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"content": " 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 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:\n- PERSON (Namen von Personen)\n- ORGANIZATION (Firmen, Institutionen, Gruppen)\n- CONCEPT (Fachbegriffe, Methoden, Theorien)\n- LOCATION (Orte, Länder)\n- DATE (Zeitangaben)\n- OTHER (Sonstiges)\n\nAntworte NUR im JSON-Format:\n{\"entities\": [{\"name\": \"...\", \"type\": \"...\", \"context\": \"kurzer Kontext der Erwähnung\"}]}\n\nText:\n{{TEXT}}\"\"\"\n\n prompt = prompt_template.replace(\"{{TEXT}}\", text[:4000])\n\n try:\n message = client.messages.create(\n model=ANTHROPIC_MODEL, max_tokens=2000, messages=[{\"role\": \"user\", \"content\": prompt}]\n )\n\n response_text = message.content[0].text\n\n # Extract JSON from response\n import re\n\n json_match = re.search(r\"\\{[\\s\\S]*\\}\", response_text)\n if json_match:\n entities = json.loads(json_match.group())\n return entities.get(\"entities\", [])\n return []\n except Exception as e:\n db.log(\"ERROR\", f\"Anthropic entity extraction failed: {e}\")\n return []\n",
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