Abstract: Aspects of the present disclosure relate to an online resource that can initiate a conversation between a user and an automated assistant provided by the online resource. The online resource identifies a plurality of queries from the user during the conversation between the user and the automated assistant and determines a context for each query. The online resource selects an agent for each query based on its context, and then sends the queries to their respective selected agents to generate responses. The online resource combines the responses received from the selected agents to form an answer to the query, and then provides the answer to the user.

Abstract: Certain aspects of the disclosure provide techniques for selecting functions. An example method includes receiving, as input, a user query; obtaining a plurality of function schemas that include function descriptions and examples for a plurality of functions; generating, for the user query and based on the plurality of function schemas, a plurality of similarity scores, the plurality of similarity scores including a respective set of similarity scores for each function of the plurality of functions; selecting, based on the plurality of similarity scores and a plurality of function-specific thresholds corresponding to the plurality of functions, a subset of the functions as relevant functions for the user query; generating a function plan that comprises one or more function definitions for one or more functions of the subset of the functions; and executing the function plan.

Abstract: Certain aspects of the disclosure provide techniques for validating function plans by a device. An example method includes receiving, as input, a function plan comprising a function definition that comprises a set of features associated with a function, a user query, and a function schema that corresponds to the function included in the function plan; determining a hallucination in the function definition by comparing the set of features of the function definition with one or more corresponding features included in the user query or the function schema; determining that a correct feature corresponding to the hallucination is not included in either the user query or the function schema; performing function-specific disambiguation to obtain the correct feature; modifying the function definition by replacing the hallucination with the correct feature; and executing the function plan with the modified function definition.

Abstract: Certain aspects of the disclosure provide techniques for a language mode (LM) based service. An example method includes receiving, as input, a user query; identifying a set of first function schemas corresponding to a set of first functions, the set of first functions satisfying a similarity score threshold to the user query; determining whether the user query satisfies an ambiguity threshold with regard to selection of one or more functions from the set of first functions; (1) obtaining a user input associated with a clarification or completion of the user query, identifying a set of second functions based on the user input, and selecting the one or more functions from at least the set of second functions, or (2) selecting the one or more functions from the set of first functions; generating a function plan based on the one or more functions; and executing the function plan.

Abstract: An automated assistant may receive a user request for assistance to complete a task, and may obtain a mapping between a sequence of steps for performing the task and a corresponding sequence of user interface (UI) elements presented on the user's display screen. The automated assistant identifies the UI element currently selected by the user, and presents instructions for the user to complete the corresponding step of the task. When the user provides input data at the currently selected UI element that completes the step, the automated assistant indicates the next step of the task for the user to complete.

Abstract: Systems and methods for assisting a user of an online resource are disclosed herein. The automated assistant may receive a request for assistance to complete a task and establish an interaction with the user. The task may include a sequence of steps corresponding to a sequence of user interface (UI) elements presented on the user's display screen. The automated assistant may generate instructions for the user based on transcripts of one or more previous user interactions, and provide the instructions to the user via an assistant interface presented on the user's display screen. The automated assistant may determine whether or not the user completes a respective step of the task, and either indicate completion of the respective step or provide additional guidance.

Abstract: Implementations of the subject matter described in this disclosure may be used to process queries received from a user of an online resource and route the received queries to various agents that are determined to be the most suitable for performing one or more functions in response the user queries. For each of one or more received queries, an example method may determine a function corresponding to the one or more queries, select, for each function, at least one agent of a plurality of agents based on the one or more queries, send the one or more queries to a respective agent of the selected one or more agents, and receive, from a responding agent of the selected at least one agent, at least one of a document, a message, or a link representing a result of performing the function.

Abstract: Aspects of the present disclosure relate to an online resource that can initiate a conversation between a user and an automated assistant provided by the online resource. The online resource identifies a plurality of queries from the user during the conversation between the user and the automated assistant and determines a context for each query. The online resource selects an agent for each query based on its context, and then sends the queries to their respective selected agents to generate responses. The online resource combines the responses received from the selected agents to form an answer to the query, and then provides the answer to the user.