Unverified50% confidenceSolutionExact time
从历史工单自动提炼标准化流程的系统通常采用RAG（检索增强生成）架构，先将历史工单向量化存入向量数据库，再通过语义检索找到相关案例，最后由LLM生成标准化流程
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8/29/2026
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Unverified工程界普遍采用RAG架构：将历史信息切分成语义块，通过嵌入模型转化为向量存入向量数据库（如Faiss、Pinecone、Weaviate），用户提问时计算余弦相似度检索最相关片段79% similarVerified典型的RAG流程包括文档切片、向量化嵌入、存入向量数据库、语义检索、上下文拼接和最终生成六个步骤78% similarUnverifiedMainstream industry strategies for context management include RAG dynamically retrieving via vector databases, sliding window mechanisms retaining execution history, and memory distillation compressing long conversations into structured summaries.78% similarUnverifiedThe workflow of a production-grade RAG system typically includes stages such as query rewriting, hybrid retrieval, reranking, answer generation, and citation annotation.77% similarUnverifiedIn the offline phase of the traditional RAG process, documents are chunked and converted into vectors via an embedding model and stored in a vector database; in the online phase, similar document chunks are retrieved using an Approximate Nearest Neighbor (ANN) algorithm.76% similar
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