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"content": "\n\ndef extract_entities_ollama(text, model=\"gemma3:27b-it-qat\"):\n \"\"\"Extract entities using Ollama.\"\"\"\n # Load prompt from database\n prompt_template = db.get_prompt(\"entity_extraction\")\n\n if not prompt_template:\n db.log(\"WARNING\", \"entity_extraction prompt not found in DB, using fallback\")\n prompt_template = \"\"\"Analysiere den Text und extrahiere wichtige Entitäten.\nKategorisiere als: PERSON, ORGANIZATION, CONCEPT, LOCATION\nAntworte NUR im JSON-Format:\n{\"entities\": [{\"name\": \"...\", \"type\": \"...\", \"description\": \"...\"}]}\n\nText:\n{{TEXT}}\"\"\"\n\n prompt = prompt_template.replace(\"{{TEXT}}\", text[:3000])\n\n try:\n start_time = time.time()\n response = requests.post(\n f\"{OLLAMA_HOST}\/api\/generate\",\n json={\"model\": model, \"prompt\": prompt, \"stream\": False, \"format\": \"json\"},\n timeout=120,\n )\n response.raise_for_status()\n data = response.json()\n duration_ms = int((time.time() - start_time) * 1000)\n\n # Parse JSON from response\n response_text = data.get(\"response\", \"{}\")\n\n # Log to ki-protokoll\n protokoll.log_llm_call(\n request=f\"[entity_extraction] {prompt[:500]}...\",\n response=response_text[:2000],\n model_name=f\"ollama:{model}\",\n tokens_input=data.get(\"prompt_eval_count\", 0),\n tokens_output=data.get(\"eval_count\", 0),\n duration_ms=duration_ms,\n status=\"completed\",\n )\n\n try:\n entities = json.loads(response_text)\n return entities.get(\"entities\", [])\n except json.JSONDecodeError:\n db.log(\"WARNING\", \"Failed to parse entity JSON from Ollama\")\n return []\n except Exception as e:\n db.log(\"ERROR\", f\"Ollama entity extraction failed: {e}\")\n protokoll.log_llm_call(\n request=f\"[entity_extraction] {prompt[:500]}...\",\n model_name=f\"ollama:{model}\",\n status=\"error\",\n error_message=str(e),\n )\n return []\n\n\ndef extract_entities_anthropic(text, client):\n \"\"\"Extract entities using Anthropic Claude.\"\"\"\n # Get prompt from database\n prompt_template = db.get_prompt(\"entity_extraction\")\n\n if not prompt_template:\n prompt_template = \"\"\"Analysiere den folgenden deutschen Text und extrahiere alle wichtigen Entitäten.\n\nKategorisiere jede Entität als:",
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