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Text to SQL application via Gemini

A Streamlit application that uses Google's Gemini AI to convert natural language questions into SQL queries, executes them on a local SQLite database, and displays the result.

🛠️ Tech Stack

  • Python 3.10+
  • Streamlit (Frontend)
  • Google GenAI SDK (google-genai)
  • SQLite (Database)

📋 Prerequisites

  1. Google Gemini API Key:

  2. Python Installed: Make sure Python is installed on your system.

⚙️ Installation

  1. Clone the repository:

    git clone https://github.com/yash-cs-ai/Text-to-Sql-using-gemini.git
cd your-repo-name

  2. Create a virtual environment (Optional but Recommended):

    python -m venv venv
# Windows
venv\Scripts\activate
# Mac/Linux
source venv/bin/activate

  3. Install dependencies:

    pip install streamlit google-genai python-dotenv pandas

  4. Set up Environment Variables:

    Create a file named .env in the root folder and add your API key:

    GEMINI_API_KEY="your_google_api_key_here"

🗄️ Database Setup

Before running the app, you need to create the dummy database.

  1. Create a file named sql.py (if not already present) with the database creation logic.

  2. Run the script to generate student.db:

    python sql.py

    This will create the student.db file with sample data (Name, Class, Section).

▶️ Usage

Run the Streamlit app:

streamlit run app.p