ensuring compliance and administrative oversight before critical model actions proceed.

Can I enforce model call limits in a multi-agent system?▼

Model call limits middleware restricts LLM invocation counts in multi-agent systems, preventing runaway token consumption and enforcing administrative budget constraints during complex workflows.

What is the best way to compress conversation context when an agent hits the token limit?▼

Summarization middleware automatically compresses and preserves relevant conversation context when token limits are approached, maintaining session continuity for long-running agent operations.

Do these agent enhancement middlewares work with any LLM provider?▼

The middlewares use provider-agnostic implementations, functioning with any LLM provider to support versatile agent enhancement across different environment configurations.

How does PII detection middleware secure LLM integration workflows?▼

PII detection middleware scans agent interactions to identify and secure sensitive personal data, addressing compliance requirements within complex administrative LLM integration workflows.

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