Conscient is an AI-powered mental health support platform that combines intelligent conversation, mood tracking, and community connection. Built with React and powered by advanced AI models, It provides a safe space for mental health support.
- AI Therapy Companion: Engage in supportive conversations with our self-learning AI model
- Smart Diary: Keep track of your thoughts and emotions with AI-powered insights
- Peer Connection: Connect with others based on AI-determined compatibility
- Secure Environment: Username/password authentication with encrypted data storage
- React.js
- Tailwind CSS
- Shadcn/UI components
- MongoDB Atlas for data storage
- Groq API integration
- Llama 3.3 Versatile-Versatile model
- Random Forest classifier (trained on Kaggle mental health dataset)
- Regression model for pattern analysis
MongoDB Atlas collections:
- Users
- Chat histories
- Diary entries
- User interactions
- Model learning patterns
- Clone the repository:
git clone https://github.com/Khushal-Me/Conscient.git
cd Conscient- Install dependencies:
npm install- Create a
.envfile in the root directory:
MONGODB_URI=your_mongodb_uri
GROQ_API_KEY=your_groq_api_key- Start the development server:
npm run dev- Adapts to user interaction patterns
- Stores learned patterns in MongoDB
- Continuous improvement through user conversations
- Kaggle dataset integration for initial model training
- Real-time pattern recognition
- Secure data handling and anonymization
- Username/password authentication
- Encrypted data storage
- Secure API communications
- Protected user matching system
- Groq API for AI model interactions
- Rate limiting for API calls
- Error handling and fallback strategies
Planned deployment on Vercel for:
- Scalable infrastructure
- Automatic deployments
- Performance optimization
- Fork the repository
- Create your feature branch (
git checkout -b feature/YourFeature) - Commit your changes (
git commit -m 'Add YourFeature') - Push to the branch (
git push origin feature/YourFeature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
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