README.md

metadata

title: PP-DocLayoutV3 Empirical Parser
emoji: 📄
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 6.9.0
app_file: app.py
pinned: false
license: mit

PDF Layout Detection with PP-DocLayoutV3

Upload any PDF and get a structured breakdown of every element on the page — titles, body text, tables, figures, formulas, headers, footers, footnotes, and more — powered by PaddlePaddle's PP-DocLayoutV3 model via the docling-pp-doc-layout plugin.

Results are displayed as interactive JSON in the browser and can be downloaded as a .json file with one click.

How to use

1. Click Source Document and upload a PDF.
2. Click Run Layout Detection.
3. Inspect the extracted elements in the JSON panel.
4. Click Download JSON to save the results.

Output format

Each detected region is returned as an object with two fields:

{
  "type": "SectionHeaderItem",
  "content": "Introduction"
}

type reflects the docling document-model class. The table below maps the model's raw labels to the types you will see:

Detected region	Output type
doc_title	TitleItem
paragraph_title	SectionHeaderItem
text, content, abstract, aside_text	TextItem
table	TableItem
image, chart, seal	PictureItem
formula	TextItem (formula)
footnote, vision_footnote	TextItem (footnote)
header	TextItem (page header)
footer	TextItem (page footer)
reference, reference_content	TextItem
algorithm	TextItem (code)

Infrastructure

Component	Detail
Hardware	ZeroGPU — NVIDIA H200 (70 GB VRAM, shared)
Layout model	PaddlePaddle/PP-DocLayoutV3_safetensors
Pipeline	docling ≥ 2.73 + docling-pp-doc-layout
SDK	Gradio 6.9.0, Python 3.10