breakpilot-compliance/backend-compliance/compliance/api/agent_scan_helpers.py

"""
Agent scan helpers — summary builder and correction generator.
Extracted from agent_scan_routes.py to keep route file under 500 LOC.
"""

import logging
import os
import re

import httpx

logger = logging.getLogger(__name__)


async def add_corrections(findings: list, dse_text: str) -> None:
    """Add correction suggestions for pre-launch mode via LLM."""
    for finding in findings:
        if finding.severity in ("HIGH", "MEDIUM") and "MISSING" in finding.code:
            service_name = finding.code.replace("DSE-MISSING-", "").replace("_", " ").title()
            try:
                ollama_url = os.environ.get("OLLAMA_URL", "http://host.docker.internal:11434")
                ollama_model = os.environ.get("OLLAMA_MODEL", "qwen3.5:35b-a3b")
                async with httpx.AsyncClient(timeout=120.0) as client:
                    resp = await client.post(f"{ollama_url}/api/generate", json={
                        "model": ollama_model,
                        "prompt": (
                            f"Erstelle einen einbaufertigen Textbaustein fuer eine deutsche "
                            f"Datenschutzerklaerung fuer den Dienst '{service_name}'. "
                            f"Enthalte: Ueberschrift, Anbietername mit Sitz, Zweck der Verarbeitung, "
                            f"Rechtsgrundlage nach DSGVO, Drittlandtransfer-Hinweis wenn noetig, "
                            f"Widerspruchsmoeglichkeit. Max 150 Woerter. "
                            f"Antworte NUR mit dem fertigen Textbaustein."
                        ),
                        "stream": False,
                    })
                    data = resp.json()
                    raw = data.get("response", "").strip()
                    raw = re.sub(r"<think>.*?</think>", "", raw, flags=re.DOTALL).strip()
                    if raw and len(raw) > 50:
                        finding.correction = raw
            except Exception as e:
                logger.warning("Correction generation failed for %s: %s", service_name, e)


def build_scan_summary(
    url: str, scan, comparison: dict, findings: list, is_live: bool,
    discovered_docs: list | None = None,
) -> str:
    """Build German scan summary including DSI document results."""
    mode = "PRUEFUNG LIVE-WEBSITE" if is_live else "INTERNE PRUEFUNG"
    n_undoc = len(comparison["undocumented"])
    n_ok = len(comparison["documented"])
    n_outdated = len(comparison["outdated"])
    n_findings = len(findings)
    high = sum(1 for f in findings if f.severity == "HIGH")

    parts = [
        f"{mode} — Website-Scan",
        f"URL: {url}",
        f"Seiten gescannt: {len(scan.pages_scanned)}",
    ]
    for page in scan.pages_scanned:
        status = scan.missing_pages.get(page, 200)
        marker = "\u2717" if status >= 400 else "\u2713"
        parts.append(f"  {marker} {page}" + (f" (HTTP {status})" if status >= 400 else ""))
    parts.extend([
        "",
        "Dienstleister-Abgleich (DSE vs. Website):",
        f"  Korrekt dokumentiert: {n_ok}",
        f"  NICHT in DSE (Verstoss): {n_undoc}",
        f"  Veraltet in DSE: {n_outdated}",
        "",
        f"Findings: {n_findings} ({high} mit hoher Prioritaet)",
    ])

    # DSI Documents section
    if discovered_docs:
        parts.extend([
            "",
            f"Rechtliche Dokumente gefunden: {len(discovered_docs)}",
        ])
        for doc in discovered_docs:
            pct = doc.completeness_pct if hasattr(doc, 'completeness_pct') else 0
            fc = doc.findings_count if hasattr(doc, 'findings_count') else 0
            wc = doc.word_count if hasattr(doc, 'word_count') else 0
            status = "OK" if pct >= 80 else "LUECKENHAFT" if pct >= 50 else "MANGELHAFT"
            dt = doc.doc_type if hasattr(doc, 'doc_type') else "unknown"
            title = doc.title if hasattr(doc, 'title') else "?"
            parts.append(
                f"  [{status}] {title} ({dt}, {wc} Woerter, "
                f"{pct}% vollstaendig, {fc} Maengel)"
            )

    if findings:
        parts.append("")
        for f in findings[:20]:
            sev = f.severity if hasattr(f, 'severity') else "?"
            txt = f.text if hasattr(f, 'text') else str(f)
            marker = "!!" if sev == "HIGH" else "!" if sev == "MEDIUM" else "i"
            parts.append(f"  [{marker}] {txt}")

    if is_live and high > 0:
        parts.extend([
            "",
            "ACHTUNG: Verstoesse auf einer bereits veroeffentlichten Website. "
            "Sofortige Korrektur empfohlen.",
        ])

    return "\n".join(parts)