Building Intelligent Search with Amazon Bedrock and OpenSearch
This article demonstrates how to implement a generative AI assistant that combines semantic and text-based search using Amazon Bedrock, Bedrock AgentCore, Strands Agents, and Amazon OpenSearch.
Why it matters
This article demonstrates a powerful approach to building intelligent search systems that leverage the strengths of generative AI and traditional search technologies.
Key Points
- 1Leveraging Amazon Bedrock and Bedrock AgentCore for generative AI assistant
- 2Integrating semantic and text-based search using Strands Agents and Amazon OpenSearch
- 3Implementing a hybrid Retrieval-Augmented Generation (RAG) solution
Details
The article discusses how to build an intelligent search system that combines the capabilities of generative AI and traditional text-based search. It showcases the use of Amazon Bedrock, a platform for developing and deploying large language models, and Bedrock AgentCore, which enables the creation of agentic AI assistants. The solution also integrates Strands Agents, a framework for building modular AI agents, and Amazon OpenSearch, a search and analytics service, to provide both semantic and text-based search capabilities. This hybrid Retrieval-Augmented Generation (RAG) approach allows the AI assistant to leverage both structured and unstructured data to provide more comprehensive and accurate responses to user queries.
No comments yet
Be the first to comment