Docling

Langflow integrates with Docling through a bundle of components for parsing documents.

Install Docling dependency

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You must install the Docling dependency to use the Docling components in Langflow.

Langflow OSS

Install the Docling extra in Langflow OSS with uv pip install 'langflow[docling]'.

Langflow Desktop

To add a dependency to Langflow Desktop, add an entry for Docling to the application's requirements.txt file. For more information, see Install custom dependencies in Langflow Desktop.

Use Docling components in a flow

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To learn more about content extraction with Docling, see the video tutorial Docling + Langflow: Document Processing for AI Workflows.

This example demonstrates how to use Docling components to split a PDF in a flow:

1. Connect a Docling and an Export DoclingDocument component to a Split Text component.

   The Docling component loads the document, and the Export DoclingDocument component converts the DoclingDocument into the format you select. This example converts the document to Markdown, with images represented as placeholders. The Split Text component will split the Markdown into chunks for the vector database to store in the next part of the flow.

2. Connect a Chroma DB vector store component to the Split Text component's Chunks output.

3. Connect an Embedding Model component to the Chroma DB component's Embedding port and a Chat Output component to view the extracted DataFrame.

4. Add your OpenAI API key to the Embedding Model component.

   

5. Add a file to the Docling component.

6. To run the flow, click Playground.

   The chunked document is loaded as vectors into your vector database.

Docling components

The following sections describe the purpose and configuration options for each component in the Docling bundle.

Docling language model

The Docling language model component ingest documents, and then uses Docling to process them by running the Docling models locally.

It outputs files, which is the processed files with DoclingDocument data.

Docling parameters

Name	Type	Description
files	File	The files to process.
pipeline	String	Docling pipeline to use (standard, vlm).
ocr_engine	String	OCR engine to use (easyocr, tesserocr, rapidocr, ocrmac).

Docling Serve

The Docling Serve component ingests documents, and then uses Docling to process them by connecting to your instance of Docling Serve.

It outputs files, which is the processed files with DoclingDocument data.

Docling Serve parameters

Name	Type	Description
files	File	The files to process.
api_url	String	URL of the Docling Serve instance.
max_concurrency	Integer	Maximum number of concurrent requests for the server.
max_poll_timeout	Float	Maximum waiting time for the document conversion to complete.
api_headers	Dict	Optional dictionary of additional headers required for connecting to Docling Serve.
docling_serve_opts	Dict	Optional dictionary of additional options for Docling Serve.

Chunk DoclingDocument

The Chunk DoclingDocument component uses the DoclingDocument chunkers to split a document into chunks.

It outputs the chunked documents as a DataFrame.

Chunk DoclingDocument parameters

Name	Type	Description
data_inputs	Data/DataFrame	The data with documents to split in chunks.
chunker	String	Which chunker to use (HybridChunker, HierarchicalChunker).
provider	String	Which tokenizer provider (Hugging Face, OpenAI).
hf_model_name	String	Model name of the tokenizer to use with the HybridChunker when Hugging Face is chosen.
openai_model_name	String	Model name of the tokenizer to use with the HybridChunker when OpenAI is chosen.
max_tokens	Integer	Maximum number of tokens for the HybridChunker.
doc_key	String	The key to use for the DoclingDocument column.

Export DoclingDocument

The Export DoclingDocument component exports DoclingDocument to Markdown, HTML, and other formats.

It can output the exported data as either Data or DataFrame.

Export DoclingDocument parameters

Name	Type	Description
data_inputs	Data/DataFrame	The data with documents to export.
export_format	String	Select the export format to convert the input (Markdown, HTML, Plaintext, DocTags).
image_mode	String	Specify how images are exported in the output (placeholder, embedded).
md_image_placeholder	String	Specify the image placeholder for markdown exports.
md_page_break_placeholder	String	Add this placeholder between pages in the markdown output.
doc_key	String	The key to use for the DoclingDocument column.