Natural Language to SQL Chain: A Dynamic Solution for SQL Query and Result Interpretation

This paper presents an innovative approach to bridging the gap between natural language and structured database querying by leveraging Google Generative AI (Gemini Pro) and advanced prompt engineering techniques. The proposed system enables users, regardless of technical proficiency, to input natural language questions that are automatically translated into SQL queries. These queries are executed on a relational database, and the results are subsequently transformed into easily comprehensible, human-readable responses. This approach addresses a critical need for intuitive data access and analysis, empowering stakeholders to retrieve insights without deep technical knowledge. Applications of this system span across business intelligence, customer support, and academic research, among others. The experimental results demonstrate the efficacy and accuracy of the proposed solution, emphasizing its potential to enhance user interaction with data systems.