PromoAtlas PIM 🎯

A headless Product Information Management system for promotional products with AI-powered semantic search via Google Gemini RAG.

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🚀 Quick Start

Prerequisites

• Node.js 18+
• PostgreSQL 14+ (or Neon account)
• Redis (or Upstash account)
• Gemini API key

Installation

# Clone the repository
git clone <repo-url>
cd PromovereAtlasPim

# Backend setup
cd backend
npm install
cp .env.example .env  # Configure your environment variables
npm run develop

# Frontend setup (in another terminal)
cd frontend
npm install
npm run dev

Environment Variables

# Required
DATABASE_URL=postgresql://...
REDIS_URL=redis://...
GEMINI_API_KEY=AIzaSy...

# Optional (for full features)
R2_ACCOUNT_ID=...
MEILISEARCH_HOST=...

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✨ Features

🤖 AI-Powered Search

• Semantic Search: Natural language product queries via Gemini File Search
• Persistent Embeddings: FileSearchStore for long-term RAG storage
• Auto-Sync: Products automatically indexed on update
• 5/5 Products Verified: Production-ready implementation

📦 Product Management

• Two-Level Hierarchy: Product → Product Variants (sizes/colors)
• Multilingual: EN/DE/FR/ES support with fallback chains
• 56 Suppliers: Promidata integration with 56 suppliers
• Hash-Based Sync: 89% efficiency with incremental updates

🔍 Advanced Search

• Meilisearch: Typo-tolerant exact search with facets
• Filters: Category, supplier, price range, brand, status
• Pagination: 12 products per page with sorting
• Real-time: Auto-indexed on product changes

🖼️ Media Management

• Cloudflare R2: Zero-egress-fee storage with CDN
• Adaptive Fitting: Smart cover/contain based on aspect ratio
• Automated Upload: Images auto-uploaded during sync

⚡ Performance

• BullMQ Queue: Background job processing with retries
• Redis Caching: Fast data access
• Batch Operations: Efficient bulk product processing

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🏗️ Architecture

Headless RAG Design

┌─────────────────┐
│   Frontend      │ (Separate Next.js repo - planned)
│  (Vercel AI)    │
└────────┬────────┘
         │ Tool Calling
    ┌────┴─────┬──────────┐
    ▼          ▼          ▼
┌────────┐ ┌────────┐ ┌─────────┐
│ Gemini │ │ Meili  │ │ Strapi  │
│  RAG   │ │ search │ │   API   │
└────────┘ └────────┘ └─────────┘

Why This Architecture?

• Gemini → Semantic understanding ("blue t-shirts under 20€")
• Meilisearch → Exact search, filters, facets
• Strapi → Source of truth, admin, write operations
• Frontend → Orchestrates all three intelligently

Data Flow

Promidata API
      │
      ▼
┌──────────────┐
│ Promidata    │
│ Sync Service │
└──────┬───────┘
       │
   ┌───┴────┬──────────┐
   ▼        ▼          ▼
Strapi  Meilisearch  Gemini
  DB      Index    FileStore

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📊 Tech Stack

Layer	Technology	Why
Backend	Strapi 5	Headless CMS with built-in admin
Database	PostgreSQL (Neon)	Relational + JSON support
Queue	BullMQ + Redis	Async processing with retries
Search	Meilisearch	Fast typo-tolerant search
RAG	Google Gemini	Semantic search & embeddings
Storage	Cloudflare R2	Zero egress fees
Frontend	React 18 + Vite	Fast builds, great DX

See .Gemini/STACK.md for detailed rationale.

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📁 Project Structure

PromovereAtlasPim/
├── backend/                 # Strapi 5 backend
│   ├── src/
│   │   ├── api/
│   │   │   ├── product/    # Product content type
│   │   │   ├── promidata-sync/  # Sync orchestration
│   │   │   └── gemini-sync/     # RAG admin endpoints
│   │   └── services/
│   │       ├── gemini/          # Gemini RAG service ⭐
│   │       ├── promidata/       # Promidata integration
│   │       └── queue/           # BullMQ workers
│   └── config/             # Strapi configuration
│
├── frontend/               # React frontend
│   └── src/
│       ├── components/     # Reusable components
│       ├── pages/          # Product list/detail
│       └── hooks/          # Custom hooks
│
└── .Gemini/               # Documentation
    ├── INDEX.md           # Documentation index
    ├── STACK.md           # Tech stack details
    └── DECISIONS.md       # Architectural decisions

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🧪 Testing

Test Gemini Integration

cd backend

# Test with mock products
node test-gemini-simple.js

# Test with real database products
node test-sync-direct.js

Expected Output:

✅ Complete: 5/5 synced

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📚 Documentation

Document	Purpose
CLAUDE.md	System overview & commands
.Gemini/INDEX.md	Documentation index
.Gemini/STACK.md	Tech stack details
.Gemini/DECISIONS.md	Architecture decisions
Walkthrough	Gemini RAG implementation

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🎯 Key Achievements

• ✅ 89% Sync Efficiency: Hash-based incremental updates
• ✅ 5/5 Products Synced: Gemini RAG production-ready
• ✅ 56 Suppliers: Full Promidata integration
• ✅ Multilingual: 4 languages with fallback
• ✅ Headless Architecture: Flexible frontend options

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🚧 Roadmap

Phase 1: Backend ✅ COMPLETE

• Strapi 5 setup with PostgreSQL
• Product → ProductVariant hierarchy
• Promidata sync with hash optimization
• Meilisearch integration
• Gemini RAG integration
• BullMQ queue system

Phase 2: Frontend (In Progress)

• Separate Next.js repo with Vercel AI SDK
• Tool calling orchestration
• Semantic search UI
• Multi-brand support

Phase 3: Advanced Features

• Product recommendations via Gemini
• Advanced analytics
• Multi-tenant support
• API rate limiting & caching

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🤝 Contributing

This project follows a strict feature branch workflow:

1. Create feature branch: feature/your-feature
2. Make changes with clear commits
3. Create Pull Request
4. Never push directly to main

See CLAUDE.md for detailed contribution guidelines.

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📄 License

[Your License Here]

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🙋 Support

For questions or issues:

• 📖 Check CLAUDE.md for common solutions
• 📝 Review .Gemini/DECISIONS.md for architecture context
• 🐛 Open an issue with detailed reproduction steps

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Built with ❤️ using Strapi, React, and Google Gemini

Last updated: 2025-11-19