ReferenceInformation-oriented

Docling API Reference

Complete reference for classes, methods, configuration options, and constants.

DocumentConverter

Main class for converting documents.

from docling.document_converter import DocumentConverter converter = DocumentConverter( format_options: dict = None,  # Per-format configuration)

Method	Parameters	Returns
convert(source)	source: str \| Path \| URL	ConversionResult
convert_batch(sources)	sources: Iterable[str \| Path]	Iterator[ConversionResult]

Configuration for PDF processing pipeline.

from docling.datamodel.pipeline_options import PdfPipelineOptions options = PdfPipelineOptions()

Parameter	Type	Default	Description
do_ocr	bool	True	Enable OCR for scanned content
do_table_structure	bool	True	Enable table detection
ocr_options	OcrOptions	RapidOcrOptions()	OCR engine configuration
images_scale	float	1.0	Scale factor for images
table_structure_options	TableStructureOptions	-	Table parsing options

Parameter	Type	Description
det_model_path	str	Path to detection model
rec_model_path	str	Path to recognition model
cls_model_path	str	Path to classification model
force_full_page_ocr	bool	Force OCR on all pages

Parameter	Type	Description
lang	str	Language code (e.g., "eng")
force_full_page_ocr	bool	Force OCR on all pages

Requires: TESSDATA_PREFIX environment variable

Pre-configured model specs for VLM pipeline.

from docling.datamodel import vlm_model_specs

Constant	Model	Backend	Best For
SMOLDOCLING_MLX	SmolDocling-256M	MLX	Apple Silicon
SMOLDOCLING_TRANSFORMERS	SmolDocling-256M	Transformers	CPU / CUDA
GRANITEDOCLING_MLX	Granite-Docling-258M	MLX	Apple Silicon
GRANITEDOCLING_VLLM	Granite-Docling-258M	vLLM	NVIDIA GPU (fastest)
GRANITE_VISION_TRANSFORMERS	Granite-Docling-258M	Transformers	CPU / CUDA

Spec	SmolDocling-256M	Granite-Docling-258M
Parameters	256M	258M
Vision Encoder	SigLIP base (93M)	siglip2-base-patch16-512
Language Model	SmolLM-2 (135M)	Granite 165M
Inference Speed	~0.35s/page (A100)	~0.35s/page (A100)
VRAM Usage	~489 MB	~500 MB
License	Apache 2.0	Apache 2.0
HuggingFace	ds4sd/SmolDocling-256M-preview	ibm-granite/granite-docling-258M

Methods available on result.document:

Method	Returns	Use Case
export_to_markdown()	str	Human-readable, LLM input
export_to_html()	str	Web display
export_to_dict()	dict	JSON serialization, lossless
export_to_text()	str	Plain text extraction
export_to_doctags()	str	Native Docling format

from docling.datamodel.base_models import InputFormat

Command	Includes
pip install docling	Core + RapidOCR
pip install "docling[vlm]"	+ VLM pipeline support
pip install "docling[easyocr]"	+ EasyOCR engine
pip install "docling[tesserocr]"	+ Tesseract binding
pip install "docling[ocrmac]"	+ macOS native OCR
pip install "docling[asr]"	+ Audio speech recognition
pip install "docling[cuda]"	+ NVIDIA CUDA support
pip install "docling[mac_intel]"	+ Intel Mac (PyTorch 2.2.2)

Combine extras: pip install "docling[vlm,easyocr]"