Feedback integrated retrieval augmented generation (RAG) framework

A system comprising:

• one or more processors;
• and
• one or more memories storing processor-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• receiving a query comprising a request content for a generative model;
• generating, using an embedding model, a query embedding for the query by embedding the request content;
• receiving, from a retrieval augmented generation (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;
• generating a generative prompt for the query and that comprises (i) prompt instructions, (ii) the request content, and (iii) the content chunk;
• generating, using the generative model, a generative output based on the generative prompt;
• and
• routing the generative output based on the preprocessing tag.

One or more non-transitory computer-readable media storing processor-executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving a query comprising a request content for a generative model;
• generating, using an embedding model, a query embedding for the query by embedding the request content;
• receiving, from a retrieval augmented generation (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;
• generating a generative prompt for the query and that comprises (i) prompt instructions, (ii) the request content, and (iii) the content chunk;
• generating, using the generative model, a generative output based on the generative prompt;
• and
• routing the generative output based on the preprocessing tag.