#5454th of 55 in Learning and cookbooks
langchain-chinese-getting-started-guide
Chinese-language LangChain tutorial with runnable OpenAI examples
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- Stars
- 9.1k
- License
- no license
- Last commit
- Apr 2026
8,794 on 1 Apr 20269,146 on 21 Oct 2026
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Overview
A Chinese-language tutorial that teaches LangChain through worked Python examples: Q&A, Google search agents, long-text summarization, local-document Q&A with Chroma and Pinecone, YouTube Q&A, and Zapier tool use. It also covers sequential chains, structured output parsing and web scraping to JSON. The author warns it was written in early April 2023 and some Colab code is outdated.
Who it is for: Chinese-reading developers learning LangChain basics and RAG
Strengths
- Examples run in order and build on each other, from one Q&A call to agents
- Covers RAG with both local Chroma and hosted Pinecone persistence
- Explains summarize chain types (stuff, map_reduce, refine) and chunk_overlap with diagrams
- Gitbook edition and a CHANGELOG are provided for reading and tracking updates
Weaknesses
- Written in April 2023; the author says some code is outdated against current LangChain
- Uses legacy APIs such as text-davinci-003, initialize_agent and ChatVectorDBChain
- Most examples need an OpenAI key, plus SerpAPI, Pinecone or Zapier accounts
- No license declared; the text is Chinese only
What it needs
- no GPU
- Needs OpenAI API, SerpAPI, Pinecone, Chroma, Zapier NLA
- Models: text-davinci-003, gpt-3.5-turbo, text-embedding-ada-002
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