{
"event": "PreToolUse",
"tool_name": "Read",
"tool_input": {
"file_path": "\/opt\/scripts\/pipeline\/vision.py",
"offset": 155,
"limit": 40
}
}
{
"tool_response": {
"type": "text",
"file": {
"filePath": "\/opt\/scripts\/pipeline\/vision.py",
"content": "\n results = []\n\n for page in pages:\n page_num = page[\"page_number\"]\n db.log(\"INFO\", f\"Analyzing page {page_num}\/{len(pages)}\")\n\n # Optional: Save image to disk\n image_path = None\n if store_images:\n filename = f\"{Path(file_path).stem}_page_{page_num:03d}.{IMAGE_FORMAT}\"\n image_path = os.path.join(image_dir, filename)\n with open(image_path, \"wb\") as f:\n f.write(page[\"image_bytes\"])\n\n # Analyze with vision model\n analysis = analyze_image_ollama(page[\"image_bytes\"], model=model)\n\n results.append(\n {\n \"page_number\": page_num,\n \"width\": page[\"width\"],\n \"height\": page[\"height\"],\n \"size_kb\": page[\"size_kb\"],\n \"image_path\": image_path,\n \"analysis\": analysis.get(\"analysis\", \"\") if analysis[\"success\"] else None,\n \"error\": analysis.get(\"error\") if not analysis[\"success\"] else None,\n \"eval_tokens\": analysis.get(\"eval_count\", 0),\n \"eval_duration_ms\": analysis.get(\"eval_duration_ms\", 0),\n }\n )\n\n if analysis[\"success\"]:\n db.log(\"INFO\", f\"Page {page_num} analyzed: {analysis.get('eval_count', 0)} tokens\")\n else:\n db.log(\"WARNING\", f\"Page {page_num} analysis failed: {analysis.get('error')}\")\n\n return results\n\n",
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"totalLines": 364
}
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}