Sweet-Shop

A full-stack web application with React (Vite) frontend, Node.js backend, Prisma ORM, and PostgreSQL database.

Project Structure

The project is organized into two main directories:

• frontend/: Contains the vite.js frontend application.
• backend/: Contains the Node.js backend server with Prisma ORM.

📖 Project Explanation

Sweet-Shop is an online store application built as a full-stack project.

• The frontend is built with React + Vite + TypeScript, styled with TailwindCSS, and uses lucide-react for icons.
• The backend is built with Node.js + Express, featuring JWT authentication with cookies.
• Prisma ORM is used to interact with a PostgreSQL database for structured and reliable data storage.
• Zod is used for validation, bcrypt for password hashing, and axios for API calls.

📦 Tech Stack

• Frontend: React (Vite) + TypeScript
• Backend: Node.js + Express
• Database: PostgreSQL
• ORM: Prisma
• Authentication: JWT + Cookies + cookie-parser
• Validation: Zod
• Security: bcrypt (password hashing)
• HTTP Requests: axios
• Styling: TailwindCSS
• Icons: lucide-react

Prerequisites

Before you begin, ensure you have the following installed on your system:

• Node.js (v18 or later recommended)
• npm (Node Package Manager)
• A database (e.g., PostgreSQL, MySQL, SQLite) for the backend.

Getting Started

Follow these steps to get the project set up and running on your local machine.

1. Clone the Repository

git clone https://github.com/itsmanasdash/Sweet-Shop

cd sweet-shop
cd backend

Install dependencies

npm install

Create a .env file based on the .env.example file

cp .env.example .env

Prisma Migrate

npx prisma migrate dev --name init

Generate Prisma Client

npx prisma generate

Start the development server

npm run dev

Open http://localhost:8000 in your browser to view the application

Setup the Frontend
cd ../frontend

Install dependencies

npm install

Start the development server

npm run dev

#🤖 My AI Usage

For this project, I leveraged AI tools to accelerate development and debugging:

Claude AI:

Used to generate the initial frontend skeleton and UI components in Svelte.

Helped bootstrap layouts and structure for the project quickly.

ChatGPT (OpenAI GPT-5):

Assisted in solving errors, debugging backend issues, and refining Prisma/Postgres integration.

Helped polish the README.md and improve documentation clarity.

Reflection

Using AI tools made my workflow significantly more efficient:

Faster prototyping: Claude helped me quickly set up a functional UI skeleton.

Error resolution: ChatGPT guided me through debugging issues that would have otherwise taken longer to research.

Documentation: ChatGPT helped create structured and professional documentation.

However, I made sure to review, understand, and modify all AI-generated code before committing it, ensuring I stayed in control of the project’s logic and quality. AI acted as a pair programmer/assistant, not as a replacement for understanding.