Eunoia: AI-Powered Mental Health Web Application

Eunoia is an AI-powered mental health web application that offers personalized emotional support, mental well-being tools, and religious therapy. Designed with inclusivity and accessibility in mind, Eunoia provides users with a holistic mental health journey through advanced AI-driven features, gamification, and scalable spiritual guidance.

🌟 Features

Mental Health and Emotional Well-Being

• Mental Health Tracking: Includes daily journaling, AI-driven sentiment analysis, and mood tracking.
• Personalized Emotional Support: Tailored recommendations and chatbot interactions powered by advanced sentiment analysis.
• AI-Powered Chatbot Assistance: Real-time support to help users manage emotions and stress.

Religious Therapy

• Personalized Religious Support: Quranic ayaat and religious text recommendations based on emotional states.
• Scalable Spiritual Guidance: Planned expansion to include spiritual texts like the Bible, Torah, and Gita.

Community and Crisis Support

• Community Engagement: Peer support forums for anonymous sharing and emotional support.
• Crisis Management: Emergency contact features, crisis hotline information, and automated alerts.

Gamification and Habit Building

• Interactive Tools: Stress-relief games, habit-building trackers, and progress visualization.
• Gamified Motivation: Achieve mental health goals through rewards and milestones.

Accessibility and Localization

• Multi-Language Support: Fully localized for diverse communities.
• Offline Functionality: Key features like journaling available offline.

Therapist Connection

• Access to Professionals: Connect with certified therapists for online video sessions.

Advanced AI Features

• Advanced Sentiment Analysis: Utilizing the Gemini API and Hugging Face Transformers for NLP.
• Self-Assessment Tools: Insightful self-assessment quizzes (non-diagnostic).

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🛠️ Tech Stack

Frontend

• Framework: React.js

Backend

• Framework: Flask

Database

• Database Management System: PostgreSQL

APIs and Libraries

• Sentiment Analysis: Gemini API
• Natural Language Processing: Hugging Face Transformers

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📖 Installation

Follow these steps to set up and run the application locally:

1. Clone the Repository

git clone https://github.com/eunoia-mazz/eunoia-app.git
cd eunoia-app

2. Set up the Backend (Flask)

Navigate to the backend directory and install dependencies:

cd backend
pip install -r requirements.txt

Start the Flask backend server:

python app.py

3. Set up the Frontend (React)

Navigate to the frontend directory and install dependencies:

cd frontend
npm install

Start the React development server:

npm run dev

4. Docker Deployment

For users preferring Docker for deployment, you can pull the pre-built Docker images and run them directly:

Pull Docker Images

You will be prompted to enter a passphrase upon pulling the Docker images. Please use the following passphrase:

Passphrase: eunoiamazz

Pull Docker Images

Frontend

docker pull eunoiamazz/eunoia-frontend:latest

Backend

docker pull eunoiamazz/eunoia-backend:latest

Run Docker Containers

Frontend

docker run -p 5173:5173 eunoiamazz/eunoia-frontend:latest

Backend

docker run -p 5000:5000 eunoiamazz/eunoia-backend:latest

This will start the frontend accessible at http://localhost:5173 and the backend at http://localhost:5000.

5. Run the Application

Once the backend and frontend are set up and running, you can access the app by navigating to http://localhost:5173 for the frontend and http://localhost:5000 for the backend.

6. Access the Application

Once both servers are running, you can access the application at:

• Frontend: http://localhost:5173
• Backend: http://localhost:5000

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🧪 Testing

Overview

The Eunoia App includes a comprehensive test suite to ensure the reliability and functionality of the application. The tests cover various components including authentication, chat functionality, activity tracking, spiritual content, and more.

Test Structure

Tests are organized in the tests/unit/ directory with each module focusing on a specific area of functionality:

• test_auth.py: Tests user authentication (signup, login)
• test_chat.py: Tests chat creation and message generation
• test_activity.py: Tests activity and subactivity models
• test_coupon.py: Tests coupon allocation functionality
• test_spiritual.py: Tests spiritual content features
• test_profile.py: Tests user profile management
• test_journal.py: Tests journal entry functionality
• test_forum.py: Tests forum post and comment features
• test_mood.py: Tests mood tracking functionality

Running Tests

To run the entire test suite:

cd tests
python run_tests.py

To run a specific test file:

cd tests
python -m unittest unit.test_auth

Continuous Integration

Tests are automatically run on GitHub Actions when code is pushed to the main branch or when a pull request is created. The workflow configuration is defined in .github/workflows/python-tests.yml.

Test Coverage

The tests use SQLite in-memory databases to ensure tests are isolated and don't affect production data. Key areas covered include:

1. Authentication

   • User registration
   • User login with valid and invalid credentials.

2. Chat Functionality

   • Creating new chats
   • Generating AI responses (with mocked AI model)
   • Retrieving chat history

3. Activities

   • Activity model validation
   • SubActivity model validation
   • Relationship between activities and subactivities

4. Coupons

   • Coupon allocation to users
   • Validation of coupon limits

5. Spiritual Content

   • Creating spiritual guidance chats
   • Testing chat creation

6. User Profiles

   • Profile retrieval through login

Adding New Tests

When adding new features, corresponding tests should be created following the existing patterns:

1. Create a new test class that inherits from unittest.TestCase
2. Implement setUp and tearDown methods
3. Add test methods that start with test_
4. Update run_tests.py to include your new test case

Mocking External Services

For tests that involve external services (like AI models), we use Python's unittest.mock to create mock responses:

@patch('app.model.generate_content')
def test_some_ai_feature(self, mock_generate_content):
    # Set up the mock
    mock_response = MagicMock()
    mock_response.text = "This is a mock response"
    mock_generate_content.return_value = mock_response
    
    # Test code that uses the AI model

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License

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

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Future Plans

• Religious Texts Expansion: Include spiritual guidance based on the Bible, Torah, Gita, and other religious texts.
• Advanced AI Features: Enhance emotional support with more advanced AI-driven insights.
• Mobile App: Launch a native mobile application for both iOS and Android.
• Global Outreach: Further language localization and accessibility improvements.

🎯 Future Plans

• Religious Text Expansion: Incorporate additional spiritual texts, including the Bible, Torah, and Gita.
• Advanced AI Features: Develop more sophisticated AI-driven insights for emotional support.
• Mobile App: Launch native iOS and Android applications.
• Global Outreach: Expand localization to support additional languages and accessibility features.

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📜 License

This project is licensed under the MIT License.

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📧 Contact

For support or inquiries, please email: [email protected].

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Elevate your mental health journey with Eunoia, where technology, emotional support, and spirituality converge. 💙