3a1a19d836
✅ RECIPES STEP FIX: - Add onComplete prop handling to RecipesSetupStep.tsx - Add "Next" button when recipes.length >= 1 - Show success message with recipe count - Button hidden when in adding mode 🎯 AI INVENTORY STEP - COMPLETE REDESIGN: Following suppliers/recipes pattern with list-based management and deferred creation. **NEW DATA MODEL**: - InventoryItemForm interface with isSuggested tracking - Items stored in list (NOT created in database yet) - Support both AI suggestions and manual entries **NEW UI PATTERN**: - List view with expandable cards showing AI confidence badges - Edit/Delete buttons per item (like suppliers) - "Add Ingredient Manually" button with full form - Next button creates ALL items at once (deferred creation) **KEY CHANGES**: 1. Items added to list first (not created immediately) 2. Can edit/delete both AI and manual items before creation 3. Manual ingredient addition form with full validation 4. All items created when clicking "Next" button 5. Progress indicator during creation 6. Sales data import happens after inventory creation **UI IMPROVEMENTS**: - "Why This Matters" info box explaining workflow - Ingredient cards show: name, category, stock, cost, shelf life, sales data - AI confidence badges (e.g., "IA 95%") - Visual success indicator when minimum met - Gradient form section matching recipe template pattern **FILES**: - UploadSalesDataStep.tsx: Completely rewritten (963 lines) - RecipesSetupStep.tsx: Added Next button (2 lines) - REDESIGN_SUMMARY.md: Complete documentation of changes Build: ✅ Success (21.46s) Pattern: Now matches suppliers/recipes workflow exactly Creation: Deferred until "Next" click (user can review/edit first)
🍞 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.