2915ee9aa7
IMPLEMENTATION COMPLETE: Successfully integrated Google Gemini CLI as mixed agent type in Hive distributed AI platform. ## Phase 4 Achievements: ✅ Enhanced MCP tools with CLI agent support ✅ Added hive_register_cli_agent, hive_get_cli_agents tools ✅ Updated HiveClient interface for CLI agent management ✅ Mixed agent type coordination via MCP ✅ Comprehensive error handling and user feedback ## Key Features: - CLI agent registration with health checks - Mixed agent dashboard (🤖 Ollama + ⚡ CLI) - Predefined agent quick setup (walnut-gemini, ironwood-gemini) - SSH-based task execution with connection pooling - Complete backward compatibility ## Technical Stack: - MCP Tools: CLI agent management interface - HiveClient: Enhanced API client with CLI support - TypeScript: Full type safety for mixed agent operations - Error Handling: Comprehensive CLI connectivity validation ## Production Ready: ✅ 16 MCP tools with CLI agent coverage ✅ Mixed agent type task coordination ✅ Health monitoring and statistics collection ✅ Robust SSH execution with timeout handling ✅ Integration tested and validated Ready for hybrid AI orchestration: 5 Ollama + 2 CLI agents 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
31 lines
1.3 KiB
Python
31 lines
1.3 KiB
Python
from sqlalchemy import Column, Integer, String, DateTime, JSON
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from sqlalchemy.sql import func
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from ..core.database import Base
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class Agent(Base):
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__tablename__ = "agents"
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id = Column(String, primary_key=True, index=True)
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endpoint = Column(String, nullable=False)
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model = Column(String, nullable=False)
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specialty = Column(String, nullable=False)
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max_concurrent = Column(Integer, default=2)
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current_tasks = Column(Integer, default=0)
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agent_type = Column(String, default="ollama") # "ollama" or "cli"
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cli_config = Column(JSON, nullable=True) # CLI-specific configuration
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created_at = Column(DateTime(timezone=True), server_default=func.now())
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updated_at = Column(DateTime(timezone=True), onupdate=func.now())
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def to_dict(self):
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return {
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"id": self.id,
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"endpoint": self.endpoint,
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"model": self.model,
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"specialty": self.specialty,
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"max_concurrent": self.max_concurrent,
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"current_tasks": self.current_tasks,
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"agent_type": self.agent_type,
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"cli_config": self.cli_config,
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"created_at": self.created_at.isoformat() if self.created_at else None,
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"updated_at": self.updated_at.isoformat() if self.updated_at else None
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} |