Prompt refinement to improve accuracy of outputs from machine learning models

A method comprising:

• receiving, from a user, a user input indicating a request for output;
• determining, based on analyzing the user input, a first output category associated with the user input, wherein the first output category is selected from a plurality of output categories comprising text-based output, visual output, and code-based output;
• selecting, based on the first output category, a first model from a plurality of models, wherein each model of the plurality of models is associated with a respective output category of the plurality of output categories;
• generating a first output by inputting the user input into the first model to cause the first model to generate the first output based on the user input;
• determining, based on analyzing the first output, that a second output category relates to further processing required for the user input;
• selecting, based on the second output category, a second model from the plurality of models, wherein the second model is different from the first model;
• generating a prompt based on the user input and the first output;
• generating a second output by inputting the prompt into the second model to cause the second model to generate the second output based on the prompt;
• and
• transmitting, to the user, a final output based on the first output and the second output.

A system comprising:

• a storage device;
• and
• one or more processors communicatively coupled to the storage device storing instructions thereon that cause the one or more processors to:
• receive, from a user, a user input indicating a request for output;
• determine, based on analyzing the user input, a first output category associated with the user input, wherein the first output category is selected from a plurality of output categories comprising text-based output, visual output, and code-based output;
• select, based on the first output category, a first model from a plurality of models, wherein each model of the plurality of models is associated with a respective output category of the plurality of output categories;
• generate a first output by inputting the user input into the first model to cause the first model to generate the first output based on the user input;
• determine, based on analyzing the first output, that a second output category relates to further processing required for the user input;
• select, based on the second output category, a second model from the plurality of models, wherein the second model is different from the first model;
• generate a prompt based on the user input and the first output;
• generate a second output by inputting the prompt into the second model to cause the second model to generate the second output based on the prompt;
• and
• transmit, to the user, a final output based on the first output and the second output.