docling/docs/faq.md

# FAQ

This is a collection of FAQ collected from the user questions on <https://github.com/DS4SD/docling/discussions>.


### Python 3.13 support

Full support for Python 3.13 is currently waiting for [pytorch](https://github.com/pytorch/pytorch).

At the moment, no release has full support, but nightly builds are available. Docling was tested on Python 3.13 with the following steps:

```sh
# Create a python 3.13 virtualenv
python3.13 -m venv venv
source ./venv/bin/activate

# Install torch nightly builds, see https://pytorch.org/
pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu

# Install docling
pip3 install docling

# Run docling
docling --no-ocr https://arxiv.org/pdf/2408.09869
```

_Note: we are disabling OCR since easyocr and the nightly torch builds have some conflicts._

Source: Issue [#136](https://github.com/DS4SD/docling/issues/136)


### Install conflicts with numpy (python 3.13)


This has been observed installing docling and langchain via poetry.

```
...
Thus, docling (>=2.7.0,<3.0.0) requires numpy (>=1.26.4,<2.0.0).
So, because ... depends on both numpy (>=2.0.2,<3.0.0) and docling (^2.7.0), version solving failed.
```

Numpy is only adding Python 3.13 support starting in some 2.x.y version. In order to prepare for 3.13, Docling depends on a 2.x.y for 3.13, otherwise depending an 1.x.y version. If you are allowing 3.13 in your pyproject.toml, Poetry will try to find some way to reconcile Docling's numpy version for 3.13 (some 2.x.y) with LangChain's version for that (some 1.x.y) — leading to the error above.

Check if Python 3.13 is among the Python versions allowed by your pyproject.toml and if so, remove it and try again.
E.g., if you have python = "^3.10", use python = ">=3.10,<3.13" instead.

If you want to retain compatibility with python 3.9-3.13, you can also use a selector in pyproject.toml similar to the following

```toml
numpy = [
    { version = "^2.1.0", markers = 'python_version >= "3.13"' },
    { version = "^1.24.4", markers = 'python_version < "3.13"' },
]
```


Source: Issue [#283](https://github.com/DS4SD/docling/issues/283#issuecomment-2465035868)


### GPU support

TBA


### Text styles (bold, underline, etc)

TBA


### How do I run completely offline?

Docling is not using any remote service, hence it can run in completely isolated air-gapped environments.

The only requirement is pointing the Docling runtime to the location where the model artifacts have been stored.

For example

```py

pipeline_options = PdfPipelineOptions(artifacts_path="your location")
converter = DocumentConverter(
    format_options={
        InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
    }
)
```

Source: Issue [#326](https://github.com/DS4SD/docling/issues/326)


### Which model weights are needed to run Docling?

Model weights are needed for the AI models used in the PDF pipeline. Other document types (docx, pptx, etc) do not have any such requirement.

For processing PDF documents, Docling requires the model weights from <https://huggingface.co/ds4sd/docling-models>.

When OCR is enabled, some engines also require model artifacts. For example EasyOCR, for which Docling has [special pipeline options](https://github.com/DS4SD/docling/blob/main/docling/datamodel/pipeline_options.py#L68) to control the runtime behavior.



### SSL error downloading model weights

```
URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1000)>
```

Similar SSL download errors have been observed by some users. This happens when model weights are fetched from Hugging Face.
The error could happen when the python environment doesn't have an up-to-date list of trusted certificates.

Possible solutions were

- Update to the latest version of [certifi](https://pypi.org/project/certifi/), i.e. `pip install --upgrade certifi`
- Use [pip-system-certs](https://pypi.org/project/pip-system-certs/) to use the latest trusted certificates on your system.


### Which OCR languages are supported?

Docling supports multiple OCR engine, each one has its own list of supported languages.
Here is a collection of links to the original OCR engine's documentation listing the OCR languages.

- [EasyOCR](https://www.jaided.ai/easyocr/)
- [Tesseract](https://tesseract-ocr.github.io/tessdoc/Data-Files-in-different-versions.html)
- [RapidOCR](https://rapidai.github.io/RapidOCRDocs/blog/2022/09/28/%E6%94%AF%E6%8C%81%E8%AF%86%E5%88%AB%E8%AF%AD%E8%A8%80/)
- [Mac OCR](https://github.com/straussmaximilian/ocrmac/tree/main?tab=readme-ov-file#example-select-language-preference)

Setting the OCR language in Docling is done via the OCR pipeline options:

```py
from docling.datamodel.pipeline_options import PdfPipelineOptions

pipeline_options = PdfPipelineOptions()
pipeline_options.ocr_options.lang = ["fr", "de", "es", "en"]  # example of languages for EasyOCR
```