Interact with MySQL Database Using Open-Source LLMs

Description :

The interact_with_MySQL project allows users to interact with a MySQL database using natural language instead of writing complex SQL queries.
The goal is to simplify data access and make interactions more intuitive for users who are not experienced with SQL.

This project uses Streamlit for the user interface, MySQL-connector for connecting to MySQL, and Groq for API integration and natural language processing (LLMs).

Features :

• Connect to a MySQL database.
• Execute SQL queries via natural language.
• Interactive user interface with Streamlit.
• Integration with the Groq API for natural language model management.

Data :

• Airline Delays :
  • Airline Delays for December 2019 and 2020
  • kaggle link : [https://www.kaggle.com/datasets/eugeniyosetrov/airline-delays?select=airline_delay.csv]

Technologies :

• Python 3.10
• Streamlit
• MySQL-connector-Python
• Groq API
• Conda (for virtual environment management)
• Git
• dotenv-python
• Pandas
• PyYaml
• fpdf

Prerequisites :

Before starting, ensure you have installed:

• Python 3.10 or higher
• Conda
• Git

Installation :

Step 1: Clone the Repository :

Clone the repository to your machine:

git clone https://github.com/HMourad2023/Querying-MySQL-Database-LLM.git

Navigate to the project directory:

cd Querying-MySQL-Database-LLM

Step 2: Create a Virtual Environment :

Create a virtual environment with Conda:

conda create --name llm python=3.10 -y

Activate the virtual environment:

conda activate llm

Step 3: Install Dependencies :

Upgrade pip and install the required libraries:

python -m pip install --upgrade pip

pip install streamlit mysql-connector-python dotenv-python groq fpfd pyyaml pandas

Step 4: Create the Project Structure :

Create the template.py file:

echo. >template.py

Run the template.py file:

python template.py