README.md

metadata

license: mit
title: A simple Data Analyzer
sdk: gradio
emoji: 📊
colorFrom: red
pinned: true
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/69848113135d8332da94b363/JFpif40IVp5pJhMZ0-n8x.png

Personal Data Assistant

A simple interactive data analysis and visualization assistant built with Python and Gradio. Ask questions about your datasets, generate insightful visualizations, and get instant answers—all in a beautiful, user-friendly web interface.

![Gradio App Screenshot] (images/image.png)

Features

• Conversational Data Analysis: Chat with the agent to analyze your CSV datasets.
• Automatic Visualizations: Instantly generate bar charts and other graphs from your data.
• Modern UI: Custom black and red theme for a sleek, professional look.
• Conversation Logging: Keeps a log of your questions and the agent's responses.
• Easy Dataset Upload: Upload your own CSV files for instant analysis.

Demo

https://your-demo-link.com

Getting Started

Prerequisites

• Python 3.10+
• pip (Python package manager)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/personal-data-assistant.git
   cd personal-data-assistant
   

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Set up environment variables:
   • Create a .env file in the project root with your API keys for the model:

     MISTRAL_API_KEY=your_mistral_api_key
     

Running the App

python app.py

The Gradio interface will launch in your browser.

Usage

• Ask questions about your dataset in natural language.
• Upload a CSV file to analyze your own data.
• View generated graphs and download them if needed.

Example Datasets

• housing_dataset.csv: Sample housing prices by city.

Project Structure

├── app.py                  # Gradio web app
├── main.py                 # Core agent logic and tools
├── housing_dataset.csv     # Example dataset
├── vgsales.csv             # Example dataset
├── conversation_log.txt    # Conversation history
├── .gitignore
└── .gradio/flagged/        # Gradio flagged data

Technologies Used

• Python
• Gradio
• Matplotlib, Seaborn, Pandas
• smolagents, LiteLLM

Customization

• Modify custom_css in app.py to change the UI theme.
• Add new tools or models in main.py.

License

MIT License. See LICENSE for details.

Acknowledgements

• Gradio
• Mistral AI
• smol-ai/smolagents

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Made with ❤️ for data enthusiasts.