# LangChain Chinese Getting Started Guide

A Chinese-language beginner's tutorial for building applications with the LangChain framework, covering model calls, prompt management, document loaders, indexing and chains.

This is a Chinese-language getting-started tutorial for LangChain, a framework for building applications powered by language models. It explains LangChain's two main capabilities, connecting an LLM to external data sources and enabling interaction with an LLM, and is also published as a GitBook alongside the GitHub repository.

It covers LLM calls across providers such as OpenAI, Hugging Face and Azure OpenAI, a fake LLM for testing, caching backed by memory, SQLite, Redis or SQL, usage tracking, and streaming output; prompt management with custom templates; document loaders for sources such as email, Markdown, PDF and YouTube; splitting documents into chunks, converting them into vectors, and storing and searching them in vector databases such as Chroma, Pinecone or Qdrant; and chains, including the basic LLMChain and various tool chains from LangChainHub.

A companion article by the same author covers a quick introduction to the Model Context Protocol, and a related book on building large-model applications with LangChain has been published.

Website: https://github.com/liaokongVFX/LangChain-Chinese-Getting-Started-Guide