LLM-Based Data Analyst Assistant

An AI-powered data analysis tool that lets you query Excel/CSV files and MySQL databases using natural language in any language. Get insights, visualizations, and SQL queries through a simple chat interface.

🚀 Features

• Multilingual Support: Ask questions in any language (Hindi, Spanish, French, etc.) and get responses in the same language
• Dual Database Support: Work with MySQL databases or upload Excel/CSV files
• Smart Visualizations: Automatic chart generation with insights
• Natural Language to SQL: Convert questions to SQL queries automatically
• Existing Table Access: Connect to MySQL and use existing tables instantly
• File Upload: Upload Excel/CSV files for analysis
• Interactive Web Interface: Clean Streamlit-based UI

📋 Prerequisites

1. Python 3.8+
2. Ollama with Llama3 model:

   # Install Ollama
   curl -fsSL https://ollama.ai/install.sh | sh
   
   # Pull Llama3 model
   ollama pull llama3
   
   # Start Ollama server
   ollama serve

3. MySQL (optional): For database connectivity

🛠️ Installation

1. Clone the repository:

   git clone <repository-url>
   cd llm-data-analyst

2. Install dependencies:

   pip install -r requirements.txt

3. Start the application:

   streamlit run web_interface.py

4. Open your browser: Navigate to http://localhost:8501

🎯 Usage

Option 1: MySQL Database Mode

1. Enter MySQL credentials in the sidebar
2. Click "Connect to MySQL"
3. View existing tables in the dropdown
4. Ask questions about your data

Option 2: File-Only Mode

1. Click "Work with Files Only" or just upload files
2. Upload Excel/CSV files
3. Enter table names for your files
4. Click "Load" for each file
5. Ask questions about your data

💬 Example Questions

English:

• "What are the top 5 products by sales?"
• "Show me revenue by region"
• "Which customers bought the most?"

Hindi:

• "सबसे ज्यादा बिकने वाले उत्पाद कौन से हैं?"
• "क्षेत्रवार आय दिखाएं"

Spanish:

• "¿Cuáles son los productos más vendidos?"
• "Muestra los ingresos por región"

PIE-CHART:what is the distribution of sales by region line-GRAPH:- "सबसे ज्यादा बिकने वाले उत्पाद कौन से हैं?"

🏗️ Architecture

📁 Project Structure

llm-data-analyst/
├── web_interface.py          # Main Streamlit app
├── data_analyst_mysql.py     # Core analysis engine
├── enhanced_visualizer.py    # Chart generation
├── requirements.txt          # Dependencies
└── README.md                # This file

🔧 Configuration

• Ollama URL: Default http://localhost:11434
• MySQL Settings: Host, Port, Username, Password, Database
• File Upload: Supports .xlsx, .xls, .csv formats

🌍 Supported Languages

• English, Hindi, Spanish, French, German, Italian, Portuguese, Russian, Chinese, Japanese, Korean, Arabic, and many more
• Automatic language detection and translation
• Responses in the same language as input

Demo

Watch the demo video

Presentation Link

Project Presentation

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

##COMMANDS TO RUN ollama --version ##to check ollama version

ollama pull llama3 ## to install ollama

ollama pull llama2

python setup_mysql.py ##to setup mysql

pip install -r requirements.txt ##Install all dependencies

streamlit run web_interface.py ## run the project on streamlit