Abstract: An example computing system retrieves information from one or more applications, and receives an indication of a natural language input. The computing system applies a machine learning model to at least a portion of the information and at least a portion of the indication of the natural language input to generate instructions for generating at least one graphical component, e.g., a custom widget. The instructions may include a temporal parameter for the at least one graphical component, in which the computing system may update, based on the temporal parameter, the instructions for generating the at least one graphical component to update the at least one graphical component.

Abstract: An example computing system retrieves, using an application programming interface, information from one or more applications, and generates, based on at least a portion of the information, personal context information for a user. Responsive to receiving an indication of a natural language request to generate at least one graphical component, the computing system applies a machine learning model to the indication of the natural language request to determine at least one user intent. The computing system generates, using one or more of the information from the one or more applications and the personal context information for the user, a set of instructions including instructions for generating the at least one graphical component, e.g., a widget based on the at least one user intent.