6a0e02ff95
When the frontend requests tenants with user_id='demo-user' in demo mode, the backend now correctly maps this to the actual demo owner ID from the current_user context (set by the gateway middleware). This fixes the issue where the tenant list API was returning empty results even though it returned 200 OK, because it was looking for a user with id='demo-user' which doesn't exist in the database. The actual user IDs are: - Professional: c1a2b3c4-d5e6-47a8-b9c0-d1e2f3a4b5c6 (María García López) - Enterprise: d2e3f4a5-b6c7-48d9-e0f1-a2b3c4d5e6f7 (Director) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
🍞 BakeWise - Multi-Service Architecture
Welcome to BakeWise, 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.