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:

   • Get your free key here: Google AI Studio

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