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ARCHITECTURAL CHANGE: Migrated from frontend-based code generation to backend-based generation following best practices discovered in the orders service implementation. RATIONALE: After investigating the codebase, found that the orders service already implements proper backend auto-generation for order numbers (ORD-YYYYMMDD-####). This approach is superior to frontend generation for several reasons: 1. **Uniqueness Guarantee**: Database-enforced uniqueness, no race conditions 2. **Sequential Numbering**: True sequential IDs per tenant per day 3. **Consistent Format**: Server-controlled format ensures consistency 4. **Audit Trail**: Full server-side logging and tracking 5. **Simplicity**: No complex frontend state management 6. **Performance**: One less re-render trigger in wizards CHANGES MADE: **InventoryWizard.tsx:** - ❌ Removed: useRef, useEffect auto-generation logic - ❌ Removed: SKU generation (SKU-{name}-{timestamp}) - ✅ Changed: SKU field to optional with new placeholder - ✅ Updated: Tooltip to indicate backend generation - ✅ Simplified: Removed unnecessary imports (useEffect, useRef) **QualityTemplateWizard.tsx:** - ❌ Removed: useRef, useEffect auto-generation logic - ❌ Removed: Template code generation (TPL-{name}-{timestamp}) - ✅ Changed: Template code field to optional - ✅ Updated: Placeholder text for clarity - ✅ Simplified: Removed unnecessary imports **CustomerOrderWizard.tsx:** - ❌ Removed: useRef, useEffect auto-generation logic - ❌ Removed: Order number generation (ORD-{timestamp}) - ✅ Changed: Order number field to read-only/disabled - ✅ Updated: Shows "Auto-generated on save" placeholder - ✅ Added: Tooltip explaining backend format (ORD-YYYYMMDD-####) NEXT STEPS (Backend Implementation Required): 1. Inventory Service: Add SKU generation method (similar to order_number) 2. Production Service: Add template code generation for quality templates 3. Format suggestions: - SKU: "SKU-{TENANT_PREFIX}-{SEQUENCE}" or similar - Template Code: "TPL-{TYPE_PREFIX}-{SEQUENCE}" BENEFITS: - ✅ Eliminates all focus loss issues from auto-generation - ✅ Removes complex state management from frontend - ✅ Ensures true uniqueness at database level - ✅ Better user experience with clear messaging - ✅ Follows established patterns from orders service - ✅ Cleaner, more maintainable code This change completes the frontend simplification. Backend services now need to implement generation logic similar to orders service pattern.
🍞 Bakery IA - Multi-Service Architecture
Welcome to Bakery IA, an advanced AI-powered platform for bakery management and optimization. This project implements a microservices architecture with multiple interconnected services to provide comprehensive bakery management solutions.
🚀 Quick Start
Prerequisites
- Docker Desktop with Kubernetes enabled
- Docker Compose
- Node.js (for frontend development)
Running the Application
-
Clone the repository:
git clone <repository-url> cd bakery-ia -
Set up environment variables:
cp .env.example .env # Edit .env with your specific configuration -
Run with Docker Compose:
docker-compose up --build -
Or run with Kubernetes (Docker Desktop):
# Enable Kubernetes in Docker Desktop # Run the setup script ./scripts/setup-kubernetes-dev.sh
🏗️ Architecture Overview
The project follows a microservices architecture with the following main components:
- Frontend: React-based dashboard for user interaction
- Gateway: API gateway handling authentication and routing
- Services: Multiple microservices handling different business domains
- Infrastructure: Redis, RabbitMQ, PostgreSQL databases
🐳 Kubernetes Infrastructure
🛠️ Services
The project includes multiple services:
- Auth Service: Authentication and authorization
- Tenant Service: Multi-tenancy management
- Sales Service: Sales processing
- External Service: Integration with external systems
- Training Service: AI model training
- Forecasting Service: Demand forecasting
- Notification Service: Notifications and alerts
- Inventory Service: Inventory management
- Recipes Service: Recipe management
- Suppliers Service: Supplier management
- POS Service: Point of sale
- Orders Service: Order management
- Production Service: Production planning
- Alert Processor: Background alert processing
📊 Monitoring
The system includes comprehensive monitoring with:
- Prometheus for metrics collection
- Grafana for visualization
- ELK stack for logging (planned)
🚀 Production Deployment
For production deployment on clouding.io with Kubernetes:
- Set up your clouding.io Kubernetes cluster
- Update image references to your container registry
- Configure production-specific values
- Deploy using the production kustomization:
kubectl apply -k infrastructure/kubernetes/environments/production/
🤝 Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Submit a pull request
📄 License
This project is licensed under the MIT License.