fix: Restore all files lost during destructive rebase
A previous `git pull --rebase origin main` dropped 177 local commits,
losing 3400+ files across admin-v2, backend, studio-v2, website,
klausur-service, and many other services. The partial restore attempt
(660295e2) only recovered some files.
This commit restores all missing files from pre-rebase ref 98933f5e
while preserving post-rebase additions (night-scheduler, night-mode UI,
NightModeWidget dashboard integration).
Restored features include:
- AI Module Sidebar (FAB), OCR Labeling, OCR Compare
- GPU Dashboard, RAG Pipeline, Magic Help
- Klausur-Korrektur (8 files), Abitur-Archiv (5+ files)
- Companion, Zeugnisse-Crawler, Screen Flow
- Full backend, studio-v2, website, klausur-service
- All compliance SDKs, agent-core, voice-service
- CI/CD configs, documentation, scripts
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
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backend/compliance/README_AI.md
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backend/compliance/README_AI.md
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# Compliance AI Integration - Quick Start
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## Schnellstart (5 Minuten)
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### 1. Environment Variables setzen
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```bash
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# In backend/.env
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COMPLIANCE_LLM_PROVIDER=mock # Für Testing ohne API-Key
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# ODER
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COMPLIANCE_LLM_PROVIDER=anthropic
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ANTHROPIC_API_KEY=sk-ant-...
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```
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### 2. Backend starten
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```bash
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cd backend
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docker-compose up -d
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# ODER
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uvicorn main:app --reload
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```
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### 3. Datenbank seeden
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```bash
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# Requirements und Module laden
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curl -X POST http://localhost:8000/api/v1/compliance/seed \
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-H "Content-Type: application/json" \
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-d '{"force": false}'
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curl -X POST http://localhost:8000/api/v1/compliance/modules/seed \
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-H "Content-Type: application/json" \
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-d '{"force": false}'
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```
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### 4. AI-Features testen
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```bash
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# Test-Script ausfuhren
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python backend/scripts/test_compliance_ai_endpoints.py
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```
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## API Endpoints
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Alle Endpoints unter: `http://localhost:8000/api/v1/compliance/ai/`
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### 1. Status prufen
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```bash
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curl http://localhost:8000/api/v1/compliance/ai/status
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```
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### 2. Requirement interpretieren
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```bash
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curl -X POST http://localhost:8000/api/v1/compliance/ai/interpret \
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-H "Content-Type: application/json" \
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-d '{
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"requirement_id": "YOUR_REQUIREMENT_ID"
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}'
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```
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### 3. Controls vorschlagen
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```bash
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curl -X POST http://localhost:8000/api/v1/compliance/ai/suggest-controls \
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-H "Content-Type: application/json" \
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-d '{
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"requirement_id": "YOUR_REQUIREMENT_ID"
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}'
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```
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### 4. Modul-Risiko bewerten
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```bash
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curl -X POST http://localhost:8000/api/v1/compliance/ai/assess-risk \
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-H "Content-Type: application/json" \
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-d '{
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"module_id": "consent-service"
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}'
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```
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### 5. Gap-Analyse
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```bash
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curl -X POST http://localhost:8000/api/v1/compliance/ai/gap-analysis \
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-H "Content-Type: application/json" \
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-d '{
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"requirement_id": "YOUR_REQUIREMENT_ID"
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}'
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```
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### 6. Batch-Interpretation
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```bash
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curl -X POST http://localhost:8000/api/v1/compliance/ai/batch-interpret \
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-H "Content-Type: application/json" \
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-d '{
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"requirement_ids": ["id1", "id2"],
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"rate_limit": 1.0
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}'
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```
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## Provider-Konfiguration
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### Option 1: Mock (Testing)
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```bash
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export COMPLIANCE_LLM_PROVIDER=mock
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```
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Vorteile:
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- Keine API-Keys erforderlich
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- Schnell
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- Deterministisch
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Nachteile:
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- Keine echten AI-Antworten
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### Option 2: Anthropic Claude (Empfohlen)
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```bash
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export COMPLIANCE_LLM_PROVIDER=anthropic
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export ANTHROPIC_API_KEY=sk-ant-...
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export ANTHROPIC_MODEL=claude-sonnet-4-20250514
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```
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Vorteile:
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- Beste Qualitat
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- Zuverlassig
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- Breakpilot-optimiert
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Nachteile:
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- API-Kosten (~$3 per 1M input tokens)
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### Option 3: Self-Hosted (Ollama/vLLM)
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```bash
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export COMPLIANCE_LLM_PROVIDER=self_hosted
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export SELF_HOSTED_LLM_URL=http://localhost:11434
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export SELF_HOSTED_LLM_MODEL=llama3.1:8b
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```
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Vorteile:
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- Kostenlos
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- Privacy (on-premise)
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- Keine Rate-Limits
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Nachteile:
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- Geringere Qualitat als Claude
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- Benotigt GPU/CPU-Ressourcen
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## Beispiel-Response
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### Interpretation
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```json
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{
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"requirement_id": "req-123",
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"summary": "Art. 32 DSGVO verlangt angemessene technische Maßnahmen zur Datensicherheit.",
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"applicability": "Gilt für alle Breakpilot-Module die personenbezogene Daten verarbeiten.",
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"technical_measures": [
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"Verschlüsselung personenbezogener Daten (AES-256)",
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"TLS 1.3 für Datenübertragung",
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"Regelmäßige Sicherheitsaudits",
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"Zugriffskontrolle mit IAM"
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],
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"affected_modules": [
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"consent-service",
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"klausur-service",
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"backend"
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],
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"risk_level": "high",
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"implementation_hints": [
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"SOPS mit Age-Keys für Secret-Management",
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"PostgreSQL transparent encryption",
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"Nginx TLS-Konfiguration prüfen"
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],
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"confidence_score": 0.85,
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"error": null
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}
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```
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### Control-Suggestion
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```json
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{
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"requirement_id": "req-123",
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"suggestions": [
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{
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"control_id": "PRIV-042",
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"domain": "priv",
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"title": "Verschlüsselung personenbezogener Daten",
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"description": "Alle personenbezogenen Daten müssen verschlüsselt gespeichert werden",
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"pass_criteria": "100% der PII in PostgreSQL sind AES-256 verschlüsselt",
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"implementation_guidance": "Verwende SOPS mit Age-Keys für Secrets. Aktiviere PostgreSQL transparent data encryption.",
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"is_automated": true,
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"automation_tool": "SOPS",
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"priority": "high",
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"confidence_score": 0.9
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}
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]
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}
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```
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## Troubleshooting
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### Problem: "AI provider is not available"
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Lösung:
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```bash
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# Prüfe Status
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curl http://localhost:8000/api/v1/compliance/ai/status
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# Prüfe Environment Variables
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echo $COMPLIANCE_LLM_PROVIDER
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echo $ANTHROPIC_API_KEY
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# Fallback auf Mock
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export COMPLIANCE_LLM_PROVIDER=mock
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```
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### Problem: "Requirement not found"
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Lösung:
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```bash
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# Datenbank seeden
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curl -X POST http://localhost:8000/api/v1/compliance/seed \
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-d '{"force": false}'
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# Requirements auflisten
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curl http://localhost:8000/api/v1/compliance/requirements
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```
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### Problem: Timeout bei Anthropic
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Lösung:
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```bash
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# Timeout erhöhen
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export COMPLIANCE_LLM_TIMEOUT=120.0
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# Oder Mock-Provider verwenden
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export COMPLIANCE_LLM_PROVIDER=mock
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```
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## Unit Tests
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```bash
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cd backend
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# Alle Tests
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pytest tests/test_compliance_ai.py -v
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# Nur Mock-Tests
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pytest tests/test_compliance_ai.py::TestMockProvider -v
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# Integration Tests (benötigt API-Key)
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pytest tests/test_compliance_ai.py -v --integration
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```
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## Weitere Dokumentation
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- **Vollständige Dokumentation**: `backend/docs/compliance_ai_integration.md`
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- **API Schemas**: `backend/compliance/api/schemas.py`
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- **LLM Provider**: `backend/compliance/services/llm_provider.py`
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- **AI Assistant**: `backend/compliance/services/ai_compliance_assistant.py`
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## Support
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Bei Problemen:
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1. Prüfe `/api/v1/compliance/ai/status`
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2. Prüfe Logs: `docker logs breakpilot-backend`
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3. Teste mit Mock: `COMPLIANCE_LLM_PROVIDER=mock`
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4. Siehe: `backend/docs/compliance_ai_integration.md`
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