raphaelmansuy

raphaelmansuy / edgequake-pdf2md

Public

Convert PDF documents to Markdown using Vision Language Models — CLI and library

crates.iocratesedgequake-pdf2md
28
3
100% credibility
Found Feb 20, 2026 at 22 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

A command-line tool and library that converts PDF documents into structured Markdown by rendering pages as images and using vision language models from various AI providers.

How It Works

1
đź“° Find the PDF Magic Tool

You discover a handy helper that turns messy PDFs into neat, editable Markdown files.

2
đź“Ą Get It Ready

Download the tool to your computer—it sets itself up quickly and easily.

3
🧠 Link Your AI Helper

Connect a smart AI service so the tool can read and understand your PDF pages like a person.

4
✨ Feed It a PDF

Give it a PDF from your files or a web link, pick pages if you want, and let it do its thing.

5
⚡ Watch It Work

It processes pages fast, showing progress as clean text appears.

âś… Perfect Markdown Ready

You now have beautifully structured, editable text—tables, headings, everything preserved perfectly.

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Star Growth

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AI-Generated Review

What is edgequake-pdf2md?

This Rust CLI tool and library converts PDF documents—local files or URLs—into clean, structured Markdown using vision language models like GPT-4o, Claude, or Gemini. It rasterizes pages into images for AI to read accurately, handling tables, math, and layouts that traditional extractors butcher. Run `pdf2md document.pdf -o output.md` for instant results, or integrate the async API for batch jobs; perfect for flipping scanned papers or reports into editable text before converting GitHub Markdown to PDF or feeding repos to LLMs.

Why is it gaining traction?

Zero-setup binaries bundle PDF rendering with no env vars or downloads, unlike Python alternatives that need manual deps. Concurrent page processing slashes time (10x speedup), multi-provider support (OpenAI, Ollama local) keeps costs low (~$0.02 for 50 pages), and post-processing fixes AI quirks like bad tables. Devs love the self-contained Rust speed over flaky OCR tools.

Who should use this?

Data engineers building RAG pipelines from research PDFs, needing convert PDF to docx/epub/word flows. Docs teams converting GitHub repo PDFs or readmes to LLM text. CLI powerusers batch-processing invoices or books to Markdown for GitHub/VSCode.

Verdict

Grab it for reliable PDF-to-Markdown if you're tired of garbled extracts—CLI shines for quick wins, library for apps. At 16 stars and 1.0% credibility, it's early (solid docs/tests but low adoption); test on your PDFs before production.

(198 words)

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