Major architectural improvement to replace in-memory task storage with
database-backed persistence while maintaining backward compatibility.
Changes:
- Created Task SQLAlchemy model matching database schema
- Added Workflow and Execution SQLAlchemy models
- Created TaskService for database CRUD operations
- Updated UnifiedCoordinator to use database persistence
- Modified task APIs to leverage database storage
- Added task loading from database on coordinator initialization
- Implemented status change persistence during task execution
- Enhanced task cleanup with database support
- Added comprehensive task statistics from database
Benefits:
- Tasks persist across application restarts
- Better scalability and reliability
- Historical task data retention
- Comprehensive task filtering and querying
- Maintains in-memory cache for performance
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Major refactoring:
- Created UnifiedCoordinator that combines HiveCoordinator and DistributedCoordinator
- Eliminated code duplication and architectural redundancy
- Unified agent management, task orchestration, and workflow execution
- Single coordinator instance replaces two global coordinators
- Backward compatibility maintained through state aliases
Key features of UnifiedCoordinator:
✅ Combined agent types: Ollama + CLI agents with unified management
✅ Dual task modes: Simple tasks + complex distributed workflows
✅ Performance monitoring: Prometheus metrics + adaptive load balancing
✅ Background processes: Health monitoring + performance optimization
✅ Redis integration: Distributed caching and coordination (optional)
✅ Database integration: Agent loading + task persistence preparation
API updates:
- Updated all API endpoints to use unified coordinator
- Maintained interface compatibility for existing endpoints
- Fixed attribute references for unified agent model
- Simplified dependency injection pattern
Architecture benefits:
- Single point of coordination eliminates race conditions
- Reduced memory footprint (one coordinator vs two)
- Simplified initialization and lifecycle management
- Consistent feature set across all orchestration modes
- Better separation of concerns within single coordinator class
This resolves the critical architectural issue of redundant coordinators
while maintaining full backward compatibility and adding enhanced features.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Parameterize CORS_ORIGINS in docker-compose.swarm.yml
- Add .env.example with configuration options
- Create comprehensive LOCAL_DEVELOPMENT.md guide
- Update README.md with environment variable documentation
- Provide alternatives for local development without production domain
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
This comprehensive implementation includes:
- FastAPI backend with MCP server integration
- React/TypeScript frontend with Vite
- PostgreSQL database with Redis caching
- Grafana/Prometheus monitoring stack
- Docker Compose orchestration
- Full MCP protocol support for Claude Code integration
Features:
- Agent discovery and management across network
- Visual workflow editor and execution engine
- Real-time task coordination and monitoring
- Multi-model support with specialized agents
- Distributed development task allocation
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
