Urtzi Alfaro fd0a96e254 Fix remaining nested session issues in training pipeline
Issues Fixed:

4️⃣ data_processor.py (Line 230-232):
- Second update_log_progress call without commit after data preparation
- Added commit() after completion update to prevent deadlock
- Added debug logging for visibility

5️⃣ prophet_manager.py _store_model (Line 750):
- Created TRIPLE nested session (training_service → trainer → lock → _store_model)
- Refactored _store_model to accept optional session parameter
- Uses parent session from lock context instead of creating new one
- Updated call site to pass db_session parameter

Complete Session Hierarchy After All Fixes:
training_service.py (session)
  └─ commit() ← FIX #2 (e585e9f)
  └─ trainer.py (new session)  OK
      └─ data_processor.py (new session)
          └─ commit() after first update ← FIX #3 (b2de56e)
          └─ commit() after second update ← FIX #4 (THIS)
      └─ prophet_manager.train_bakery_model (uses parent or new session) ← FIX #1 (caff497)
          └─ lock.acquire(session)
              └─ _store_model(session=parent) ← FIX #5 (THIS)
                  └─ NO NESTED SESSION 

All nested session deadlocks in training path are now resolved.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-05 16:41:53 +01:00
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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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