Content retrieval standardization using generative artificial intelligence (ai) models

A system comprising:

• a processing system having a processor;
• and
• a computer memory including instructions that, when executed by the processing system, cause the system to carry out operations comprising:
• in response to receiving a user query, generating a query intent prompt with instructions to generate a search query intent based on the user query and user profile information outputted in a standardized object format;
• generating one or more content item prompts with instructions to generate categories of content items outputted in the standardized object format;
• based on receiving a query intent response for the query intent prompt from a generative AI model and receiving one or more content category responses for the one or more content item prompts from the generative AI model, determining a set of content matches between the user query and the content items;
• determining a correlation score for each content match in the set of content matches using a distilled encoder neural network;
• and
• selecting a content item from the content items based on correlation scores.

A computer-implemented method for performing content item retrieval based on one or more generative artificial intelligence (AI) models, comprising:

• in response to receiving a user query, generating a query intent prompt with instructions to generate a search query intent based on the user query and user profile information outputted in a standardized object format;
• based on receiving a query intent response for the query intent prompt from a generative AI model, determining a set of content matches between the query intent response and content items with attributes and features formatted in the standardized object format;
• determining a correlation score for each content match in the set of content matches using a distilled encoder neural network;
• and
• selecting a content item from the content items based on correlation scores.