MishtiFlow

A modern sweet shop management system for browsing, purchasing, and managing Indian sweets inventory.

🚀 Features

For Customers:

• Browse sweets with search & filters (name, category, price)
• Real-time stock availability
• Purchase sweets with instant quantity updates

For Admins:

• Add, edit, and delete sweets
• Restock inventory
• Manage complete product catalog

Security:

• JWT authentication with HTTP-only cookies
• Role-based access (USER/ADMIN)
• Bcrypt password hashing

🛠️ Tech Stack

Backend: Next.js 16 API Routes, MongoDB, TypeScript
Frontend: React 19, Tailwind CSS v4, shadcn/ui
Testing: Jest with comprehensive test coverage

📦 Setup

Prerequisites

• Node.js 18+
• MongoDB Atlas account (or local MongoDB)

Installation

1. Clone and install:

git clone https://github.com/Anomasingh/MishtiFlow.git
cd MishtiFlow
npm install

2. Environment variables (.env.local):

MONGODB_URI=your_mongodb_connection_string
JWT_SECRET=your_secret_key

3. Seed database:

npx tsx scripts/seed-database.ts

Default credentials:

• Admin: admin@mishtiflow.com / admin123
• User: user@mishtiflow.com / user123

4. Run development server:

npm run dev

Visit http://localhost:3000

Testing

npm test              # Run tests
npm run test:watch    # Watch mode

Project Structure

``` ├── app/ │ ├── api/ # API routes │ │ ├── auth/ # Authentication endpoints │ │ └── sweets/ # Sweet management endpoints │ ├── admin/ # Admin panel page │ ├── dashboard/ # Main dashboard │ ├── login/ # Login page │ └── register/ # Registration page ├── components/ │ ├── ui/ # shadcn/ui components │ ├── navbar.tsx # Navigation bar │ ├── sweet-card.tsx # Sweet display card │ ├── search-filter-bar.tsx │ └── [admin components] ├── lib/ │ ├── auth.ts # JWT utilities │ ├── db.ts # Database utilities │ └── validators.ts # Zod schemas ├── tests/ # Test files ├── scripts/ # Database scripts └── prisma/ # Prisma schema ```

API Endpoints

Authentication

• POST /api/auth/register - Register new user
• POST /api/auth/login - Login user
• POST /api/auth/logout - Logout user
• GET /api/auth/me - Get current user

Sweets

• GET /api/sweets - List all sweets (with filters)
• POST /api/sweets - Create sweet (ADMIN)
• GET /api/sweets/:id - Get single sweet
• PUT /api/sweets/:id - Update sweet (ADMIN)
• DELETE /api/sweets/:id - Delete sweet (ADMIN)
• POST /api/sweets/:id/purchase - Purchase sweet
• POST /api/sweets/:id/restock - Restock sweet (ADMIN)

My AI Usage

This project was built with assistance from v0 by Vercel, an AI-powered development assistant. Here's how AI contributed to the development process:

What AI Helped With

1. Boilerplate Code Generation: AI helped generate initial project structure, component scaffolding, and configuration files, significantly reducing setup time.

2. UI Design: AI generated design inspiration and helped implement a cohesive color palette inspired by Indian sweets (saffron, rose, pistachio, cardamom) with proper Tailwind CSS theming.

3. Test Writing: AI assisted in writing comprehensive test cases following TDD principles, covering authentication, validation, CRUD operations, and edge cases.

4. API Route Implementation: AI helped structure API routes with proper error handling, validation, and response formatting.

5. Type Safety: AI helped ensure TypeScript types were properly defined throughout the application.

Human Oversight and Refinement

While AI provided a strong foundation, human engineering judgment was crucial for:

• Architecture Decisions: Choosing between Prisma ORM vs raw SQL queries (opted for raw SQL for better control)
• Security Implementation: Ensuring proper JWT handling, HTTP-only cookies, and bcrypt configuration
• Business Logic: Atomic stock updates, purchase validation, and authorization rules
• Database Design: Schema structure, relationships, and query optimization
• Error Handling: Context-specific error messages and proper HTTP status codes
• Testing Strategy: Deciding what to test and ensuring meaningful coverage

Productivity Impact

AI significantly improved productivity by:

• Reducing time spent on repetitive code patterns
• Providing instant syntax and API reference
• Generating test cases that might have been overlooked
• Suggesting accessibility improvements and best practices

However, AI did not replace the need for:

• Understanding business requirements
• Making architectural trade-offs
• Debugging complex issues
• Code review and refactoring
• Security auditing

The combination of AI assistance and human expertise resulted in a production-ready application built faster without compromising quality or security.

Deployment

Backend Deployment (Railway/Render)

1. Create a PostgreSQL database on your hosting platform
2. Set environment variables:
   • DATABASE_URL
   • JWT_SECRET
3. Deploy the Next.js application
4. Run database scripts after deployment

Frontend Deployment (Vercel)

1. Connect your GitHub repository to Vercel
2. Set environment variables in Vercel dashboard
3. Deploy automatically on push to main branch

Best Practices Followed

• Test-Driven Development: Comprehensive test coverage for critical paths
• SOLID Principles: Separation of concerns, single responsibility
• Security First: Password hashing, JWT tokens, authorization checks
• Type Safety: Full TypeScript coverage
• Clean Code: Meaningful names, proper comments, modular structure
• Atomic Operations: Database transactions for inventory updates
• Error Handling: Centralized error handling with clear messages
• Validation: Input validation at API and UI levels
• Responsive Design: Mobile-first approach with Tailwind CSS

License

MIT

Contact

For questions or support, please open an issue on GitHub.