Biocommunicator is a cutting-edge AI-driven platform focused on enabling communication with nature, specifically plants and animals, through artificial intelligence. Our goal is to create tools that translate interactions between living organisms, bringing humans closer to the natural world.

🚀 Features

• AI Communication Models: Enable communication with plants and animals through our advanced AI models.
• Real-time Data Processing: Collect and process data from nature in real time.
• User-friendly Interface: Easy-to-use web interface to interact with our AI models.
• Scalable Architecture: Built with scalability in mind for handling large datasets and multiple interactions.

📦 Repository Structure

/biocommunicator
│
├── /src/               # Source code files
│   ├── /data/          # Data handling and preprocessing
│   ├── /model/         # AI model code
│   ├── /utils/         # Utility functions and helpers
│   ├── /interface/     # User interface components
│   └── main.py         # Main script to run the project
│
├── /tests/             # Unit and integration tests
├── /docs/              # Documentation for the project
├── README.md           # Project documentation
├── LICENSE             # Licensing information
├── .gitignore          # Ignoring unnecessary files (e.g., logs, env)
├── requirements.txt    # Dependencies for the project
└── setup.py            # Setup script for package management

📖 Getting Started

Follow these steps to set up and run Biocommunicator on your local machine.

Prerequisites

• Python 3.9+
• pip for managing Python packages

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/biocommunicator.git
   cd biocommunicator

2. Install dependencies:

   pip install -r requirements.txt

3. Run the main script:

   python src/main.py

Running Tests

Biocommunicator uses Python's built-in unittest framework for testing. All test files are stored in the tests/ directory.

To run the tests:

python -m unittest discover -s tests

You can add new test files to the tests/ directory following this example:

# tests/test_sample.py

import unittest

class TestSample(unittest.TestCase):
    def test_addition(self):
        self.assertEqual(1 + 1, 2)
    
    def test_subtraction(self):
        self.assertEqual(5 - 3, 2)

if __name__ == '__main__':
    unittest.main()

Each test file should follow the naming convention test_*.py, and be structured similarly.

📚 Documentation

Full documentation for Biocommunicator can be found in the docs folder.

🌱 Future Roadmap

• Model optimization for higher accuracy in nature communication.
• Implement real-time interaction dashboard.
• Expand support for more species of plants and animals.
• Integration with hardware sensors for live data collection.

🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-name).
3. Commit your changes (git commit -m 'Add feature').
4. Push to the branch (git push origin feature-name).
5. Create a Pull Request.

Please see the Contributing Guidelines for more details.

🛠️ Built With

• Python - Core programming language
• TensorFlow / PyTorch - AI and Machine Learning
• Next.js - For building a web interface (if applicable)
• PostgreSQL - Database (if applicable)
• Docker - For containerization and deployment

📄 License

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

✨ Acknowledgments

• Inspired by the quest to connect humanity and nature.
• Special thanks to our contributors and community members.