glmv-pdf-to-ppt

PDF → HTML PPT Skill

Convert any PDF into a multi-slide HTML presentation. Pages are converted to images at DPI 120, read sequentially to understand the content, then a structured outline.json is saved, images are cropped locally (no cloud upload), slides are rendered one by one, and finally a summary.md is generated.

Scripts are in: {SKILL_DIR}/scripts/

Dependencies

Python packages (install once):

pip install pymupdf pillow

System tools: curl (pre-installed on macOS/Linux).

When to Use

Trigger when the user asks to make slides or a presentation from a PDF — phrases like: "make a PPT from a PDF", "convert PDF to slides", "create a presentation from this paper", "根据pdf做ppt", "根据论文做幻灯片", "做PPT", "做幻灯片", "生成演示文稿", "把这个pdf转成ppt", or any similar intent in Chinese or English.

Output Directory Convention

All output goes under {WORKSPACE}/ppt/<pdf_stem>_<timestamp>/:

ppt/
└── <pdf_stem>_<timestamp>/
    ├── outline.json        ← structured slide plan (SlidesPlan schema)
    ├── crops/              ← locally-saved cropped images
    │   ├── slide3_method_crop.png
    │   └── slide5_results_crop.png
    ├── slide_01.html
    ├── slide_02.html
    ├── ...
    └── summary.md          ← final summary document

• <pdf_stem> = PDF filename without extension
• <timestamp> = format YYYYMMDD_HHMMSS (e.g. 20240119_143022)
• Cropped images go in crops/ subfolder
• Each slide HTML references images via relative path crops/<name>.png

Input

$ARGUMENTS is the path to the PDF file (local) or an HTTP/HTTPS URL.

• If user provides a URL: download with curl first, then convert
• If user provides a local PDF path: convert directly

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Workflow

Phase 0 — Create Output Directory

Compute the output path:

import os, datetime
pdf_stem = os.path.splitext(os.path.basename(pdf_path))[0]
timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
out_dir = os.path.join(workspace, "ppt", f"{pdf_stem}_{timestamp}")