fix(agents): Impressum+Cookie delegieren MC-Laden ans Main Tool — Scope-Filter + Maßnahmen
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Regression: Der v3-Agent-Pfad baute eine parallele MC-Pipeline (_load_impressum_mcs / _load_cookie_mcs, Roh-SELECT) und lief damit an allen Schutzmechanismen der Engine vorbei → GOV/Branchen-MCs als HIGH bei OEM/Zulieferer, fremde MCs (Bestellbestätigung), und action=check_question (Fragen statt Maßnahmen im Frontend). - Agent delegiert MC-Laden an rag_document_checker._load_controls (P72-Scope, check_type='text', fits_doc_type/scope_requires). - Subtraktives Sektor-Gate (SECTOR_PREFIXES) + Themen-Gate am Agent-Rand. - action = konkrete Maßnahme (Imperativ) statt check_question. - rag_document_checker: from __future__ import annotations (3.9-Import). - mcs: Name-Pattern erkennt "Aktiengesellschaft" (OEM-Impressums). - Tote GT-/Semantic-/Routes-Tests wiederbelebt (v3-Mismatch + agent.cascade-Patch-Target). Alle 72 Specialist-Tests grün. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
@@ -14,6 +14,11 @@ Flow:
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→ Returns structured results compatible with CheckItem format
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"""
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# Lazy annotations: dieses Modul nutzt PEP-604-Hints (z.B. `set[str] | None`)
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# und muss auch auf Python 3.9 importierbar bleiben (lokale Tests / safe-
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# import in compliance.api). Keine Pydantic-Modelle hier — daher unkritisch.
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from __future__ import annotations
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import logging
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import os
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import re
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@@ -44,6 +44,19 @@ _SEV_TO_ENUM = {
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}
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def _build_measure(label: str, norm: str) -> str:
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"""Maßnahme (Imperativ) statt Pruef-Frage als action. Das Tool
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definiert Maßnahmen im Frontend — es stellt keine Fragen."""
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base = (label or "").strip().rstrip(".")
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if not base:
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return ("Cookie-Angabe ergänzen und gegen die gesetzlichen "
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"Vorgaben prüfen.")
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msg = f"Cookie-Angabe ergänzen: {base}."
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if norm:
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msg += f" Rechtsgrundlage: {norm}."
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return msg
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class CookiePolicyAgent(BaseSpecialistAgent):
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agent_id = "cookie_policy"
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agent_version = "3.0"
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@@ -77,6 +90,11 @@ class CookiePolicyAgent(BaseSpecialistAgent):
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f"{telemetry.get('layer_0_field_hits', 0)} Pattern-Boosts · "
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f"{telemetry.get('layer_0_boost_overrides', 0)} Boost-Overrides"
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)
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if telemetry.get("sector_dropped"):
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notes_parts.append(
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f"Scope-Filter: {telemetry['sector_dropped']} "
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"Branchen-MCs entfernt"
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)
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seen: set[str] = set()
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for r in results:
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@@ -96,6 +114,9 @@ class CookiePolicyAgent(BaseSpecialistAgent):
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if passed:
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continue
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label = r.get("label") or r.get("hint") or ""
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norm_str = str(r.get("regulation") or "")
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if r.get("article"):
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norm_str = (norm_str + f" Art. {r.get('article')}").strip()
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findings.append(Finding(
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check_id=f"DBMC-{mc_id}",
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agent=self.agent_id,
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@@ -104,12 +125,9 @@ class CookiePolicyAgent(BaseSpecialistAgent):
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severity=sev,
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severity_reason="db_mc_failed",
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title=str(label)[:200] or f"DB-MC {mc_id} nicht erfüllt",
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norm=str(r.get("regulation") or "") +
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(f" Art. {r.get('article')}"
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if r.get("article") else ""),
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norm=norm_str,
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evidence="",
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action=str(r.get("hint") or "")[:400]
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or "Bitte gegen die Cookie-Pflichten prüfen.",
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action=_build_measure(str(label), norm_str)[:400],
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confidence=0.9,
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sources=[EvidenceSource(
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source_type=SourceType.MC,
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+67
-49
@@ -1,7 +1,10 @@
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"""Cookie-Policy v3-Pipeline — analog zu impressum/v3_engine.py.
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Lädt 381 Cookie-MCs aus compliance.doc_check_controls (doc_type='cookie'),
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ruft den deterministischen Keyword-Check + Embedding-Match + Boost-Override.
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MC-Laden DELEGIERT an die Main-Tool-Engine (rag_document_checker._load_controls,
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doc_type='cookie'): eine Quelle der Wahrheit inkl. P72-Scope, check_type='text'
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und fits_doc_type/scope_requires. KEINE parallele Roh-Query mehr. Danach
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deterministischer Keyword-Check + Embedding-Match + Boost-Override.
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Zusaetzlich ein subtraktives Sektor-Gate (Branchen-Prefix) am Agent-Rand.
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"""
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from __future__ import annotations
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@@ -13,9 +16,17 @@ from .regex_boost import boost_matches_db_mc, compute_regex_boosts
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logger = logging.getLogger(__name__)
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# Branchen-Prefix -> erwarteter Scope-Token (reuse aus dem Mail-V2-Filter).
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try:
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from compliance.services.mail_render_v2._scope_filter import (
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SECTOR_PREFIXES,
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)
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except Exception: # pragma: no cover
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SECTOR_PREFIXES = {}
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async def run_v3_pipeline(
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text: str, business_scope: set[str],
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text: str, business_scope: set[str], db_url: str = "",
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) -> tuple[list[dict[str, Any]], dict[str, Any]]:
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if not text or len(text) < 100:
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return [], {"reason": "text too short"}
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@@ -24,8 +35,16 @@ async def run_v3_pipeline(
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boosts = compute_regex_boosts(text)
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boost_field_ids = sorted(boosts)
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# Layer 1: alle 381 Cookie-MCs aus DB laden
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controls = await _load_cookie_mcs()
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# Layer 1: MC-Laden DELEGIERT an die Main-Tool-Engine (Scope-Schutz
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# inklusive). Danach subtraktives Sektor-Gate am Agent-Rand.
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try:
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from compliance.services.rag_document_checker import _load_controls
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controls = await _load_controls("cookie", db_url, 0, business_scope)
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except Exception as e:
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logger.warning("cookie v3 load via main-tool engine failed: %s", e)
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controls = []
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_normalize_criteria(controls)
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controls, sector_dropped = _filter_sector(controls, business_scope)
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results: list[dict[str, Any]] = []
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if controls:
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try:
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@@ -91,51 +110,50 @@ async def run_v3_pipeline(
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"layer_1_pass": layer_1_pass,
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"layer_0_boost_overrides": boost_overrides,
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"total_mcs": len(results),
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"sector_dropped": sector_dropped,
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}
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return results, telemetry
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async def _load_cookie_mcs() -> list[dict]:
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"""Lädt alle 381 Cookie-MCs aus compliance.doc_check_controls."""
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try:
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import json
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from classroom_engine.database import SessionLocal
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from sqlalchemy import text as _sa_text
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db = SessionLocal()
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try:
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rows = db.execute(_sa_text(
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"SELECT id, control_id, control_uuid, title, regulation, "
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" article, check_question, pass_criteria, "
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" fail_criteria, severity "
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"FROM compliance.doc_check_controls "
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"WHERE doc_type='cookie' "
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"ORDER BY severity DESC, title"
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)).fetchall()
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finally:
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db.close()
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out = []
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for r in rows:
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def _parse(v):
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if isinstance(v, list): return v
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if isinstance(v, str):
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try:
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j = json.loads(v)
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return j if isinstance(j, list) else [v]
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except Exception: return [v]
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return []
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out.append({
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"id": str(r[0]),
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"control_id": r[1],
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"control_uuid": str(r[2]) if r[2] else "",
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"title": r[3] or "",
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"regulation": r[4] or "",
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"article": r[5] or "",
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"check_question": r[6] or "",
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"pass_criteria": _parse(r[7]),
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"fail_criteria": _parse(r[8]),
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"severity": r[9] or "MEDIUM",
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})
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return out
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except Exception as e:
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logger.warning("_load_cookie_mcs failed: %s", e)
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return []
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def _normalize_criteria(controls: list[dict[str, Any]]) -> None:
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"""asyncpg liefert JSONB-Spalten als Roh-String → zu Listen parsen."""
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import json
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for c in controls:
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for key in ("pass_criteria", "fail_criteria"):
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v = c.get(key)
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if isinstance(v, list):
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continue
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if isinstance(v, str):
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try:
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parsed = json.loads(v)
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c[key] = parsed if isinstance(parsed, list) else [v]
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except Exception:
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c[key] = [v] if v else []
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else:
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c[key] = []
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def _filter_sector(
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controls: list[dict[str, Any]],
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business_scope: set[str],
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) -> tuple[list[dict[str, Any]], int]:
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"""Subtraktives Sektor-Gate: MCs deren control_id-Prefix eine Branche
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bezeichnet (FIN/GOV/MED/INS/EDU/LEG/REL/POL), die NICHT im business_scope
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liegt, werden verworfen — sonst tauchen z.B. GOV-MCs bei einem
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OEM/Zulieferer als Finding auf. Reuse der SECTOR_PREFIXES."""
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scope_lc = {s.lower() for s in (business_scope or set())}
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kept: list[dict[str, Any]] = []
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dropped = 0
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for c in controls:
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cid = c.get("control_id") or ""
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prefix = cid.split("-")[0].upper() if "-" in cid else ""
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required = SECTOR_PREFIXES.get(prefix)
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if required and not (scope_lc & required):
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dropped += 1
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continue
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kept.append(c)
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if dropped:
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logger.info("cookie v3 sector-filter: -%d Branchen-MCs", dropped)
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return kept, dropped
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@@ -54,6 +54,24 @@ _SEV_TO_ENUM = {
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}
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def _build_measure(label: str, norm: str) -> str:
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"""Formuliert aus einer fehlenden Pflichtangabe eine konkrete Maßnahme
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(Imperativ) statt die Pruef-Frage auszugeben.
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Das Tool definiert Maßnahmen im Frontend — es stellt keine Fragen. Der
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check_question-Text ('Ist X angegeben?') wird daher NICHT mehr als
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action durchgereicht (sonst zeigt die Finding-Card eine Frage unter
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'Pflicht-Maßnahme')."""
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base = (label or "").strip().rstrip(".")
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if not base:
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return ("Pflichtangabe ergänzen und gegen die gesetzlichen "
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"Vorgaben prüfen.")
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msg = f"Pflichtangabe ergänzen: {base}."
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if norm:
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msg += f" Rechtsgrundlage: {norm}."
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return msg
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class ImpressumAgent(BaseSpecialistAgent):
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agent_id = "impressum"
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agent_version = "3.0"
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@@ -96,6 +114,13 @@ class ImpressumAgent(BaseSpecialistAgent):
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f"{telemetry.get('layer_0_field_hits', 0)} Pattern-Boosts · "
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f"{telemetry.get('layer_0_boost_overrides', 0)} Boost-Overrides"
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)
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sec_drop = telemetry.get("sector_dropped", 0)
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off_drop = telemetry.get("offtopic_dropped", 0)
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if sec_drop or off_drop:
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notes_parts.append(
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f"Scope-Filter: {sec_drop} Branchen-MCs + "
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f"{off_drop} themenfremde MCs entfernt"
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)
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# DB-MCs → Findings + Coverage
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seen_db_mcs: set[str] = set()
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@@ -116,6 +141,9 @@ class ImpressumAgent(BaseSpecialistAgent):
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if passed:
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continue
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label = r.get("label") or r.get("hint") or ""
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norm_str = str(r.get("regulation") or "")
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if r.get("article"):
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norm_str = (norm_str + f" Art. {r.get('article')}").strip()
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findings.append(Finding(
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check_id=f"DBMC-{mc_id}",
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agent=self.agent_id,
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@@ -124,12 +152,9 @@ class ImpressumAgent(BaseSpecialistAgent):
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severity=sev,
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severity_reason="db_mc_failed",
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title=str(label)[:200] or f"DB-MC {mc_id} nicht erfüllt",
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norm=str(r.get("regulation") or "") +
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(f" Art. {r.get('article')}"
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if r.get("article") else ""),
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norm=norm_str,
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evidence="",
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action=str(r.get("hint") or "")[:400]
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or "Bitte gegen die Pflichtangaben prüfen.",
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action=_build_measure(str(label), norm_str)[:400],
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confidence=0.9,
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sources=[EvidenceSource(
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source_type=SourceType.MC,
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@@ -43,7 +43,8 @@ MCS: tuple[MC, ...] = (
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# Label-free fallback: Firma (Rechtsform) + Adresse
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re.compile(
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r"\b[A-ZÄÖÜ][\w\-\& ]{1,80}?\s+"
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r"(?:GmbH|AG|UG|KG|SE|GbR|OHG|Limited|Ltd|LLC)\s*"
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r"(?:Aktiengesellschaft|GmbH|AG|UG|KG|SE|GbR|OHG|"
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r"Limited|Ltd|LLC)\s*"
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r"[\s\S]{0,400}?"
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r"\b\d{5}\s+[A-ZÄÖÜ]",
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re.IGNORECASE,
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@@ -150,3 +150,44 @@ def boost_matches_db_mc(
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if best is None or match_count > best[0]:
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best = (match_count, field_id)
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return best[1] if best else None
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def criteria_on_topic(
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pass_criteria: list | None,
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fail_criteria: list | None = None,
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min_hits: int = 2,
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) -> bool:
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"""Deterministischer Themen-Gate: gehoert eine DB-MC ueberhaupt ins
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Impressum-Themenfeld?
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Prueft ob die kombinierten pass/fail_criteria mindestens `min_hits`
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UNTERSCHIEDLICHE Schluesselwoerter aus IRGENDEINEM der 12 Impressum-
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Felder (BOOST_KEYWORDS) enthalten. Fremd-MCs (z.B. 'Bestellbestaetigung',
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'behoerdliche Anzeige'), die faelschlich unter doc_type='impressum'
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getaggt sind, haben keinen Themen-Ueberlapp und werden so aussortiert
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— unabhaengig von DB-Sidecar/Klassifikation.
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Konservativ in beide Richtungen:
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- ein einzelner inzidenteller Treffer (z.B. 'E-Mail' in einer
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Bestellbestaetigung) reicht NICHT -> >=2 verschiedene Stichwoerter.
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- leere Kriterien -> on-topic behalten (lieber ein FP als eine echte
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Pflichtangabe verlieren).
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"""
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crit_parts: list[str] = []
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for c in (pass_criteria or []):
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if c:
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crit_parts.append(str(c).lower())
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for c in (fail_criteria or []):
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if c:
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crit_parts.append(str(c).lower())
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if not crit_parts:
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return True
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crit_text = " ".join(crit_parts)
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hits: set[str] = set()
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for kws in BOOST_KEYWORDS.values():
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for kw in kws:
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if kw in crit_text:
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hits.add(kw)
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if len(hits) >= min_hits:
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return True
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return False
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@@ -1,17 +1,20 @@
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"""Sprint-1.12 v3-Engine: läuft die volle 4-Layer-Pipeline auf einem
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Impressum-Text:
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"""v3-Engine: läuft die 4-Layer-Pipeline auf einem Impressum-Text.
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|
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Layer 0 — Regex-Boost (meine 12 Patterns aus mcs.py)
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Layer 1 — Keyword-Match aus doc_check_controls.pass_criteria
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(75 MCs in DB für Impressum)
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Layer 2 — BGE-M3 Embedding-Match als Fallback (im
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rag_document_checker integriert)
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Layer 3 — Semantic-Validator (LLM) wenn auch Embedding nicht half
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(im Agent angefasst, hier nur Ergebnisse durchgereicht)
|
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Layer 0 — Regex-Boost (die 12 deterministischen Agent-Patterns)
|
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Layer 1 — MC-Laden + Keyword-Match. Das LADEN delegiert an die
|
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Main-Tool-Engine (rag_document_checker._load_controls):
|
||||
eine Quelle der Wahrheit inkl. P72-Scope, check_type='text'
|
||||
und fits_doc_type/scope_requires aus dem Sidecar. KEINE
|
||||
parallele Roh-Query mehr.
|
||||
Layer 2 — BGE-M3 Embedding-Match (mc_embedding_matcher, shared)
|
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Layer 3 — Semantic-Validator (LLM) im Agent (hier nur durchgereicht)
|
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|
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Output: Liste Result-Dicts kompatibel mit rag_document_checker (passed,
|
||||
severity, control_id, regulation, ...). Der Agent konvertiert sie dann
|
||||
zu Finding-Objekten.
|
||||
Zusätzlich am Agent-Rand: subtraktives Sektor-/Themen-Gate
|
||||
(_filter_controls) — das Sektor-Gate (Branchen-Prefix) macht die Engine
|
||||
nicht, es lebt sonst im Mail-V2-Report.
|
||||
|
||||
Output: Liste Result-Dicts kompatibel mit rag_document_checker. Der Agent
|
||||
konvertiert sie zu Finding-Objekten.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
@@ -19,10 +22,25 @@ from __future__ import annotations
|
||||
import logging
|
||||
from typing import Any
|
||||
|
||||
from .regex_boost import boost_matches_db_mc, compute_regex_boosts
|
||||
from .regex_boost import (
|
||||
boost_matches_db_mc,
|
||||
compute_regex_boosts,
|
||||
criteria_on_topic,
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Branchen-Prefix -> erwarteter Scope-Token. Reuse aus dem Mail-V2-
|
||||
# Scope-Filter, damit Agent-Pfad und Report-Pfad dieselbe Quelle nutzen
|
||||
# (keine divergente Zweit-Logik). Import defensiv: faellt der Mail-Pfad
|
||||
# weg, bleibt der Agent lauffaehig (ohne Sektor-Gate).
|
||||
try:
|
||||
from compliance.services.mail_render_v2._scope_filter import (
|
||||
SECTOR_PREFIXES,
|
||||
)
|
||||
except Exception: # pragma: no cover - defensiver Fallback
|
||||
SECTOR_PREFIXES = {}
|
||||
|
||||
|
||||
async def run_v3_pipeline(
|
||||
text: str,
|
||||
@@ -43,11 +61,22 @@ async def run_v3_pipeline(
|
||||
logger.info("v3 Layer-0 boosts: %d hits — %s",
|
||||
len(boost_field_ids), boost_field_ids)
|
||||
|
||||
# Layer 1: lade ALLE 75 doc_check_controls für 'impressum' direkt
|
||||
# aus DB. Sidecar-Klassifizierung wird bewusst übersprungen — der
|
||||
# Agent soll auf der vollen MC-Liste arbeiten (Layer 3 LLM-Validator
|
||||
# demoted Pattern-Misses zu LOW, sodass Breitenwirkung kein Risiko ist).
|
||||
controls = await _load_impressum_mcs()
|
||||
# Layer 1: MC-Laden DELEGIERT an die Main-Tool-Engine. Damit erbt der
|
||||
# Agent automatisch deren Scope-Schutz (P72 canonical-scope,
|
||||
# check_type='text', fits_doc_type/scope_requires) — genau die Filter,
|
||||
# an denen die alte parallele Roh-Query vorbeilief.
|
||||
try:
|
||||
from compliance.services.rag_document_checker import _load_controls
|
||||
controls = await _load_controls(
|
||||
"impressum", db_url, 0, business_scope,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning("v3 load via main-tool engine failed: %s", e)
|
||||
controls = []
|
||||
_normalize_criteria(controls)
|
||||
# Agent-Rand-Backstop (DB-unabhaengig): Sektor-Gate (Branchen-Prefix,
|
||||
# macht die Engine nicht) + Themen-Gate (falls der Sidecar leer ist).
|
||||
controls, drop_stats = _filter_controls(controls, business_scope)
|
||||
results: list[dict[str, Any]] = []
|
||||
if controls:
|
||||
try:
|
||||
@@ -122,55 +151,73 @@ async def run_v3_pipeline(
|
||||
"layer_1_fail": layer_1_fail,
|
||||
"layer_0_boost_overrides": boost_overrides,
|
||||
"total_mcs": len(results),
|
||||
"sector_dropped": drop_stats.get("sector_dropped", 0),
|
||||
"offtopic_dropped": drop_stats.get("offtopic_dropped", 0),
|
||||
}
|
||||
logger.info("v3 telemetry: %s", telemetry)
|
||||
return results, telemetry
|
||||
|
||||
|
||||
async def _load_impressum_mcs() -> list[dict]:
|
||||
"""Lädt alle Impressum-MCs aus compliance.doc_check_controls — ohne
|
||||
Sidecar-Filter. v3_engine nimmt die volle Breite."""
|
||||
try:
|
||||
import json
|
||||
from classroom_engine.database import SessionLocal
|
||||
from sqlalchemy import text as _sa_text
|
||||
db = SessionLocal()
|
||||
try:
|
||||
rows = db.execute(_sa_text(
|
||||
"SELECT id, control_id, control_uuid, title, regulation, "
|
||||
" article, check_question, pass_criteria, "
|
||||
" fail_criteria, severity "
|
||||
"FROM compliance.doc_check_controls "
|
||||
"WHERE doc_type='impressum' "
|
||||
"ORDER BY severity DESC, title"
|
||||
)).fetchall()
|
||||
finally:
|
||||
db.close()
|
||||
out: list[dict] = []
|
||||
for r in rows:
|
||||
def _parse(v):
|
||||
if isinstance(v, list):
|
||||
return v
|
||||
if isinstance(v, str):
|
||||
try:
|
||||
j = json.loads(v)
|
||||
return j if isinstance(j, list) else [v]
|
||||
except Exception:
|
||||
return [v]
|
||||
return []
|
||||
out.append({
|
||||
"id": str(r[0]),
|
||||
"control_id": r[1],
|
||||
"control_uuid": str(r[2]) if r[2] else "",
|
||||
"title": r[3] or "",
|
||||
"regulation": r[4] or "",
|
||||
"article": r[5] or "",
|
||||
"check_question": r[6] or "",
|
||||
"pass_criteria": _parse(r[7]),
|
||||
"fail_criteria": _parse(r[8]),
|
||||
"severity": r[9] or "MEDIUM",
|
||||
})
|
||||
return out
|
||||
except Exception as e:
|
||||
logger.warning("_load_impressum_mcs failed: %s", e)
|
||||
return []
|
||||
def _filter_controls(
|
||||
controls: list[dict[str, Any]],
|
||||
business_scope: set[str],
|
||||
) -> tuple[list[dict[str, Any]], dict[str, int]]:
|
||||
"""Subtraktiver Scope-Filter VOR der Bewertung.
|
||||
|
||||
1. Sektor-Gate — MCs deren control_id-Prefix eine Branche bezeichnet
|
||||
(FIN/GOV/MED/INS/EDU/LEG/REL/POL), die NICHT im business_scope
|
||||
liegt, werden verworfen. Fuer einen OEM/Zulieferer/Maschinenbauer
|
||||
(kein Behoerden-/Finanz-/Medizin-Scope) fallen GOV/FIN/MED-MCs so
|
||||
heraus — derselbe Mechanismus wie im Mail-V2-Report.
|
||||
2. Themen-Gate — MCs ohne Impressum-Themenueberlapp werden verworfen
|
||||
(faengt fremd-getaggte MCs wie 'Bestellbestaetigung').
|
||||
|
||||
Rein subtraktiv: entfernt nur falsch-positive Kandidaten, erzeugt nie
|
||||
neue Findings.
|
||||
"""
|
||||
scope_lc = {s.lower() for s in (business_scope or set())}
|
||||
kept: list[dict[str, Any]] = []
|
||||
sector_dropped = 0
|
||||
offtopic_dropped = 0
|
||||
for c in controls:
|
||||
cid = c.get("control_id") or ""
|
||||
prefix = cid.split("-")[0].upper() if "-" in cid else ""
|
||||
required = SECTOR_PREFIXES.get(prefix)
|
||||
if required and not (scope_lc & required):
|
||||
sector_dropped += 1
|
||||
continue
|
||||
if not criteria_on_topic(c.get("pass_criteria"),
|
||||
c.get("fail_criteria")):
|
||||
offtopic_dropped += 1
|
||||
continue
|
||||
kept.append(c)
|
||||
if sector_dropped or offtopic_dropped:
|
||||
logger.info(
|
||||
"v3 scope-filter: -%d Branchen-MCs, -%d themenfremde MCs "
|
||||
"(scope=%s)", sector_dropped, offtopic_dropped,
|
||||
sorted(scope_lc) or "leer",
|
||||
)
|
||||
return kept, {
|
||||
"sector_dropped": sector_dropped,
|
||||
"offtopic_dropped": offtopic_dropped,
|
||||
}
|
||||
|
||||
|
||||
def _normalize_criteria(controls: list[dict[str, Any]]) -> None:
|
||||
"""asyncpg liefert JSONB-Spalten (pass_criteria/fail_criteria) als
|
||||
Roh-String. In echte Listen parsen, damit Sektor-/Themen-Gate und
|
||||
der Boost-Layer Element-weise (nicht Zeichen-weise) iterieren."""
|
||||
import json
|
||||
for c in controls:
|
||||
for key in ("pass_criteria", "fail_criteria"):
|
||||
v = c.get(key)
|
||||
if isinstance(v, list):
|
||||
continue
|
||||
if isinstance(v, str):
|
||||
try:
|
||||
parsed = json.loads(v)
|
||||
c[key] = parsed if isinstance(parsed, list) else [v]
|
||||
except Exception:
|
||||
c[key] = [v] if v else []
|
||||
else:
|
||||
c[key] = []
|
||||
|
||||
@@ -207,3 +207,47 @@ HECTRONIC = ImpressumGT(
|
||||
|
||||
|
||||
ALL_GROUND_TRUTH = (ETO, SAFETYKON, BMW, ELLI, HECTRONIC)
|
||||
|
||||
|
||||
def make_mc(
|
||||
control_id: str,
|
||||
pass_criteria: list[str],
|
||||
severity: str = "HIGH",
|
||||
title: str | None = None,
|
||||
regulation: str = "TMG",
|
||||
article: str = "§ 5",
|
||||
check_question: str | None = None,
|
||||
) -> dict:
|
||||
"""Baut ein doc_check_controls-MC-Dict wie `_load_controls` es liefert —
|
||||
fuer Tests die `_load_controls` mocken (Agent delegiert ans Main Tool)."""
|
||||
return {
|
||||
"id": control_id,
|
||||
"control_id": control_id,
|
||||
"title": title or control_id,
|
||||
"regulation": regulation,
|
||||
"article": article,
|
||||
"severity": severity,
|
||||
"check_question": check_question or f"Ist {control_id} vorhanden?",
|
||||
"pass_criteria": list(pass_criteria),
|
||||
"fail_criteria": [],
|
||||
}
|
||||
|
||||
|
||||
# Kern-Impressum-MCs die ein vollstaendiges Impressum erfuellt. Der
|
||||
# Regex-Boost (Layer 0) hebt sie bei vorhandenen Pflichtangaben auf PASS,
|
||||
# sodass ein sauberes Impressum 0 Findings produziert. Jede pass_criteria
|
||||
# enthaelt >=2 Boost-Keywords damit boost_matches_db_mc greift.
|
||||
CORE_IMPRESSUM_MCS: list[dict] = [
|
||||
make_mc("IMP-NAME-A1", ["Anbieter Anschrift Adresse Firma angegeben"]),
|
||||
make_mc("IMP-MAIL-A1", ["E-Mail Kontaktmöglichkeit angegeben"]),
|
||||
make_mc("IMP-TEL-A1", ["Telefon Telefonnummer Rufnummer angegeben"],
|
||||
severity="MEDIUM"),
|
||||
make_mc("IMP-HR-A1", ["Handelsregister Registernummer HRB angegeben"]),
|
||||
make_mc("IMP-UST-A1", ["Umsatzsteuer USt-IdNr angegeben"],
|
||||
severity="MEDIUM"),
|
||||
make_mc("IMP-VTR-A1",
|
||||
["Geschäftsführer Vorstand Vertretungsberechtigt angegeben"]),
|
||||
make_mc("IMP-VTRL-A1",
|
||||
["Geschäftsführer Vorstand deutsche Bezeichnung Rechtsform"],
|
||||
severity="MEDIUM"),
|
||||
]
|
||||
|
||||
@@ -0,0 +1,69 @@
|
||||
"""Tests für Cookie-Policy-Agent v3 — Delegation an die Main-Tool-Engine,
|
||||
Sektor-Filter und Maßnahmen statt Fragen."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
|
||||
from compliance.services.specialist_agents.cookie_policy import v3_engine
|
||||
from compliance.services.specialist_agents.cookie_policy.agent import (
|
||||
_build_measure,
|
||||
)
|
||||
|
||||
|
||||
def _run(coro):
|
||||
return asyncio.get_event_loop().run_until_complete(coro)
|
||||
|
||||
|
||||
def test_build_measure_is_imperative_not_question():
|
||||
m = _build_measure("Speicherdauer der Cookies", "TDDDG § 25")
|
||||
assert "?" not in m
|
||||
assert "ergänzen" in m.lower()
|
||||
assert "Rechtsgrundlage" in m
|
||||
|
||||
|
||||
def test_build_measure_handles_empty_label():
|
||||
m = _build_measure("", "")
|
||||
assert "?" not in m
|
||||
assert m.strip() != ""
|
||||
|
||||
|
||||
def test_cookie_v3_delegates_and_sector_filters(monkeypatch):
|
||||
"""run_v3_pipeline lädt über die Main-Tool-Engine (cookie) und das
|
||||
Sektor-Gate entfernt GOV-MCs out-of-scope."""
|
||||
async def _fake_load(doc_type, db_url, limit, business_scope=None):
|
||||
assert doc_type == "cookie"
|
||||
return [
|
||||
{"control_id": "COOKIE-1-A1", "title": "Cookie-Kategorien",
|
||||
"regulation": "TDDDG", "article": "§ 25", "severity": "HIGH",
|
||||
"check_question": "Kategorien genannt?",
|
||||
"pass_criteria": '["Cookie Kategorien essentiell"]',
|
||||
"fail_criteria": "[]"},
|
||||
{"control_id": "GOV-9-A1", "title": "Behörden-Cookie",
|
||||
"regulation": "X", "article": "", "severity": "HIGH",
|
||||
"check_question": "Behörde?",
|
||||
"pass_criteria": '["Behörde Aufsicht"]',
|
||||
"fail_criteria": "[]"},
|
||||
]
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.rag_document_checker._load_controls",
|
||||
_fake_load,
|
||||
)
|
||||
|
||||
async def _no_match(*a, **kw):
|
||||
return set()
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.mc_embedding_matcher.embedding_match",
|
||||
_no_match, raising=False,
|
||||
)
|
||||
|
||||
text = ("Diese Website verwendet Cookies. Cookie-Kategorien: "
|
||||
"essentiell, funktional. Speicherdauer und Zweck beschrieben. "
|
||||
) * 4 # > 100 Zeichen
|
||||
results, telem = _run(
|
||||
v3_engine.run_v3_pipeline(text, business_scope=set()),
|
||||
)
|
||||
cids = {r["control_id"] for r in results}
|
||||
assert "GOV-9-A1" not in cids # Sektor out-of-scope entfernt
|
||||
assert "COOKIE-1-A1" in cids # cookie-MC bleibt
|
||||
assert telem["sector_dropped"] == 1
|
||||
@@ -11,7 +11,10 @@ import asyncio
|
||||
import pytest
|
||||
|
||||
from compliance.services.specialist_agents import AgentInput, ImpressumAgent
|
||||
from tests.fixtures.impressum_groundtruth import ALL_GROUND_TRUTH
|
||||
from tests.fixtures.impressum_groundtruth import (
|
||||
ALL_GROUND_TRUTH,
|
||||
CORE_IMPRESSUM_MCS,
|
||||
)
|
||||
|
||||
|
||||
def _run(coro):
|
||||
@@ -19,15 +22,40 @@ def _run(coro):
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _no_llm(monkeypatch):
|
||||
"""Skip LLM-Eskalation in den GT-Tests — wir testen MC-Pattern,
|
||||
nicht LLM-Halluzinationen."""
|
||||
async def _no_cascade(*a, **kw): return None, []
|
||||
def _agent_offline(monkeypatch):
|
||||
"""GT-Tests offline + deterministisch: LLM-Eskalation aus, MC-Laden ueber
|
||||
die gemockte Main-Tool-Engine (CORE_IMPRESSUM_MCS), Embedding aus. Der
|
||||
Agent delegiert jetzt ans Main Tool — daher `_load_controls` mocken."""
|
||||
import copy
|
||||
|
||||
async def _no_cascade(*a, **kw):
|
||||
return None, []
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.specialist_agents.impressum.agent.cascade",
|
||||
"compliance.services.specialist_agents._semantic_validator.cascade",
|
||||
_no_cascade,
|
||||
)
|
||||
|
||||
async def _fake_load(doc_type, db_url, limit, business_scope=None):
|
||||
return copy.deepcopy(CORE_IMPRESSUM_MCS)
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.rag_document_checker._load_controls",
|
||||
_fake_load,
|
||||
)
|
||||
|
||||
async def _no_embed(*a, **kw):
|
||||
return None
|
||||
|
||||
async def _no_match(*a, **kw):
|
||||
return set()
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.mc_embedding_matcher.ensure_mc_embeddings",
|
||||
_no_embed, raising=False,
|
||||
)
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.mc_embedding_matcher.embedding_match",
|
||||
_no_match, raising=False,
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.parametrize("gt", ALL_GROUND_TRUTH, ids=lambda g: g.name)
|
||||
def test_no_false_positives_on_expected_clean(gt):
|
||||
|
||||
@@ -15,10 +15,17 @@ from compliance.services.specialist_agents import (
|
||||
ImpressumAgent,
|
||||
Severity,
|
||||
)
|
||||
from compliance.services.specialist_agents.impressum.agent import (
|
||||
_build_measure,
|
||||
)
|
||||
from compliance.services.specialist_agents.impressum.regex_boost import (
|
||||
BOOST_KEYWORDS,
|
||||
boost_matches_db_mc,
|
||||
compute_regex_boosts,
|
||||
criteria_on_topic,
|
||||
)
|
||||
from compliance.services.specialist_agents.impressum.v3_engine import (
|
||||
_filter_controls,
|
||||
)
|
||||
|
||||
|
||||
@@ -187,3 +194,152 @@ def test_short_text_skipped():
|
||||
def test_agent_version_is_three():
|
||||
agent = ImpressumAgent()
|
||||
assert agent.agent_version == "3.0"
|
||||
|
||||
|
||||
# ── Themen-Gate: criteria_on_topic ──────────────────────────────────
|
||||
|
||||
|
||||
def test_criteria_on_topic_keeps_genuine_telefon():
|
||||
assert criteria_on_topic([
|
||||
"Telefonnummer angeben",
|
||||
"Erreichbar per Telefon",
|
||||
]) is True
|
||||
|
||||
|
||||
def test_criteria_on_topic_keeps_genuine_address():
|
||||
assert criteria_on_topic([
|
||||
"Vollständige Postadresse (Straße, Hausnummer, PLZ, Ort)",
|
||||
]) is True
|
||||
|
||||
|
||||
def test_criteria_on_topic_drops_bestellbestaetigung():
|
||||
# Fremd-MC: kein Impressum-Themenüberlapp → raus.
|
||||
assert criteria_on_topic([
|
||||
"Bestellbestätigung wird nach Vertragsschluss versendet",
|
||||
"Bestelleingang wird dokumentiert",
|
||||
]) is False
|
||||
|
||||
|
||||
def test_criteria_on_topic_single_incidental_hit_dropped():
|
||||
# 'E-Mail' allein (1 Treffer) reicht nicht — braucht >=2.
|
||||
assert criteria_on_topic([
|
||||
"Bestellbestätigung wird per E-Mail versendet",
|
||||
]) is False
|
||||
|
||||
|
||||
def test_criteria_on_topic_drops_behoerdliche_anzeige():
|
||||
assert criteria_on_topic([
|
||||
"Behördliche Anzeige der Tätigkeit erfolgt",
|
||||
"Gewerbeanmeldung liegt vor",
|
||||
]) is False
|
||||
|
||||
|
||||
def test_criteria_on_topic_empty_kept():
|
||||
# Keine Kriterien = kein Signal → konservativ behalten.
|
||||
assert criteria_on_topic([]) is True
|
||||
|
||||
|
||||
# ── Scope-Filter: _filter_controls ──────────────────────────────────
|
||||
|
||||
|
||||
def _mc(control_id, pass_criteria):
|
||||
return {"control_id": control_id, "pass_criteria": pass_criteria,
|
||||
"fail_criteria": []}
|
||||
|
||||
|
||||
def test_filter_controls_drops_gov_when_out_of_scope():
|
||||
controls = [_mc("GOV-814-A03", ["Behörde meldet an Aufsichtsstelle"])]
|
||||
kept, stats = _filter_controls(controls, business_scope=set())
|
||||
assert kept == []
|
||||
assert stats["sector_dropped"] == 1
|
||||
|
||||
|
||||
def test_filter_controls_keeps_gov_when_in_scope():
|
||||
controls = [_mc("GOV-814-A03",
|
||||
["Aufsichtsbehörde und Behörde benannt"])]
|
||||
kept, stats = _filter_controls(controls,
|
||||
business_scope={"government"})
|
||||
assert len(kept) == 1
|
||||
assert stats["sector_dropped"] == 0
|
||||
|
||||
|
||||
def test_filter_controls_keeps_genuine_impressum_mc():
|
||||
controls = [_mc("AUTH-1954-A07",
|
||||
["Vollständige Postadresse mit Straße und PLZ"])]
|
||||
kept, stats = _filter_controls(controls, business_scope=set())
|
||||
assert len(kept) == 1
|
||||
assert stats["sector_dropped"] == 0
|
||||
assert stats["offtopic_dropped"] == 0
|
||||
|
||||
|
||||
def test_filter_controls_drops_offtopic_non_sector_mc():
|
||||
controls = [_mc("ECOM-1-A1",
|
||||
["Bestellbestätigung nach Vertragsschluss versenden"])]
|
||||
kept, stats = _filter_controls(controls, business_scope=set())
|
||||
assert kept == []
|
||||
assert stats["offtopic_dropped"] == 1
|
||||
|
||||
|
||||
# ── Maßnahme statt Frage: _build_measure ────────────────────────────
|
||||
|
||||
|
||||
def test_build_measure_is_imperative_not_question():
|
||||
m = _build_measure("USt-IdNr", "§ 5 Abs. 1 Nr. 6 TMG")
|
||||
assert "?" not in m
|
||||
assert "ergänzen" in m.lower()
|
||||
assert "Rechtsgrundlage" in m
|
||||
|
||||
|
||||
def test_build_measure_handles_empty_label():
|
||||
m = _build_measure("", "")
|
||||
assert "?" not in m
|
||||
assert m.strip() != ""
|
||||
|
||||
|
||||
# ── Delegation an Main-Tool-Engine + Filter (Integration) ───────────
|
||||
|
||||
|
||||
def test_run_v3_pipeline_delegates_and_filters(monkeypatch):
|
||||
"""run_v3_pipeline lädt über die Main-Tool-Engine (_load_controls
|
||||
gemockt), normalisiert JSONB-Strings und das Sektor-/Themen-Gate
|
||||
entfernt GOV (out-of-scope) + fremde MCs. Genuine MC bleibt."""
|
||||
from compliance.services.specialist_agents.impressum import v3_engine
|
||||
|
||||
async def _fake_load(doc_type, db_url, limit, business_scope=None):
|
||||
# pass_criteria absichtlich als JSON-STRING (wie asyncpg JSONB)
|
||||
return [
|
||||
{"control_id": "AUTH-1954-A07", "title": "USt-IdNr",
|
||||
"regulation": "TMG", "article": "§ 5", "severity": "HIGH",
|
||||
"check_question": "Ist die USt-IdNr angegeben?",
|
||||
"pass_criteria": '["USt-IdNr"]',
|
||||
"fail_criteria": "[]"},
|
||||
{"control_id": "GOV-814-A03", "title": "Behördliche Anzeige",
|
||||
"regulation": "X", "article": "", "severity": "HIGH",
|
||||
"check_question": "Behörde informiert?",
|
||||
"pass_criteria": '["Aufsichtsbehörde und Behörde benannt"]',
|
||||
"fail_criteria": "[]"},
|
||||
{"control_id": "ECOM-1-A1", "title": "Bestellbestätigung",
|
||||
"regulation": "X", "article": "", "severity": "HIGH",
|
||||
"check_question": "Bestellbestätigung versandt?",
|
||||
"pass_criteria":
|
||||
'["Bestellbestätigung nach Vertragsschluss versenden"]',
|
||||
"fail_criteria": "[]"},
|
||||
]
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.rag_document_checker._load_controls",
|
||||
_fake_load,
|
||||
)
|
||||
# AUTH-MC matched per Keyword → kein Layer-2-Embedding nötig; kein
|
||||
# mc_embedding_matcher-Mock erforderlich.
|
||||
|
||||
text = ("Beispiel GmbH\nMusterstr. 1\n12345 Berlin\n"
|
||||
"USt-IdNr: DE123456789\n") * 5 # >100 Zeichen
|
||||
results, telem = _run(
|
||||
v3_engine.run_v3_pipeline(text, business_scope=set()),
|
||||
)
|
||||
cids = {r["control_id"] for r in results}
|
||||
assert "GOV-814-A03" not in cids # Sektor out-of-scope
|
||||
assert "ECOM-1-A1" not in cids # themenfremd
|
||||
assert "AUTH-1954-A07" in cids # genuine MC bleibt
|
||||
assert telem["sector_dropped"] == 1
|
||||
assert telem["offtopic_dropped"] == 1
|
||||
|
||||
@@ -13,6 +13,7 @@ from compliance.services.specialist_agents._semantic_validator import (
|
||||
standard_label,
|
||||
validate_present,
|
||||
)
|
||||
from tests.fixtures.impressum_groundtruth import make_mc
|
||||
|
||||
|
||||
def _run(coro):
|
||||
@@ -91,10 +92,33 @@ def test_semantic_demotion_high_to_low(monkeypatch):
|
||||
"compliance.services.specialist_agents._semantic_validator.cascade",
|
||||
_fake_cascade,
|
||||
)
|
||||
|
||||
# Agent delegiert MC-Laden ans Main Tool → _load_controls mocken.
|
||||
# control_id == field_id 'kontakt_telefon', damit der Semantic-Demote
|
||||
# das Finding ueber die LLM-Antwort zuordnet.
|
||||
async def _fake_load(doc_type, db_url, limit, business_scope=None):
|
||||
return [make_mc("kontakt_telefon",
|
||||
["Telefon Telefonnummer Rufnummer"],
|
||||
severity="HIGH")]
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.specialist_agents.impressum.agent.cascade",
|
||||
_fake_cascade,
|
||||
"compliance.services.rag_document_checker._load_controls",
|
||||
_fake_load,
|
||||
)
|
||||
|
||||
async def _no_match(*a, **kw):
|
||||
return set()
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.mc_embedding_matcher.embedding_match",
|
||||
_no_match, raising=False,
|
||||
)
|
||||
|
||||
async def _no_embed(*a, **kw):
|
||||
return None
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.mc_embedding_matcher.ensure_mc_embeddings",
|
||||
_no_embed, raising=False,
|
||||
)
|
||||
|
||||
# Text OHNE Telefon-Label → MC matched nicht → HIGH-Finding
|
||||
text = (
|
||||
"Beispiel GmbH\nMusterstr. 1\n12345 Berlin\n"
|
||||
|
||||
@@ -9,6 +9,8 @@ from unittest.mock import AsyncMock, patch
|
||||
import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from tests.fixtures.impressum_groundtruth import make_mc
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def app(tmp_path, monkeypatch):
|
||||
@@ -69,9 +71,37 @@ def test_run_result_after_text_input(client, monkeypatch):
|
||||
# Skip LLM
|
||||
async def _no_cascade(*a, **kw): return None, []
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.specialist_agents.impressum.agent.cascade",
|
||||
"compliance.services.specialist_agents._semantic_validator.cascade",
|
||||
_no_cascade,
|
||||
)
|
||||
# Agent delegiert MC-Laden ans Main Tool → _load_controls mocken.
|
||||
# Tesla nennt 'Management' (engl.) statt deutschem GF-Label → das
|
||||
# label_korrekt-MC schlaegt fehl → erwartetes Finding.
|
||||
async def _fake_load(doc_type, db_url, limit, business_scope=None):
|
||||
# pass_criteria nur mit label_korrekt-eigenen Keywords (deutsche/
|
||||
# Bezeichnung/Rechtsform) — NICHT 'Geschäftsführer/Vorstand', sonst
|
||||
# boostet das aktive vertretungsberechtigte-Feld (Tesla: 'Management')
|
||||
# das MC faelschlich auf PASS.
|
||||
return [make_mc(
|
||||
"vertretungsberechtigte_label_korrekt",
|
||||
["deutsche Bezeichnung Rechtsform Pflicht angeben"],
|
||||
)]
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.rag_document_checker._load_controls",
|
||||
_fake_load,
|
||||
)
|
||||
|
||||
async def _no_match(*a, **kw): return set()
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.mc_embedding_matcher.embedding_match",
|
||||
_no_match, raising=False,
|
||||
)
|
||||
|
||||
async def _no_embed(*a, **kw): return None
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.mc_embedding_matcher.ensure_mc_embeddings",
|
||||
_no_embed, raising=False,
|
||||
)
|
||||
r = client.post("/api/v1/specialist-agent/test/start",
|
||||
json={"agent_id": "impressum",
|
||||
"raw_texts": [
|
||||
@@ -103,7 +133,7 @@ def test_run_result_after_text_input(client, monkeypatch):
|
||||
def test_artifacts_listing(client, monkeypatch):
|
||||
async def _no_cascade(*a, **kw): return None, []
|
||||
monkeypatch.setattr(
|
||||
"compliance.services.specialist_agents.impressum.agent.cascade",
|
||||
"compliance.services.specialist_agents._semantic_validator.cascade",
|
||||
_no_cascade,
|
||||
)
|
||||
r = client.post("/api/v1/specialist-agent/test/start",
|
||||
|
||||
Reference in New Issue
Block a user