[Ariya Mathrawala] (https://github.com/ariyamath29) [Nikita Bhaskar] (https://github.com/nikitabhaskar) [Jonathan Gao] (https://github.com/jg169) [Ethan Zheng] (https://github.com/ez2146)
A web application that generates personalized recipes based on available ingredients and health goals using AI.
/web-app/ # Main application directory
├── app.py # Flask application
├── mlclient.py # AI/ML integration
├── test_app.py # Tests
├── templates/ # HTML templates
│ └── index.html # Main page
├── static/ # Static files (CSS, JS, etc.)
└── .env # Environment variables (not in git)
Install the following software on your machine:
- Clone the repository:
git clone https://github.com/software-students-spring2025/5-final-bten.git
cd 5-final-bten
- Build and Run
docker-compose-up --build
- Run Tests
docker exec -it . pytest
Access the web interface at http://127.0.0.1:3000
- Virtual Environment Setup
Using pipenv
:**
pip install pipenv
pipenv shell
Using venv
:**
python3 -m venv .venv
source .venv/bin/activate #On Mac
.venv\Scripts\activate.bat #On Windows
- Install Dependencies
pip install -r requirements.txt
- Create and set up environment variables:
cp ./sample_env.txt .env
# Edit .env with your MongoDB URI
-
Connect to database using mongosh
-
Run Application
cd web-app
python3 app.py
- Run Tests
cd web-app
pytest test_app.py
The application will be available at http://localhost:3000
- Input available ingredients
- Specify health goals and dietary preferences
- Get AI-generated recipes
- View recipe history
- MongoDB integration for recipe storage
- Main branch: Production-ready code
- Development happens in feature branches
- PRs required for merging into main
- CI/CD pipeline runs tests automatically