Agentic retrieval with LangChain and Amazon Bedrock Knowledge Bases

What happened

Agentic retrieval is available on Amazon Bedrock Managed Knowledge Base. Build a Retrieval Augmented Generation (RAG (letting a model look information up instead of relying on memory)) application on Amazon Bedrock Managed Knowledge Base with LangChain (language model application development framework), and see how agentic (AI that carries out multi-step tasks rather than answering one question) 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. 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 operates with a single query vector to encapsulate all the intents. Yet the retrieved chunks, while topically relevant, only cover a fraction of what the question actually asked.

Key facts

• Similarity search — uses: a single query vector to encapsulate all the intents