✨ Features:
- Comprehensive Pydantic response models with examples
- Enhanced FastAPI configuration with rich OpenAPI metadata
- Centralized error handling with standardized error codes
- Professional Swagger UI styling and branding
- Health check endpoints with detailed component status
- Type-safe request/response models for all endpoints
📊 Coverage:
- Agent Management API fully documented
- Standardized error responses across all endpoints
- Interactive API documentation with try-it-now functionality
- Custom OpenAPI schema with authentication schemes
🛠️ Technical Improvements:
- Created app/models/responses.py with comprehensive models
- Added app/core/error_handlers.py for centralized error handling
- Enhanced app/api/agents.py with detailed documentation
- Custom documentation configuration in app/docs_config.py
- Global exception handlers for consistent error responses
🌐 Access Points:
- Swagger UI: /docs
- ReDoc: /redoc
- OpenAPI JSON: /openapi.json
This establishes professional-grade API documentation that matches
Hive's technical excellence and provides developers with comprehensive,
interactive documentation for efficient integration.
🤖 Generated with Claude 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>
Major Features Added:
- Fix Socket.IO connectivity by updating Dockerfile to use socket_app
- Resolve distributed workflows API to return arrays instead of errors
- Expand agent coverage from 3 to 7 agents (added OAK and ROSEWOOD)
- Create comprehensive systemd service for MCP server with auto-discovery
- Add daemon mode with periodic agent discovery every 5 minutes
- Implement comprehensive test suite with 100% pass rate
Infrastructure Improvements:
- Enhanced database connection handling with retry logic
- Improved agent registration with persistent storage
- Added proper error handling for distributed workflows endpoint
- Created management scripts for service lifecycle operations
Agent Cluster Expansion:
- ACACIA: deepseek-r1:7b (kernel_dev)
- WALNUT: starcoder2:15b (pytorch_dev)
- IRONWOOD: deepseek-coder-v2 (profiler)
- OAK: codellama:latest (docs_writer)
- OAK-TESTER: deepseek-r1:latest (tester)
- ROSEWOOD: deepseek-coder-v2:latest (kernel_dev)
- ROSEWOOD-VISION: llama3.2-vision:11b (tester)
System Status: All 7 agents healthy, Socket.IO operational, MCP server fully functional
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Changes:
- Updated default endpoints to use https://hive.home.deepblack.cloud
- Added support for HIVE_TIMEOUT environment variable
- Created .env.example with multiple deployment configurations
- Updated Claude Desktop configuration for production/development
- Updated README with comprehensive configuration guide
Production endpoints:
- API: https://hive.home.deepblack.cloud
- WebSocket: wss://hive.home.deepblack.cloud
Development fallback to localhost still available via env vars.
🤖 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>
