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modelscope.cn

langchain-docs

Local LangChain AI documentation reference. Use when asked about LangChain, LangGraph, agents, chains, prompts, memory, tools, retrieval, RAG, vector stores, document loaders, or building LLM applications.

Installation

$ npx skills add https://modelscope.cn
View on skills.sh ↗ Website ↗

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npx skills add https://modelscope.cn
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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,494 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

LangChain Documentation

LangChain is a framework for building LLM-powered applications. It provides components for chains, agents, RAG, memory, and tools. LangGraph extends this with stateful multi-agent orchestration.

Navigation Guide

LangChain: references/langchain/ - Core framework docs (51 files)

  • Agents, chains, RAG, memory, tools, models, guardrails
  • Key files: overview.mdx, agents.mdx, knowledge-base.mdx

LangGraph: references/langgraph/ - Multi-agent orchestration (35 files)

  • Graph API, memory, interrupts, durable execution
  • Key files: graph-api.mdx, memory.mdx, agentic-rag.mdx

Python SDK: references/python/ - Python API reference (1283 files)

  • Complete API docs for langchain-core, langchain, langgraph

JavaScript SDK: references/javascript/ - JS/TS API reference (299 files)

  • Complete API docs for @langchain/core, langchain, langgraph

Concepts: references/concepts/ - Foundational concepts (2 files)

Deep Agents: references/deepagents/ - Advanced agent patterns (10 files)

Key Entry Points

Task Start Here
Getting started references/learn.mdx
LangChain overview references/langchain/overview.mdx
Build an agent references/langchain/agents.mdx
RAG implementation references/langchain/knowledge-base.mdx
LangGraph intro references/langgraph/graph-api.mdx
Memory & state references/langgraph/memory.mdx
Python API references/python/
JavaScript API references/javascript/

When to use

Use this skill when the user asks about:

  • LangChain chains, agents, or components
  • LangGraph multi-agent orchestration
  • RAG (Retrieval Augmented Generation)
  • Memory and conversation history
  • Tools and tool calling
  • Vector stores and embeddings
  • Building LLM applications

How to find information

  1. First, read references/STRUCTURE.md to see all 1688 documentation files organized by directory
  2. Use Navigation Guide to find the section
  3. Check Key Entry Points for common tasks
  4. For API details: references/python/ or references/javascript/

STRUCTURE.md contains a complete file listing - always check it first when searching for specific topics.