microsoft / microsoft/markitdown
Use Marker for PDF text extraction
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- Dominant language
- Python
- Stars
- 186k
- Forks
- 13.7k
- Avg merge
- 1d 4h
- Merged PRs (30d)
- 49
Description
Marker is a library that extracts the content of PDFs qyuxly, while preserving semantic context. It runs quickly and has both GPU acceleration and LLM support. Output can be Markdown or structured.
Config is simple:
from marker.converters.pdf import PdfConverter
from marker.models import create_model_dict
from marker.output import text_from_rendered
converter = PdfConverter(
artifact_dict=create_model_dict(),
)
rendered = converter("FILEPATH")
text, _, images = text_from_rendered(rendered)
How it works:
- Extract text, OCR if necessary (heuristics, surya)
- Detect page layout and find reading order (surya)
- Clean and format each block (heuristics, texify, surya)
- Optionally use an LLM to improve quality
- Combine blocks and postprocess complete text
nb, I’m not a maintainer of the project.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no repository files or tests. Start by locating the current PDF conversion entry point and dependency configuration, then compare them with Marker’s documented PdfConverter flow; done means PDF conversion uses Marker and existing output behavior remains covered.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- tooling
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100