9bbdcc96aa
* ci: re-trigger full-pytest * docs: ADR-0146 — L10 Shape B hybrid engine-state persistence * feat(W-008): Shape B engine-state persistence spike (ADR-0146) * fix(W-008): eval isolation + env-var path + empty-manifest guard - evals/run_cognition_eval.py: all ChatRuntime() calls pass no_load_state=True so parallel eval workers never touch engine_state/ checkpoints - engine_state/__init__.py: honour CORE_ENGINE_STATE_DIR env var (ADR-0146 spec) - engine_state/__init__.py: load_manifest() skips empty file instead of crashing (defensive against partial writes in concurrent contexts) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
"""RecognizerRegistry -- per-teaching-set recognizer store (ADR-0146).
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Holds DerivedRecognizer instances keyed by teaching_set_id. Wired into
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EngineStateStore for Shape B persistence. Empty registry is the valid
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initial state (no teaching examples yet).
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"""
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from __future__ import annotations
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from recognition.anti_unifier import DerivedRecognizer
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class RecognizerRegistry:
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def __init__(self) -> None:
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self._registry: dict[str, DerivedRecognizer] = {}
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def register(self, recognizer: DerivedRecognizer) -> None:
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self._registry[recognizer.teaching_set_id] = recognizer
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def get(self, teaching_set_id: str) -> DerivedRecognizer | None:
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return self._registry.get(teaching_set_id)
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def all(self) -> list[DerivedRecognizer]:
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return list(self._registry.values())
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def __len__(self) -> int:
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return len(self._registry)
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@classmethod
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def from_recognizers(
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cls,
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recognizers: list[DerivedRecognizer],
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) -> "RecognizerRegistry":
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reg = cls()
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for recognizer in recognizers:
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reg.register(recognizer)
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return reg
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__all__ = ["RecognizerRegistry"]
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