Unverified60% confidenceFactTime unknown
The core process of Native RAG includes five steps: document chunking, embedding vectorization, storing in a vector database, semantic retrieval, and generating answers.
2
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60%
Confidence
Long-term
Relevance
6/1/2026
First Seen
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UnverifiedRAG的核心工作流程分为五步：接收用户查询、生成检索关键词、调用外部数据源、将检索结果注入提示词上下文、基于最新信息生成回答78% similarVerifiedThe typical workflow of RAG (Retrieval-Augmented Generation) consists of four steps: document chunking, vector embedding, similarity search, and context injection.78% similarVerifiedRAG（检索增强生成）技术架构将文档切片、向量化、存入向量数据库，查询时先检索相关片段再交给模型生成回答76% similar
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