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# SQL Query Generator with Google Gemini
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This project is a Streamlit application that converts English questions into SQL queries using Google Gemini's generative AI capabilities. It allows users to retrieve data from an SQLite database named **STUDENT**, which contains information about students, their classes, sections, and marks.
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This project is a Streamlit application that converts English questions into SQL queries using Google Gemini's generative AI capabilities. It allows users to retrieve data from an SQLite database named **student.db**, which contains information about students, their classes, sections, and marks.
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## Table of Contents
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## Features
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- Convert natural language questions into SQL queries.
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- Execute generated SQL queries against an SQLite database.
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- Execute generated SQL queries against the SQLite database.
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- User-friendly interface built with Streamlit.
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- Response cleaning to ensure valid SQL execution.
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## Technologies Used
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-[Streamlit](https://streamlit.io/) - For building the web application.
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-[SQLite](https://www.sqlite.org/index.html) - Lightweight database to store student records.
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-[Google Generative AI](https://developers.google.com/generative-ai) - To generate SQL queries from text input.
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-[Python](https://www.python.org/) - Programming language used to build the application.
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-[Regex](https://docs.python.org/3/library/re.html) - For cleaning generated SQL queries.
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## Installation
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## Database Schema
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The database **STUDENT** has the following schema:
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The database **student.db** has the following schema:
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