Natural Language Interface to SQL Databases Leveraging Groq

Overview

This project enables users to interact with SQL databases through natural language queries. Leveraging the capabilities of LangChain and the Groq API, it provides an intuitive interface built with Streamlit, supporting both SQLite and MySQL databases.

Features

• Natural Language Querying: Allows users to ask questions in plain English, which are then translated into SQL queries.
• Database Support:
  • SQLite: Utilizes a local SQLite database (student.db) for quick setup and testing.
  • MySQL: Connects to MySQL databases for more extensive applications.
• Interactive Interface: Provides a user-friendly chat interface using Streamlit.

Installation

Follow these steps to set up the project locally:

1. Clone the Repository:

   git clone https://github.com/Rohit-Madhesiya/Chat-with-SQL-DB-using-Groq.git
   

2. Navigate to the Project Directory:

   cd Chat-with-SQL-DB-using-Groq
   

3. Install Dependencies: Ensure you have Python installed. Then, install the required packages:

    pip install -r requirements.txt
   

4. Set Up the Database:
   • SQLite: A sample database (student.db) is included. No additional setup is required.
   • MySQL: Ensure you have a MySQL server running and accessible.

Usage

Provide instructions on how to use the application.

1. Launch the Application:

    streamlit run app.py
   

2. Select Database Type:

   • Choose between SQLite or MySQL in the sidebar.

3. Configure Database Connection:

   • SQLite: Ensure student.db is in the project directory.
   • MySQL: Provide the necessary credentials (host, port, username, password, database name).

4. Interact with the Chat Interface:

   • Enter natural language queries in the input box.
   • The application will process the input, convert it to an SQL query, execute it, and display the results.

Examples

• Query: "Show all students majoring in Computer Science."
  • SQL Equivalent:

        SELECT * FROM students WHERE major = 'Computer Science';
  

• Query: "What is the average GPA of students in the database?"
  • SQL Equivalent:

        SELECT AVG(gpa) FROM students;

Project Structure

Chat-with-SQL-DB-using-Groq/
│
├── app.py                  # Main application file
├── requirements.txt        # List of Python dependencies
├── student.db              # Sample SQLite database
├── README.md               # Project documentation
└── .github/
    └── workflows/
        └── python-app.yml  # GitHub Actions workflow

Dependencies

• Python Packages:

  • streamlit
  • langchain
  • mysql-connector-python
  • sqlite3 (included in Python's standard library)

• External Services:

  • Groq API access

Contributing

Contributions are welcome! To contribute:

1. Fork the repository.

2. Create a new branch:

   git checkout -b feature-name
   

3. Make your changes and commit them:

    git commit -m 'Add new feature'
   

4. Push to the branch:

   git push origin feature-name
   

5. Submit a pull request.

Acknowledgments

• LangChain: For facilitating natural language processing.
• Groq: For providing the AI acceleration API.
• Streamlit: For the interactive web application framework.