A python library to define and validate data types in Docling.
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Author: Cesar Berrospi Ramis
Maintainer: Cesar Berrospi Ramis
Requires Python: >=3.9,<4.0
Classifiers
Development Status
- 5 - Production/Stable
Intended Audience
- Developers
- Science/Research
License
- OSI Approved :: MIT License
Natural Language
- English
Operating System
- OS Independent
Programming Language
- Python :: 3
- Python :: 3.9
- Python :: 3.10
- Python :: 3.11
- Python :: 3.12
Topic
- Database
- Scientific/Engineering :: Information Analysis
- Software Development :: Libraries :: Python Modules
Typing
- Typed
Docling Core
Docling Core is a library that defines the data types in Docling, leveraging pydantic models.
Installation
To use Docling Core, simply install docling-core from your package manager, e.g. pip:
pip install docling-core
Development setup
To develop for Docling Core, you need Python 3.9 / 3.10 / 3.11 / 3.12 / 3.13 and Poetry. You can then install from your local clone's root dir:
poetry install
To run the pytest suite, execute:
poetry run pytest test
Basic Usage
-
You can validate your JSON objects using the pydantic class definition.
from docling_core.types import DoclingDocument data_dict = {...} # here the object you want to validate, as a dictionary DoclingDocument.model_validate(data_dict) data_str = {...} # here the object as a JSON string DoclingDocument.model_validate_json(data_str)
-
You can generate the JSON schema of a model with the script
generate_jsonschema.# for the `DoclingDocument` type generate_jsonschema DoclingDocument # for the use `Record` type generate_jsonschema Record
Documentation
Docling Core contains 3 top-level data types:
- DoclingDocument for publications like books, articles, reports, or patents. The JSON that can be exported using Docling follows this schema. The DoclingDocument type also models the metadata that may be attached to the converted document. Check DoclingDocument for the full JSON schema.
- Record for structured database records, centered on an entity or subject that is provided with a list of attributes. Related to records, the statements can represent annotations on text by Natural Language Processing (NLP) tools. Check Record for the full JSON schema.
- Generic for any data representation, ensuring minimal configuration and maximum flexibility. Check Generic for the full JSON schema.
The data schemas are defined using pydantic models, which provide built-in processes to support the creation of data that adhere to those models.
Contributing
Please read Contributing to Docling Core for details.
References
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
}
License
The Docling Core codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.
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