Benjamin Admin
3e3644f83d
Generalise "Embedding finds, Claude decides" into the shared Pruefer-Library: - router.route_and_check dispatches control -> sensor_classification -> Checker. - build_spec reads sensor_classification (CONTENT/LLM -> judge=haiku, the validated sufficiency tier; the Qwen-first cascade is disproven for sufficiency). - LLMChecker gains a Haiku-direct tier (reuses the validated deep_check prompt). - Cookie Layer-3 now routes through route_and_check instead of bespoke code, so cookie is the first real router consumer -- proves the architecture end-to-end. Reproduces the validated result via the shared path: FN 159->14, recall 0.13->0.92, precision 0.89 (vs bespoke 12/0.93/0.90 -- within Haiku noise). Tests: 10/10 (router dispatch + build_spec + haiku tier + cookie rewire). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
69 lines
2.5 KiB
Python
69 lines
2.5 KiB
Python
"""Prüfer-Router — method-agnostischer Dispatch.
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control → sensor_classification (verification_method + decision_method) → Checker.
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Ein neues Modul liefert nur ControlSpecs; der Router wählt den Prüfer. Damit wird
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der „Embedding findet, Claude entscheidet"-Pfad EIN gemeinsamer CONTENT/LLM-Prüfer
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statt Cookie-Sonderlogik. Nicht-gebaute Prüfer (PLAYWRIGHT/AUDIT/SCANNER/REGEX-
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FIELD) → present=None (fail-safe: Aufrufer behält sein deterministisches Ergebnis).
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"""
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from __future__ import annotations
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from typing import Any, Optional
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from .base import CheckResult, ControlSpec, DecisionMethod, DocContext
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from .embedding_checker import EmbeddingChecker
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from .llm_checker import LLMChecker
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from .reference_checker import ReferenceChecker
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_LLM = LLMChecker()
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_EMB = EmbeddingChecker()
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_REF = ReferenceChecker()
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# decision_method → Checker. Fehlende Mechanismen bewusst None (noch nicht gebaut).
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_BY_DECISION: dict[str, Any] = {
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DecisionMethod.LLM: _LLM,
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DecisionMethod.EMBEDDING: _EMB,
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DecisionMethod.LINK_RESOLVER: _REF,
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}
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async def route_and_check(ctrl: ControlSpec, doc: DocContext) -> CheckResult:
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checker = _BY_DECISION.get((ctrl.decision_method or "").upper())
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if checker is None:
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return CheckResult(present=None,
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source=f"no_checker:{ctrl.decision_method}")
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return await checker.check(ctrl, doc)
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def build_spec(
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control_id: str,
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sensor_classification: Optional[dict[str, Any]],
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*,
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label: str = "",
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criteria: Optional[list] = None,
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question: str = "",
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patterns: Optional[list[str]] = None,
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embed_threshold: Optional[float] = None,
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) -> ControlSpec:
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"""Baut ein ControlSpec aus der GESPEICHERTEN sensor_classification
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(canonical_controls.generation_metadata.sensor_classification) + den
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Control-Kriterien. CONTENT/LLM → judge='haiku' (validierter Sufficiency-
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Judge; Default für Sufficiency lt. Entscheidung 2026-06-22)."""
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sc = sensor_classification or {}
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vm = (sc.get("verification_method") or "").upper()
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dm = (sc.get("decision_method") or "").upper()
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extra: dict[str, Any] = {}
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if vm == "CONTENT" and dm == "LLM":
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extra["judge"] = "haiku"
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return ControlSpec(
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control_id=control_id,
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verification_method=vm,
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decision_method=dm,
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label=label,
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paraphrases=[str(c) for c in (criteria or []) if c],
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question=question,
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patterns=patterns or [],
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embed_threshold=embed_threshold,
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extra=extra,
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)
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