81718a0952
- RecognizerRegistry.first_admitted() — deterministic first-registered selection - CognitiveTurnPipeline consults runtime registry when no recognizer explicitly passed - ChatRuntime gains _pending_recognizer_examples + record_recognition_example() - checkpoint_engine_state() derives and registers recognizer from accumulated examples - RuntimeConfig.recognition_grounded_graph gate (already existed) controls wiring - ADR-0149 decision record
46 lines
1.4 KiB
Python
46 lines
1.4 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 first_admitted(self) -> DerivedRecognizer | None:
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"""Return the first registered recognizer, or None if registry is empty."""
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if not self._registry:
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return None
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return next(iter(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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