Unverified50% confidenceFactExact time
RAG系统的行为由基础语言模型、向量数据库中的知识文档、检索策略和提示词模板三个变量共同决定
1
Sources
50%
Confidence
Long-term
Relevance
7/11/2026
First Seen
Sources
Related Claims
UnverifiedRAG (Retrieval-Augmented Generation) is collaboratively composed of three components: a vector database, an embedding model, and a generative model.83% 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).79% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/474815API
curl https://kongchang.com/api/v1/knowledge/claims/474815MCP
get_claim(id=474815)