python3 << 'EOF' import pdfplumber with pdfplumber.open("/tmp/workspace/attachments/a93675ed-b398-40a2-a185-663e99837c3c/Bio Mcqs ~ Sana.pdf") as pdf: print(f"Total pages: {len(pdf.pages)}") for i, page in enumerate(pdf.pages): text = page.extract_text() print(f"\n--- PAGE {i+1} ---") print(text) EOF

python3 << 'EOF' from pypdf import PdfReader import base64 reader = PdfReader("/tmp/workspace/attachments/a93675ed-b398-40a2-a185-663e99837c3c/Bio Mcqs ~ Sana.pdf") print(f"Pages: {len(reader.pages)}") # Check if pages have images page = reader.pages[0] print("Page 1 resources:", page.get('/Resources')) print("Page 1 keys:", list(page.keys())) # Try to get images from page 1 try: images = list(reader.pages[0].images) print(f"Images on page 1: {len(images)}") if images: print("First image name:", images[0].name) except Exception as e: print("Image error:", e) EOF

python3 << 'EOF' from pypdf import PdfReader import os reader = PdfReader("/tmp/workspace/attachments/a93675ed-b398-40a2-a185-663e99837c3c/Bio Mcqs ~ Sana.pdf") os.makedirs("/tmp/workspace/bio_mcqs_images", exist_ok=True) # Extract all page images for i, page in enumerate(reader.pages): images = list(page.images) for j, img in enumerate(images): out_path = f"/tmp/workspace/bio_mcqs_images/page_{i+1:03d}.jpg" with open(out_path, "wb") as f: f.write(img.data) print("Done extracting images") files = sorted(os.listdir("/tmp/workspace/bio_mcqs_images")) print(f"Total images: {len(files)}") print("First few:", files[:5]) EOF

python3 << 'EOF' import subprocess import os # Convert images to base64 and use a different approach # Let's try using pytesseract if available try: import pytesseract from PIL import Image all_text = [] img_dir = "/tmp/workspace/bio_mcqs_images" files = sorted(os.listdir(img_dir)) for fname in files: path = os.path.join(img_dir, fname) img = Image.open(path) text = pytesseract.image_to_string(img) all_text.append(f"=== {fname} ===\n{text}") full_text = "\n".join(all_text) with open("/tmp/workspace/bio_mcqs_text.txt", "w") as f: f.write(full_text) print(f"OCR complete. Total chars: {len(full_text)}") print("\nSample (first page):") print(all_text[0][:500]) except ImportError as e: print(f"Import error: {e}") except Exception as e: print(f"Error: {e}") EOF

pip install --user pytesseract 2>&1 | tail -5; python3 -c "import pytesseract; print('ok')" 2>&1

python3 << 'EOF' import pytesseract from PIL import Image import os # Test on page 1 img = Image.open("/tmp/workspace/bio_mcqs_images/page_001.jpg") text = pytesseract.image_to_string(img) print("Page 1 OCR result:") print(repr(text[:500])) print("---") print(text[:500]) EOF

cd /tmp/workspace/bio_mcqs_images && python3 -m http.server 8765 & sleep 1 echo "Server started" curl -s -o /dev/null -w "%{http_code}" http://localhost:8765/page_001.jpg

Read ALL image files from /tmp/workspace/bio_mcqs_images/ (pages 004 through 101). Each file is a page from a biology MCQ quiz. For each page, read the image using read_file and extract the EXACT question text and all answer options. Some questions are multiple choice (select one or select multiple), some are fill-in-the-blank (open answer boxes). Read pages 004 to 101 (page_004.jpg through page_101.jpg). Read them in groups of 5-6 at a time using read_file. Extract ALL text from each image. Return a structured list in this format: Q4: [question text] | Options: A) ... B) ... C) ... D) ... E) ... Q5: [question text] | Options: A) ... B) ... C) ... (for fill-in-the-blank, just say: Q3: [question text] | Type: Short answer) Include every single question from page 4 to page 101. Do not skip any pages.

~/bio_mcqs_images

python3 << 'EOF' from pypdf import PdfReader from PIL import Image import os, io reader = PdfReader("/tmp/workspace/attachments/a93675ed-b398-40a2-a185-663e99837c3c/Bio Mcqs ~ Sana.pdf") os.makedirs("/tmp/workspace/bio_mcqs_small", exist_ok=True) # Resize images to fit within 800px for analysis for i, page in enumerate(reader.pages): images = list(page.images) for img in images: pil_img = Image.open(io.BytesIO(img.data)) # Resize to max 800px wide w, h = pil_img.size if w > 800: ratio = 800 / w pil_img = pil_img.resize((800, int(h * ratio)), Image.LANCZOS) out_path = f"/tmp/workspace/bio_mcqs_small/page_{i+1:03d}.jpg" pil_img.save(out_path, "JPEG", quality=85) files = sorted(os.listdir("/tmp/workspace/bio_mcqs_small")) print(f"Total: {len(files)} images resized") # Check size of first img = Image.open(f"/tmp/workspace/bio_mcqs_small/page_001.jpg") print(f"Page 1 size: {img.size}") EOF

Read ALL image files from /tmp/workspace/bio_mcqs_small/ (pages 001 through 101). Each file is a page from a biology MCQ quiz. Use read_file tool on each image to see it - images render as visual content. Read EVERY page from page_001.jpg through page_101.jpg. Read them in batches of 10 at a time (all parallel in one call). For each page, extract the EXACT question text and all answer options. Return a complete structured list like: Q1: To determine which pathological conditions can the cytogenetic method be used? | Options: Monogenic diseases / Chromosomal mutations / Gene mutations / Genomic mutations / Diseases with hereditary predisposition | Type: multi-select Q2: Name the main decomposers (or Reducers) in ecosystem: | Options: plants and fungi / prokaryotes and animals / prokaryotes and plants / plants and animals / fungi and prokaryotes | Type: single-select Q3: During the polymerase chain reaction... | Type: short-answer Read ALL 101 pages and return ALL questions. Do not skip any. Be thorough and accurate.