☕ MatchMyCoffee

MatchMyCoffee is an integrated webshop designed to help coffee lovers discover personalized roasts and flavors through a unique taste-profile recommendation system.

---

📖 Overview

The platform connects coffee enthusiasts with artisanal roasters, fostering a community where quality meets personal taste.

• For Coffee Lovers: Discover new flavors, order high-quality beans, and get personalized recommendations based on your taste profile.
• For Roasters: Small, local roasters can showcase their products and reach a wider audience.

🏗️ Architecture & Tech Stack

The application is built on a microservice architecture, ensuring modularity and scalability.

📂 Repository Structure

Service	Technology	Description
Frontend	React + TypeScript	The user interface for the webshop and admin panels.
Backend	Java (Spring Boot)	Handles core business logic, user management, and order processing.
Agent	Python + LangGraph	AI-driven service for the recommendation system and intelligent features.
Database	PostgreSQL	Relational database configurations and scripts.

Deployment: Designed for deployment on AWS.

---

✨ Key Features

👤 User Experience

• Coffee Recommendation System: Users fill out an interactive questionnaire to generate a taste profile, receiving tailored coffee suggestions.
• Webshop & Ordering: Browse detailed product info (roast, origin, notes), manage a cart, and securely place orders.
• Reviews: Users can rate coffees and write feedback to help the community.

🛠️ Administration & Marketing

• Product Management: Administrators can add, modify, or remove products and moderate user reviews.
• Blog & Content: The Marketing role can publish articles, brewing tips (e.g., "How to brew the perfect pour-over"), and updates on new trends.

---

🚀 Getting Started

Prerequisites

• Node.js & npm/yarn
• Java JDK 17+
• Python 3.10+
• PostgreSQL
• Docker (optional, for running services together)

Installation

1. Clone the repository

   git clone https://github.com/yourusername/matchmycoffee.git

2. Database Setup Navigate to the database folder and run the initialization scripts to set up the PostgreSQL schema.

3. Backend (Spring Boot)

   cd backend
   ./mvnw spring-boot:run

4. Agent (Python/LangGraph)

   cd agent
   pip install -r requirements.txt
   uvicorn main:app --reload

5. Frontend (React)

   cd frontend
   npm install
   npm start

---

👥 Authors

• Demeter Beniamin
• Daroczi Levente

---

Note: Features like Dark Mode, Wishlists, and non-coffee products are excluded from this MVP version.