Text-To-SQL-LLM-App

This project is an application that uses Google Gemini Pro to convert natural language questions into SQL queries and retrieves data from a SQLite database. The application is implemented using Python and Streamlit.

Table of Contents

• Setup
• Usage
• Troubleshooting
• Contributions
• License

Setup

Follow these steps to set up the Text-To-SQL-LLM-App:

1. Clone the Repository:

    git clone <repository_url>
    cd text-to-sql-llm-app
   

2. Create a .env file:

   In the root directory of the project, create a .env file and add the following variables:

    GOOGLE_API_KEY=your_google_api_key
   

3. Install Dependencies:

   Install the required Python packages from the requirements.txt file:

    pip install -r requirements.txt
   

4. Set up the SQLite Database:

   Use the provided SQL schema to create the required tables in your SQLite database.

5. Modify the app.py file:

   Adjust any configuration settings in the app.py file to match your setup.

Usage

1. Run the application:

   Start the application using Streamlit:

    streamlit run app.py
   

2. Interact with the application:

   Use the provided user interface to input natural language questions and retrieve SQL data.

Troubleshooting

• Ensure that the Google API key and database settings in the .env file are correct and up to date.
• Double-check your database connection string and the database schema.
• If you encounter any errors, review the application logs for more details on the issue.

Contributions

Contributions are welcome! Please submit a pull request with your changes.

License

This project is licensed under the MIT License.

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