Backend API for MindfulEats — a behavioral weight management platform that combines mindful eating, mood tracking, and AI-driven dietary pattern analysis to promote healthy, sustainable habits.
- Node.js
- Express.js
- MongoDB with Mongoose
- TensorFlow.js for AI-based food classification & pattern detection
- Cloudinary for meal image storage
- Clarifai & Food101 integration for food recognition (image → prediction)
- Postman for API documentation & testing
✅ Actively in development
The backend currently includes:
- 🔐 User authentication (JWT-secured)
- 🍱 Meal logging with hunger levels, images, and food predictions
- 😊 Mood logging for emotion analysis
- 🧠 AI-powered dietary pattern detection (e.g., snacking habits, meal skipping)
Live API: https://mindfuleats.onrender.com Postman Docs: API Documentation
| Week | Milestone |
|---|---|
| 1 | ✅ Set up database, user authentication, basic mood/meal logging |
| 2 | ✅ Integrated AI food prediction (TF.js + Clarifai), added group support |
| 3 | 🚧 Building habit engine, notifications, and content delivery APIs |
# 1. Clone this repo
git clone https://github.com/your-username/mindfuleats-backend.git
# 2. Navigate into the project
cd mindfuleats-backend
# 3. Install dependencies
npm install
# 4. Set up your environment
cp .env.example .env
# Fill in MONGODB_URL, JWT_SECRET, etc.
# 5. Run the server
npm run devMake sure your .env includes:
MONGODB_URL=your_mongo_connection_string
JWT_SECRET=your_secret_key
CLARIFAI_API_KEY=your_api_key
CLOUDINARY_CLOUD_NAME=xxx
CLOUDINARY_API_KEY=xxx
CLOUDINARY_API_SECRET=xxx
├── controllers/ # API logic
├── model/ # Mongoose schemas
├── routes/ # API route definitions
├── middleware/ # Auth, error handling, etc.
├── Service/ # Business logic, dietary pattern AI, etc.
├── seed/ # Sample data for testing
└── server.js # Entry point
This project is open-source and available under the MIT License.
For questions, feedback, or contributions:
- Open an issue on GitHub
- Reach out to the team directly via the API docs link above