handy-ollama

Why we included this project

Most open-source LLMs assume you have a GPU to run them, which rules out a lot of ordinary laptops and desktops. This Chinese-first tutorial closes that gap with Ollama: it covers installing the tool on macOS, Windows, Linux, or Docker, importing GGUF and Safetensors weights, defining custom prompts, and calling the REST API from Python, Java, JavaScript, or C++ code. Later chapters get into real integration, wiring Ollama into LangChain and building RAG and agent examples with FastAPI and WebUI front ends. The project also carries some institutional weight, since the Ollama team listed it as the reference tutorial in their own repository. It is documentation and sample code rather than something you deploy directly, so treat it as a learning resource, but one full of concrete commands that suit teams prototyping local inference on modest hardware.