Google patents feedback buttons for specific parts of AI answers

1. A method implemented using one or more processors, the method comprising: receiving a user query, the user query being received via a user interface of a client device; generating, using a generative model, a generative response that is responsive to the user query and that includes at least media content to be rendered and one or more selectable elements to be rendered with respect to media content, wherein each of the one or more selectable elements are selectable and correspond to a respective type of user feedback that evaluates the media content with respect to the user query, and wherein the one or more selectable elements includes a given selectable element that corresponds to negative user feedback; causing the media content to be rendered at the user interface; causing the one or more selectable elements to be rendered at the user interface and with respect to the media content; in response to receiving user input that selects the given selectable element, of the one or more selectable elements, that corresponds to the negative user feedback: determining, based on the received user input that selects the given selectable element, user feedback that evaluates the media content with respect to the user query, wherein determining the user feedback that evaluates the media content with respect to the user query comprises: causing a feedback window to be rendered at the user interface, wherein the feedback window is rendered in response to receiving the user input that selects the given selectable element, and wherein the feedback window includes one or more selectable options each displaying a corresponding description that classifies the negative user feedback; receiving additional user input that selects one of the one or more selectable options; and determining a classification of the negative user feedback based on the additional user input; and training or fine-tuning the generative model based on at least the user feedback that evaluates the media content with respect to the user query, wherein training or fine-tuning the generative model based on the user query and the user feedback that evaluates the media content with respect to the user query comprises: in response to determining that the classification of the negative user feedback is a first classification: reinforcing the generative model to not output a tag or prompt utilized to obtain the media content in response to the user query, and in response to determining that the classification of the negative user feedback is a second classification different from the first classification: rewriting an input prompt that is processed as input using the generative model; and training or fine-tuning the generative model using the rewritten input prompt.