Meal planning user interface with large language models

A non-transitory computer-readable storage medium storing instructions that, when executed by a computer processor, cause the computer processor to perform operations comprising:

• transmitting instructions for presenting a user interface on a client device, the user interface displaying one or more categories of preferences for a user for generating a personalized meal plan for the user of the client device;
• receiving, via the user interface presented on the client device, a set of user preferences for the personalized meal plan;
• generating a prompt for execution by a machine-learned model trained as a large language model on a large corpus of training data to perform natural language processing tasks, the prompt comprising at least a request to generate the personalized meal plan for the user and the set of user preferences;
• providing the prompt to the machine-learning model for execution;
• receiving, as output from the machine-learning model, the personalized meal plan for the user comprising a list of one or more meals for the user and a list of ingredients for making each meal;
• selecting one or more meals from the personalized meal plan for an upcoming time period;
• identifying one or more items in an item catalog corresponding to the ingredients for the one or more meals selected from the personalized meal plan;
• and
• generating an order including the items identified in the item catalog for the user to order from one or more retailer locations.

A system comprising:

• a computer processor;
• and
• a non-transitory computer-readable storage medium storing instructions that, when executed by the computer processor, cause the computer processor to perform operations comprising:
• transmitting instructions for presenting a user interface on a client device, the user interface displaying one or more categories of preferences for a user for generating a personalized meal plan for the user of the client device;
• receiving, via the user interface presented on the client device, a set of user preferences for the personalized meal plan;
• generating a prompt for execution by a machine-learned model trained as a large language model on a large corpus of training data to perform natural language processing tasks, the prompt comprising at least a request to generate the personalized meal plan for the user and the set of user preferences;
• providing the prompt to the machine-learning model for execution;
• receiving, as output from the machine-learning model, the personalized meal plan for the user comprising a list of one or more meals for the user and a list of ingredients for making each meal;
• selecting one or more meals from the personalized meal plan for an upcoming time period;
• identifying one or more items in an item catalog corresponding to the ingredients for the one or more meals selected from the personalized meal plan;
• and
• generating an order including the items identified in the item catalog for the user to order from one or more retailer locations.