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HokiePlatePal 🍽️ Your AI-Powered Campus Nutrition Companion

🎯 Overview

HokiePlate is a personalized nutritionist and food tracker app designed specifically for college students' campus dining experience. The app creates customized meal plans based on real-time menus from nearby dining halls, integrating with VT's dining infrastructure to provide intelligent food recommendations.

✨ Key Features

🤖 AI-Powered Nutrition Chatbot: "PlatePal" provides instant meal suggestions based on your dietary needs 📱 Quick-Prompt Functionality: Perfect for students in a rush between classes 🕒 Real-Time Dining Hall Status: Live hours and walking distances to campus dining locations 📊 Comprehensive Food Tracking: Monitor nutrition across all campus dining options 🗺️ Integrated Campus Mapping: Seamless navigation to dining locations 🎯 Personalized Meal Plans: Custom recommendations based on calorie goals and dietary restrictions 📍 GPS Integration: Smart location-based dining suggestions

🏗️ Architecture

Frontend

React Native - Cross-platform mobile application JavaScript - Core application logic HTML/CSS - User interface styling Visual Studio Code - Development environment

Backend

Python - Core backend logic Flask API - RESTful endpoints for frontend communication Web Scraper - Real-time VT dining hall data extraction JSON Database - Structured nutrition and menu storage Daily Scheduler - Automated data refresh system

AI Integration

OpenAI API - Intelligent meal recommendation engine Role-Based Prompting - PlatePal nutrition expert persona Few-Shot Learning - Enhanced meal planning examples Rule-Based Validation - Dietary restriction compliance checking

🚀 Getting Started

Prerequisites

Node.js (v14 or higher) Python 3.8+ React Native development environment OpenAI API key

Installation

Clone the repository

bash git clone https://github.com/KashishUdhani/HokiePlatePal.git cd HokiePlatePal

Set up the backend

bash Install Python dependencies pip install -r requirements.txt

Set up environment variables cp .env.example .env Add your OpenAI API key to .env

Set up the frontend

bash cd frontend npm install

Start the development servers

Backend:

bash python app.py Frontend: bash cd frontend npm start Environment Variables Create a .env file in the root directory: envOPENAI_API_KEY=your_openai_api_key_here FLASK_ENV=development DATABASE_URL=your_database_url 📱 Usage

Launch the app and create your profile Set dietary preferences and calorie goals Ask PlatePal for meal recommendations:

"What's healthy at D2 for lunch?" "I need a high-protein dinner under 600 calories"

View real-time dining hall info including hours and distances Track your meals throughout the day Navigate to dining locations using integrated mapping

🤝 Contributing We welcome contributions! Please see our Contributing Guidelines for details.

Fork the repository Create your feature branch (git checkout -b feature/AmazingFeature) Commit your changes (git commit -m 'Add some AmazingFeature') Push to the branch (git push origin feature/AmazingFeature) Open a Pull Request

📋 Project Structure HokiePlatePal/ ├── frontend/ # React Native mobile app │ ├── src/ │ ├── components/ │ └── package.json ├── backend/ # Python Flask API │ ├── app.py │ ├── scraper/ │ └── requirements.txt ├── gps.py # GPS functionality ├── .env.example # Environment variables template ├── .gitignore └── README.md

🛣️ Roadmap

What's Next for HokiePlate

🌍 Multi-University Expansion: Scale to serve students across different college campuses nationwide 🧭 Enhanced Mapping Integration: Implement turn-by-turn navigation directly within the app 🏫 Official University Partnerships: Secure authorization through VT for student credential login and dining plan integration 💰 Dining Dollar Management: Include balance tracking and end-of-semester donation options for unused funds 📈 Advanced Analytics Dashboard: Provide insights into eating patterns and nutritional trends 👥 Community Features: Enable students to share meal recommendations and dining hall reviews

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

Kashish Udhani - Project Lead [Add other team members here]

🙏 Acknowledgments

Virginia Tech Dining Services for menu data OpenAI for AI capabilities React Native community for mobile development resources

📞 Support If you have any questions or need help getting started:

📧 Email: [your-email@example.com] 🐛 Issues: GitHub Issues 💬 Discussions: GitHub Discussions

Made with ❤️ for Hokie students by Hokie students

About

An AI-powered nutrition chatbot built with Flask, Python, and OpenAI API that generates personalized meal recommendations for Virginia Tech students based on real-time dining hall data. Features sophisticated prompt engineering, rule-based validation, and context-aware responses for optimal campus dining guidance.

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