Protokoll #13636

ID13636
Zeitstempel2025-12-25 02:08:21.296714
Clientroot
IP145.224.72.140
Modellclaude-sonnet-4-20250514
Statuscompleted
Tokens326 (Input: 277, Output: 49)
Dauer88722 ms
Request-Zeit2025-12-25 02:08:21.296714
Response-Zeit2025-12-25 02:09:50.018310

Request

{
    "event": "PreToolUse",
    "tool_name": "Bash",
    "tool_input": {
        "command": "# Verify search actually works (brute force should still work)\necho \"=== Search Performance Test ===\"\ncd \/var\/www\/scripts\/pipeline\n\n# Generate a test vector\n.\/venv\/bin\/python << 'EOF'\nimport requests\nimport time\n\n# Get embedding\nresp = requests.post('http:\/\/localhost:11434\/api\/embeddings', json={\n    'model': 'mxbai-embed-large',\n    'prompt': 'Was ist systemisches Coaching?'\n})\nvector = resp.json()['embedding']\n\n# Time the search\nstart = time.time()\nsearch_resp = requests.post('http:\/\/localhost:6333\/collections\/documents\/points\/search', json={\n    'vector': vector,\n    'limit': 5,\n    'with_payload': False\n})\nelapsed = time.time() - start\ndata = search_resp.json()\n\nresults = data.get('result', [])\nprint(f'Search time: {elapsed*1000:.1f}ms')\nprint(f'Results: {len(results)}')\nif results:\n    print(f'Top score: {results[0][\"score\"]:.4f}')\n    print(f'Score range: {results[-1][\"score\"]:.4f} - {results[0][\"score\"]:.4f}')\nEOF",
        "timeout": 30000,
        "description": "Test search performance"
    }
}

Response

{
    "tool_response": {
        "stdout": "=== Search Performance Test ===\nSearch time: 3.4ms\nResults: 5\nTop score: 0.8739\nScore range: 0.8462 - 0.8739",
        "stderr": "",
        "interrupted": false,
        "isImage": false
    }
}
← Vorheriger Zur Liste Nächster →