Recommending items or recipes based on health conditions associated with online system users

A computer program product comprising a non-transitory computer-readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to perform steps comprising:

• retrieving, at an online system, a set of historical interaction data for a user of the online system describing a set of objects with which the user previously interacted;
• receiving a set of health data associated with the user;
• accessing a multiclass classification model trained to classify whether the user has each health condition of a set of health conditions, wherein the multiclass classification model is trained by:
• receiving historical interaction data describing a plurality of objects with which a plurality of users of the online system previously interacted,
• receiving health data for the plurality of users,
• receiving a set of labels for each user of the plurality of users, wherein each label of the set of labels indicates an existence of a health condition associated with a corresponding user, and
• training the multiclass classification model based at least in part on the historical interaction data, the health data, and the label for each user of the plurality of users;
• applying the multiclass classification model to classify whether the user has each health condition of a set of health conditions based at least in part on the set of historical interaction data for the user and the set of health data associated with the user;
• generating a prompt comprising a set of classes associated with the user and a request for a set of objects appropriate for the user, wherein the set of classes indicates whether the user has each health condition of the set of health conditions and an appropriateness of an object for the user is based at least in part on whether the user has each health condition of the set of health conditions;
• providing the prompt to a large language model to obtain a textual output;
• extracting, from the textual output of the large language model, one or more objects for recommendation to the user, wherein the one or more objects comprise one or more of an item or a recipe;
• and
• sending a recommendation for the one or more objects for display to a client device associated with the user.

A computer system comprising:

• a processor;
• and
• a non-transitory computer-readable storage medium storing instructions that, when executed by the processor, perform actions comprising:
• retrieving, at an online system, a set of historical interaction data for a user of the online system describing a set of objects with which the user previously interacted;
• receiving a set of health data associated with the user;
• accessing a multiclass classification model trained to classify whether the user has each health condition of a set of health conditions, wherein the multiclass classification model is trained by:
• receiving historical interaction data describing a plurality of objects with which a plurality of users of the online system previously interacted,
• receiving health data for the plurality of users,
• receiving a set of labels for each user of the plurality of users, wherein each label of the set of labels indicates an existence of a health condition associated with a corresponding user, and
• training the multiclass classification model based at least in part on the historical interaction data, the health data, and the label for each user of the plurality of users;
• applying the multiclass classification model to classify whether the user has each health condition of a set of health conditions based at least in part on the set of historical interaction data for the user and the set of health data associated with the user;
• generating a prompt comprising a set of classes associated with the user and a request for a set of objects appropriate for the user, wherein the set of classes indicates whether the user has each health condition of the set of health conditions and an appropriateness of an object for the user is based at least in part on whether the user has each health condition of the set of health conditions;
• providing the prompt to a large language model to obtain a textual output;
• extracting, from the textual output of the large language model, one or more objects for recommendation to the user, wherein the one or more objects comprise one or more of an item or a recipe;
• and
• sending a recommendation for the one or more objects for display to a client device associated with the user.