Skip to main content

pdf2md-study

CI

English | 한국어

Convert papers and lecture slides (PDF) into study-ready Markdown for LLMs — equations and code kept as images, logos and references stripped.

Built on Docling.

Why

Uploading a PDF to an LLM sends the text and an image of every page. The Markdown is several times smaller and keeps what matters for studying. Each conversion prints an estimate like these:

Document PDF Markdown + images
26-page paper ~53,900 tokens ~14,600 ~3,300
39-page lecture slides ~116,400 tokens ~6,700 ~18,300

Features

  • Equations and code are cropped as images, so nothing is lost to recognition errors.
  • Logos and decorations repeated across pages are removed.
  • The references section is removed.
  • Slides get a [p.N] label on each page.
  • Images are named by page: p04_1.png, p05_eq1.png, p30_code1.png.

Get started

With uv installed:

uv tool install pdf2md-study
pdf2md-study paper.pdf

Or with Docker, with Docling's models included:

docker run --rm --user "$(id -u):$(id -g)" -v "$PWD:/data" ghcr.io/inhyunseo/pdf2md-study paper.pdf

paper.md and paper_artifacts/ appear next to the PDF.

  • Quickstart: step by step on Ubuntu, WSL2, macOS, and Windows
  • Usage: options, output, and tips for sending to an LLM

Development

git clone https://github.com/InHyunseo/pdf2md-study.git
cd pdf2md-study
uv sync
uv run pytest
uv run ruff check

Pull requests run lint and tests on Ubuntu, Windows, and macOS.

License

MIT

Metadata

Release files for pdf2md-study 0.3.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pdf2md-study 0.3.0
File Size Uploaded
pdf2md_study-0.3.0.tar.gz 12.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pdf2md-study 0.3.0
File Interpreter ABI Platform
pdf2md_study-0.3.0-py3-none-any.whl Python 3 none any Details

Total release size: 29.0 kB

Release files / pdf2md_study-0.3.0.tar.gz

Download URL pdf2md_study-0.3.0.tar.gz
Size 12.9 kB
Tags Source
SHA-256 checksum
How to use checksums
8324510f6a2a385afcad3aa7c3bcd2fe0e829a1db4154d0bf14896a2e17c9b8d
BLAKE2b-256 checksum
How to use checksums
0b5d281288302ff12d87c1133891cddddf77c871968c42ef3882579ad7640e40
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.12.23 {"installer":{"name":"uv","version":"0.12.23","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release files / pdf2md_study-0.3.0-py3-none-any.whl

Download URL pdf2md_study-0.3.0-py3-none-any.whl
Size 16.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
83acf01dfd24674d11ae2f206b7fb6255cb08d84f92df5d8174fb3d64f4c5da2
BLAKE2b-256 checksum
How to use checksums
38e8a2968a61fc540567241cb5e59c1e187d7b364845c4cbc6c12aa14c554b56
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.12.23 {"installer":{"name":"uv","version":"0.12.23","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release history Release notifications | RSS feed

This release

0.3.0 This release

2 release files

0.2.1

2 release files

0.2.0

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page