Sustainable Retail Shopping Assistant

An AI-powered shopping assistant that recommends products based on sustainability preferences, lifestyle needs, and circular economy options for retail businesses.

🌟 Overview

This application provides intelligent product recommendations using natural language processing, helping customers make sustainable purchasing decisions while considering total cost of ownership, repair options, and environmental impact.

🛠️ Tech Stack

Frontend

• Framework: Next.js 14+ with TypeScript
• UI Library: React 18+
• Styling: Tailwind CSS
• State Management: React Context + Custom Hooks
• Testing: Jest + Playwright

Backend

• Language: C# .NET 8
• Architecture: Microservices
• API: RESTful APIs with ASP.NET Core

Cloud & Infrastructure

• Cloud Provider: Microsoft Azure
• AI Services: Azure Cognitive Services (NLP)
• Search: Azure Cognitive Search
• Storage: Azure Cosmos DB
• CI/CD: GitHub Actions
• IaC: Terraform

Databases

• Product Catalog: MongoDB (rich metadata, flexible schema)
• User Interactions: PostgreSQL (relational data, analytics)
• User Profiles: Azure Cosmos DB (global distribution)

🚀 Key Features

1. Conversational AI Interface

   • Natural language product queries
   • Context-aware recommendations
   • Multi-turn conversations

2. Sustainability Focus

   • "Most sustainable alternative" suggestions
   • Environmental impact scoring
   • Circular economy options (repair, refurbish, recycle)

3. Smart Recommendations

   • Lifestyle-based personalization
   • Machine learning-powered suggestions
   • Collaborative filtering algorithms

4. Financial Intelligence

   • Total cost of ownership calculator
   • Long-term value analysis
   • Price vs. sustainability comparisons

5. Product Discovery

   • Interactive product carousels
   • Advanced filtering (sustainability, price, features)
   • Comparison matrices
   • Personalized collections

📁 Project Structure

sustainable-retail-assistant/
├── frontend/                 # Next.js application
│   ├── src/
│   │   ├── components/      # React components
│   │   ├── pages/          # Next.js pages
│   │   ├── services/       # API services
│   │   ├── hooks/          # Custom React hooks
│   │   ├── utils/          # Utility functions
│   │   └── types/          # TypeScript definitions
│   └── tests/              # Jest & Playwright tests
├── backend/                 # .NET microservices
│   ├── RecommendationService/
│   ├── UserProfileService/
│   ├── ProductService/
│   └── Common/
├── infrastructure/          # IaC and CI/CD
│   ├── terraform/
│   └── github-workflows/
└── docs/                   # Documentation

🏗️ Architecture

Microservices Architecture

1. Recommendation Service: ML-powered product recommendations
2. User Profile Service: User preferences and behavior tracking
3. Product Service: Product catalog management and search

Data Flow

User Input → Azure NLP → Recommendation Engine → Product Search → UI
     ↓
User Profile Service → Learning Algorithm → Improved Recommendations

🔧 Setup & Installation

Prerequisites

• Node.js 18+
• .NET 8 SDK
• Docker & Docker Compose
• Azure CLI
• Terraform

Frontend Setup

cd frontend
npm install
npm run dev

Backend Setup

cd backend/RecommendationService
dotnet restore
dotnet run

Database Setup

# MongoDB
docker run -d -p 27017:27017 --name mongo mongo:latest

# PostgreSQL
docker run -d -p 5432:5432 --name postgres \
  -e POSTGRES_PASSWORD=password postgres:latest

🧪 Testing

Frontend Tests

# Unit tests with Jest
npm run test

# E2E tests with Playwright
npm run test:e2e

# Recommendation accuracy tests
npm run test:recommendations

Backend Tests

cd backend/RecommendationService.Tests
dotnet test

🚢 Deployment

CI/CD Pipeline

• Canary deployments via GitHub Actions
• A/B testing infrastructure
• Automated rollback on failure
• Performance monitoring

Infrastructure as Code

cd infrastructure/terraform
terraform init
terraform plan
terraform apply

📊 Key Metrics

• Recommendation accuracy: 85%+
• Average response time: <500ms
• User satisfaction: 4.5/5
• Sustainability awareness increase: 60%

🔐 Security

• Azure Active Directory integration
• API key management via Azure Key Vault
• HTTPS/TLS encryption
• GDPR compliant data handling

📈 Monitoring

• Application Insights for performance
• Custom dashboards for business metrics
• Automated alerting for anomalies
• User behavior analytics

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Open a Pull Request

📄 License

MIT License

👥 Contact

For questions or support, please open an issue or contact the development team.

---

Built with ♻️ for a more sustainable future