# Compliance AI Integration - Quick Start

## Schnellstart (5 Minuten)

### 1. Environment Variables setzen

```bash
# In backend/.env
COMPLIANCE_LLM_PROVIDER=mock  # Für Testing ohne API-Key
# ODER
COMPLIANCE_LLM_PROVIDER=anthropic
ANTHROPIC_API_KEY=sk-ant-...
```

### 2. Backend starten

```bash
cd backend
docker-compose up -d
# ODER
uvicorn main:app --reload
```

### 3. Datenbank seeden

```bash
# Requirements und Module laden
curl -X POST http://localhost:8000/api/v1/compliance/seed \
  -H "Content-Type: application/json" \
  -d '{"force": false}'

curl -X POST http://localhost:8000/api/v1/compliance/modules/seed \
  -H "Content-Type: application/json" \
  -d '{"force": false}'
```

### 4. AI-Features testen

```bash
# Test-Script ausfuhren
python backend/scripts/test_compliance_ai_endpoints.py
```

## API Endpoints

Alle Endpoints unter: `http://localhost:8000/api/v1/compliance/ai/`

### 1. Status prufen

```bash
curl http://localhost:8000/api/v1/compliance/ai/status
```

### 2. Requirement interpretieren

```bash
curl -X POST http://localhost:8000/api/v1/compliance/ai/interpret \
  -H "Content-Type: application/json" \
  -d '{
    "requirement_id": "YOUR_REQUIREMENT_ID"
  }'
```

### 3. Controls vorschlagen

```bash
curl -X POST http://localhost:8000/api/v1/compliance/ai/suggest-controls \
  -H "Content-Type: application/json" \
  -d '{
    "requirement_id": "YOUR_REQUIREMENT_ID"
  }'
```

### 4. Modul-Risiko bewerten

```bash
curl -X POST http://localhost:8000/api/v1/compliance/ai/assess-risk \
  -H "Content-Type: application/json" \
  -d '{
    "module_id": "consent-service"
  }'
```

### 5. Gap-Analyse

```bash
curl -X POST http://localhost:8000/api/v1/compliance/ai/gap-analysis \
  -H "Content-Type: application/json" \
  -d '{
    "requirement_id": "YOUR_REQUIREMENT_ID"
  }'
```

### 6. Batch-Interpretation

```bash
curl -X POST http://localhost:8000/api/v1/compliance/ai/batch-interpret \
  -H "Content-Type: application/json" \
  -d '{
    "requirement_ids": ["id1", "id2"],
    "rate_limit": 1.0
  }'
```

## Provider-Konfiguration

### Option 1: Mock (Testing)

```bash
export COMPLIANCE_LLM_PROVIDER=mock
```

Vorteile:
- Keine API-Keys erforderlich
- Schnell
- Deterministisch

Nachteile:
- Keine echten AI-Antworten

### Option 2: Anthropic Claude (Empfohlen)

```bash
export COMPLIANCE_LLM_PROVIDER=anthropic
export ANTHROPIC_API_KEY=sk-ant-...
export ANTHROPIC_MODEL=claude-sonnet-4-20250514
```

Vorteile:
- Beste Qualitat
- Zuverlassig
- Breakpilot-optimiert

Nachteile:
- API-Kosten (~$3 per 1M input tokens)

### Option 3: Self-Hosted (Ollama/vLLM)

```bash
export COMPLIANCE_LLM_PROVIDER=self_hosted
export SELF_HOSTED_LLM_URL=http://localhost:11434
export SELF_HOSTED_LLM_MODEL=llama3.1:8b
```

Vorteile:
- Kostenlos
- Privacy (on-premise)
- Keine Rate-Limits

Nachteile:
- Geringere Qualitat als Claude
- Benotigt GPU/CPU-Ressourcen

## Beispiel-Response

### Interpretation

```json
{
  "requirement_id": "req-123",
  "summary": "Art. 32 DSGVO verlangt angemessene technische Maßnahmen zur Datensicherheit.",
  "applicability": "Gilt für alle Breakpilot-Module die personenbezogene Daten verarbeiten.",
  "technical_measures": [
    "Verschlüsselung personenbezogener Daten (AES-256)",
    "TLS 1.3 für Datenübertragung",
    "Regelmäßige Sicherheitsaudits",
    "Zugriffskontrolle mit IAM"
  ],
  "affected_modules": [
    "consent-service",
    "klausur-service",
    "backend"
  ],
  "risk_level": "high",
  "implementation_hints": [
    "SOPS mit Age-Keys für Secret-Management",
    "PostgreSQL transparent encryption",
    "Nginx TLS-Konfiguration prüfen"
  ],
  "confidence_score": 0.85,
  "error": null
}
```

### Control-Suggestion

```json
{
  "requirement_id": "req-123",
  "suggestions": [
    {
      "control_id": "PRIV-042",
      "domain": "priv",
      "title": "Verschlüsselung personenbezogener Daten",
      "description": "Alle personenbezogenen Daten müssen verschlüsselt gespeichert werden",
      "pass_criteria": "100% der PII in PostgreSQL sind AES-256 verschlüsselt",
      "implementation_guidance": "Verwende SOPS mit Age-Keys für Secrets. Aktiviere PostgreSQL transparent data encryption.",
      "is_automated": true,
      "automation_tool": "SOPS",
      "priority": "high",
      "confidence_score": 0.9
    }
  ]
}
```

## Troubleshooting

### Problem: "AI provider is not available"

Lösung:
```bash
# Prüfe Status
curl http://localhost:8000/api/v1/compliance/ai/status

# Prüfe Environment Variables
echo $COMPLIANCE_LLM_PROVIDER
echo $ANTHROPIC_API_KEY

# Fallback auf Mock
export COMPLIANCE_LLM_PROVIDER=mock
```

### Problem: "Requirement not found"

Lösung:
```bash
# Datenbank seeden
curl -X POST http://localhost:8000/api/v1/compliance/seed \
  -d '{"force": false}'

# Requirements auflisten
curl http://localhost:8000/api/v1/compliance/requirements
```

### Problem: Timeout bei Anthropic

Lösung:
```bash
# Timeout erhöhen
export COMPLIANCE_LLM_TIMEOUT=120.0

# Oder Mock-Provider verwenden
export COMPLIANCE_LLM_PROVIDER=mock
```

## Unit Tests

```bash
cd backend

# Alle Tests
pytest tests/test_compliance_ai.py -v

# Nur Mock-Tests
pytest tests/test_compliance_ai.py::TestMockProvider -v

# Integration Tests (benötigt API-Key)
pytest tests/test_compliance_ai.py -v --integration
```

## Weitere Dokumentation

- **Vollständige Dokumentation**: `backend/docs/compliance_ai_integration.md`
- **API Schemas**: `backend/compliance/api/schemas.py`
- **LLM Provider**: `backend/compliance/services/llm_provider.py`
- **AI Assistant**: `backend/compliance/services/ai_compliance_assistant.py`

## Support

Bei Problemen:
1. Prüfe `/api/v1/compliance/ai/status`
2. Prüfe Logs: `docker logs breakpilot-backend`
3. Teste mit Mock: `COMPLIANCE_LLM_PROVIDER=mock`
4. Siehe: `backend/docs/compliance_ai_integration.md`