A sql generation method and system based on a power field large language model

By using a SQL code library and database processing language model based on the power industry, the problem of targeted SQL code generation is solved, enabling efficient SQL statement generation in complex scenarios and providing convenient support.

CN122153024APending Publication Date: 2026-06-05BEIJING GUODIANTONG NETWORK TECH CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING GUODIANTONG NETWORK TECH CO LTD
Filing Date
2024-12-03
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing technologies lack specificity for the SQL language, making it difficult to handle complex scenarios, and the codebase cannot cover all use cases, resulting in difficulties in generating SQL code.

Method used

Based on SQL code libraries and databases in the power industry, a large language model is processed, and by vectorizing table structures and descriptive information, an external database is formed to generate SQL statements specific to the power industry.

Benefits of technology

Generate corresponding SQL query code in complex production scenarios, providing convenience for developers, lowering the threshold for using SQL, and improving code generation efficiency.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application provides a sql generation method and system based on a power field large language model, comprising: processing a power field large language model based on a power field SQL code library and a power field database; and substituting a database operation requirement into the processed power field large language model to obtain a sql statement corresponding to the database operation requirement. The application processes the power field large language model based on the power field SQL code library and the power field database, and the processed power field large language model can also generate a corresponding sql query code when facing a complex production scene, thereby providing convenient support for developers.
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