# Docling [](https://pypi.org/project/docling/)  [](https://python-poetry.org/) [](https://github.com/psf/black) [](https://pycqa.github.io/isort/) [](https://pydantic.dev) [](https://github.com/pre-commit/pre-commit) [](https://opensource.org/licenses/MIT) Docling bundles PDF document conversion to JSON and Markdown in an easy, self-contained package. ## Features * ⚡ Converts any PDF document to JSON or Markdown format, stable and lightning fast * 📑 Understands detailed page layout, reading order and recovers table structures * 📝 Extracts metadata from the document, such as title, authors, references and language * 🔍 Optionally applies OCR (use with scanned PDFs) ## Installation To use Docling, simply install `docling` from your package manager, e.g. pip: ```bash pip install docling ``` > [!NOTE] > Works on macOS and Linux environments. Windows platforms are currently not tested. ### Development setup To develop for Docling, you need Python 3.11 / 3.12 and Poetry. You can then install from your local clone's root dir: ```bash poetry install ``` ## Usage For basic usage, see the [convert.py](https://github.com/DS4SD/docling/blob/main/examples/convert.py) example module. Run with: ``` python examples/convert.py ``` The output of the above command will be written to `./scratch`. ### Enable or disable pipeline features You can control if table structure recognition or OCR should be performed by arguments passed to `DocumentConverter`: ```python doc_converter = DocumentConverter( artifacts_path=artifacts_path, pipeline_options=PipelineOptions( do_table_structure=False, # controls if table structure is recovered do_ocr=True, # controls if OCR is applied (ignores programmatic content) ), ) ``` ### Impose limits on the document size You can limit the file size and number of pages which should be allowed to process per document: ```python conv_input = DocumentConversionInput.from_paths( paths=[Path("./test/data/2206.01062.pdf")], limits=DocumentLimits(max_num_pages=100, max_file_size=20971520) ) ``` ### Convert from binary PDF streams You can convert PDFs from a binary stream instead of from the filesystem as follows: ```python buf = BytesIO(your_binary_stream) docs = [DocumentStream(filename="my_doc.pdf", stream=buf)] conv_input = DocumentConversionInput.from_streams(docs) converted_docs = doc_converter.convert(conv_input) ``` ### Limit resource usage You can limit the CPU threads used by Docling by setting the environment variable `OMP_NUM_THREADS` accordingly. The default setting is using 4 CPU threads. ## Contributing Please read [Contributing to Docling](https://github.com/DS4SD/docling/blob/main/CONTRIBUTING.md) for details. ## References If you use Docling in your projects, please consider citing the following: ```bib @software{Docling, author = {Deep Search Team}, month = {7}, title = {{Docling}}, url = {https://github.com/DS4SD/docling}, version = {main}, year = {2024} } ``` ## License The Docling codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.