LangChain Docs — Guide

LangChain Docs — User Guide

LangChain documentation.

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Strengths

LangChain official authoritative document
Contains numerous code examples and tutorials
Covers all LangChain components
Updated regularly to reflect the latest version
Provides interactive notebook examples

Best for

Learn how to use the LangChain framework
Find API documentation for a specific component
Understand how functions such as RAG and Agent are implemented
Learn best practices from LangChain
Troubleshooting issues in using LangChain

Document structure navigation

The LangChain documentation is rich in content, and you can quickly find the information you need by mastering the navigation method.

Scenario

Get started quickly

Prompt example

Main parts of LangChain documentation:

1. Get Started
   - Installation and configuration
   - The first LangChain application

2. Tutorials
   - Build simple LLM applications
   - Build chatbots
   - Build RAG applications
   - Build Agent

3. How-to Guides
   - How specific tasks are accomplished
   - Solutions to common problems

4. Conceptual Guide
   - Core concepts of LangChain
   - Architectural design description

5. API Reference
   - Complete documentation of all classes and functions

Output / what to expect

Through the document structure,

Beginners start with Tutorials,

Experienced developers can directly check the API Reference.

Tips

LangChain is updated frequently. When encountering problems, please check whether the document version is consistent with the installed version.

Scenario

Find documentation for a specific feature

Prompt example

Document locations for commonly used functions:




Document Loaders:


python.langchain.com/docs/integrations/document_loaders/




Vector Stores:


python.langchain.com/docs/integrations/vectorstores/




LLM integration:


python.langchain.com/docs/integrations/llms/




Tools:


python.langchain.com/docs/integrations/tools/




Search tips:


- Use Ctrl+K to search quickly


- Search GitHub Issues for specific issues

Output / what to expect

Quickly find the integration documents you need,

LangChain supports hundreds of integrations,

There is sample code in the documentation.

Tips

If you can't find the answer in the documentation, LangChain's GitHub Issues and Discord communities can often solve the problem.

Version compatibility

LangChain is updated frequently, and it is important to understand version changes.

Scenario

Handle version compatibility issues

Prompt example

LangChain version notes:




Current major version:


- langchain-core: core abstraction


- langchain: main framework


- langchain-community: community integration


- langchain-openai: OpenAI integration




Installation suggestions:


pip install langchain langchain-openai




Common compatibility issues:


- The import path of the old version has been changed


- Some APIs are deprecated


- Check out the Migration Guide for changes




Check version:


pip show langchain

Output / what to expect

After understanding the version structure,

Compatibility issues can be better handled,

The Migration Guide is a must-read when upgrading.

Tips

It is recommended that new projects use the latest stable version and check the Changelog regularly for important changes.

Compared with similar tools

Tool	Strength	Best for	Pricing
LangChain Docs This tool	Official and authoritative, with the most complete content and rich examples	LangChain developer, learn LLM application development	completely free
LlamaIndex Docs	RAG functions are more focused and in-depth	Focus on RAG and data connectivity	completely free
LangSmith Docs	LangChain Debugging and Monitoring	Debugging LangChain applications	Free version/paid version
LangGraph Docs	Complex Agent Workflow	Building a stateful Agent	completely free

Sources & references:

LangChain official documentation (2025-03)
LangChain GitHub (2025-03)