RAGIdeal-Chat is a retrieval-augmented generation (RAG) model specifically tailored for Chinese environments. This model not only utilizes the Chinese translation of the GlaiveAI/RAG-v1 dataset but also integrates query rewriting datasets, aiming to significantly enhance its expressiveness and practicality in Chinese application scenarios. By implementing low-rank adaptation (LoRA) fine-tuning using the Qwen2.5-14B-Instruct model, along with the integration of adapter models, and processing steps such as quantization using llama.cpp, RAGIdeal-Chat is optimized to deliver superior performance.