Knowledgebase recipes use a data processing workflow to create knowledgebases for Generative AI applications. They ingest data from configured sources and datasets, generate vector embeddings, and persist them in a vector store (for example, OpenSearch). The resulting knowledgebase can then be consumed by downstream workflows to retrieve relevant context for user queries.
