HomeBridge is a voice-interactive web application designed to help international students at the University of British Columbia (UBC) cope with homesickness and adapt to their new environment.

HomeBridge uses natural language processing and machine learning to analyze students' spoken or written input about their experiences, then provides personalized resilience strategies and resources tailored to their needs.

• Voice Interaction: Speak naturally about your feelings and experiences to receive support
• Advanced Sentiment Analysis: AI-powered analysis of your emotional state and homesickness level
• Personalized Strategies: Receive tailored resilience strategies based on your specific situation
• Progress Tracking: Monitor your emotional well-being over time with mood tracking
• Resource Directory: Access UBC-specific resources for international students
• Gratitude Practice: Record things you're grateful for to improve well-being
• Neuroplasticity Support: Features designed based on research showing gratitude journaling increases dorsolateral prefrontal activity by 29%, creating cognitive buffers

• Backend: Flask (Python)
• Frontend: HTML, CSS, JavaScript, Bootstrap
• Database: SQLite (with SQLAlchemy ORM)
• NLP/ML: NLTK, scikit-learn
• Data Visualization: Plotly, Matplotlib

Before running HomeBridge, ensure you have:

1. Python 3.8 or higher installed
2. Git installed (for cloning the repository)

1. Clone the repository:

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

2. Create and activate a virtual environment (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:

   # Step 1: Copy the example environment file
   cp .env.example .env
   
   # Step 2: Edit .env with your configuration
   # Open .env in your preferred text editor and update the following:
   
   # 1. Generate a secure SESSION_SECRET:
   #    Run this command in your terminal:
   #    python -c "import secrets; print(secrets.token_hex(32))"
   #    Copy the output and replace 'your_session_secret_here' in .env
   
   # 2. Database Configuration:
   #    - For local development, you can use the default SQLite database
   #    - If using PostgreSQL, update DATABASE_URL with your credentials
   
   # 3. Optional Settings:
   #    - FLASK_ENV: Set to 'development' for local development
   #    - FLASK_DEBUG: Set to 1 for detailed error messages
   #    - SENTRY_DSN: Only needed if you want error tracking

   Example of a properly configured .env file:

   FLASK_APP=app.py
   FLASK_ENV=development
   FLASK_DEBUG=1
   SESSION_SECRET=8d969eef6ecad3c29a3a629280e686cf0c3f5d5a86aff3ca12020c923adc6c92
   DATABASE_URL=postgresql://user:password@localhost:5432/homebridge
   

   ⚠️ Important Notes:

   • Never commit your .env file to version control
   • Keep your secrets secure
   • The example values above are placeholders - replace them with your actual values

5. Install NLTK resources:

   python -c "import nltk; nltk.download('punkt')"

There are multiple ways to run HomeBridge:

FLASK_APP=app.py flask run --port=5003

The application will be available at http://127.0.0.1:5003

Note: If port 5003 is in use, you can try other ports (e.g., 5004, 5005).

python main.py

gunicorn --bind 0.0.0.0:5003 --workers 4 app:app

1. Port Already in Use: If you see "Address already in use", try:

   • Using a different port (e.g., 5003, 5004, 5005)
   • On macOS, check System Settings > General > AirDrop & Handoff for AirPlay settings

2. NLTK Resources: If you see NLTK-related errors:

   python -c "import nltk; nltk.download('punkt')"

3. Missing Dependencies: If you encounter ModuleNotFoundError:

   pip install -r requirements.txt

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

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

HomeBridge is built on scientific research:

• Neuroplasticity Potential: Gratitude journaling increases dorsolateral prefrontal activity by 29%
• AI Efficacy: NLP systems trained on grief-related narratives can detect high-risk linguistic markers
• Addressing Loneliness: Designed to counter the 42% increase in reported loneliness among bereaved individuals