Feedback integrated retrieval augmented generation (rag) framework

Abstract

Various embodiments of the present disclosure provide a feedback integrated retrieval augmented generation (RAG) framework that improves the functionality of a computer in various aspects. The techniques comprise receiving a query comprising a request content for a generative model and generating, using an embedding model, a query embedding for the query by embedding the request content. The techniques comprise receiving, from a RAG datastore, a content chunk based on the query embedding and a content embedding of the content chunk, wherein the content chunk is assigned a preprocessing tag. The techniques comprise generating a generative prompt for the query and that comprises (i) prompt instructions, (ii) the request content, and (iii) the content chunk and generating, using the generative model, a generative output based on the generative prompt. The techniques comprise routing the generative output based on the preprocessing tag.