Protokoll #25080

ID25080
Zeitstempel2025-12-28 02:13:42.805373
Clientroot
IP145.224.72.140
Modellclaude-sonnet-4-20250514
Statuscompleted
Tokens731 (Input: 622, Output: 109)
Dauer27511 ms
Request-Zeit2025-12-28 02:13:42.805373
Response-Zeit2025-12-28 02:14:10.316609

Request

{
    "event": "PreToolUse",
    "tool_name": "Bash",
    "tool_input": {
        "command": "cd \/var\/www\/scripts\/pipeline && 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 chunks for doc 12\ncursor = db.execute('SELECT id, content FROM chunks WHERE document_id = 12 LIMIT 3')\nchunks = cursor.fetchall()\ncursor.close()\n\nPROMPT = '''Analysiere den Text. Antworte NUR mit diesem JSON-Format:\n{\\\"statement_form\\\": \\\"assertion\\\", \\\"intent\\\": \\\"explain\\\", \\\"frame\\\": \\\"practical\\\", \\\"is_negated\\\": false, \\\"discourse_role\\\": \\\"thesis\\\"}\n\nText: '''\n\nfor chunk in chunks:\n    print(f'Chunk {chunk[\\\"id\\\"]}...')\n    try:\n        response = ollama.generate(model='mistral', prompt=PROMPT + chunk['content'][:1000], options={'num_predict': 150})\n        resp_text = response['response'].strip()\n        \n        # Extract first JSON object\n        match = re.search(r'\\{[^{}]+\\}', resp_text)\n        if match:\n            sem = json.loads(match.group())\n            print(f'  -> {sem.get(\\\"statement_form\\\")}, {sem.get(\\\"intent\\\")}, {sem.get(\\\"discourse_role\\\")}')\n            \n            # Store in DB\n            cursor = db.execute('''INSERT INTO chunk_text_semantics \n                (chunk_id, statement_form, intent, frame, is_negated, discourse_role, model_used)\n                VALUES (%s, %s, %s, %s, %s, %s, %s)\n                ON DUPLICATE KEY UPDATE statement_form=VALUES(statement_form), intent=VALUES(intent),\n                frame=VALUES(frame), discourse_role=VALUES(discourse_role)''',\n                (chunk['id'], sem.get('statement_form','assertion'), sem.get('intent'), sem.get('frame'), \n                 sem.get('is_negated', False), sem.get('discourse_role'), 'mistral'))\n            db.commit()\n            cursor.close()\n            print('  -> Saved!')\n        else:\n            print(f'  -> No JSON found')\n    except Exception as e:\n        print(f'  -> Error: {e}')\n\nprint()\nprint('Verify stored data:')\ncursor = db.execute('SELECT chunk_id, statement_form, intent, discourse_role FROM chunk_text_semantics LIMIT 5')\nfor row in cursor.fetchall():\n    print(f'  Chunk {row[\\\"chunk_id\\\"]}: {row[\\\"statement_form\\\"]}, {row[\\\"intent\\\"]}, {row[\\\"discourse_role\\\"]}')\ncursor.close()\n\ndb.disconnect()\n\"",
        "timeout": 180000,
        "description": "Test semantic analysis with full path"
    }
}

Response

{
    "tool_response": {
        "stdout": "Chunk 41...\n  -> explanation, describe, background\n  -> Error: 1265 (01000): Data truncated for column 'statement_form' at row 1\nChunk 42...\n  -> assertion, explain, thesis\n  -> Saved!\nChunk 43...\n  -> assertion, explain, thesis\n  -> Saved!\n\nVerify stored data:\n  Chunk 42: assertion, explain, thesis\n  Chunk 43: assertion, explain, thesis",
        "stderr": "",
        "interrupted": false,
        "isImage": false
    }
}
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