Add appropriate images in the space left for the images. Do not change

Add appropriate images in the space left for the images. Do not change the content of the presentation. Provide me in pdf form

Reading File

Running Command

cd /home/daytona/workspace && python -m markitdown attachments/66c4a9e0-e8c3-4990-97ee-d34ed039d555/Atypical_Cardiomyopathy_Pediatrics.pptx 2>&1 | head -300

Running Command

cd /home/daytona/workspace && python /home/daytona/skills/pptx/scripts/thumbnail.py "attachments/66c4a9e0-e8c3-4990-97ee-d34ed039d555/Atypical_Cardiomyopathy_Pediatrics.pptx" 2>&1; ls -la *.jpg 2>/dev/null || ls -la thumbnails* 2>/dev/null

Reading File

I can see the slides clearly. There are image placeholders on:

Slide 2: "[LVNC Echo Image]" - echocardiogram showing LVNC trabeculations
Slide 3: "[ARVC MRI Image]" - cardiac MRI showing ARVC
Slide 4: "[RCM CMR Image]" - cardiac MRI showing RCM

Let me unpack the PPTX and search for appropriate images in parallel.

Running Command

cd /home/daytona/workspace && python /home/daytona/skills/pptx/scripts/office/unpack.py "attachments/66c4a9e0-e8c3-4990-97ee-d34ed039d555/Atypical_Cardiomyopathy_Pediatrics.pptx" unpacked_cmp/ 2>&1

Searching Images

LVNC left ventricular non-compaction echocardiogram pediatric spongy myocardium trabeculations

The unpack timed out. Let me try again with a longer timeout, and simultaneously search for the other images.

Running Command

cd /home/daytona/workspace && python /home/daytona/skills/pptx/scripts/office/unpack.py "attachments/66c4a9e0-e8c3-4990-97ee-d34ed039d555/Atypical_Cardiomyopathy_Pediatrics.pptx" unpacked_cmp/ 2>&1

Searching Images

ARVC arrhythmogenic right ventricular cardiomyopathy cardiac MRI fat infiltration right ventricle

Searching Images

restrictive cardiomyopathy cardiac MRI late gadolinium enhancement biatrial enlargement

Excellent! I have all three images. Now let me examine the slide XML files to find exactly where the image placeholders are, and understand the exact placeholder dimensions and positioning.

Running Command

ls /home/daytona/workspace/unpacked_cmp/ppt/slides/ 2>&1

Running Command

Running Command

Running Command

I can see the image placeholders are text boxes containing "[LVNC Echo Image]", "[ARVC MRI Image]", "[RCM CMR Image]". I need to find the exact position/size of these text boxes. Let me read the relevant sections of each slide XML to get the coordinates.

Running Command

Reading File

Now I know the image placeholder position on slide2. The "[LVNC Echo Image]" placeholder is at x=4114800, y=3108960, cx=3108960, cy=457200. But there must be a larger box/rectangle around it. Let me look for the containing rectangle shape and check slide 3 and 4 placeholders too.

Reading File

Now I have all the coordinates. The containing rectangle "Rectangle 16" in slide2 is at x=3977639, y=1965960, cx=3383280, cy=2743200. Let me find the rectangles for slides 3 and 4 as well. I now have enough to write a Python script to:

Download the three images
Add them into the PPTX as actual pictures, replacing the placeholder text boxes
Convert to PDF

Running Command

grep -n "name=\"Rectangle\|off x\|ext cx" /home/daytona/workspace/unpacked_cmp/ppt/slides/slide3.xml | head -30

Running Command

grep -n "name=\"Rectangle\|off x\|ext cx" /home/daytona/workspace/unpacked_cmp/ppt/slides/slide4.xml | head -30

Now I have all the data I need. Let me now write a Python script to:

Download the 3 medical images
Use python-pptx to add images at exact positions matching the placeholder rectangles
Remove the placeholder text boxes
Save the modified PPTX, then convert to PDF

Running Command

cd /home/daytona/workspace && python3 << 'EOF' import requests import os from pptx import Presentation from pptx.util import Emu from pptx.enum.text import PP_ALIGN import io # Image URLs chosen (best matching images): # Slide 2 (LVNC): dual-panel echo with NC:C ratio measurement - very educational LVNC_URL = "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_94d0d4c659ecda38390bba36342535f0c5d3d9d51c431a093333d40eb61dd304.jpg" # Slide 3 (ARVC): multi-panel cardiac MRI showing fat infiltration ARVC_URL = "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_a3e0d6cb91e2172ed02e53ddf5b9ec43c9b44cc0833909fab5653447edc82bd8.jpg" # Slide 4 (RCM): cardiac MRI with LGE showing biatrial enlargement RCM_URL = "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_638eef1517cf09e35921a6cc5d3e4e349e7c26ed673c78f562e61e934a8c552e.jpg" # Download images def download_image(url, path): r = requests.get(url, timeout=30) r.raise_for_status() with open(path, 'wb') as f: f.write(r.content) print(f"Downloaded {path} ({len(r.content)} bytes)") os.makedirs("images_tmp", exist_ok=True) download_image(LVNC_URL, "images_tmp/lvnc.jpg") download_image(ARVC_URL, "images_tmp/arvc.jpg") download_image(RCM_URL, "images_tmp/rcm.jpg") print("All images downloaded.") EOF

Running Command

which python3 && python3 -c "import sys; print(sys.version)" && pip3 show python-pptx 2>/dev/null | head -3; pip show python-pptx 2>/dev/null | head -3; ls /home/daytona/skills/pptx/scripts/ 2>&1

python-pptx is not installed but the skill uses XML/pack approach. I'll use the node.js fetch_images helper (already confirmed working from the skills), then manipulate the XML directly to insert <p:pic> elements and remove the placeholder text boxes, then pack and convert to PDF with LibreOffice.

Running Command

cd /home/daytona/workspace && node /home/daytona/skills/shared/scripts/fetch_images.js \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_94d0d4c659ecda38390bba36342535f0c5d3d9d51c431a093333d40eb61dd304.jpg" \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_a3e0d6cb91e2172ed02e53ddf5b9ec43c9b44cc0833909fab5653447edc82bd8.jpg" \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_638eef1517cf09e35921a6cc5d3e4e349e7c26ed673c78f562e61e934a8c552e.jpg" 2>&1 | python3 -c " import sys, json, base64 data = json.load(sys.stdin) for i, item in enumerate(data): if item['error']: print(f'ERROR {i}: {item[\"error\"]}') else: b64 = item['base64'] # format: 'image/jpeg;base64,...' header, encoded = b64.split(',', 1) ext = 'jpg' if 'jpeg' in header else 'png' fname = f'images_tmp/img{i}.{ext}' import os; os.makedirs('images_tmp', exist_ok=True) with open(fname, 'wb') as f: f.write(base64.b64decode(encoded)) print(f'Saved {fname} ({len(encoded)} chars base64)') "

Images downloaded. Now I'll write a comprehensive Python script to modify the XML slides directly, add the images as media, and then pack and convert to PDF.

Running Command

cd /home/daytona/workspace && python3 << 'PYEOF' import os, shutil, re, base64 # ── Copy images into media folder ────────────────────────────────────────── media_dir = "unpacked_cmp/ppt/media" os.makedirs(media_dir, exist_ok=True) shutil.copy("images_tmp/img0.jpg", f"{media_dir}/lvnc_echo.jpg") shutil.copy("images_tmp/img1.jpg", f"{media_dir}/arvc_mri.jpg") shutil.copy("images_tmp/img2.jpg", f"{media_dir}/rcm_cmr.jpg") print("Media copied.") # ── Helper: build p:pic XML ───────────────────────────────────────────────── def pic_xml(rid, pic_id, name, x, y, cx, cy): return f''' <p:pic> <p:nvPicPr> <p:cNvPr id="{pic_id}" name="{name}"/> <p:cNvPicPr> <a:picLocks noChangeAspect="1"/> </p:cNvPicPr> <p:nvPr/> </p:nvPicPr> <p:blipFill> <a:blip r:embed="{rid}"/> <a:stretch> <a:fillRect/> </a:stretch> </p:blipFill> <p:spPr> <a:xfrm> <a:off x="{x}" y="{y}"/> <a:ext cx="{cx}" cy="{cy}"/> </a:xfrm> <a:prstGeom prst="rect"> <a:avLst/> </a:prstGeom> </p:spPr> </p:pic>''' # ── Process each slide ────────────────────────────────────────────────────── slides_info = [ { "slide": "unpacked_cmp/ppt/slides/slide2.xml", "rels": "unpacked_cmp/ppt/slides/_rels/slide2.xml.rels", "placeholder_text": "[LVNC Echo Image]", "media_file": "../media/lvnc_echo.jpg", "media_fname": "lvnc_echo.jpg", "rid": "rId_lvnc", "pic_id": 900, "pic_name": "LVNC Echo", # The containing rectangle: x=3977639, y=1965960, cx=3383280, cy=2743200 # Place image just below the "Pathophysiology" header (~y 1965960+320040=2286000) # Use most of the rectangle for the image "x": 3977639, "y": 1965960, "cx": 3383280, "cy": 2743200, }, { "slide": "unpacked_cmp/ppt/slides/slide3.xml", "rels": "unpacked_cmp/ppt/slides/_rels/slide3.xml.rels", "placeholder_text": "[ARVC MRI Image]", "media_file": "../media/arvc_mri.jpg", "media_fname": "arvc_mri.jpg", "rid": "rId_arvc", "pic_id": 901, "pic_name": "ARVC MRI", # Rectangle 8: x=228600, y=1965960, cx=3383280, cy=2560320 "x": 228600, "y": 1965960, "cx": 3383280, "cy": 2560320, }, { "slide": "unpacked_cmp/ppt/slides/slide4.xml", "rels": "unpacked_cmp/ppt/slides/_rels/slide4.xml.rels", "placeholder_text": "[RCM CMR Image]", "media_file": "../media/rcm_cmr.jpg", "media_fname": "rcm_cmr.jpg", "rid": "rId_rcm", "pic_id": 902, "pic_name": "RCM CMR", # Rectangle 8: x=4023360, y=1965960, cx=3291840, cy=2926080 "x": 4023360, "y": 1965960, "cx": 3291840, "cy": 2926080, }, ] for info in slides_info: # 1. Read slide XML with open(info["slide"], "r", encoding="utf-8") as f: xml = f.read() # 2. Remove the placeholder text box containing e.g. "[LVNC Echo Image]" # Find the entire <p:sp>...</p:sp> block that contains the placeholder text # Pattern: find <p:sp> block that contains the placeholder text pattern = r'<p:sp>\s*<p:nvSpPr>.*?</p:nvSpPr>.*?</p:sp>' def remove_placeholder_sp(xml, text): # Use regex with DOTALL to find p:sp blocks containing the placeholder text blocks = list(re.finditer(r'<p:sp>.*?</p:sp>', xml, re.DOTALL)) for block in blocks: if text in block.group(): xml = xml[:block.start()] + xml[block.end():] break return xml xml = remove_placeholder_sp(xml, info["placeholder_text"]) # 3. Insert the image pic element before </p:spTree> img = pic_xml(info["rid"], info["pic_id"], info["pic_name"], info["x"], info["y"], info["cx"], info["cy"]) xml = xml.replace("</p:spTree>", img + "\n </p:spTree>") # 4. Write back with open(info["slide"], "w", encoding="utf-8") as f: f.write(xml) print(f"Updated {info['slide']}") # 5. Add relationship to rels file with open(info["rels"], "r", encoding="utf-8") as f: rels = f.read() new_rel = f' <Relationship Id="{info["rid"]}" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="{info["media_file"]}"/>' rels = rels.replace("</Relationships>", new_rel + "\n</Relationships>") with open(info["rels"], "w", encoding="utf-8") as f: f.write(rels) print(f"Updated rels for {info['slide']}") print("Done editing slides.") PYEOF

Running Command

ls -la /home/daytona/workspace/unpacked_cmp/ppt/media/ 2>&1 | head -20; chmod -R u+w /home/daytona/workspace/unpacked_cmp/ 2>&1 && echo "chmod ok"

Model call limits exceeded: run limit (20/20)

Atleast give me the images

Here are the three medical images I found for each placeholder in the presentation:

Slide 2 — [LVNC Echo Image] Transthoracic echocardiogram showing Left Ventricular Non-Compaction (LVNC) with prominent trabeculations and deep intertrabecular recesses — classic "spongy" myocardium appearance.

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