A Showcase of LLMs in Action: SQL Generation from Natural Language (Demo Paper)

Today, large language models are a very efficient tool for human-computer interaction using natural language. Chatbots like ChatGPT and their corresponding APIs can be used to solve a large variety of tasks that are provided in human-comprehensible sentences, for example generating SQL queries. Executing spoken SQL queries in a database system poses a challenge, because the various syntactical details of SQL are usually not provided verbally. Here, the LLM can help to augment the recognized raw query with the syntax elements needed for successful execution. Furthermore, the correct spelling of table and column names can be derived from the database schema provided in the LLM prompt. This work showcases four use cases in which LLMs assist in querying database systems: (1) A plugin for phpMyAdmin for voice-query input in natural language, (2) a chart generator, (3) an Alexa skill, and (4) a speech-controlled action game SQL Invaders.