This repository is a hands-on LangChain tutorial series for LLM application development, and its name indicates that its goal is to help developers learn through hands-on practice how to use LangChain to build large language model applications. The repository organizes content in the form of folders and files, and lists tutorial topics in the repository navigation.
Purpose: To provide hands-on tutorials related to LangChain, aimed at developers who want to develop LLM applications.
Main capabilities (based on the topics listed in the repository):
- LangChain Basics
- Retrieval Augmented Generation (RAG) based on LangChain
- Advanced LangChain Techniques
- Building LLM Agents with LangGraph
- Managing Agentic Memory with LangMem
- Getting Started with LangSmith
How to use: The material does not provide specific installation commands, code examples, or running steps; it only states that this is a GitHub repository tutorial, and the repository must be accessed to obtain the files and instructions.
Applicable scenarios: Suitable for developers learning the LangChain ecosystem, building LLM applications, RAG systems, agents, and memory management.
Limitations: The material does not provide information such as fees, pricing, platform support, specific feature details, or usage prerequisites. The above content is based only on the repository title and the listed topics; missing facts are not provided for now.
