LangChain 与 Amazon Bedrock 知识库的智能体检索

AI 摘要

AWS Machine Learning Blog 发布了一篇技术文章，介绍如何在 Amazon Bedrock Managed Knowledge Base 上结合 LangChain 实现 agentic retrieval（智能体检索）。文章对比了标准单次检索与智能体检索：后者会将多部分问题拆解为子查询、执行检索、判断证据是否充分，并在不足时再次检索，通过 AgenticRetrieveStream API 以 trace 事件流式返回规划步骤。文章还给出了基于 S3 数据源、IAM 权限配置和 langchain-aws 包的完整实现步骤，并讨论了两种检索路径的成本差异及适用场景。

正文节选

Agentic retrieval with LangChain and Amazon Bedrock Knowledge Bases When a user asks the support assistant, a Retrieval Augmented Generation (RAG) application built with LangChain to compare two products across three dimensions, they’re effectively posing six questions simultaneously. Similarity search uses a single query vector to encapsulate all the intents. The retriever then generates the best approximation of the average of those intents. The resulting answer comes back concise. The search

发布时间：2026-10-05 23:53

抓取时间：2026-10-06 00:36

来源机构：AWS