retrieve

You can search an Amazon Bedrock knowledge base using RAG by querying indexed documents with keywords. The retrieval skill utilizes vector search to return matched content chunks alongside source URLs and titles for reference.

Yes, you can retrieve specific content from S3 and web-crawled documents. The RAG-based retrieval searches indexed knowledge base content, returning matched text chunks and providing links to the original web pages or stored S3 files for reference.

RAG retrieval works by using vector search to find relevant content within an indexed knowledge base. When you query, it matches your search terms to stored document chunks, eliminating manual sifting and returning targeted results with source references.

Yes, you need the boto3 Python library installed as a dependency to use this knowledge base retrieval skill. It provides the necessary API interface to communicate with Amazon Bedrock and execute RAG-based search queries on your indexed documents.

The best way to query cloud architecture best practices from uploaded documents is using a RAG-based knowledge base search. It retrieves relevant document chunks via vector search and returns them with URLs to the original sources, saving manual review time.