✨ Features Added:
- Task Management API with comprehensive filtering and statistics
- Workflow Management API with multi-agent orchestration
- CLI Agent Management API with health monitoring
- Extended response models with performance metrics
- Advanced error handling with standardized error codes
📊 API Coverage Completed:
- Tasks API: CRUD operations, filtering, pagination, statistics, cancellation
- Workflows API: Creation, execution, monitoring, template management
- CLI Agents API: Registration, health checks, predefined setups, SSH management
- Enhanced CLI agent models with performance analytics
🛠️ Technical Improvements:
- Comprehensive Pydantic models for all CLI agent operations
- Advanced filtering with type safety and validation
- Performance metrics integration across all endpoints
- Health monitoring with deep check capabilities
- Predefined agent configuration for quick setup
🌐 Developer Experience:
- Interactive API documentation with realistic examples
- Comprehensive error responses with troubleshooting guidance
- Best practices and use case documentation
- Professional-grade endpoint descriptions with detailed workflows
Phase 2 establishes enterprise-grade API documentation standards
across all major Hive components, providing developers with
comprehensive, interactive documentation for efficient integration.
🤖 Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
Major Features:
✅ JWT Bearer Token authentication system with secure token management
✅ API key generation and management with scoped permissions
✅ Complete user management (registration, login, logout, password change)
✅ Frontend authentication components and context integration
Backend Architecture Improvements:
✅ CORS configuration via environment variables (CORS_ORIGINS)
✅ Dependency injection pattern for unified coordinator
✅ Database schema fixes with UUID support and SQLAlchemy compliance
✅ Task persistence replaced in-memory storage with database-backed system
✅ Service separation following Single Responsibility Principle
✅ Fixed SQLAlchemy metadata column naming conflicts
Infrastructure & Testing:
✅ Comprehensive Jest unit testing and Playwright e2e testing infrastructure
✅ GitHub Actions CI/CD pipeline integration
✅ Enhanced API clients matching PROJECT_PLAN.md specifications
✅ Docker Swarm deployment with proper networking and service connectivity
Database & Security:
✅ UUID-based user models with proper validation
✅ Unified database schema with authentication tables
✅ Token blacklisting and refresh token management
✅ Secure password hashing with bcrypt
✅ API key scoping and permissions system
API Enhancements:
✅ Authentication endpoints (/api/auth/*)
✅ Task management with database persistence
✅ Enhanced monitoring and health check endpoints
✅ Comprehensive error handling and validation
Deployment:
✅ Successfully deployed to Docker Swarm at https://hive.home.deepblack.cloud✅ All services operational with proper networking
✅ Environment-based configuration support
🛠️ Technical Debt Resolved:
- Fixed global coordinator instances with proper dependency injection
- Replaced hardcoded CORS origins with environment variables
- Unified User model schema conflicts across authentication system
- Implemented database persistence for critical task storage
- Created comprehensive testing infrastructure
This release transforms Hive from a development prototype into a production-ready
distributed AI orchestration platform with enterprise-grade authentication,
proper architectural patterns, and robust deployment infrastructure.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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>
