GENERATING AND MAINTAINING COMPOSITE ACTIONS UTILIZING LARGE LANGUAGE MODELS

    公开(公告)号:US20250111149A1

    公开(公告)日:2025-04-03

    申请号:US18478066

    申请日:2023-09-29

    Applicant: Dropbox, Inc.

    Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating composite actions for a user account. In particular, in one or more embodiments, the disclosed systems determine a set of tasks performable by the user account using software tools on a client device. In some embodiments, the disclosed systems generate a task initialization prompt to provide to a large language model. Additionally, in some implementations, the disclosed systems generate a composite action comprising a hybridized combination of the set of tasks performable by the user account along with a set of content items relevant to the set of tasks. Moreover, in some embodiments, the disclosed systems provide access to the composite action and the set of content items via a user interface of the client device. Furthermore, in some implementations, the disclosed systems generate and insert predicted content into a content item without user input.

    GENERATING AND MAINTAINING COMPOSITE ACTIONS UTILIZING LARGE LANGUAGE MODELS

    公开(公告)号:US20250111148A1

    公开(公告)日:2025-04-03

    申请号:US18478061

    申请日:2023-09-29

    Applicant: Dropbox, Inc.

    Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating composite actions for a user account. In particular, in one or more embodiments, the disclosed systems determine a set of tasks performable by the user account using software tools on a client device. In some embodiments, the disclosed systems generate a task initialization prompt to provide to a large language model. Additionally, in some implementations, the disclosed systems generate a composite action comprising a hybridized combination of the set of tasks performable by the user account along with a set of content items relevant to the set of tasks. Moreover, in some embodiments, the disclosed systems provide access to the composite action and the set of content items via a user interface of the client device. Furthermore, in some implementations, the disclosed systems generate and insert predicted content into a content item without user input.

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