cd "/tmp/workspace/attachments/d796a7e2-2668-4999-a743-36cfb6df8727/" && python3 -c " import pdfplumber import json pdf_path = 'DocScanner 27-Jul-2026 10-26 AM.pdf' all_text = [] with pdfplumber.open(pdf_path) as pdf: print(f'Total pages: {len(pdf.pages)}') for i, page in enumerate(pdf.pages): text = page.extract_text() if text: all_text.append(f'=== PAGE {i+1} ===\n{text}') else: all_text.append(f'=== PAGE {i+1} === [no text extracted]') full = '\n\n'.join(all_text) print(full[:8000]) "

python3 -c " from PIL import Image import pypdf, io, os pdf_path = '/tmp/workspace/attachments/d796a7e2-2668-4999-a743-36cfb6df8727/DocScanner 27-Jul-2026 10-26 AM.pdf' out_dir = '/tmp/workspace/qp_pages' os.makedirs(out_dir, exist_ok=True) # Try extracting images from PDF pages reader = pypdf.PdfReader(pdf_path) print(f'Pages: {len(reader.pages)}') for i, page in enumerate(reader.pages): images = page.images print(f'Page {i+1}: {len(images)} images') if images: img_data = images[0].data with open(f'{out_dir}/page_{i+1:02d}.jpg', 'wb') as f: f.write(img_data) print(f' Saved page_{i+1:02d}.jpg, size={len(img_data)}') "

python3 -c " import os # Check if tesseract or any OCR tools are available import subprocess result = subprocess.run(['which', 'tesseract'], capture_output=True, text=True) print('tesseract:', result.stdout.strip()) result2 = subprocess.run(['python3', '-c', 'import pytesseract; print(pytesseract.__version__)'], capture_output=True, text=True) print('pytesseract:', result2.stdout.strip(), result2.stderr.strip()) result3 = subprocess.run(['python3', '-c', 'import easyocr; print(\"easyocr ok\")'], capture_output=True, text=True) print('easyocr:', result3.stdout.strip(), result3.stderr.strip()[:100]) "

pip install --user pytesseract 2>&1 | tail -3; apt-get install -y tesseract-ocr 2>&1 | tail -5

python3 -c " import sys sys.path.insert(0, '/opt/amazon/genesis1p-tools/var/.local/lib/python3.12/site-packages') import pytesseract from PIL import Image import os pages_dir = '/tmp/workspace/qp_pages' out_file = '/tmp/workspace/qp_text.txt' all_text = [] for i in range(1, 25): img_path = f'{pages_dir}/page_{i:02d}.jpg' if os.path.exists(img_path): try: img = Image.open(img_path) text = pytesseract.image_to_string(img) all_text.append(f'=== PAGE {i} ===\n{text}') print(f'Page {i}: {len(text)} chars') except Exception as e: print(f'Page {i} error: {e}') with open(out_file, 'w') as f: f.write('\n\n'.join(all_text)) print('Done. Total pages:', len(all_text)) " 2>&1

python3 -c " # Try markitdown on the PDF from markitdown import MarkItDown md = MarkItDown() result = md.convert('/tmp/workspace/attachments/d796a7e2-2668-4999-a743-36cfb6df8727/DocScanner 27-Jul-2026 10-26 AM.pdf') print(result.text_content[:3000]) " 2>&1

python3 -c " import base64, os # Convert first few pages to base64 to use with analyse_media via data URL img_path = '/tmp/workspace/qp_pages/page_01.jpg' with open(img_path, 'rb') as f: data = f.read() b64 = base64.b64encode(data).decode() print(f'Page 1 size: {len(data)} bytes, b64 length: {len(b64)}') print('data:image/jpeg;base64,' + b64[:100] + '...') # Also serve files via a simple HTTP server - check if we can import subprocess r = subprocess.run(['python3', '-m', 'http.server', '--help'], capture_output=True, text=True) print('http.server available:', 'usage' in r.stdout.lower() or 'usage' in r.stderr.lower()) "

# Start a background HTTP server to serve the images, then use analyse_media with the URL python3 -m http.server 8765 --directory /tmp/workspace/qp_pages & SERVER_PID=$! echo "Server PID: $SERVER_PID" sleep 2 # Test if it's running curl -s -I http://localhost:8765/page_01.jpg | head -5 echo "---" echo $SERVER_PID > /tmp/http_server_pid.txt

I need you to read and extract ALL text from 24 scanned question paper images saved at /tmp/workspace/qp_pages/page_01.jpg through page_24.jpg. These are pages from a 10-year previous year question paper (likely an Indian university or board exam). The images are scanned pages. Your job: 1. Use the `analyse_media` tool with localhost URLs to read each page image. The images are served at http://localhost:8765/page_01.jpg, http://localhost:8765/page_02.jpg ... http://localhost:8765/page_24.jpg 2. For EACH page, extract: the exam year (if shown), subject name, all question numbers and their full question text. 3. After reading all pages, compile a COMPLETE structured list of all questions organized by year and topic. 4. Identify which topics/questions repeat across years. 5. Return the COMPLETE raw transcript of all questions + a summary of repeating topics. Use analyse_media tool for EACH page URL (batch them in groups of 4-5 at a time for efficiency). Return: - Full question list by year - Topics that appear in 2+ years (repeat topics) - Topics that appear in 3+ years (very frequently tested) - The subject/course name of this exam

~/qp_pages

ls /tmp/workspace/ && mkdir -p /tmp/workspace/qr-pdf

python3 << 'EOF' from reportlab.lib.pagesizes import A4 from reportlab.lib import colors from reportlab.lib.units import cm from reportlab.platypus import SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer, HRFlowable from reportlab.lib.styles import ParagraphStyle from reportlab.lib.enums import TA_CENTER, TA_LEFT from reportlab.pdfbase import pdfmetrics output = "/tmp/workspace/qr-pdf/Last_Minute_Checklist.pdf" doc = SimpleDocTemplate( output, pagesize=A4, topMargin=0.6*cm, bottomMargin=0.6*cm, leftMargin=1.0*cm, rightMargin=1.0*cm ) # Colors RED = colors.HexColor("#C0392B") ORANGE = colors.HexColor("#E67E22") GREEN = colors.HexColor("#27AE60") BLUE = colors.HexColor("#2980B9") DGRAY = colors.HexColor("#2C3E50") LGRAY = colors.HexColor("#ECF0F1") WHITE = colors.white YELLOW = colors.HexColor("#F9E79F") PINK = colors.HexColor("#FADBD8") LGREEN = colors.HexColor("#D5F5E3") LORANGE = colors.HexColor("#FDEBD0") story = [] # ── HEADER ────────────────────────────────────────────────────────────────── header_data = [[ Paragraph( '<font color="white"><b>PAPER XIII — PAEDIATRICS &amp; GERIATRICS</b><br/>' 'Last-Minute Revision Checklist &nbsp;|&nbsp; BPT / BOT &nbsp;|&nbsp; Exam: 30 July 2026</font>', ParagraphStyle('h', fontSize=12, leading=16, alignment=TA_CENTER) ) ]] header_table = Table(header_data, colWidths=[19*cm]) header_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,-1), DGRAY), ('ALIGN', (0,0), (-1,-1), 'CENTER'), ('VALIGN', (0,0), (-1,-1), 'MIDDLE'), ('TOPPADDING', (0,0), (-1,-1), 8), ('BOTTOMPADDING', (0,0), (-1,-1), 8), ('ROUNDEDCORNERS', [4]), ])) story.append(header_table) story.append(Spacer(1, 0.25*cm)) # ── LEGEND ────────────────────────────────────────────────────────────────── legend_data = [[ Paragraph('<b>🔴 MUST KNOW</b> — Very likely in exam', ParagraphStyle('l', fontSize=8, alignment=TA_CENTER)), Paragraph('<b>🟠 HIGH PRIORITY</b> — Probable question', ParagraphStyle('l', fontSize=8, alignment=TA_CENTER)), Paragraph('<b>🟡 GOOD TO KNOW</b> — Easy marks if comes', ParagraphStyle('l', fontSize=8, alignment=TA_CENTER)), Paragraph('<b>☐</b> Tick when revised', ParagraphStyle('l', fontSize=8, alignment=TA_CENTER)), ]] leg_table = Table(legend_data, colWidths=[4.75*cm]*4) leg_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (0,0), PINK), ('BACKGROUND', (1,0), (1,0), LORANGE), ('BACKGROUND', (2,0), (2,0), YELLOW), ('BACKGROUND', (3,0), (3,0), LGRAY), ('ALIGN', (0,0), (-1,-1), 'CENTER'), ('VALIGN', (0,0), (-1,-1), 'MIDDLE'), ('TOPPADDING', (0,0), (-1,-1), 4), ('BOTTOMPADDING', (0,0), (-1,-1), 4), ('BOX', (0,0), (-1,-1), 0.5, colors.grey), ('INNERGRID', (0,0), (-1,-1), 0.5, colors.grey), ])) story.append(leg_table) story.append(Spacer(1, 0.25*cm)) # ── HELPER STYLES ──────────────────────────────────────────────────────────── def sec_hdr(text, bg): return Paragraph( f'<font color="white"><b>{text}</b></font>', ParagraphStyle('sh', fontSize=9, alignment=TA_CENTER) ), bg def row(priority, topic, hint): box = "☐" if priority == "R": bg, dot = PINK, "🔴" elif priority == "O": bg, dot = LORANGE, "🟠" else: bg, dot = YELLOW, "🟡" t = Paragraph(f'{dot} <b>{topic}</b>', ParagraphStyle('t', fontSize=8, leading=10)) h = Paragraph(f'<i>{hint}</i>', ParagraphStyle('h', fontSize=7, leading=9, textColor=colors.HexColor("#555555"))) return [box, t, h, bg] # ── DATA ───────────────────────────────────────────────────────────────────── paeds_rows = [ row("R","Cerebral Palsy", "Def → Classification (spastic/athetoid/ataxic) → Aetio → Clinical → Mgmt"), row("R","Fallot's Tetralogy", "Nada's criteria | 4 defects: VSD, PS, RVH, Overriding Aorta | Tet spell Rx"), row("R","PEM / Marasmus / Kwashiorkor","Classify: Mild/Mod/Severe | Compare Marasmus vs Kwashiorkor table | Mgmt"), row("R","Down's Syndrome", "Trisomy 21 | Simian crease, epicanthic fold | IQ, cardiac defects | Mgmt"), row("R","National Immunization Sched.","BCG, OPV, DPT, HepB, IPV, MR, JE — ages for each. Vitamin A doses"), row("R","Lumbar Puncture", "Indications, contraindications, L3-L4 level, procedure steps, CSF findings"), row("R","Milestones of Development", "0→3→6→9→12→18 months, 2 yrs: gross motor, fine motor, speech, social"), row("R","Cephalhaematoma", "Subperiosteal bleed, doesn't cross suture, vs caput succedaneum"), row("R","Juvenile Idiopathic Arthritis","Pauci/Poly/Systemic types | RF, ANA | Uveitis | NSAIDs, DMARDs"), row("O","Hydrocephalus", "Obstructive vs communicating | Sunset sign | VP shunt"), row("O","Duchenne Muscular Dystrophy","X-linked recessive | Dystrophin | Gower's sign | Pseudohypertrophy | CK↑"), row("O","Advantages of Breast Feeding","Colostrum, IgA, bonding, nutrition, anti-infective factors"), row("O","Meningomyelocele", "Neural tube defect | L/S region | Arnold-Chiari | Surgical closure"), row("O","Club Foot (CTEV)", "Cavus, Adductus, Varus, Equinus | Ponseti method | Denis Browne splint"), row("O","Rickets", "Vit D deficiency | Craniotabes, rachitic rosary, Harrison's sulcus | Rx: Vit D"), row("Y","Pneumonia", "Streptococcal | Consolidation | Fever, cough, tachypnoea | Amoxicillin"), row("Y","Febrile Seizures", "6m–5yr, temp >38°C, simple vs complex | Diazepam | Reassure parents"), row("Y","Ventricular Septal Defect", "Holosystolic murmur L sternal border | Eisenmenger | Surgical closure"), row("Y","Apgar Score", "A-Appearance P-Pulse G-Grimace A-Activity R-Respiration | 0/1/2 each"), ] geri_rows = [ row("R","Hypertension in Elderly", "ISH (SBP≥140, DBP<90) | Thiazide/CCB first line | Target <150/90 in >60yr"), row("R","Physiological Changes of Ageing","CVS: ↓CO | Resp: ↓FEV1 | Renal: ↓GFR | CNS: ↓neurons | MSK: ↓BMD"), row("R","Sleep Disorders in Elderly", "Insomnia, OSA, RLS | Non-pharm first (sleep hygiene) | CBT-I | Melatonin"), row("R","Depression in Elderly", "GDS scale | Bio-psycho-social factors | SSRIs | ECT if severe | Suicide risk"), row("R","Dementia / Alzheimer's", "MMSE <24 | Stages: mild/mod/severe | Cholinesterase inhibitors | Memantine"), row("R","Stroke in Elderly", "Ischaemic (80%) vs Haemorrhagic | FAST | tPA <4.5h | Rehab, aspirin"), row("O","Diabetes Mellitus in Elderly","Atypical presentation | HbA1c target <7.5 | Metformin | Hypoglycaemia risk"), row("O","COPD in Elderly", "Smoking hx | FEV1/FVC <0.7 | GOLD staging | SABA, LABA, ICS | O2 therapy"), row("O","Falls in Elderly", "Intrinsic (vision, BP, meds) + Extrinsic (floor, lighting) | Timed Up & Go test"), row("O","Osteoarthritis", "Wear & tear | Weight-bearing joints | Heberden/Bouchard nodes | NSAIDs, TKR"), row("O","Malnutrition / Nutrition", "MNA tool | Protein 1–1.2g/kg | Vit D, Ca, B12 deficiency common in elderly"), row("O","Peripheral Neuropathy", "DM, B12 def, alcohol | Glove-stocking pattern | NCS | Gabapentin, B12"), row("Y","Constipation in Elderly", "Immobility, low fibre, drugs | Bulk laxatives, osmotic laxatives, enema"), row("Y","Osteoporosis", "T-score ≤ -2.5 | DEXA scan | Ca+Vit D | Bisphosphonates | Fall prevention"), row("Y","MMSE", "30-point scale | Orientation(10), Memory(3), Attention(5), Language(8), Copy(1)"), row("Y","Socio-economic Impact of Ageing","Retirement, poverty, isolation, dependency ratio, elder abuse"), row("Y","Burden of Disease / India", "60+ = 10.5% population | NCDs dominant | Lack of geriatric services"), ] def build_section(title, bg_color, rows_data, col_widths): """Build a section header + rows as a Table.""" # Section header spanning all cols hdr = Paragraph(f'<font color="white"><b>{title}</b></font>', ParagraphStyle('sh', fontSize=9.5, alignment=TA_CENTER)) table_rows = [[hdr, '', '', '']] styles = [ ('SPAN', (0,0), (-1,0)), ('BACKGROUND', (0,0), (-1,0), bg_color), ('ALIGN', (0,0), (-1,0), 'CENTER'), ('TOPPADDING', (0,0), (-1,0), 5), ('BOTTOMPADDING', (0,0), (-1,0), 5), ('INNERGRID', (0,1), (-1,-1), 0.3, colors.HexColor("#CCCCCC")), ('BOX', (0,0), (-1,-1), 0.5, colors.HexColor("#AAAAAA")), ('VALIGN', (0,0), (-1,-1), 'MIDDLE'), ] for i, r in enumerate(rows_data, start=1): bg = r[3] table_rows.append([r[0], r[1], r[2], '']) styles += [ ('BACKGROUND', (0,i), (-1,i), bg), ('ALIGN', (0,i), (0,i), 'CENTER'), ('TOPPADDING', (0,i), (-1,i), 2), ('BOTTOMPADDING',(0,i),(-1,-1), 2), ] t = Table(table_rows, colWidths=col_widths) t.setStyle(TableStyle(styles)) return t # Two-column layout: Paeds left, Geri right # Build each as its own table then put side by side cw_p = [0.6*cm, 5.0*cm, 3.8*cm, 0*cm] # check | topic | hint | (bg col hidden) cw_g = [0.6*cm, 5.0*cm, 3.5*cm, 0*cm] paeds_tbl = build_section("PAEDIATRICS (Part I)", BLUE, paeds_rows, cw_p) geri_tbl = build_section("GERIATRICS (Part II)", GREEN, geri_rows, cw_g) combined = Table([[paeds_tbl, geri_tbl]], colWidths=[9.6*cm, 9.4*cm]) combined.setStyle(TableStyle([ ('VALIGN', (0,0), (-1,-1), 'TOP'), ('LEFTPADDING', (0,0), (-1,-1), 2), ('RIGHTPADDING', (0,0), (-1,-1), 2), ])) story.append(combined) story.append(Spacer(1, 0.2*cm)) # ── EXAM-DAY TIPS BAR ──────────────────────────────────────────────────────── tips = [ "Read ALL 8 Qs first", "Attempt best 3 per part", "25-30 min per long Q", "Always: Def → Classification → Clinical → Management", "Attempt ALL 6 — no blanks", ] tips_text = " | ".join(f"✔ {t}" for t in tips) tip_data = [[Paragraph(f'<font color="white"><b>EXAM DAY TIPS: </b>{tips_text}</font>', ParagraphStyle('tp', fontSize=7.5, alignment=TA_CENTER))]] tip_table = Table(tip_data, colWidths=[19*cm]) tip_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,-1), DGRAY), ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5), ])) story.append(tip_table) doc.build(story) print("PDF created:", output) import os; print("Size:", os.path.getsize(output), "bytes") EOF

mkdir -p /tmp/workspace/qr-pdf && python3 << 'EOF' from reportlab.lib.pagesizes import A4 from reportlab.lib import colors from reportlab.lib.units import cm from reportlab.platypus import SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer from reportlab.lib.styles import ParagraphStyle from reportlab.lib.enums import TA_CENTER, TA_LEFT output = "/tmp/workspace/qr-pdf/Last_Minute_Checklist.pdf" doc = SimpleDocTemplate( output, pagesize=A4, topMargin=0.6*cm, bottomMargin=0.6*cm, leftMargin=1.0*cm, rightMargin=1.0*cm ) RED=colors.HexColor("#C0392B"); ORANGE=colors.HexColor("#E67E22") BLUE=colors.HexColor("#2980B9"); GREEN=colors.HexColor("#27AE60") DGRAY=colors.HexColor("#2C3E50"); LGRAY=colors.HexColor("#ECF0F1") WHITE=colors.white; YELLOW=colors.HexColor("#FEF9E7") PINK=colors.HexColor("#FDEDEC"); LGREEN=colors.HexColor("#EAFAF1") LORANGE=colors.HexColor("#FEF5E7"); LBLUE=colors.HexColor("#EBF5FB") story = [] # HEADER hdr_data = [[Paragraph( '<font color="white"><b>PAPER XIII — PAEDIATRICS &amp; GERIATRICS &nbsp;|&nbsp; BPT / BOT' '&nbsp;|&nbsp; Last-Minute Revision Checklist &nbsp;|&nbsp; Exam: 30 July 2026</b></font>', ParagraphStyle('h', fontSize=11, leading=15, alignment=TA_CENTER) )]] hdr = Table(hdr_data, colWidths=[19*cm]) hdr.setStyle(TableStyle([ ('BACKGROUND',(0,0),(-1,-1),DGRAY), ('TOPPADDING',(0,0),(-1,-1),7),('BOTTOMPADDING',(0,0),(-1,-1),7), ])) story.append(hdr); story.append(Spacer(1,0.2*cm)) # LEGEND leg_data = [[ Paragraph('<b>🔴 MUST KNOW</b> — Near-certain to appear', ParagraphStyle('l',fontSize=7.5,alignment=TA_CENTER)), Paragraph('<b>🟠 HIGH PRIORITY</b> — Very probable', ParagraphStyle('l',fontSize=7.5,alignment=TA_CENTER)), Paragraph('<b>🟡 GOOD TO KNOW</b> — Easy marks if it comes', ParagraphStyle('l',fontSize=7.5,alignment=TA_CENTER)), Paragraph('<b>☐ Tick</b> each box when revised', ParagraphStyle('l',fontSize=7.5,alignment=TA_CENTER)), ]] leg = Table(leg_data, colWidths=[4.75*cm]*4) leg.setStyle(TableStyle([ ('BACKGROUND',(0,0),(0,0),PINK),('BACKGROUND',(1,0),(1,0),LORANGE), ('BACKGROUND',(2,0),(2,0),YELLOW),('BACKGROUND',(3,0),(3,0),LGRAY), ('ALIGN',(0,0),(-1,-1),'CENTER'),('VALIGN',(0,0),(-1,-1),'MIDDLE'), ('TOPPADDING',(0,0),(-1,-1),4),('BOTTOMPADDING',(0,0),(-1,-1),4), ('BOX',(0,0),(-1,-1),0.5,colors.grey),('INNERGRID',(0,0),(-1,-1),0.5,colors.grey), ])) story.append(leg); story.append(Spacer(1,0.2*cm)) def mkrow(pri, topic, hint): if pri=="R": bg,dot = PINK, "🔴" elif pri=="O": bg,dot = LORANGE, "🟠" else: bg,dot = YELLOW, "🟡" t = Paragraph(f'{dot} <b>{topic}</b>', ParagraphStyle('t',fontSize=7.8,leading=10)) h = Paragraph(f'<font color="#555555"><i>{hint}</i></font>', ParagraphStyle('h',fontSize=6.8,leading=9)) return ["☐", t, h, bg] paeds = [ mkrow("R","Cerebral Palsy", "Definition → Spastic/Athetoid/Ataxic/Mixed → Aetio → Clinical → Mgmt (physio, OT, drugs)"), mkrow("R","Fallot's Tetralogy", "Nada's criteria | 4 defects: VSD+PS+RVH+Overriding Ao | Tet spell: knee-chest, O2, morphine | Surgery"), mkrow("R","PEM / Marasmus / Kwashiorkor","Grades: Mild/Mod/Severe | Marasmus=calorie | Kwash=protein | Compare table | F-75→F-100 diet"), mkrow("R","Down's Syndrome", "Trisomy 21 | Simian crease, epicanthic fold, flat occiput | IQ 40-70 | VSD, ASD | Mgmt: early intervention"), mkrow("R","National Immunization Sched.","BCG(birth) OPV(0,6,10,14w) DPT HepB IPV(6,10,14w) MR(9m,16m) JE(9-12m) VitA(9m+)"), mkrow("R","Lumbar Puncture", "L3-L4 space | Indications: meningitis, encephalitis | Contraind: raised ICP, coagulopathy | Steps | CSF normal values"), mkrow("R","Milestones of Development", "3m:head control | 6m:sit support | 9m:stand hold | 12m:walk,2 words | 18m:walk stairs | 2yr:phrases"), mkrow("R","Cephalhaematoma", "Subperiosteal bleed | Doesn't cross suture | No Rx needed | vs Caput: crosses suture, present at birth"), mkrow("R","Juvenile Idiopathic Arthritis","Pauci(<5j)/Poly(≥5j)/Systemic | ANA+, RF± | Uveitis risk | NSAIDs, Methotrexate, biologics"), mkrow("O","Hydrocephalus", "Obstructive vs Communicating | Bulging fontanelle, sunset sign, ↑HC | CT/MRI | VP shunt"), mkrow("O","Duchenne Muscular Dystrophy", "X-linked rec | Dystrophin absent | Gower's sign | Calf pseudohypertrophy | CK↑↑ | Steroids, physio"), mkrow("O","Breast Feeding Advantages", "Colostrum (IgA) | LCPUFA for brain | Anti-infective | Bonding | Reduces infections/allergies | WHO: 6m exclusive"), mkrow("O","Meningomyelocele", "Lumbosacral NTD | Arnold-Chiari II | Folic acid prevention | Surgical closure within 24-48h | Bladder care"), mkrow("O","Club Foot (CTEV)", "Cavus+Adductus+Varus+Equinus | Ponseti: serial casting × 6-8wks → tenotomy → Denis Browne splint"), mkrow("O","Rickets", "Vit D deficiency | Craniotabes, rachitic rosary, Harrison's sulcus, genu varum | X-ray: cupping/fraying | VitD+Ca"), mkrow("Y","Pneumonia", "Strep pneumoniae | Tachypnoea, fever, crepitations | CXR consolidation | Amoxicillin 7-10 days"), mkrow("Y","Febrile Seizures", "6m-5yr, T>38°C | Simple(<15min,generalised) vs Complex | Diazepam PR/IV | Reassure parents"), mkrow("Y","Ventricular Septal Defect", "Holosystolic murmur LLSB | Small=closes spontaneously | Large=Eisenmenger | Patch repair"), mkrow("Y","Apgar Score", "0-1-2 each: Appearance Pulse Grimace Activity Respiration | ≥7 normal | <4 needs resuscitation"), ] geri = [ mkrow("R","Hypertension in Elderly", "ISH: SBP≥140+DBP<90 | Thiazide/CCB/ACEi first line | Target <150/90 (>60yr) | White coat HTN"), mkrow("R","Physiological Changes/Ageing","CVS:↓CO,↑SVR | Resp:↓FVC,↓FEV1 | Renal:↓GFR | CNS:↓neurons | MSK:↓BMD,sarcopenia | Immune:↓T-cell"), mkrow("R","Sleep Disorders in Elderly", "Insomnia(most common) OSA RLS | Sleep hygiene first | CBT-I | Melatonin | Avoid BZDs | CPAP for OSA"), mkrow("R","Depression in Elderly", "GDS-15 scale | Bio(neurotransmitters)+Psych(loss)+Social(isolation) | SSRIs | ECT | Suicide risk assessment"), mkrow("R","Dementia / Alzheimer's", "MMSE<24 | Alzheimer(60%)>Vascular>Lewy Body | Stages: mild/mod/severe | Donepezil | Memantine | Caregiver support"), mkrow("R","Stroke in Elderly", "Ischaemic 80% | FAST (Face-Arm-Speech-Time) | CT to exclude haemorrhage | tPA<4.5h | Aspirin 300mg | Rehab"), mkrow("O","Diabetes Mellitus in Elderly","Atypical: falls, confusion, incontinence | HbA1c target 7-7.5% | Metformin | Hypoglycaemia danger | Foot care"), mkrow("O","COPD in Elderly", "Smoking hx | FEV1/FVC<0.7 post-bronchodilator | GOLD I-IV | SABA→LABA→ICS | O2 if SpO2<88% | Pulm rehab"), mkrow("O","Falls in Elderly", "Intrinsic: BP, vision, neuropathy, meds | Extrinsic: floor, lighting | Timed Up & Go test | Hip protectors | Vit D"), mkrow("O","Osteoarthritis", "Wear & tear | Knee>Hip>Hand | Heberden(DIP)/Bouchard(PIP) nodes | X-ray: JSN,osteophytes | NSAIDs, TKR"), mkrow("O","Malnutrition / Nutrition", "MNA screening tool | Protein 1-1.2g/kg/day | Vit D 800IU | Ca 1200mg | B12 supplementation | Oral nutritional supp"), mkrow("O","Peripheral Neuropathy", "DM>B12 def>alcohol>drugs | Glove-stocking sensory loss | NCS/EMG | Gabapentin/Pregabalin | B12 injections"), mkrow("Y","Constipation in Elderly", "Immobility+low fibre+drugs | Rome III criteria | Bulk laxatives (ispaghula) → osmotic (lactulose) → stimulant"), mkrow("Y","Osteoporosis", "T-score ≤ -2.5 (DEXA) | Ca+VitD | Bisphosphonates (alendronate) | FRAX tool | Fall prevention"), mkrow("Y","MMSE", "30 points: Orientation(10)+Registration(3)+Attention(5)+Recall(3)+Language(8)+Copy(1) | <24=cognitive impairment"), mkrow("Y","Socio-economic Impact/Ageing","↑Dependency ratio | Retirement+poverty | Social isolation | Elder abuse | Lack of geriatric services in India"), mkrow("Y","Burden of Disease (India)", "60+=10.5% population (140M) | NCDs: HTN,DM,COPD,stroke dominant | Multimorbidity common | Policy gap"), ] def build_section(title, bg, rows, cws): hdr = Paragraph(f'<font color="white"><b> {title}</b></font>', ParagraphStyle('sh',fontSize=9,alignment=TA_LEFT)) trows = [[hdr,'','','']] sts = [ ('SPAN',(0,0),(-1,0)),('BACKGROUND',(0,0),(-1,0),bg), ('TOPPADDING',(0,0),(-1,0),5),('BOTTOMPADDING',(0,0),(-1,0),5), ('BOX',(0,0),(-1,-1),0.5,colors.HexColor("#AAAAAA")), ('INNERGRID',(0,1),(-1,-1),0.3,colors.HexColor("#CCCCCC")), ('VALIGN',(0,0),(-1,-1),'MIDDLE'), ] for i,r in enumerate(rows,1): trows.append([r[0],r[1],r[2],'']) sts += [ ('BACKGROUND',(0,i),(-1,i),r[3]), ('ALIGN',(0,i),(0,i),'CENTER'), ('TOPPADDING',(0,i),(-1,i),2), ('BOTTOMPADDING',(0,i),(-1,i),2), ] t = Table(trows, colWidths=cws) t.setStyle(TableStyle(sts)) return t cw_p = [0.55*cm, 4.6*cm, 4.25*cm, 0.01*cm] cw_g = [0.55*cm, 4.5*cm, 4.2*cm, 0.01*cm] pt = build_section("PAEDIATRICS — Part I", BLUE, paeds, cw_p) gt = build_section("GERIATRICS — Part II", GREEN, geri, cw_g) combo = Table([[pt, gt]], colWidths=[9.55*cm, 9.45*cm]) combo.setStyle(TableStyle([('VALIGN',(0,0),(-1,-1),'TOP'), ('LEFTPADDING',(0,0),(-1,-1),1), ('RIGHTPADDING',(0,0),(-1,-1),1)])) story.append(combo); story.append(Spacer(1,0.2*cm)) # EXAM TIPS BAR tips = "✔ Read ALL 8 questions first | ✔ Pick your best 3 per part | ✔ Structure every answer: Def → Classification → Clinical Features → Management | ✔ 25-30 min per long Q | ✔ Never leave a question blank" tip_data = [[Paragraph(f'<font color="white"><b>EXAM DAY: </b>{tips}</font>', ParagraphStyle('tp',fontSize=7.5,alignment=TA_CENTER))]] tip_tbl = Table(tip_data, colWidths=[19*cm]) tip_tbl.setStyle(TableStyle([ ('BACKGROUND',(0,0),(-1,-1),DGRAY), ('TOPPADDING',(0,0),(-1,-1),5),('BOTTOMPADDING',(0,0),(-1,-1),5), ])) story.append(tip_tbl) doc.build(story) import os sz = os.path.getsize(output) print(f"Done: {output} ({sz:,} bytes)") EOF