EatSuggester-AI-Food-Predictor

AI-powered web app to predict your girlfriend's food desires

Developed with the software and tools below.

📑 Table of Contents

• 📍 Overview
• 📦 Features
• 📂 Structure
• 💻 Installation
• 🏗️ Usage
• 🌐 Hosting
• 📄 License
• 👏 Authors

📍 Overview

EatSuggester-AI-Food-Predictor is an innovative web application that utilizes AI to predict your girlfriend's hidden food cravings. This MVP tackles the age-old problem of deciding on dinner when your partner says "I don't care." By gathering contextual data about her preferences, time, and mood, the app generates personalized food suggestions, making you a hero in the process.

📦 Features

	Feature	Description
⚙️	Architecture	The application follows a client-server architecture, with a React frontend for user interaction and a Node.js backend for data processing.
📄	Documentation	The repository includes a README file that provides a detailed overview of the project, its features, and usage instructions.
🔗	Dependencies	The codebase relies on various external libraries and packages such as Next.js, React, Tailwind CSS, and Axios, which are essential for building and styling the UI components, handling API calls, and form management.
🧩	Modularity	The modular structure allows for easier maintenance and reusability of the code, with separate directories and files for different functionalities such as pages, components, services, and hooks.
🧪	Testing	Unit tests using Jest are included to ensure the reliability and robustness of the codebase.
⚡️	Performance	Optimized for fast loading times and efficient suggestion generation, using a combination of React's built-in state management and lightweight libraries.
🔐	Security	Implements basic security measures such as input validation and secure authentication using environment variables for sensitive data.
🔀	Version Control	Utilizes Git for version control with GitHub Actions for automated build and release processes.
🔌	Integrations	Interacts with the browser API for user interaction, utilizing a user-friendly form, and a robust suggestion generation algorithm.
📶	Scalability	The application is designed for scalability, leveraging Next.js for improved performance and server-side rendering, and can be easily expanded to include more features and data sources.

📂 Structure

eat-suggester-ai/
├── apps/
│   ├── web/
│   │   └── src/
│   │       └── ... (React app code)
│   └── api/
│       └── src/
│           └── ... (Node.js API code)
├── packages/
│   └── utils/
│       └── ... (Shared utility functions)
├── .eslintrc.js
├── tsconfig.json
├── babel.config.js
└── ... (Other configurations)

💻 Installation

🔧 Prerequisites

• Node.js v16+
• npm 6+ or yarn
• SQLite (optional for database)

🚀 Setup Instructions

1. Clone the repository:

   git clone https://github.com/coslynx/EatSuggester-AI-Food-Predictor.git
   cd EatSuggester-AI-Food-Predictor

2. Install dependencies:

   npm install

3. Configure environment variables:

   cp .env.example .env

   Open .env and set the following variables:

   • NEXT_PUBLIC_API_KEY: (if using external API)
   • DATABASE_URL: (if using SQLite)
   • PORT: (optional, default is 3000)

🏗️ Usage

🏃‍♂️ Running the MVP

1. Start the development server:

   npm run dev

2. Access the application:
   • Web interface: http://localhost:3000

🌐 Hosting

🚀 Deployment Instructions

1. Deploy to Vercel:
   • Visit the Vercel website and connect your GitHub repository.
   • Follow Vercel's instructions to deploy the application.
   • Ensure environment variables are correctly set on Vercel's platform.

🔑 Environment Variables

• NEXT_PUBLIC_API_KEY: (if using external API)
• DATABASE_URL: (if using SQLite)
• PORT: (optional, default is 3000)

📜 License & Attribution

📄 License

This Minimum Viable Product (MVP) is licensed under the GNU AGPLv3 license.

🤖 AI-Generated MVP

This MVP was entirely generated using artificial intelligence through CosLynx.com.

No human was directly involved in the coding process of the repository: EatSuggester-AI-Food-Predictor

📞 Contact

For any questions or concerns regarding this AI-generated MVP, please contact CosLynx at:

• Website: CosLynx.com
• Twitter: @CosLynxAI

🌐 CosLynx.com

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