LangChain Documentation

Comprehensive documentation for LangChain and LangGraph frameworks. Covers building LLM applications, agents, and stateful workflows in Python and JavaScript/TypeScript.

Quick Reference

When to use

Use this skill when the user asks about:

• Building LLM applications with LangChain
• Creating agents and multi-agent systems
• Building stateful workflows with LangGraph
• Integrating with chat models, embeddings, vector stores, and tools
• Python or JavaScript/TypeScript implementations
• Prompt engineering, context management, and structured outputs
• RAG (Retrieval-Augmented Generation) patterns
• Memory management and state persistence
• Middleware, guardrails, and observability
• Deploying LangChain applications

How to find information

1. First, read TOC.md for complete file listing organized by directory
2. Choose the appropriate language section (python/ or javascript/)
3. Pick the framework (langchain/ for core, langgraph/ for stateful workflows)
4. Navigate to specific integrations, guides, or API references

TOC.md contains all 1700+ files organized by directory - always check it first.

Documentation Organization

• langchain/: Core framework concepts, agents, tools, models, memory
• langgraph/: Stateful workflows, graph API, persistence, interrupts
• python/: 1290 Python files including extensive integrations
• javascript/: 306 JavaScript/TypeScript files with provider integrations
• integrations/: Provider-specific documentation (chat models, embeddings, vector stores, etc.)
• migrate/: Version migration guides
• concepts/: Architectural concepts
• reference/: API reference documentation

Use the Quick Reference table above to quickly access common entry points, then explore related files for detailed information.