Grocery List App

Overview

The Grocery List App is a platform designed to simplify grocery shopping and nutritional analysis. It allows users to easily analyze the macronutrient profile of food items and make healthier choices. The app is built with a user-friendly interface and offers AI-driven features for enhanced functionality.

Features

• Smart Grocery List: Allows users to create, modify, and view grocery lists.
• Nutritional Analysis: Provides detailed nutritional information about food items.
• AI-Driven Food Categorization: Uses an AI model to suggest additional categories for food items based on their names.
• Scoring System: Food items are scored based on their nutritional profiles, similar to the Dutch Nutri-Score system. The scoring system ranges from A to D.

Technologies Used

• Frontend: React.js
• Backend: Python (Flask for API)
• AI Model: Rule-based AI system for nutritional scoring and category suggestions
• Database: Local JSON or API-based storage for food data

Installation

Clone the Repository

git clone https://github.com/Amir-Mohseni/grocery-list-app

Install Dependencies

1. Navigate tot he project directory:

cd grocery-list-app

2. Install Python Dependencies:

pip install -r src/requirements.txt

3. Install Node.js dependencies for the frontend:

npm install

Setup and Run the Application

1. Start the backend server for the scoring system:

python src/food_rater.py

2. Start the React Application:

npm start

This will open the application in your default browser.

How to Use

1. Create a Grocery List: Add items to your list by typing their names into the search bar.
2. View Nutritional Information: After adding an item to the list, click on it to view its nutritional profile.
3. AI Food Categorization: The app suggests possible categories for each food item based on its name and nutritional profile.
4. Scoring System: Each food item is rated from A to D based on its nutritional value. The higher the score, the healthier the item.

Future Improvements

• Augmented Reality (AR) Integration: To allow real-time food identification via a front-facing camera.
• Enhanced AI Features: More advanced AI models for food categorization and personalized recommendations.
• Mobile Application: Porting the app to mobile platforms for on-the-go use.

Contributors

• Amir Mohseni
• Dimitrios Tsiplakis

License

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

Acknowledgments

• Nutri-Score System: The scoring system is inspired by the Dutch Nutri-Score system.
• Shapley Additive Explanations (SHAP): For the AI model transparency and explainability.