cd /tmp/workspace/attachments/b9a37df6-4850-4642-ba87-efc13868e0dd/ && python3 -c " import pdfplumber pdf_path = '10. FMT Hyperrevision.pdf' with pdfplumber.open(pdf_path) as pdf: print(f'Total pages: {len(pdf.pages)}') # Show first 2 pages text to understand structure for i, page in enumerate(pdf.pages[:3]): text = page.extract_text() print(f'--- PAGE {i+1} ---') print(text[:1000] if text else '[No text]') print() "

cd /tmp/workspace/attachments/b9a37df6-4850-4642-ba87-efc13868e0dd/ && python3 -c " import pdfplumber pdf_path = '10. FMT Hyperrevision.pdf' all_pages = {} with pdfplumber.open(pdf_path) as pdf: for i, page in enumerate(pdf.pages): text = page.extract_text() all_pages[i+1] = text if text else '' # Save to file import json with open('/tmp/workspace/fmt_pages.json', 'w') as f: json.dump(all_pages, f) print('Done extracting', len(all_pages), 'pages') # Print lengths for pg, txt in all_pages.items(): print(f'Page {pg}: {len(txt)} chars') "

You are a medical education expert. Your job is to read extracted text from an FMT (Forensic Medicine & Toxicology) PDF and generate exactly 20 one-word answer questions from each page. The extracted text is saved at: /tmp/workspace/fmt_pages.json This JSON file maps page numbers (as strings "1" through "42") to the extracted text of each page. Pages 40-42 are nearly empty (ignore them). So work on pages 1 through 39. For each page: 1. Read the text content 2. Generate exactly 20 questions whose answers are ONE WORD each (a single term, number, name, or short phrase of max 2 words if truly unavoidable) 3. Questions should be factual, directly answerable from the page text 4. Format: Q: [question] | A: [one-word/short answer] Output a Python dictionary (as a .py file) saved to /tmp/workspace/fmt_qa.py with this structure: ```python qa_data = { 1: [ {"q": "What term describes moral principles in medical conduct?", "a": "Ethics"}, ... # 20 items ], 2: [...], ... 39: [...] } ``` Make sure every page has exactly 20 Q&A pairs. The questions must be directly based on the text of that specific page. Answers must be one word or at most two words (like "Res Ipsa", "BNS Section", etc.). Read the JSON file first using the read_file tool or execute tool, then generate the questions page by page. IMPORTANT: Save the final output as a valid Python file at /tmp/workspace/fmt_qa.py Here is the content of each page to help you get started - you MUST read /tmp/workspace/fmt_pages.json using execute: ```python import json with open('/tmp/workspace/fmt_pages.json') as f: pages = json.load(f) # pages is a dict with string keys "1" to "42" ``` Generate all 39 pages worth of Q&A (pages 1-39) and write to /tmp/workspace/fmt_qa.py

cd /tmp/workspace && python3 -c " import json with open('fmt_pages.json') as f: pages = json.load(f) print('Keys:', list(pages.keys())[:5]) print('Total pages:', len(pages)) print('--- PAGE 1 ---') print(pages['1'][:3000]) "

cd /tmp/workspace && python3 -c " import json with open('fmt_pages.json') as f: pages = json.load(f) for p in ['2','3','4','5']: print(f'--- PAGE {p} ---') print(pages[p][:2500]) print() "

cd /tmp/workspace && python3 -c " import json with open('fmt_pages.json') as f: pages = json.load(f) for p in ['6','7','8','9','10']: print(f'--- PAGE {p} ---') print(pages[p][:2500]) print() "

cd /tmp/workspace && python3 -c " import json with open('fmt_pages.json') as f: pages = json.load(f) for p in ['11','12','13','14','15']: print(f'--- PAGE {p} ---') print(pages[p][:2500]) print() "

cd /tmp/workspace && python3 -c " import json with open('fmt_pages.json') as f: pages = json.load(f) for p in ['16','17','18','19','20']: print(f'--- PAGE {p} ---') print(pages[p][:2500]) print() "

cd /tmp/workspace && python3 -c " import json with open('fmt_pages.json') as f: pages = json.load(f) for p in ['21','22','23','24','25']: print(f'--- PAGE {p} ---') print(pages[p][:2500]) print() "

cd /tmp/workspace && python3 -c " import json with open('fmt_pages.json') as f: pages = json.load(f) for p in ['26','27','28','29','30']: print(f'--- PAGE {p} ---') print(pages[p][:2500]) print() "

cd /tmp/workspace && python3 -c " import json with open('fmt_pages.json') as f: pages = json.load(f) for p in ['31','32','33','34','35']: print(f'--- PAGE {p} ---') print(pages[p][:2500]) print() "

cd /tmp/workspace && python3 -c " import json with open('fmt_pages.json') as f: pages = json.load(f) for p in ['36','37','38','39']: print(f'--- PAGE {p} ---') print(pages[p][:3000]) print() "