dynamic-image-to-pdf-converter

name	Dynamic Image to PDF Converter
description	Automatically transcribes, structures, and compiles images or text drafts into professional, print-ready vector A4 PDFs using WeasyPrint. Universal - handles any content type: badges, code blocks, tables, blockquotes, RTL text, images, and more.

Dependency Management

Important: Use uv for all package and environment management. Do NOT use pip directly. Refer to global standards in ~/.claude/docs/tooling/package-management.md.

Supported Markdown + HTML Features

The compiler supports a rich set of Markdown extensions and raw HTML:

Feature	Syntax	Example
Badges/Chips	Raw HTML <span>	<span class="badge orange">REACT</span>
Code blocks	Fenced code	```python ... ```
Project trees	Fenced code (text)	```text ... ```
Tables	Markdown pipes	| Col1 | Col2 |
Blockquotes	> prefix	> quoted text
RTL text	HTML wrapper	<div class="urdu-text">...</div>
Images	Markdown/HTML	 or <img>
Horizontal rules	---	---
Lists	- or 1.	Unordered / ordered
Table of Contents	HTML <a> + .toc	<div class="toc"><a href="#sec1">Title</a></div>
Repeating Headers	<thead> in HTML	<table><thead>...</thead></table>
Section Headers	.section-header	<div class="section-header">My Section</div>

Available badge classes: orange, grey, purple, pink, blue-purple, blue, light-blue, green, red, yellow, teal, indigo, cyan, rose, slate, amber, lime, emerald, sky, violet, fuchsia

Utility classes: text-center, text-left, text-right, text-sm, text-lg, mt-0, mb-0, page-break

Process Workflow

When a user provides images or text to convert into a professional PDF, execute this sequence:

1. Analysis & Structure Extraction

   • Read and extract text from the images.
   • Visual Audit: Analyze the source image for non-text elements:
     • Badges/Chips: Identify labels and assign the closest color class.
     • Code Blocks/Trees: Identify project structures or code snippets.
     • Tables: Identify tabular data with headers and rows.
     • Layout: Note specific alignments (centered headers, justified text).
   • Separate content logically into sections using Markdown headers (# Title), metadata, and bullet points.
   • For multilingual content (e.g., Urdu), wrap in <div class="urdu-text"> for RTL support.

2. Payload Generation

   • Write the extracted content into a .md file using Markdown + inline HTML where needed.
   • Styling rules:
     • Badges: <div class="badge-container"><span class="badge color">TEXT</span></div>
     • Code/trees: Use fenced code blocks (text ... ) to preserve formatting.
     • Tables: Use standard Markdown pipe syntax.
     • Blockquotes: Use > prefix.
   • Call: python scripts/compile_pdf.py <input_file.md> <output_file.pdf>

3. Verification & Iterative Refinement

   • Confirm the output is a professional vector PDF.
   • Check for: tree alignment, header spacing, badge colors, table formatting.
   • If layout issues exist, refine the CSS in scripts/compile_pdf.py and re-compile.

Customization

To add new badge colors or utility classes, edit scripts/compile_pdf.py and add CSS rules under the /* ---- Badges ---- */ or /* ---- Utility ---- */ sections. The compiler auto-bootstraps its venv on first run.