🎨 DRESSLY

AI-Powered Fashion Advisory Platform

Upload your wardrobe. Get styled by AI. Dress with confidence.

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🧠 What is Dressly?

Dressly is a production-grade, AI-powered fashion advisory platform that helps users build smarter wardrobes and generate stunning outfit combinations. Powered by Google Gemini 2.0 Flash multimodal AI, users upload clothing images and receive AI-curated outfit recommendations complete with style scores, occasion matching, and personalized fashion advice.

Built to handle 1–3 million concurrent users with a Rust backend delivering sub-5ms API latency.

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✨ Features

Feature	Description
🤖 AI Outfit Generation	Text + multiple clothing images → AI-generated outfit with style score
👔 Occasion-Based Styling	Outfits matched to events — formal, casual, party, wedding, interview
🗄️ Digital Wardrobe	Upload and categorize your entire clothing collection
📊 Dress Code Analysis	AI analyzes outfit photos and suggests improvements
💎 Pro Subscription	Unlimited AI generations, premium features via Razorpay
🔔 Real-Time Notifications	Push notifications via FCM/APNs for AI results, payments, tips
🌐 WebSocket Support	1:1 persistent connections with heartbeat and auto-reconnect
🛡️ Admin Dashboard	User management, dynamic pricing, analytics, broadcast messaging
🌙 Dark/Light Mode	System-aware theming across platforms

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🏗️ Architecture

Client (Flutter / React)
        │
        ▼  HTTPS / WSS (TLS 1.3)
   CloudFlare CDN + WAF
        │
        ▼
   Nginx Load Balancer
        │
        ▼
  ┌─────────────────────────────────┐
  │  Rust Backend (Actix-Web 4)     │
  │  ┌─────┬──────┬────────┬─────┐ │
  │  │Auth │ User │ AI/ML  │Pay  │ │
  │  │ Svc │ Svc  │ Svc    │ Svc │ │
  │  └─────┴──────┴────────┴─────┘ │
  │  WebSocket Manager (DashMap)    │
  │  Tokio Async Runtime            │
  └─────────────┬───────────────────┘
                │
    ┌───────────┼───────────┬──────────────┐
    ▼           ▼           ▼              ▼
PostgreSQL   Redis 7     S3/R2       Gemini API
 (Primary    (Cache +    (Media)     (Multimodal
 + Replicas)  PubSub)                  AI)

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🛠️ Tech Stack

Backend

Component	Technology
Language	Rust 1.75+
Framework	Actix-Web 4
Async Runtime	Tokio
Database	PostgreSQL 16 + SQLx (compile-time checked)
Cache	Redis 7 (Cluster)
Auth	JWT (RS256) + Argon2id
AI	Google Gemini 2.0 Flash
Payments	Razorpay
Serialization	Serde + simd-json
Logging	tracing + tracing-subscriber

Mobile

Component	Technology
Framework	Flutter 3.x
State Management	Riverpod
Navigation	GoRouter
HTTP Client	Dio
Secure Storage	flutter_secure_storage
Image Handling	cached_network_image

Web

Component	Technology
Framework	React
Language	JavaScript

Infrastructure

Component	Technology
Containers	Docker + Docker Compose
Orchestration	Kubernetes
CI/CD	GitHub Actions + Codemagic
CDN + WAF	CloudFlare
Monitoring	Prometheus + Grafana
Tracing	Jaeger

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📂 Project Structure

Dressly/
├── backend/              # Rust API server (Actix-Web)
│   ├── src/
│   │   ├── api/          # Routes, handlers, middleware, responses
│   │   ├── config/       # App configuration
│   │   ├── db/           # Models, migrations, repositories
│   │   ├── errors/       # Error types
│   │   ├── services/     # Auth, AI, Payment, WebSocket, Notifications
│   │   ├── utils/        # Helpers
│   │   └── workers/      # Background job processors
│   ├── tests/            # Unit, integration, property-based tests
│   └── benches/          # Criterion benchmarks
│
├── mobile_flutter/       # Flutter cross-platform app (iOS + Android)
│   ├── lib/
│   │   ├── constants/    # App-wide constants
│   │   ├── models/       # Data models
│   │   ├── providers/    # Riverpod state management
│   │   ├── router/       # GoRouter navigation
│   │   ├── screens/      # UI screens
│   │   ├── services/     # API & WebSocket services
│   │   └── widgets/      # Reusable UI components
│   └── test/             # Widget & unit tests
│
├── web/                  # React web dashboard
│   └── src/
│       ├── components/   # UI components
│       ├── contexts/     # React contexts
│       ├── pages/        # Page views
│       └── services/     # API services
│
├── infra/                # Infrastructure configs
│   ├── k8s/              # Kubernetes manifests
│   └── prometheus.yml    # Monitoring config
│
├── docker-compose.yml    # Local development stack
├── codemagic.yaml        # Mobile CI/CD pipeline
├── SYSTEM_DESIGN.md      # Full system design document
└── LICENSE               # MIT License

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🚀 Getting Started

Prerequisites

• Rust 1.75+ — Install
• Flutter 3.x — Install
• Docker & Docker Compose — Install
• Node.js 18+ — Install

1. Clone the repository

git clone https://github.com/RahulSingh/Dressly.git
cd Dressly

2. Start infrastructure (PostgreSQL + Redis)

docker-compose up -d postgres redis

3. Run the backend

cd backend
cp .env.example .env    # configure your environment variables
cargo run --release

The API will be available at http://localhost:8080.

4. Run the Flutter app

cd mobile_flutter
flutter pub get
flutter run

5. Run the web dashboard

cd web
npm install
npm start

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🧪 Testing

Backend

cd backend

# Unit + integration tests
cargo test

# Property-based tests
cargo test --test test_proptest

# Benchmarks
cargo bench

Mobile

cd mobile_flutter
flutter test

Web

cd web
npm test

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⚡ Performance Targets

Metric	Target
REST API latency (p50)	< 5ms
REST API latency (p99)	< 50ms
WebSocket message latency	< 2ms
Requests/sec per node	100,000+
WebSocket connections per node	50,000+
AI generation throughput	1,000/min

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🔒 Security

• OWASP Top 10 mitigations baked in
• Compile-time SQL injection prevention via SQLx
• Argon2id password hashing (memory-hard)
• JWT with RS256 signing + token rotation
• TLS 1.3 everywhere, HSTS enabled
• Rate limiting (token bucket — 100 req/min/user)
• CloudFlare WAF + DDoS protection
• AES-256-GCM encryption for PII at rest
• All auth events logged with IP + user agent

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💰 Business Model

Tier	Price	Features
Free	₹0	5 AI generations/day, basic wardrobe, limited styles
Pro	Admin-controlled	Unlimited AI, advanced features, priority support

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📖 Documentation

• System Design Document — Full architecture, data models, API design, scaling strategy

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🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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📄 License

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

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👤 Author

Rahul Singh

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_{Built with ❤️ using Rust, Flutter, React, and Gemini AI}