Machine learning model training data generation from generative artificial intelligence and user feedback

Abstract

Implementations of this disclosure provide a machine learning model training system that receives user input being a natural language description of a search query, and packages and transmits the natural language description as a prompt to a plurality of large learning models (LLMs). The model training system also receives response from the plurality of LLMs being translations of the natural language descriptions to an executable search query and displays the translations to a user via a graphical user interface. The model training system receives user feedback via the graphical user interface that corresponds to indications as to whether each translation is correct, syntactically and/or semantically, and, in some examples, an indication of which response was preferred. The model training system also generates training data from the user input, translations generated by the plurality of LLMs, and user feedback, and subsequently, initiates training of a LLM using the training data.