SweetFriend is a comprehensive diabetes management app designed to help users track their glucose levels, log meals and exercises, and receive personalized insights powered by AI.
- React: To build our frontend user interfaces, enabling graph visualizations and easy logging.
- Flask: Used for developing the API that serves the frontend and interacts with our services.
- MongoDB: Our database used for storing user logs and data efficiently, allowing flexible schema design.
- Dexcom API: Used for accessing real-time glucose data from users' Dexcom devices, facilitating seamless integration of vital health information.
- Tune Studio: Utilized for vision model inference (GPT-4o), specifically for accurately estimating carbohydrate content from food images using machine learning models.
- Cerebras: Provides super-fast AI chatbot inference, enhancing user interaction through quick and responsive conversations.
- Twilio: Used for sending user notifications and alerts, ensuring timely communication about glucose levels and other important health metrics.
- Python 3.12
git clone https://github.com/dmicz/SweetFriend.git
cd SweetFriend
python -m venv .venv
.venv/bin/setup.sh # For Linux
.venv\Scripts\activate.bat # For Windows
pip install -r requirements.txt
export FLASK_APP=api/app.py # For Linux
set FLASK_APP=api/app.py # For Windows
flask run --debug