llm-action is a comprehensive resource hub for large language model engineering that combines theoretical explanations with practical implementation code. It covers the full LLM lifecycle including data engineering, training (full fine-tuning and parameter-efficient methods like LoRA/QLoRA), model compression (quantization, pruning, distillation), inference serving, deployment, and evaluation. The repository contains both educational documentation and runnable code examples, with particular emphasis on Chinese-language resources and domestic AI hardware adaptation (especially Huawei Ascend NPUs). While it serves as a knowledge base, its inclusion of actual training scripts, inference servers, and utility tools makes it primarily application-oriented rather than purely research-focused.