Agentic retrieval with LangChain and Amazon Bedrock Knowledge Bases
中文摘要
在 Amazon Bedrock 受管理的知识库上构建一个检索增强生成（RAG）应用程序，使用 LangChain，并查看代理检索如何处理单次检索回答不好的多部分问题。通过两种路径运行相同的查询，阅读跟踪事件，并比较每种检索路径的成本。
英文原文
Build a Retrieval Augmented Generation (RAG) application on Amazon Bedrock Managed Knowledge Base with LangChain, and see how agentic retrieval handles the multi-part questions that single-shot retrieval answers poorly. Run the same query through both paths, read the trace events, and compare what each retrieval path costs.