Protokoll #27112

ID27112
Zeitstempel2025-12-28 02:26:55.440802
Clientroot
IP145.224.72.140
Modellclaude-sonnet-4-20250514
Statuscompleted
Tokens660 (Input: 529, Output: 131)
Dauer54206 ms
Request-Zeit2025-12-28 02:26:55.440802
Response-Zeit2025-12-28 02:27:49.646410

Request

{
    "event": "PreToolUse",
    "tool_name": "Bash",
    "tool_input": {
        "command": "DB_PASSWORD=\"v8mFLmkF2fth_r\" timeout 120 .\/venv\/bin\/python -c \"\nimport json\nimport re\nimport ollama\nfrom db import db\n\ndb.connect()\n\n# Get one entity\ncursor = db.execute('''\n    SELECT e.id, e.name, e.type, ce.chunk_id, LEFT(c.content, 300) as context\n    FROM entities e \n    JOIN chunk_entities ce ON e.id = ce.entity_id \n    JOIN chunks c ON ce.chunk_id = c.id \n    WHERE e.id = 377\n''')\nentity = cursor.fetchone()\n# Consume any remaining results\nwhile cursor.fetchone():\n    pass\ncursor.close()\n\nprint(f'Entity: {entity[\\\"name\\\"]} ({entity[\\\"type\\\"]})')\n\nPROMPT = '''Analysiere diese Entität. Antworte NUR mit JSON:\n{\\\"semantic_role\\\": \\\"agent\\\", \\\"functional_category\\\": \\\"concept\\\", \\\"context_meaning\\\": \\\"Bedeutung\\\"}\n\nEntität: ''' + entity['name'] + ''' (''' + entity['type'] + ''')'''\n\nresponse = ollama.generate(model='mistral', prompt=PROMPT, options={'num_predict': 150})\nresp_text = response['response'].strip()\nprint(f'Response: {resp_text[:200]}')\n\nmatch = re.search(r'\\{[^{}]+\\}', resp_text)\nif match:\n    sem = json.loads(match.group())\n    print(f'Parsed: {sem}')\n    \n    role = sem.get('semantic_role', 'agent')\n    cat = sem.get('functional_category', 'concept') \n    meaning = str(sem.get('context_meaning', ''))[:200]\n    \n    # Validate\n    if role not in ['agent', 'patient', 'instrument', 'location', 'cause', 'effect']:\n        role = 'agent'\n    if cat not in ['method', 'tool', 'concept', 'actor', 'outcome', 'process']:\n        cat = 'concept'\n    \n    cursor = db.execute('''INSERT INTO entity_knowledge_semantics \n        (entity_id, chunk_id, semantic_role, functional_category, context_meaning, model_used)\n        VALUES (%s, %s, %s, %s, %s, %s)''',\n        (entity['id'], entity['chunk_id'], role, cat, meaning, 'mistral'))\n    db.commit()\n    cursor.close()\n    print(f'Saved: {entity[\\\"name\\\"]} -> {role}, {cat}')\n\ndb.disconnect()\n\"",
        "timeout": 120000,
        "description": "Test single entity with fixed cursor"
    }
}

Response

{
    "tool_response": {
        "stdout": "Entity: Coach (ROLE)\nResponse: {\n\"semantic_role\": \"agent\",\n\"functional_category\": \"occupation\",\n\"context_meaning\": \"Eine Person, die eine sportliche oder mentale Entwicklung von anderen Menschen betreut.\"\n}\nParsed: {'semantic_role': 'agent', 'functional_category': 'occupation', 'context_meaning': 'Eine Person, die eine sportliche oder mentale Entwicklung von anderen Menschen betreut.'}\nSaved: Coach -> agent, concept",
        "stderr": "",
        "interrupted": false,
        "isImage": false
    }
}
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