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Docling Core is a library that defines core data types and transformations in Docling.
To use Docling Core, simply install docling-core
from your package manager, e.g. pip:
pip install docling-core
To develop for Docling Core, you need Python 3.9 / 3.10 / 3.11 / 3.12 / 3.13 and uv. You can then install from your local clone's root dir:
uv sync --all-extras
To run the pytest suite, execute:
uv run pytest -s test
Docling Core provides the foundational DoclingDocument data model and API, as well as additional APIs for tasks like serialization and chunking, which are key to developing generative AI applications using Docling.
Docling Core defines the DoclingDocument as a Pydantic model, allowing for advanced data model control, customizability, and interoperability.
In addition to specifying the schema, it provides a handy API for building documents, as well as for basic operations, e.g. exporting to various formats, like Markdown, HTML, and others.
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Different users can have varying requirements when it comes to serialization. To address this, the Serialization API introduces a design that allows easy extension, while providing feature-rich built-in implementations (on which the respective DoclingDocument helpers are actually based).
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Similarly to above, the Chunking API provides built-in chunking capabilities as well as a design that enables easy extension, this way tackling customization requirements of different use cases.
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Please read Contributing to Docling Core for details.
If you use Docling Core in your projects, please consider citing the following:
@techreport{Docling,
author = "Deep Search Team",
month = 8,
title = "Docling Technical Report",
url = "https://arxiv.org/abs/2408.09869",
eprint = "2408.09869",
doi = "10.48550/arXiv.2408.09869",
version = "1.0.0",
year = 2024
}
The Docling Core codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.
FAQs
A python library to define and validate data types in Docling.
We found that docling-core demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago.Ā It has 1 open source maintainer collaborating on the project.
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