You can access the website at - https://sql-query-generator-lcmmrl3rurizsup225bez2.streamlit.app/

# 📊 SQL Query Generator

A simple yet powerful web application that generates SQL queries from plain English prompts using **Google's Gemini Pro Model**. This tool also provides explanations and sample outputs for the generated SQL queries.

## 🚀 Features

- ✅ Convert natural language to SQL queries
- ✅ Get **sample outputs** for your SQL queries
- ✅ Simple and easy-to-understand **query explanations**
- ✅ Interactive UI built with **Streamlit**

## 🛠️ Technologies Used

- **Python** - Core programming language
- **Streamlit** - For building the interactive web app
- **Google Generative AI (Gemini Pro)** - For generating SQL queries and explanations
- **HTML & Markdown** - Used within Streamlit for UI styling
- **SQL** - Generated as output queries

## 📦 Installation

1. **Clone the Repository:**
   ```bash
   git clone https://github.com/your-username/sql-query-generator.git
   cd sql-query-generator

2. Create a Virtual Environment (Optional but Recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies:

   pip install -r requirements.txt

4. Set Up Google API Key:

   • Get your API key from Google Cloud Console.
   • Replace the placeholder in the code with your API key:

     GOOGLE_API_KEY = "YOUR_API_KEY_HERE"

5. Run the App:

   streamlit run app.py

💡 Usage

1. Enter your request in plain English (e.g., "Get all employees who joined after 2020").
2. Click on "Generate SQL Query".
3. The app will display:
   • ✅ The SQL Query
   • 📊 A sample output table
   • 📝 A simple explanation of the query

📷 Screenshots

(Add screenshots of your app here)

📝 Example

Input:

Show me the top 5 customers with the highest purchases in 2023.

Generated SQL:

SELECT customer_name, SUM(purchase_amount) AS total_purchases
FROM sales
WHERE YEAR(purchase_date) = 2023
GROUP BY customer_name
ORDER BY total_purchases DESC
LIMIT 5;

🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature-name)
3. Commit your changes (git commit -m 'Add new feature')
4. Push to the branch (git push origin feature-name)
5. Open a Pull Request

📜 License

This project is licensed under the MIT License.

🙌 Acknowledgments

• Streamlit
• Google Generative AI
• SQL Documentation

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