LLM Introductory Tutorial Chinese Version

Motivation

LLM is gradually changing people’s lives, and for developers, how to quickly and easily develop some applications with stronger capabilities and integrated LLM based on the APIs provided by LLM to conveniently realize some more novel and practical capabilities is an important capability that is urgently needed to learn.

The Big Model series of tutorials launched by Mr. Ernest Wu in cooperation with OpenAI starts from the basic skills of developers in the era of Big Model, and introduces in depth how to quickly develop applications combining the powerful capabilities of Big Model based on the Big Model API and LangChain architecture. Among them, “Prompt Engineering for Developers” is a classic tutorial for the beginner LLM developers, which introduces in depth how to construct a Prompt and realize various common functions including summarization, inference, transformation, etc. based on the API provided by OpenAI; “Building Systems with the ChatGPT” is a classic tutorial for the beginner LLM developers; “Building Systems with the ChatGPT” is an in-depth tutorial for the beginner LLM developers. Building Systems with the ChatGPT API" is a classic tutorial to get started in LLM development; “Building Systems with the ChatGPT API” is aimed at developers who want to develop applications based on LLM, and it introduces how to build a complete dialog system based on the ChatGPT API in a concise, effective and systematic way; “LangChain for LLM Application The “LangChain for LLM Application Development” tutorial combines the classic open source framework for large models, LangChain, and introduces how to develop applications with practical functions and comprehensive capabilities based on the LangChain framework, and the “LangChain Chat With Your Data” tutorial further introduces how to develop personalized large model applications using the LangChain architecture in combination with personal private data. The “LangChain Chat With Your Data” tutorial builds on this foundation by showing how to use the LangChain architecture to develop personalized big model applications that incorporate private personal data.

These tutorials are ideal for developers who want to get started on the road to actually building applications based on LLM. Therefore, we have translated this series of courses into Chinese, reproduced the sample code, and added Chinese subtitles to one of the videos to support Chinese learners in China, so as to help Chinese learners learn LLM development better; we have also implemented a Chinese Prompt with roughly the same effect, so as to support learners to feel the learning and use of LLM in the Chinese context, and to master the design of Prompts and LLM in the multi-language context. We have also implemented a Chinese Prompt with similar effect to support learners to experience the use of LLM in Chinese context, and to compare the design of Prompt and LLM development in multilingual context. In the future, we will add more advanced Prompt techniques to enrich the content of this course and help developers master more and more skillful Prompt skills.