Protokoll #10547
| ID | 10547 |
|---|---|
| Zeitstempel | 2025-12-23 15:27:55.326465 |
| Client | root |
| IP | Warning: Undefined array key "request_ip" in /var/www/dev.campus.systemische-tools.de/src/View/protokoll/show.php on line 13 Deprecated: htmlspecialchars(): Passing null to parameter #1 ($string) of type string is deprecated in /var/www/dev.campus.systemische-tools.de/src/View/protokoll/show.php on line 13 |
| Modell | claude-sonnet-4-20250514 |
| Status | completed |
| Tokens | 375 (Input: 0, Output: 0) |
| Dauer | 127 ms |
| Request-Zeit | Warning: Undefined array key "request_timestamp" in /var/www/dev.campus.systemische-tools.de/src/View/protokoll/show.php on line 18 |
| Response-Zeit | - |
Warning: Undefined array key "error_message" in /var/www/dev.campus.systemische-tools.de/src/View/protokoll/show.php on line 22
Request
{
"event": "PreToolUse",
"tool_name": "Read",
"tool_input": {
"file_path": "\/opt\/scripts\/pipeline\/analyze.py",
"offset": 639,
"limit": 50
}
}Response
{
"tool_response": {
"type": "text",
"file": {
"filePath": "\/opt\/scripts\/pipeline\/analyze.py",
"content": "def analyze_chunks_semantics(document_id, client=None):\n \"\"\"Analyze all chunks of a document for semantics.\"\"\"\n cursor = db.execute(\n \"SELECT id, content FROM chunks WHERE document_id = %s ORDER BY chunk_index\",\n (document_id,)\n )\n chunks = cursor.fetchall()\n cursor.close()\n\n db.log(\"INFO\", f\"Analyzing semantics for {len(chunks)} chunks\")\n\n analyzed = 0\n for chunk in chunks:\n result = analyze_chunk_semantics(chunk[\"id\"], chunk[\"content\"], client)\n if result:\n analyzed += 1\n\n db.log(\"INFO\", f\"Analyzed {analyzed}\/{len(chunks)} chunks for semantics\")\n return analyzed\n\n\nif __name__ == \"__main__\":\n test_text = \"\"\"\n Carl Rogers entwickelte die klientenzentrierte Gesprächstherapie.\n Diese Methode basiert auf Empathie, Kongruenz und bedingungsloser Wertschätzung.\n Sie wird heute weltweit in der Psychotherapie eingesetzt.\n \"\"\"\n\n print(\"Testing entity extraction with Ollama...\")\n entities = extract_entities_ollama(test_text)\n print(f\"Found {len(entities)} entities:\")\n for e in entities:\n print(f\" - {e['name']} ({e['type']})\")\n",
"numLines": 34,
"startLine": 639,
"totalLines": 672
}
}
}