Systems and methods for automated machine learning model training for a custom authored prompt

A system for training a model for a custom authored prompt, the system comprising:

• a memory comprising:
• a content library database comprising a plurality of prompts, and
• a model database comprising at least one prompt evaluation model trained to evaluate prompts;
• and
• at least one processor configured to:
• receive a prompt;
• parse the prompt to identify a plurality of prompt evaluation portions;
• identify pre-existing data relevant to at least one prompt evaluation portion of the prompt evaluation portions;
• train a response evaluation model for evaluating responses to the prompt at least in part based on the pre-existing data;
• provide the prompt to a user;
• receive a response to the provided prompt;
• generate an evaluation of the received response;
• determine sufficiency of the training of the response evaluation model;
• update the training based on the received response and on the evaluation of the received response to determine new training data when the training of the response evaluation model is insufficient;
• determine a plurality of responses and a plurality of evaluations of the plurality of received responses;
• determine an ordering to the received responses;
• train based on the ordering of the received responses;
• and
• generate a training indicator, wherein the training indicator is configured to provide a graphical depiction of a degree to which the response evaluation model is trained based upon the updating of the training of the response evaluation model.