- Create dedicated service classes for separated concerns:
* AgentService: Agent management and health monitoring
* WorkflowService: Workflow parsing and execution tracking
* PerformanceService: Metrics and load balancing
* BackgroundService: Background processes and cleanup
* TaskService: Database persistence (already existed)
- Refactor UnifiedCoordinator into UnifiedCoordinatorRefactored
* Clean separation of responsibilities
* Improved maintainability and testability
* Dependency injection pattern for services
* Clear service boundaries and interfaces
- Maintain backward compatibility through re-exports
- Update main.py to use refactored coordinator
🚀 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Frontend Enhancements:
- Complete React TypeScript frontend with modern UI components
- Distributed workflows management interface with real-time updates
- Socket.IO integration for live agent status monitoring
- Agent management dashboard with cluster visualization
- Project management interface with metrics and task tracking
- Responsive design with proper error handling and loading states
Backend Infrastructure:
- Distributed coordinator for multi-agent workflow orchestration
- Cluster management API with comprehensive agent operations
- Enhanced database models for agents and projects
- Project service for filesystem-based project discovery
- Performance monitoring and metrics collection
- Comprehensive API documentation and error handling
Documentation:
- Complete distributed development guide (README_DISTRIBUTED.md)
- Comprehensive development report with architecture insights
- System configuration templates and deployment guides
The platform now provides a complete web interface for managing the distributed AI cluster
with real-time monitoring, workflow orchestration, and agent coordination capabilities.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
