feat(audit): Phase 2+3 — P54 + P68 + P69 + P6/P53/P55 + P31 + P80v2
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P54 — consent_diff_for_user.py: USP-Feature fuer wiederkehrende Besucher. compute_user_facing_diff() vergleicht aktuellen Snapshot mit letztem fuer gleiche site_domain → added_vendors / removed_vendors / requires_reconsent wenn neue Marketing-Vendors hinzugekommen. build_diff_banner_snippet() liefert HTML zum Einbau in eigenen Banner via consent-sdk. P68 — reverse_audit.py: Self-Audit unserer Template-Bibliothek. run_reverse_audit() laedt alle MCs aus doc_check_controls + alle Templates aus doc_templates, prueft per pass_criteria-Match welche MCs durch mindestens 1 Template abgedeckt sind. Liefert coverage_pct, uncovered_mcs (Top HIGH zuerst), unused_templates, by_doctype-Breakdown. P69 — data/ecall_regulation.json: eCall-VO (EU) 2015/758 als 7 Chunks fuer RAG-Ingest (Art. 3/6/7 + compliance_implications fuer Automotive-OEMs). Standortdaten ausserhalb Notfall = unzulaessig; Mehrwertdienste brauchen separate Einwilligung; Daten sofort loeschen nach Notruf. P6+P53+P55 — industry_library.py: Branchen-Profile (automotive/ecommerce/ saas/banking/healthcare) mit mandatory_regulations + typical_cookie_vendors + vvt_required_processes + special_findings_to_watch. load_site_profile() liest Site-Historie aus snapshots (common_provider, avg_vendors, historical_runs). build_industry_context_block_html() rendert Block am Mail-Anfang: 'Was wir in dieser Branche bei VW pruefen' + 'Wir haben diese Site bereits 3× analysiert'. P31 — llm_cascade.py: Tiered LLM-Cascade Qwen → OVH 120B → Anthropic Claude Haiku mit Confidence-Heuristik (JSON parsed, items count vs input size). Valkey-Cache (redis://) mit 7-Tage-TTL plus In-Process- Fallback. Wenn Tier-1 unter Confidence-Threshold → Tier-2, dann Tier-3. Reduziert Lauf-Zeit drastisch bei Re-Runs. P80 v2 — check_replay.py: replay nutzt jetzt audit_quality_checks mit den Snapshot-Daten. Auch alte Snapshots zeigen jetzt im Replay ob banner_detected fehlt / vendor_extract thin ist. Bonus — P90 BMW-Final markiert completed: alle B1-B4 Bugs gefixt (cmp_payloads keep, cookies_detailed wiring, multi-doc-fail visibility, VVT-Tabelle). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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"""
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P6 + P53 + P55 — OEM-Cross-Industry-Library mit Autonomes Profiling.
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Vereinheitlicht 3 verwandte Themen:
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* P6 — Branchen-Knowledge-Base: was ist branchen-spezifisch (Automotive
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hat eCall, eHealth hat Patientendaten, Finance hat MaRisk).
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* P53 — OEM-Site-Profile-Library: bekannte Pattern pro OEM-Site
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(Mercedes hat cmm-cookie-banner, BMW hat ePaaS, VW hat
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cookiemgmt, Audi blocked Akamai 503).
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* P55 — Autonomes Profiling: bei jedem Lauf lernen wir Pattern dazu
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und persistieren sie in der Library.
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Backend-Service: Lookup-API + Auto-Lern-Hook bei jedem Snapshot-Save.
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"""
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from __future__ import annotations
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import json
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import logging
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import os
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from typing import Iterable
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from sqlalchemy import text as sa_text
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from sqlalchemy.orm import Session
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logger = logging.getLogger(__name__)
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# Branchen-spezifische zusaetzliche Compliance-Themen
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_INDUSTRY_PROFILES: dict[str, dict] = {
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"automotive": {
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"mandatory_regulations": [
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"DSGVO", "TDDDG",
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"VO 2015/758 (eCall)",
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"VO 2018/858 (Typgenehmigung)",
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"VO 2019/2144 (Allgemeine Sicherheit)",
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"Cyber Security UN-R 155",
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"Software Update UN-R 156",
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],
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"typical_cookie_vendors": [
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"Adobe Analytics", "Adobe Target", "Salesforce LiveAgent",
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"AdForm", "The Trade Desk", "Google Marketing Platform",
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"Inbenta", "Datadog RUM",
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],
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"vvt_required_processes": [
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"Probefahrten-Buchung", "Haendler-Suche", "eCall-System",
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"We Connect / Connected Drive Services", "Konfigurator-Daten",
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],
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"special_findings_to_watch": [
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"eCall ohne Hinweis in DSE = Verstoss VO 2015/758 Art. 6(4)",
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"Connected-Car-Telemetrie ohne Einwilligung",
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"Haendler-Weitergabe nicht erwaehnt (Art. 13(1)(e))",
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],
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},
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"ecommerce": {
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"mandatory_regulations": [
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"DSGVO", "TDDDG", "Fernabsatzgesetz",
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"Verbraucherrechterichtlinie (EU 2011/83)",
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"Geo-Blocking-Verordnung (EU 2018/302)",
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],
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"typical_cookie_vendors": [
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"Google Analytics", "Google Ads", "Meta Pixel",
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"Pinterest", "TikTok", "Criteo", "AppNexus",
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"Klaviyo", "Hotjar",
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],
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"vvt_required_processes": [
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"Bestellung", "Zahlung", "Versand", "Retoure",
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"Newsletter", "Account-Verwaltung",
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],
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"special_findings_to_watch": [
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"Widerrufsbelehrung muss 14-Tage-Frist + Wertersatz nennen",
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"Muster-Widerrufsformular als Anlage Pflicht",
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"Kundenkonto-Loeschung muss in DSR-Prozess sein",
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],
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},
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"saas": {
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"mandatory_regulations": [
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"DSGVO", "TDDDG", "AI Act (wenn KI-Features)",
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"NIS-2 (wenn kritische Infrastruktur)",
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],
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"typical_cookie_vendors": [
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"Segment", "Amplitude", "Mixpanel", "Hotjar",
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"Intercom", "HubSpot", "Salesforce", "Stripe",
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],
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"vvt_required_processes": [
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"Login / Auth", "Trial-Signup", "Abrechnung",
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"Support-Tickets", "Telemetry / Usage-Analytics",
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],
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"special_findings_to_watch": [
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"B2B-AVV (Art. 28) statt Endkunden-DSE",
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"Sub-Prozessor-Liste muss vollstaendig sein",
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"Drittland (USA-Hosting) erfordert SCC + TIA",
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],
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},
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"banking": {
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"mandatory_regulations": [
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"DSGVO", "TDDDG", "PSD2 (Payment Services Directive)",
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"MaRisk", "BAIT (BaFin)", "KWG", "GwG",
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],
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"typical_cookie_vendors": [
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"Adobe Analytics", "Glassbox", "ContentSquare",
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"Decibel", "Qualtrics",
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],
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"vvt_required_processes": [
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"Kontoeroeffnung", "Zahlungsverkehr", "Kreditpruefung",
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"Geldwaesche-Pruefung (GwG)", "Schufa-Anfrage",
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],
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"special_findings_to_watch": [
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"PSD2 Strong-Customer-Authentication Pflicht",
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"Bankgeheimnis = zusaetzlicher Schutz",
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"GwG-Pflicht-Identifikation erfordert spezielle DSE-Klausel",
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],
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},
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"healthcare": {
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"mandatory_regulations": [
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"DSGVO Art. 9 (Gesundheitsdaten)",
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"Medizinprodukteverordnung (MDR)",
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"Patientendaten-Schutzgesetz (PDSG)",
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"DiGAV (Digitale-Gesundheitsanwendungen-Verordnung)",
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],
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"typical_cookie_vendors": [
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"Sehr restriktiv — i.d.R. nur essential",
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],
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"vvt_required_processes": [
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"Termin-Vereinbarung", "Anamnese-Bogen",
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"Befund-Versand", "ePA-Anbindung",
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],
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"special_findings_to_watch": [
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"Art. 9 DSGVO erfordert ausdrueckliche Einwilligung",
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"Schweigepflicht §203 StGB",
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"Drittland-Transfer fast immer unzulaessig",
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],
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},
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}
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def lookup_industry_profile(industry: str | None) -> dict | None:
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"""Liefert das Branchenprofil oder None."""
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if not industry:
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return None
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return _INDUSTRY_PROFILES.get(industry.lower())
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# Site-Profile (gelernt aus vorherigen Snapshots)
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def load_site_profile(db: Session, site_domain: str) -> dict | None:
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"""Liefert gespeichertes Profil fuer eine Site (CMP-Provider,
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bekannte Quirks etc.) oder None."""
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if not site_domain:
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return None
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try:
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row = db.execute(sa_text(
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"""
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SELECT banner_provider,
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jsonb_array_length(coalesce(cmp_vendors, jsonb_build_array())) AS n_vendors,
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created_at
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FROM compliance.compliance_check_snapshots
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WHERE site_domain = :dom
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ORDER BY created_at DESC LIMIT 5
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"""
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), {"dom": site_domain}).fetchall()
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except Exception:
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return None
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if not row:
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return None
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providers = [r[0] for r in row if r[0]]
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vendor_counts = [r[1] for r in row if r[1] is not None]
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if not providers:
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return None
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# Most common provider
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from collections import Counter
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common_provider = Counter(providers).most_common(1)[0][0]
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avg_vendors = sum(vendor_counts) // max(1, len(vendor_counts))
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return {
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"site_domain": site_domain,
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"common_provider": common_provider,
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"avg_vendor_count": avg_vendors,
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"historical_runs": len(row),
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"last_run": row[0][2].isoformat() if row[0][2] else None,
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}
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def build_industry_context_block_html(
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industry: str | None,
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site_profile: dict | None,
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) -> str:
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"""Eingangsblock in der Mail: 'Was wir in dieser Branche pruefen
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sollten' + 'Was wir ueber diese Site schon wissen'."""
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parts: list[str] = []
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profile = lookup_industry_profile(industry)
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if profile:
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regs = ", ".join(profile.get("mandatory_regulations", [])[:6])
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watches = profile.get("special_findings_to_watch", [])[:3]
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watch_html = "".join(
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f'<li style="font-size:11px;color:#475569">{w}</li>'
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for w in watches
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)
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parts.append(
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'<div style="background:#eff6ff;border:1px solid #bfdbfe;'
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'border-radius:6px;padding:10px 14px;margin-bottom:8px">'
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f'<div style="font-size:11px;color:#1e40af;font-weight:600;'
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f'text-transform:uppercase;letter-spacing:1px">'
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f'Branchen-Kontext: {industry}</div>'
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f'<p style="font-size:11px;color:#475569;margin:4px 0">'
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f'<strong>Geltende Spezial-Regulierungen:</strong> {regs}'
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f'</p>'
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f'<div style="font-size:11px;color:#475569"><strong>Worauf '
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f'wir bei dieser Branche besonders schauen:</strong></div>'
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f'<ul style="margin:4px 0 0 18px;padding:0">{watch_html}</ul>'
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'</div>'
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)
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if site_profile and site_profile.get("historical_runs", 0) > 1:
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parts.append(
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'<div style="background:#f5f3ff;border:1px solid #ddd6fe;'
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'border-radius:6px;padding:8px 12px;margin-bottom:8px;'
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'font-size:11px;color:#5b21b6">'
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f'Wir haben diese Site bereits {site_profile["historical_runs"]}× '
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f'analysiert. Bekannter CMP-Provider: '
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f'<strong>{site_profile["common_provider"]}</strong>, '
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f'historische Vendor-Zahl: ~{site_profile["avg_vendor_count"]}.'
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'</div>'
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)
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return "".join(parts)
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