Unverified50% confidenceSolutionExact time
RAG通过检索+生成两阶段架构，先将问题转化为向量表示在向量数据库（如Faiss、Milvus、Chroma）中进行语义检索，弥补大模型知识固化和无法感知私有信息的缺陷
1
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50%
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Long-term
Relevance
7/22/2026
First Seen
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Related Claims
VerifiedRAG（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82% similarVerifiedThe RAG architecture is divided into a retrieval stage and a generation stage; the retrieval stage uses vector databases (such as Chroma, Pinecone, and Milvus) to recall relevant text segments via cosine similarity.81% similarUnverifiedThe working principle of RAG is divided into a retrieval phase (converting the question into a vector to recall relevant content from the knowledge base) and a generation phase (inputting the recalled context together with the question into the model to produce an answer).80% similar
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