84d38842ab
Created comprehensive multilingual translation system for JTBD dashboard reasoning fields. Backend generates structured data, frontend translates using i18n in EN, ES, and EU (Euskara). Frontend Changes: 1. Created reasoning.json translation files (EN, ES, EU) - Purchase order reasoning types - Production batch reasoning types - Consequence translations - Severity levels - Error codes - All JTBD dashboard UI text 2. Created useReasoningTranslation hook - translatePOReasonng() - For purchase orders - translateBatchReasoning() - For production batches - translateConsequence() - For consequences - translateSeverity() - For severity levels - translateError() - For error codes - useReasoningFormatter() - Higher-level formatting Translation Examples: EN: "Low stock for Harinas del Norte. Stock runs out in 3 days." ES: "Stock bajo para Harinas del Norte. Se agota en 3 días." EU: "Harinas del Norte-rentzat stock baxua. 3 egunetan amaituko da." Documentation: - Created REASONING_I18N_AUDIT.md with full audit of hardcoded text - Identified all files needing updates - Documented strategy for backend error codes Next Steps: - Update dashboard components to use translations - Fix demo seed scripts - Fix backend services to return error codes
🍞 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.