🌐 bandOptimizer

A cutting-edge solution for optimizing bandwidth usage in schools and hospitals with AI/ML predictions.

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🚀 About the Project

BandOptimizer is a Streamlit-based web application designed to help schools and hospitals manage and optimize their bandwidth usage efficiently. Using AI/ML predictions, it provides insights into bandwidth categories and allows administrators to make data-driven decisions to enhance performance and resource allocation.

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✨ Key Features

• AI/ML-Powered Insights: Automatically categorize and predict school/ hospital bandwidth requirements.
• Easy-to-Use Interface: Streamlit ensures a seamless and interactive user experience.
• CSV File Support: Upload data in CSV format to analyze and get predictions instantly.
• Sample Files Included: Use the provided sample CSV files in the repository to test the app and see predictions in action.

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🔧 Installation

1. Clone the repository:

   git clone https://github.com/your-username/bandOptimizer.git
   cd bandOptimizer
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Add your API key: Create a .env file in the project directory and add your ML API key:

   ML_API_KEY=your-api-key-here
   

4. Run the app:

   streamlit run app.py
   

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📁 Usage

• Upload Your CSV File:

  • Use the "Upload CSV" feature to upload your school/ hospital data file for analysis.

• View Predictions:

  • See AI/ML-generated bandwidth usage categories tailored to your uploaded data.

• Test with Sample Files:

  • The repository contains sample CSV files to help you test the app and explore its features without additional setup.

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🔐 Protect Your Secrets

To ensure your API keys remain secure:

• Use the .env file for local development (excluded from version control via .gitignore).
• Use secrets.toml for deployment on Streamlit Cloud.

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🛠️ Built With

• Streamlit: For creating an interactive web app.
• Python: Core programming language for development.
• AI/ML API: For generating bandwidth predictions.

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🤝 Contributing

Contributions, issues, and feature requests are welcome!

Fork the repository:

• Create a new branch:

  git checkout -b feature-name.
  

• Commit your changes:

  git commit -m 'Add new feature'.
  

• Push to the branch:

  git push origin feature-name.
  

• Open a pull request.

📄 License

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

📬 Contact

Feel free to reach out for any questions or feedback!