Introduction

It has long been a difficult task to generate precise SQL queries from customers’ natural language inquiries (text-to-SQL). Understanding user queries, appreciating the structure and semantics of a particular database schema, and accurately producing executable SQL statements are some of the elements that contribute to the complexity.  

Large language models (LLMs) have opened up new avenues for text-to-SQL research. Superior natural language understanding skills are demonstrated by LLMs, and their scalability offers special chances to improve SQL creation.