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<p>Large Language Models have advanced to a&#xa0;resourceful tool with many applications. One particularly interesting use case is the LLM-aided generation of ad-hoc database queries and the possibility of subsequent processing of the results in a&#xa0;way suiting the users intents. In this article, practical ways and experiences are described on how to effectively use LLMs to map a&#xa0;natural-language user query to an SQL query conforming to a&#xa0;specific database schema and post-processing the results of this query in order to, for example, create an appealing visualization. Best results are achieved under favorable circumstances, as, for example, a&#xa0;clean and meaningful named database schema.</p>

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Experience Report: Hey LLM, Generate SQL!

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月1日

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  • Florian Heinz,
  • Johannes Schildgen

摘要

Large Language Models have advanced to a resourceful tool with many applications. One particularly interesting use case is the LLM-aided generation of ad-hoc database queries and the possibility of subsequent processing of the results in a way suiting the users intents. In this article, practical ways and experiences are described on how to effectively use LLMs to map a natural-language user query to an SQL query conforming to a specific database schema and post-processing the results of this query in order to, for example, create an appealing visualization. Best results are achieved under favorable circumstances, as, for example, a clean and meaningful named database schema.