“LangChain”

Python framework of interoperable components and integrations for building agents and LLM apps, with LangGraph and Deep Agents layered above it.

JavaScript and TypeScript framework of interoperable components for building LLM apps and agents, with LangGraph.js and Deep Agents above it.

Open-source agent harness from LangChain for building agents with code, with LangSmith for testing and monitoring.

Framework for building LLM-powered applications with agents, chains, and RAG.

MCP server for langchain documentation, generated by doc2mcp.

Library that lets LangGraph agents extract, consolidate and search their own long-term memory.

Low-level Python orchestration framework for long-running stateful agents, with durable execution, human review points and short- and long-term memory.

Opinionated agent harness on LangGraph with sub-agents, filesystem access, context management, persistent memory and approval of tool calls.

Tracing, evaluation and monitoring for LLM apps and agents, with SDKs for several languages

The batteries included agent harness.

用于 LangChain 相关问题，获取官方文档和代码示例

AGENTS.md from langchain-ai/langchain: 391 lines covering Corridor security analysis, Project architecture and context, Core development principles, Model…

AGENTS.md from langchain-ai/langchainjs: 449 lines covering Corridor security analysis, Project Overview, Repository Structure, Development Setup and more.

LangChain framework for building LLM apps with agents, chains, and RAG across providers.

AGENTS.md from langchain-ai/deepagents: 164 lines covering Corridor security analysis, Development workflow, PR conventions, Core development principles and…

Advanced guide for Arabic Langchain

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system.

AGENTS.md from langchain-ai/open-swe: 68 lines covering Constant gardening, Conventions, Testing, Pull Requests and more.

Run LangChain Open Deep Research or LangGraph-based iterative research workflows with configurable retrieval, reflection, and server-backed execution.

Plan, implement, or review langchain architecture work in an existing codebase with compatibility, security, and verification controls.

Go implementation of LangChain for writing LLM-based programs from composable building blocks.

Design LLM applications using LangChain 1.x and LangGraph for agents, memory, and tool integration.

INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph…

Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.