Add a Knowledge Base to your Amazon Bedrock app
You can use Knowledge Base components to store data from an external data source for use in a chat agent app or flow app. The data source for a Knowledge Base can be a document, such as a PDF file, or content from a web crawler that gathers content from specific source URLs. When you create a Knowledge Base, you specify an embeddings model to convert the data into numerical vector representations and a vector store for storing and managing your embeddings. Vector stores can be easily indexed for efficient retrieval in a process known as retrieval augmented generation (RAG). RAG enables foundation models to generate more accurate responses by providing relevant context from the vector store.
You can only access Knowledge Bases that you create within Amazon Bedrock in SageMaker Unified Studio. You can't access Knowledge Bases that you create in the Amazon Bedrock console or AWS SDK.
For more information, see Build and manage knowledge bases for retrieval and responses in the Amazon Bedrock User Guide.