feat: pre-launch vs post-launch analysis modes
- Backend: mode field in request, adapts summary tone and email subject - Pre-launch: "Implementieren Sie X vor Veroeffentlichung" - Post-launch: "ACHTUNG: Maengel sind oeffentlich sichtbar, sofortige Nachbesserung" - Frontend: Mode toggle (internes Dokument vs. Live-Website) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
@@ -39,7 +39,7 @@ export function useAgentAnalysis() {
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const [result, setResult] = useState<AnalysisResult | null>(null)
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const [result, setResult] = useState<AnalysisResult | null>(null)
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const [history, setHistory] = useState<AnalysisResult[]>([])
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const [history, setHistory] = useState<AnalysisResult[]>([])
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async function analyze(url: string) {
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async function analyze(url: string, mode: string = 'post_launch') {
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setLoading(true)
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setLoading(true)
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setError(null)
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setError(null)
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setResult(null)
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setResult(null)
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@@ -48,7 +48,7 @@ export function useAgentAnalysis() {
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const fetchRes = await fetch('/api/sdk/v1/agent/analyze', {
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const fetchRes = await fetch('/api/sdk/v1/agent/analyze', {
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method: 'POST',
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({ url }),
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body: JSON.stringify({ url, mode }),
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})
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})
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if (!fetchRes.ok) {
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if (!fetchRes.ok) {
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@@ -6,14 +6,32 @@ import { AnalysisResult } from './_components/AnalysisResult'
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import { AnalysisHistory } from './_components/AnalysisHistory'
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import { AnalysisHistory } from './_components/AnalysisHistory'
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import { FollowUpQuestions } from './_components/FollowUpQuestions'
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import { FollowUpQuestions } from './_components/FollowUpQuestions'
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type AnalysisMode = 'pre_launch' | 'post_launch'
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const MODES: { id: AnalysisMode; label: string; desc: string; icon: string }[] = [
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{
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id: 'pre_launch',
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label: 'Internes Dokument pruefen',
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desc: 'Dokument oder Website VOR Veroeffentlichung pruefen',
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icon: '📋',
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},
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{
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id: 'post_launch',
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label: 'Live-Website pruefen',
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desc: 'Bereits veroeffentlichte Website oder Dokument analysieren',
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icon: '🌐',
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},
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]
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export default function AgentPage() {
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export default function AgentPage() {
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const [url, setUrl] = useState('')
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const [url, setUrl] = useState('')
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const [mode, setMode] = useState<AnalysisMode>('post_launch')
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const { analyze, answerFollowUp, loading, error, result, history } = useAgentAnalysis()
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const { analyze, answerFollowUp, loading, error, result, history } = useAgentAnalysis()
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const handleSubmit = (e: React.FormEvent) => {
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const handleSubmit = (e: React.FormEvent) => {
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e.preventDefault()
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e.preventDefault()
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if (!url.trim()) return
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if (!url.trim()) return
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analyze(url.trim())
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analyze(url.trim(), mode)
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}
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}
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return (
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return (
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@@ -22,18 +40,44 @@ export default function AgentPage() {
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<div>
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<div>
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<h1 className="text-2xl font-bold text-gray-900">Compliance Agent</h1>
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<h1 className="text-2xl font-bold text-gray-900">Compliance Agent</h1>
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<p className="text-gray-500 mt-1">
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<p className="text-gray-500 mt-1">
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Analysiere Webseiten auf DSGVO-Konformitaet. Der Agent holt das Dokument,
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Analysiere Dokumente und Webseiten auf DSGVO-Konformitaet.
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klassifiziert es, bewertet das Risiko und weist die Aufgabe der zustaendigen Rolle zu.
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</p>
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</p>
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</div>
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</div>
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{/* Mode Selection */}
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<div className="grid grid-cols-2 gap-3">
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{MODES.map(m => (
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<button
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key={m.id}
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onClick={() => setMode(m.id)}
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className={`p-4 rounded-xl border-2 text-left transition-all ${
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mode === m.id
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? 'border-purple-500 bg-purple-50 shadow-sm'
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: 'border-gray-200 bg-white hover:border-gray-300'
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}`}
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>
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<div className="flex items-center gap-3">
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<span className="text-2xl">{m.icon}</span>
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<div>
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<p className={`text-sm font-semibold ${mode === m.id ? 'text-purple-900' : 'text-gray-900'}`}>
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{m.label}
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</p>
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<p className="text-xs text-gray-500 mt-0.5">{m.desc}</p>
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</div>
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</div>
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</button>
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))}
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</div>
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{/* URL Input */}
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{/* URL Input */}
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<form onSubmit={handleSubmit} className="flex gap-3">
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<form onSubmit={handleSubmit} className="flex gap-3">
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<input
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<input
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type="url"
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type="url"
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value={url}
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value={url}
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onChange={e => setUrl(e.target.value)}
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onChange={e => setUrl(e.target.value)}
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placeholder="https://example.com/datenschutz"
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placeholder={mode === 'pre_launch'
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? 'https://staging.example.com/datenschutz'
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: 'https://www.example.com/datenschutz'}
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className="flex-1 px-4 py-3 border border-gray-300 rounded-lg focus:ring-2 focus:ring-purple-500 focus:border-transparent text-sm"
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className="flex-1 px-4 py-3 border border-gray-300 rounded-lg focus:ring-2 focus:ring-purple-500 focus:border-transparent text-sm"
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disabled={loading}
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disabled={loading}
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required
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required
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@@ -87,7 +131,7 @@ export default function AgentPage() {
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history={history}
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history={history}
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onSelect={r => {
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onSelect={r => {
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setUrl(r.url)
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setUrl(r.url)
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analyze(r.url)
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analyze(r.url, mode)
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}}
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}}
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/>
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/>
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</div>
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</div>
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@@ -41,6 +41,7 @@ SDK_HEADERS = {
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class AnalyzeRequest(BaseModel):
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class AnalyzeRequest(BaseModel):
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url: str
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url: str
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recipient: str = "dsb@breakpilot.local"
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recipient: str = "dsb@breakpilot.local"
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mode: str = "post_launch" # "pre_launch" or "post_launch"
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class FollowUpQuestion(BaseModel):
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class FollowUpQuestion(BaseModel):
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@@ -97,12 +98,13 @@ async def analyze_url(req: AnalyzeRequest):
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esc_level = "E1"
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esc_level = "E1"
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role = ESCALATION_ROLES["E1"]
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role = ESCALATION_ROLES["E1"]
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summary = _build_summary(req.url, classification, assessment, role, findings_str, controls_str)
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summary = _build_summary(req.url, classification, assessment, role, findings_str, controls_str, req.mode)
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# Step 7: Send notification
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# Step 7: Send notification
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mode_label = "INTERNE PRUEFUNG" if req.mode == "pre_launch" else "LIVE-WEBSITE"
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email_result = send_email(
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email_result = send_email(
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recipient=req.recipient,
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recipient=req.recipient,
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subject=f"Compliance-Finding: {classification} — {req.url[:60]}",
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subject=f"[{mode_label}] Compliance-Finding: {classification} — {req.url[:60]}",
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body_html=f"<div>{summary}</div>",
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body_html=f"<div>{summary}</div>",
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)
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)
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@@ -350,17 +352,27 @@ def _risk_to_escalation(risk_level: str) -> str:
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def _build_summary(
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def _build_summary(
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url: str, classification: str, assessment: dict, role: str,
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url: str, classification: str, assessment: dict, role: str,
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findings_str: list[str], controls_str: list[str],
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findings_str: list[str], controls_str: list[str],
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mode: str = "post_launch",
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) -> str:
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) -> str:
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"""Build a German manager summary."""
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"""Build a German manager summary, adapted to pre/post-launch context."""
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risk = assessment.get("risk_level", "unbekannt")
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risk = assessment.get("risk_level", "unbekannt")
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score = assessment.get("risk_score", 0)
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score = assessment.get("risk_score", 0)
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recommendation = assessment.get("recommendation", "")
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recommendation = assessment.get("recommendation", "")
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dsfa = assessment.get("dsfa_recommended", False)
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dsfa = assessment.get("dsfa_recommended", False)
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is_live = mode == "post_launch"
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findings_text = "\n".join(f"- {f}" for f in findings_str[:5]) if findings_str else "Keine"
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findings_text = "\n".join(f"- {f}" for f in findings_str[:5]) if findings_str else "Keine"
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controls_text = "\n".join(f"- {c}" for c in controls_str[:5]) if controls_str else "Keine"
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controls_text = "\n".join(f"- {c}" for c in controls_str[:5]) if controls_str else "Keine"
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mode_header = (
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"PRUEFUNG LIVE-WEBSITE — Das Dokument ist bereits oeffentlich zugaenglich."
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if is_live else
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"INTERNE PRUEFUNG — Das Dokument ist noch nicht veroeffentlicht."
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)
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parts = [
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parts = [
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mode_header,
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"",
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f"Dokumenttyp: {classification}",
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f"Dokumenttyp: {classification}",
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f"Quelle: {url}",
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f"Quelle: {url}",
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f"Risikobewertung: {risk} ({score}/100)",
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f"Risikobewertung: {risk} ({score}/100)",
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@@ -371,6 +383,19 @@ def _build_summary(
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"",
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"",
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f"Erforderliche Massnahmen:\n{controls_text}",
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f"Erforderliche Massnahmen:\n{controls_text}",
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]
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]
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if is_live and findings_str:
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parts.extend([
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"",
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"ACHTUNG: Diese Maengel sind bereits oeffentlich sichtbar. "
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"Sofortige Nachbesserung empfohlen um Abmahnrisiken zu minimieren.",
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])
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elif not is_live and controls_str:
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parts.extend([
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"",
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"Empfehlung: Implementieren Sie die erforderlichen Kontrollen vor der Veroeffentlichung.",
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])
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if recommendation:
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if recommendation:
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parts.extend(["", f"Empfehlung: {recommendation}"])
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parts.extend(["", f"Weitere Empfehlung: {recommendation}"])
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return "\n".join(parts)
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return "\n".join(parts)
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