Search Processing Based On Routing Predictions For Searching Across Local And Server Datasets

A computer-implemented method for personal data indexing and search, the method comprising:

• obtaining, by a computing system comprising one or more processors, a search query from a user computing device associated with a particular user;
• processing, by the computing system, the search query with one or more machine-learned planning models to generate one or more first application programming interface calls, wherein the one or more first programming interface calls comprise one or more first queries and instructions to interface with one or more first application-specific index datasets of a plurality of different application-specific index datasets;
• performing, by the computing system, the one or more first application programming interface calls to obtain one or more first result sets;
• processing, by the computing system, the search query and the one or more first result sets with the one or more machine-learned planning models to generate one or more second application programming interface calls, wherein the one or more second programming interface calls comprises one or more second queries and instructions to interface with one or more second application-specific index datasets of the plurality of different application-specific index datasets;
• performing, by the computing system, the one or more second application programming interface calls to obtain one or more second result sets;
• processing, by the computing system, the search query, the one or more first result sets, and the one or more second result sets with one or more generative response models to generate one or more model-generated responses to the search query, wherein the one or more model-generated responses comprise details of the one or more first result sets and the one or more second result sets in a natural language response to one or more prompts of the search query;
• and
• transmitting, by the computing system, the one or more model-generated responses to the user computing device associated with the particular user.

A server computing system for cross-application search, the system comprising:

• one or more machine-learned planning models configured to process a query to generate predicted planning data descriptive of particular tools to utilize and particular datasets to search;
• one or more server-side generative response models tuned to process queries and result datasets to generate predicted responses;
• a memory comprising a plurality of different application-specific index datasets, wherein the plurality of different application-specific index datasets are descriptive of personal data instances across a plurality of different application profiles associated with a particular user;
• one or more processors;
• and
• one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors, cause the computing system to perform operations, the operations comprising:
• obtaining a search query from a user computing device associated with the particular user;
• processing the search query with the one or more machine-learned planning models to generate one or more refined queries and to determine one or more particular subsets of the plurality of different application-specific index datasets to search;
• searching, via one or more personal data intelligence models based on one or more planning model outputs, the one or more particular subsets of the plurality of different application-specific index datasets based on the one or more refined queries to determine one or more search results;
• processing the search query and the one or more search results with the one or more server-side generative response models to generate one or more model-generated responses to the search query, wherein the one or more model-generated responses comprise details of the one or more search results in a natural language response to a prompt of the search query;
• and
• transmitting the one or more model-generated responses to the user computing device associated with the particular user.