f74b8d5402
Completed the migration to structured reasoning_data for multilingual
dashboard support. Removed hardcoded TEXT fields (reasoning, consequence)
and updated all related code to use JSONB reasoning_data.
Changes:
1. Models Updated (removed TEXT fields):
- PurchaseOrder: Removed reasoning, consequence TEXT columns
- ProductionBatch: Removed reasoning TEXT column
- Both now use only reasoning_data (JSONB/JSON)
2. Dashboard Service Updated:
- Changed to return reasoning_data instead of TEXT fields
- Creates default reasoning_data if missing
- PO actions: reasoning_data with type and parameters
- Production timeline: reasoning_data for each batch
3. Unified Schemas Updated (no separate migration):
- services/procurement/migrations/001_unified_initial_schema.py
- services/production/migrations/001_unified_initial_schema.py
- Removed reasoning/consequence columns from table definitions
- Updated comments to reflect i18n approach
Database Schema:
- purchase_orders: Only reasoning_data (JSONB)
- production_batches: Only reasoning_data (JSON)
Backend now generates:
{
"type": "low_stock_detection",
"parameters": {
"supplier_name": "Harinas del Norte",
"days_until_stockout": 3,
...
},
"consequence": {
"type": "stockout_risk",
"severity": "high"
}
}
Next Steps:
- Frontend: Create i18n translation keys
- Frontend: Update components to translate reasoning_data
- Test multilingual support (ES, EN, CA)
🍞 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.