Claude 877e0b6b47 Implement Phase 2: Recipe & Supplier wizard modals (JTBD-driven UX)
Following Jobs-To-Be-Done analysis, break down complex forms into multi-step wizards to reduce cognitive load for non-technical bakery owners.

**Core Infrastructure:**
- Add reusable WizardModal component with progress tracking, validation, and navigation
  - Multi-step progress bar with clickable previous steps
  - Per-step validation with clear error messaging
  - Back/Next/Complete navigation with loading states
  - Optional step skipping support
  - Responsive modal design (sm/md/lg/xl/2xl sizes)

**Recipe Wizard (4 steps):**
- Step 1 (Product): Name, category, finished product, cuisine type, difficulty, description
- Step 2 (Ingredients): Dynamic ingredient list with add/remove, quantities, units, optional flags
- Step 3 (Production): Times (prep/cook/rest), yield, batch sizes, temperature, humidity, special flags
- Step 4 (Review): Instructions, storage, nutritional info, allergens, final summary

**Supplier Wizard (3 steps):**
- Step 1 (Basic): Name, type, status, contact person, email, phone, tax ID, registration
- Step 2 (Delivery): Payment terms, lead time, minimum order, delivery schedule, address
- Step 3 (Review): Certifications, sustainability practices, notes, summary

**Benefits:**
- Reduces form overwhelm from 8 sections to 4 sequential steps (recipes) and 3 steps (suppliers)
- Clear progress indication and next actions
- Validation feedback per step instead of at end
- Summary review before final submission
- Matches mental model of "configure then review" workflow

Files:
- WizardModal: Reusable wizard infrastructure
- RecipeWizard: 4-step recipe creation (Product → Ingredients → Production → Review)
- SupplierWizard: 3-step supplier creation (Basic → Delivery → Review)

Related to Phase 1 (ConfigurationProgressWidget) for post-onboarding guidance.
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🍞 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

  1. Clone the repository:

    git clone <repository-url>
    cd bakery-ia
    
  2. Set up environment variables:

    cp .env.example .env
    # Edit .env with your specific configuration
    
  3. Run with Docker Compose:

    docker-compose up --build
    
  4. 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:

  1. Set up your clouding.io Kubernetes cluster
  2. Update image references to your container registry
  3. Configure production-specific values
  4. Deploy using the production kustomization:
    kubectl apply -k infrastructure/kubernetes/environments/production/
    

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Submit a pull request

📄 License

This project is licensed under the MIT License.

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