- Add agent core modules (agent_core, factory, registry, skill_loader) - Add runtime system for agent execution management - Add REST API for agents, workspaces, and runtime control - Add process supervisor for agent lifecycle management - Add workspace template system with agent profiles - Add frontend RuntimeView and runtime API integration - Add per-agent skill workspaces for smoke_fullstack run - Refactor skill system with active/installed separation Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
27 lines
776 B
Python
27 lines
776 B
Python
from __future__ import annotations
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from dataclasses import dataclass, field
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from datetime import datetime, UTC
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from typing import Any, Dict
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@dataclass
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class AgentRuntimeState:
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agent_id: str
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status: str = "idle"
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last_session: str | None = None
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last_updated: datetime = field(default_factory=lambda: datetime.now(UTC))
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def update(self, status: str, session_key: str | None = None) -> None:
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self.status = status
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self.last_session = session_key
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self.last_updated = datetime.now(UTC)
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def to_dict(self) -> Dict[str, Any]:
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return {
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"agent_id": self.agent_id,
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"status": self.status,
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"last_session": self.last_session,
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"last_updated": self.last_updated.isoformat(),
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}
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