{
"event": "PreToolUse",
"tool_name": "Bash",
"tool_input": {
"command": "PYTHONUNBUFFERED=1 .\/venv\/bin\/python -c \"\nfrom analyze import extract_entities_ollama, store_entities, link_chunk_entities\nfrom db import db\n\ndb.connect()\n\ncursor = db.execute('SELECT id, content FROM chunks WHERE document_id = 1 ORDER BY chunk_index')\nchunks = cursor.fetchall()\ncursor.close()\nprint(f'Processing {len(chunks)} chunks with normalizer...')\n\nimport time\nstart = time.time()\n\nfor i, chunk in enumerate(chunks):\n entities = extract_entities_ollama(chunk['content'][:2000])\n if entities:\n store_entities(db, entities)\n \n if (i+1) % 10 == 0:\n cursor = db.execute('SELECT COUNT(*) as cnt FROM entities')\n cnt = cursor.fetchone()['cnt']\n cursor.close()\n print(f' {i+1}\/{len(chunks)} chunks, {cnt} entities')\n\nelapsed = time.time() - start\ncursor = db.execute('SELECT COUNT(*) as cnt FROM entities')\ncnt = cursor.fetchone()['cnt']\ncursor.close()\nprint(f'Extraction: {cnt} entities in {elapsed:.1f}s')\n\nprint('Linking...')\nlinks = link_chunk_entities(1)\nprint(f'{links} chunk-entity links created')\n\ndb.disconnect()\n\" 2>&1",
"timeout": 600000,
"description": "Run full extraction pipeline with normalizer",
"run_in_background": true
}
}
{
"tool_response": {
"stdout": "",
"stderr": "",
"interrupted": false,
"isImage": false,
"backgroundTaskId": "be1637a"
}
}