francwa
de02bdea06
- Refactor memory system (episodic/STM/LTM with components) - Implement complete subtitle domain (scanner, matcher, placer) - Add YAML workflow infrastructure - Externalize knowledge base (patterns, release groups) - Add comprehensive testing suite - Create manual testing CLIs"
54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
"""Workflow — tracks the current in-progress agent task."""
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import logging
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from dataclasses import dataclass
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from datetime import datetime
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logger = logging.getLogger(__name__)
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@dataclass
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class Workflow:
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current: dict | None = None
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def start(self, workflow_type: str, target: dict) -> None:
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self.current = {
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"type": workflow_type,
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"target": target,
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"stage": "started",
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"started_at": datetime.now().isoformat(),
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}
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logger.info(f"Workflow: Started '{workflow_type}'")
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def update_stage(self, stage: str) -> None:
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if self.current:
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self.current["stage"] = stage
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logger.debug(f"Workflow: Stage -> {stage}")
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def end(self) -> None:
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if self.current:
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logger.info(f"Workflow: Ended '{self.current.get('type')}'")
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self.current = None
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def clear(self) -> None:
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self.current = None
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@classmethod
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def describe(cls) -> dict:
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return {
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"name": "Workflow",
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"tier": "stm",
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"access": "read-write",
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"description": (
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"Tracks the current in-progress multi-step task. "
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"Read to know what you are currently doing and what stage you are at. "
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"Write to start, advance, or end a workflow as you execute steps."
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),
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"fields": {
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"current": "Active workflow dict with keys: type, target, stage, started_at. None if idle.",
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},
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}
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def to_dict(self) -> dict | None:
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return self.current
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