Abstract: A method includes receiving a request indication indicating a GUI interaction by a user on a user device, and in response, providing to the device a response configured to cause the device to display, within a GUI, a structured prompt including a plurality of user input fields, each user input field representing a corresponding training sample and including a first corresponding text input field for capturing input text to be provided to an ML model, and a second corresponding text input field for capturing ground-truth output text. The method also includes receiving, from the device, the training samples, and, in response, adjusting the ML model using the training samples. The method further includes receiving, from the device, test input text, generating, using the adjusted ML model, test output text based on the test input text, and providing, to the user device, the test output text for display within the GUI.

Abstract: A method includes receiving a request indication indicating a GUI interaction by a user on a user device, and in response, providing to the device a response configured to cause the device to display, within a GUI, a structured prompt including a plurality of user input fields, each user input field representing a corresponding training sample and including a first corresponding text input field for capturing input text to be provided to an ML model, and a second corresponding text input field for capturing ground-truth output text. The method also includes receiving, from the device, the training samples, and, in response, adjusting the ML model using the training samples. The method further includes receiving, from the device, test input text, generating, using the adjusted ML model, test output text based on the test input text, and providing, to the user device, the test output text for display within the GUI.