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WellBite.ai

WellBite-Logo

WellBite.ai is a cutting-edge web-based platform designed to provide personalized dietary recommendations based on medical advice and restrictions. Leveraging advanced AI technology and a secure, scalable infrastructure, WellBite.ai helps patients maintain their health by analyzing their food intake and aligning it with their doctor's prescribed dietary restrictions. It offers seamless interaction between patients, doctors, and AI models through an intuitive, user-friendly interface.

Table of Contents

Features

For Patients:

  • AI-powered food analysis: Patients can upload pictures of their meals, and the AI model will analyze the ingredients, portion sizes, and nutritional information.
  • Dietary recommendations: Based on the doctor's orders, the system will advise the patient on whether the meal complies with their dietary restrictions.
  • Interactive dashboard: A personalized dashboard where patients can view their meal history, recommendations, and health progress.

For Doctors:

  • Manage patient dietary restrictions: Doctors can log in to the platform and set specific dietary restrictions for each patient.
  • Monitor patient compliance: Doctors can track their patients' dietary choices over time to ensure adherence to prescribed diets.

Key Features:

  • Secure and private: Data is encrypted, ensuring patient information is securely handled and stored.
  • Scalable infrastructure: Built using MongoDB, Flask, and Cloudflare for reliability and performance.
  • Real-time feedback: Instant dietary advice after uploading a food image.

Tech Stack

Component Technology Responsible Person
Frontend React.js Tojo Tsimalay, Stevenson M.
Backend Python, Flask Stevenson Michel, Amir Aref
Database MongoDB Amir Aref
AI Model Custom model using Llama Tojo Tsimalay
Hosting Platform Cloudflare Moise Dete-Kpinssounon
QR Scan QuaggaJS Moise Dete-Kpinssounon

Why We Chose This Stack:

  • React.js: Provides a responsive and dynamic front-end, allowing users to easily upload photos and interact with the app.
  • Flask: Lightweight and powerful, Flask seamlessly integrates with the AI model and handles requests efficiently.
  • MongoDB: NoSQL database ideal for storing flexible, unstructured data such as food images, dietary information, and user records.
  • Cloudflare: Ensures top-notch security and fast content delivery, making the app scalable and secure.
  • Llama AI Model: Accurately analyzes food content from images and cross-references it with dietary restrictions for personalized recommendations.

Installation

To set up the WellBite.ai project on your local machine:

Prerequisites:

  • Node.js and npm (for front-end)
  • Python 3.x (for back-end)
  • MongoDB (local or cloud instance)
  • Flask and related Python libraries
  • React.js and related JavaScript libraries

1. Clone the Repository:

git clone https://github.com/your-repo/wellbite-ai.git
cd wellbite-ai

2. Backend Setup (Flask and AI):

  • Navigate to the backend folder:
    cd backend
  • Install the Python dependencies:
    pip install -r requirements.txt
  • Configure MongoDB connection in the config.py file:
    MONGO_URI = 'your-mongodb-connection-string'
  • Start the Flask server:
    python app.py

3. Frontend Setup (React.js):

  • Navigate to the frontend folder:
    cd frontend
  • Install dependencies:
    npm install
  • Start the development server:
    npm start

4. MongoDB Setup:

  • If you don't have MongoDB installed, you can use MongoDB Atlas for cloud-based storage or install MongoDB locally.

Usage

For Patients:

  1. Sign up for an account and log in.
  2. Upload a photo of your meal using the intuitive image upload interface.
  3. The AI model will analyze the meal and provide dietary advice based on your doctor's restrictions.

For Doctors:

  1. Log in to your doctor account.
  2. Access your patient list and set dietary restrictions based on their medical needs.
  3. Make adjustments to their dietary plan when necessary.

Contributing

We welcome contributions to WellBite.ai! To contribute:

  1. Fork the repository.
  2. Create a new branch (git checkout -b feature-branch).
  3. Make your changes and commit them (git commit -m 'Add new feature').
  4. Push to the branch (git push origin feature-branch).
  5. Submit a pull request.

Please make sure to follow the contribution guidelines.

License

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


WellBite.ai strives to make healthcare more personalized and proactive, empowering users to make better dietary choices through technology. By providing a seamless platform where patients and doctors can collaborate, we aim to enhance health outcomes and improve overall well-being.

Let’s build a healthier future together with WellBite.ai!

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