BiteByte

BiteByte is a react web app powered by a Spring AI and MongoDB.

Table of Contents

• Features
• Architecture
• Installation
• Usage
• API Endpoints
• Contributing
• License

Features

• AI Recipe Customization using OpenAI
• Add and View Recipes
• Participate in Live Cooking Classes
• User Authentication and Authorization
• Dark and Light Theme Toggle

Architecture

The project is divided into two main parts:

1. Backend: A modular monolithic Spring Boot application that handles the API and business logic. The backend is divided into the following modules:

   • ai: Handles AI-related functionalities using OpenAI.
   • common: Contains common utilities and configurations used across other modules.
   • livecooking: Manages live cooking classes.
   • recipe: Manages recipe-related functionalities.
   • security: Handles user authentication and authorization.
   • user: Manages user-related functionalities.
   • util: Contains utility classes and methods.

2. Frontend: A React application that provides the user interface.

Technologies Used

• Backend:

  • Java (Amazon Corretto)
  • Spring Boot
  • Spring AI
  • MongoDB
  • OpenAI API

• Frontend:

  • React
  • Vite

Installation

Prerequisites

• Node.js
• npm
• Amazon Corretto
• Gradle
• MongoDB

Backend Setup

1. Clone the repository:

   git clone https://github.com/yourusername/BiteByte.git
   cd BiteByte

2. Navigate to the backend directory:

   cd src/main/java/com/main/bitebyte

3. Build the project using Gradle:

   ./gradlew build

4. Run the Spring Boot application:

   ./gradlew bootRun

5. Configure the application properties file:

   spring.data.mongodb.uri=mongodb+srv://<username>:<password>@<cluster>.umrcw.mongodb.net/?retryWrites=true&w=majority&appName=bitebyte
   
   spring.data.mongodb.database=bitebyte
   spring.data.mongodb.auto-index-creation=false
   
   spring.ai.openai.api-key= <OpenAI Key>
   spring.ai.openai.model=gpt-4o
   spring.ai.openai.urls.base=https://api.openai.com
   spring.ai.openai.urls.chat-completion=/v1/chat/completions
   
   # JWT Configuration
   jwt.secret= <JWT>
   jwt.expiration=86400000
   jwt.expiration.ms=3600000
   
   # Add this line
   app.jwtSecret=${jwt.secret}
   
   # Server configuration
   server.port=8080
   
   # Disable context path
   server.servlet.context-path=
   
   # Vector store configuration
   spring.ai.vectorstore.name=vector_store

Frontend Setup

1. Navigate to the client directory:

   cd client

2. Install the dependencies:

   npm install

3. Start the development server:

   npm start

Usage

1. Open your browser and navigate to http://localhost:3000.
2. Sign up or sign in to your account.
3. Use the navigation bar to access different features like adding recipes, viewing recipes, and participating in live cooking classes.
4. Customize recipes using the AI Recipe Customization feature.

API Endpoints

Authentication

• POST /api/auth/signup - Sign up a new user
• POST /api/auth/signin - Sign in an existing user

Recipes

• GET /api/recipes - Get all recipes
• GET /api/recipes/{id} - Get a specific recipe by ID
• POST /api/recipes - Add a new recipe (Admin only)
• PUT /api/recipes/{id} - Update a recipe (Admin only)
• DELETE /api/recipes/{id} - Delete a recipe (Admin only)

Live Cooking Classes

• GET /api/live-classes - Get all live cooking classes
• POST /api/live-classes - Add a new live cooking class (Admin only)

AI Recipe Customization

• POST /api/ai-customization - Customize a recipe using AI

Contributing

Contributions are welcome! Please follow these steps to contribute:

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

License

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