A practical course code repository based on the LangChain framework, containing 23 chapters of hands-on examples to help developers master LLM application development.
One-Minute Overview#
LangChain in Action is a comprehensive learning resource for the LangChain framework, suitable for developers with Python and AI background who want to build applications based on Large Language Models. This course consists of 23 practical chapters systematically explaining core concepts and real-world applications of LangChain, enabling you to master AI application development from theory to practice.
Core Value: Systematic practical tutorials that help you quickly master the complete development workflow of the LangChain framework.
Quick Start#
Installation Difficulty: Medium - The project has many dependencies including multiple LangChain-related libraries and database components
git clone https://github.com/huangjia2019/langchain-in-action.git
cd langchain-in-action
pip install -r requirements_v0.2.txt
Is this suitable for my needs?
- ✅ Developers wanting to systematically learn the LangChain framework: The course structure is clear, progressing from basic to advanced concepts
- ✅ AI application developers needing practical examples: Includes complete sample code for 23 chapters
- ❌ Complete AI beginners: Need to understand Python and basic AI concepts first
- ❌ Developers seeking simple solutions: The project has high complexity and requires significant learning investment
Core Capabilities (Optional)#
1. Complete LangChain Learning System - From Beginner to Professional#
- 23 structured chapters covering core concepts and advanced applications of LangChain Actual Value: Helps developers build a systematic knowledge framework of LangChain, avoiding fragmented learning
2. Rich Practical Examples - Theory Combined with Practice#
- Each chapter includes practical code examples that can be run and modified directly Actual Value: Deepens understanding through practice and enables quick start on real projects
3. Enterprise Application Scenarios - Cutting-Edge Technology Implementation#
- Covers enterprise-level applications like intelligent Q&A, document processing, and knowledge base construction Actual Value: Master ready-to-use solutions that can be applied in real work scenarios
Tech Stack & Integration (Optional)#
Development Language: Python Main Dependencies: LangChain series libraries (langchain-core, langchain-openai, langchain-community), OpenAI API, SQLAlchemy, Qdrant vector database Integration Method: Library/Framework
Maintenance Status (Optional)#
- Development Activity: Low - Project update frequency is not high, but course content is quite comprehensive
- Recent Updates: Not updated for a long time, but course materials have formed a complete system
- Community Response: Moderate - There are 3 open issues, indicating some user feedback
Documentation & Learning Resources (Optional)#
- Documentation Quality: Comprehensive - Includes complete course materials and sample code
- Official Documentation: Course Link
- Sample Code: Yes - Complete sample code for 23 chapters