{
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"content": " total_pages = extract_result.get(\"total_pages\", 0)\n\n # Check if cancelled after extraction\n if progress and progress.is_cancelled():\n return \"cancelled\", 0, 0\n\n # Step 2: Load document\n doc_id = load_step.create_document(file_info)\n\n # Step 3: Vision analysis (PDFs only)\n if file_info[\"type\"] == \".pdf\":\n transform_step.execute_vision(doc_id, file_path, file_info[\"type\"])\n\n # Check if cancelled after vision\n if progress and progress.is_cancelled():\n return \"cancelled\", 0, 0\n\n # Step 4: Chunking\n chunks = transform_step.execute_chunking(extraction, total_pages)\n\n # Step 5: Store chunks\n chunks = load_step.store_chunks(doc_id, chunks)\n\n # Check if cancelled after chunking\n if progress and progress.is_cancelled():\n return \"cancelled\", len(chunks), 0\n\n # Step 6: Enrichment (PDFs only)\n if file_info[\"type\"] == \".pdf\":\n transform_step.execute_enrichment(doc_id, file_info[\"type\"])\n\n # Check if cancelled after enrichment\n if progress and progress.is_cancelled():\n return \"cancelled\", len(chunks), 0\n\n # Step 7: Embeddings\n embedded = embed_step.execute(chunks, doc_id, file_name, file_path)\n\n # Check if cancelled after embedding\n if progress and progress.is_cancelled():\n return \"cancelled\", len(chunks), embedded\n\n # Step 8: Semantic analysis\n full_text = extract_step.get_full_text_from_extraction(extraction)\n transform_step.execute_analysis(doc_id, full_text)\n\n # Step 9: Update status\n load_step.update_document_status(doc_id, \"done\")\n\n if progress:",
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