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Docling LangChain integration

PyPI version PyPI - Python Version Poetry Code style: black Imports: isort Pydantic v2 pre-commit License MIT

A Docling integration for LangChain.

Installation

Simply install langchain-docling from your package manager, e.g. pip:

pip install langchain-docling

Usage

Basic usage

Basic usage of DoclingLoader looks as follows:

from langchain_docling import DoclingLoader

FILE_PATH = ["https://arxiv.org/pdf/2408.09869"]  # Docling Technical Report

loader = DoclingLoader(file_path=FILE_PATH)
docs = loader.load()

Advanced usage

When initializing a DoclingLoader, you can use the following parameters:

  • file_path: source as single str (URL or local file) or iterable thereof
  • converter (optional): any specific Docling converter instance to use
  • convert_kwargs (optional): any specific kwargs for conversion execution
  • export_type (optional): export mode to use: ExportType.DOC_CHUNKS (default) or ExportType.MARKDOWN
  • md_export_kwargs (optional): any specific Markdown export kwargs (for Markdown mode)
  • chunker (optional): any specific Docling chunker instance to use (for doc-chunk mode)
  • meta_extractor (optional): any specific metadata extractor to use

Example

For an end-to-end usage example, check out this notebook.