DATA PROCESSING METHOD AND APPARATUS, DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20210191846A1

    公开(公告)日:2021-06-24

    申请号:US17190573

    申请日:2021-03-03

    Abstract: The present application discloses a data processing method and apparatus, a device, and a storage medium. The specific implementation solution is: acquiring attribute information of a detection object, where the attribute information includes a type of the detection object and at least one of the following: a level coefficient of the detection object and a validity of the detection object; a processing module, configured to test a tested object by the detection object according to the type of the detection object to obtain a test result, where the test result includes first abnormal information detected in the tested object; the processing module is further configured to update the attribute information of the detection object according to the test result. In the above solution, the attribute information of the detection object needs no manual intervention and can be updated in time, thereby reducing quality risks.

    CODE RETRIEVAL METHOD AND APPARATUS BASED ON LARGE LANGUAGE MODEL

    公开(公告)号:US20240403344A1

    公开(公告)日:2024-12-05

    申请号:US18803085

    申请日:2024-08-13

    Abstract: There is provided a code retrieval method and apparatus based on a large language model, an electronic device and a readable storage medium, which relates to the field of artificial intelligence technologies, such as large language model technologies, big data technologies, cloud service technologies, or the like. The method for code retrieval based on a large language model includes: acquiring a code retrieval query to obtain a retrieval vector of the code retrieval query; acquiring a first index of a target code library, the first index including a plurality of code blocks and a plurality of code block vectors; acquiring a target code block according to the retrieval vector and the first index; acquiring a second index of the target code library, the second index being a code architecture knowledge graph; acquiring a target code file corresponding to the target code block according to a source code file corresponding to the target code block and the second index; and acquiring a retrieval result according to the target code block and the target code file.

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