{
"event": "PreToolUse",
"tool_name": "Grep",
"tool_input": {
"pattern": "Semantische Analyse|analyze_document",
"path": "\/opt\/scripts\/pipeline",
"glob": "*.py",
"output_mode": "content"
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{
"tool_response": {
"mode": "content",
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"content": "\/opt\/scripts\/pipeline\/pipeline.py:21:from analyze import analyze_document\n\/opt\/scripts\/pipeline\/pipeline.py:152: progress.add_log(\"Semantische Analyse...\")\n\/opt\/scripts\/pipeline\/pipeline.py:155: analysis = analyze_document(doc_id, full_text)\n\/opt\/scripts\/pipeline\/semantic_chunk_analyzer.py:40: \"\"\"Semantische Analyse eines Chunks.\"\"\"\n\/opt\/scripts\/pipeline\/vision.py:131:def analyze_document(file_path, model=DEFAULT_VISION_MODEL, store_images=False, image_dir=None, progress=None):\n\/opt\/scripts\/pipeline\/vision.py:209: page_results: List of page analysis results from analyze_document()\n\/opt\/scripts\/pipeline\/vision.py:299: results = analyze_document(file_path, model=model, store_images=store_images, progress=progress)\n\/opt\/scripts\/pipeline\/vision.py:370: results = analyze_document(file_path, store_images=True)\n\/opt\/scripts\/pipeline\/knowledge.py:781: def analyze_document(self, document_id: int, text: str) -> dict:\n\/opt\/scripts\/pipeline\/knowledge.py:866: results[\"document\"] = extractor.analyze_document(document_id, doc[\"full_text\"][:10000])\n\/opt\/scripts\/pipeline\/analyze.py:358:def analyze_document(document_id, text, use_anthropic=True):",
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