{
"event": "PreToolUse",
"tool_name": "Read",
"tool_input": {
"file_path": "\/var\/www\/scripts\/pipeline\/step_semantic_extended.py",
"offset": 120,
"limit": 20
}
}
{
"tool_response": {
"type": "text",
"file": {
"filePath": "\/var\/www\/scripts\/pipeline\/step_semantic_extended.py",
"content": " list: Chunks with added 'text_semantics' field\n \"\"\"\n if self.progress:\n self.progress.update_step(\"text_semantic_analyze\")\n self.progress.add_log(f\"Textsemantik-Analyse für {len(chunks)} Chunks...\")\n\n model = config.get(\"model\", \"mistral\")\n analyzed = 0\n errors = 0\n\n for chunk in chunks:\n try:\n prompt = self.PROMPT_TEMPLATE.format(content=chunk[\"content\"][:2000])\n\n response = ollama.generate(\n model=model,\n prompt=prompt,\n options={\"num_predict\": 200},\n )\n",
"numLines": 20,
"startLine": 120,
"totalLines": 461
}
}
}