Chunk documents Transform

May 5, 2025 · View on GitHub

Please see the set of transform project conventions for details on general project conventions, transform configuration, testing and IDE set up.

Description

This transform is chunking documents. It supports multiple chunker modules (see the chunking_type parameter).

When using documents converted to JSON, the transform leverages the Docling Core HierarchicalChunker to chunk according to the document layout segmentation, i.e. respecting the original document components as paragraphs, tables, enumerations, etc. It relies on documents converted with the Docling library in the docling2parquet transform using the option contents_type: "application/json", which provides the required JSON structure.

When using documents converted to Markdown, the transform leverages the Llama Index MarkdownNodeParser, which is relying on its internal Markdown splitting logic.

Input

input column name	data type	description
the one specified in content_column_name configuration	string	the content used in this transform

Output format

The output parquet file will contain all the original columns, but the content will be replaced with the individual chunks.

Tracing the origin of the chunks

The transform allows to trace the origin of the chunk with the source_doc_id which is set to the value of the document_id column (if present) in the input table. The actual name of columns can be customized with the parameters described below.

Configuration

The transform can be tuned with the following parameters.

Parameter	Default	Description
`chunking_type`	`dl_json`	Chunking type to apply. Valid options are `li_markdown` for using the LlamaIndex Markdown chunking, `dl_json` for using the Docling JSON chunking, `li_token_text` for using the LlamaIndex Token Text Splitter, which chunks the text into fixed-sized windows of tokens.
`content_column_name`	`contents`	Name of the column containing the text to be chunked.
`doc_id_column_name`	`document_id`	Name of the column containing the doc_id to be propagated in the output.
`chunk_size_tokens`	`128`	Size of the chunk in tokens for the token text chunker.
`chunk_overlap_tokens`	`30`	Number of tokens overlapping between chunks for the token text chunker.
`output_chunk_column_name`	`contents`	Column name to store the chunks in the output table.
`output_source_doc_id_column_name`	`source_document_id`	Column name to store the `doc_id` from the input table.
`output_jsonpath_column_name`	`doc_jsonpath`	Column name to store the document path of the chunk in the output table.
`output_pageno_column_name`	`page_number`	Column name to store the page number of the chunk in the output table.
`output_bbox_column_name`	`bbox`	Column name to store the bbox of the chunk in the output table.

Usage

Launched Command Line Options

When invoking the CLI, the parameters must be set as --doc_chunk_<name>, e.g., --doc_chunk_column_name=myoutput.

Code example

See a sample notebook

Transforming data using the transform image

To use the transform image to transform your data, please refer to the running images quickstart, substituting the name of this transform image and runtime as appropriate.