LLM Universe
A Chinese-language, hands-on tutorial that teaches beginner developers to build large language model applications, from calling LLM APIs through building a knowledge-base RAG assistant to iterative evaluation.
LLM Universe is a tutorial for developers new to building large language model applications, organized around one running example: a personal knowledge-base assistant. It introduces what large models and LangChain are, then covers calling large-model APIs directly, wrapped as LangChain components, or wrapped behind FastAPI, with unified handling for several Chinese and international model providers.
Later sections cover building a knowledge base, including loading and processing different document types and setting up a vector database, constructing a retrieval-augmented generation pipeline by connecting an LLM to LangChain's retrieval chain, deploying the result with Streamlit, and iterating on and evaluating the finished application.
The course is aimed at developers with basic Python skills and assumes no prior algorithms or machine-learning background; it does not require a GPU and provides a guide for a free Alibaba Cloud student server as well as a local setup path. A companion project from the same authors covers deploying open-source models locally, and another covers the theory behind large models in more depth.