Abstract: Agentic digital assistant methods and systems for generating a response to a user query are disclosed. A computer-implemented method includes accessing a query, executing planner modules in parallel to generate respective executable actions to retrieve information for answering the query, using a primary planner module of the planner modules to generate an execution plan for executing the executable actions, executing the executable actions per the execution plan to generate a set of results for the executable actions, and generating a response to the query using the set of results.

Abstract: A computer-implemented method includes receiving a query in natural language, generating an input for a large language model, the input including a prompt generated based on the query, and identifying a plurality of slots associated with a plurality of sections of a content item. The method further includes generating a query result based on the input, the query result including a subset of the plurality of slots selected, extracting one or more document chunks from a database storing a plurality of document chunks as one or more relevant document chunks associated with the query result, formatting the relevant document chunks into a response to the query, and providing the response to a client system. The plurality of document chunks is generated by dividing each content item of a plurality of content items into the plurality of document chunks based on sections within each content item.

Abstract: Methods and systems for cluster-based historical data are disclosed. In one embodiment, a method includes accessing historical data associated with a plurality of users and, based on the historical data, constructing a plurality of clusters including historical data associated with a subset of the users. The method further includes, for each cluster, identifying users in the subset of users that are historically improving users, and, for each historically improving user, determining, based on the historical data associated with the historically improving user, a positive predictive attribute indicative of historical improvement. The method further includes receiving, from a new user, a request for a recommendation, accessing historical data associated with the new user, based on the historical data associated with the new user, selecting a cluster, determining the recommendation based on the positive predictive attribute for the selected cluster, and providing the recommendation to the new user.

Abstract: Methods and systems for cluster-based historical data are disclosed. In one embodiment, a method includes accessing historical data associated with a plurality of users and, based on the historical data, constructing a plurality of clusters. Constructing each cluster involves selecting a subset of comparable users and including in the cluster historical data associated with the subset of comparable users. The operations further include storing the cluster, receiving, from a new user, a request for a recommendation, and accessing historical data associated with the new user. The operations further include, based on the historical data associated with the new user, selecting a cluster for which the subset of comparable users is comparable to the new user, based on the selected cluster, determining a recommendation, and providing the recommendation to the new user.