{
"assistant_response": "## Antwort: BEIDES\n\n### ✅ DB-Konfiguration existiert (GUI)\n\n```\npipeline_steps (ki_content, Pipeline #5):\n├── text_semantic_analyze: \"model\": \"mistral\"\n├── entity_extract: \"model\": \"mistral\" \n└── knowledge_semantic_analyze: \"model\": \"mistral\"\n```\n\n### ⚠️ ABER: Noch hardcodiert in Python\n\n| Datei | Zeile | Problem |\n|-------|-------|---------|\n| `pipeline.py` | 242 | `{\"model\": \"mistral\"}` |\n| `pipeline.py` | 286 | `{\"model\": \"mistral\"}` |\n| `pipeline.py` | 557 | `model = \"mistral:latest\"` |\n| `step_semantic_extended.py` | 126, 286 | `config.get(\"model\", \"mistral\")` |\n| `step_entity_enrich.py` | 20 | `DEFAULT_MODEL = \"mistral:latest\"` |\n| `generate_entity_descriptions.py` | 30 | `DEFAULT_MODEL = \"mistral:latest\"` |\n\n### Empfehlung\n\n**Option A**: Nur DB ändern (Quick-Fix)\n```sql\nUPDATE pipeline_steps \nSET config = JSON_SET(config, '$.model', 'gemma3:27b-it-qat')\nWHERE pipeline_id = 5 \n AND step_type IN ('text_semantic_analyze', 'knowledge_semantic_analyze', 'entity_extract');\n```\n\n**Option B**: Hardcoded Werte entfernen (Clean Solution)\n- Alle Python-Files auf `get_pipeline_model()` umstellen\n- Dann greift DB-Config automatisch\n\nWas soll ich tun?"
}