A technical guide demonstrates how to build a Retrieval-Augmented Generation (RAG) pipeline using Chinese large language models, specifically Qwen and DeepSeek. The process involves chunking source documents, embedding them into a vector store for retrieval, and then using a combination of models like Qwen3 for drafting and DeepSeek-R1 for analytical reasoning. The guide emphasizes evaluating the pipeline's faithfulness and relevance, noting that retrieval recall is often the primary challenge in Chinese RAG applications. AI
IMPACT Provides a practical blueprint for leveraging Chinese LLMs in RAG systems, highlighting their strengths in Mandarin comprehension and long context.
RANK_REASON Technical guide on implementing a specific AI application pattern.
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