待验证60% 置信事实精确时间
A typical RAG pipeline includes document chunking, vector embedding, vector database storage and retrieval, and final answer generation.
2
来源数
60%
置信度
中期 (~90 天)
时效性
2026/7/2
首次发现
有效期至：2026/9/30
来源
相关事实
待验证The offline pipeline in traditional RAG consists of document loading, text chunking, vectorization, and storage stages.77% 相似待验证Traditional RAG architectures typically require chunking documents and storing them in vector databases like Pinecone or Weaviate, with document updates requiring re-triggering of embedding and indexing pipelines77% 相似待验证RAG technology typically chunks large documents and stores them in a vector database, retrieving relevant fragments to inject into context during queries.77% 相似待验证The online pipeline in traditional RAG consists of query rewriting, dual-path retrieval (BM25 + vector), context assembly, and answer generation.76% 相似已验证RAG（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73% 相似
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