Preserve tables, titles (structure) of PDF documents #41

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1. Gagan Bansal (gagb)

   added

   enhancementNew feature or requestNew feature or request

   open for contributionInvites open-source developers to contribute to the project.Invites open-source developers to contribute to the project.

   on Dec 15, 2024
2. ckpearson commented on Dec 16, 2024

   

   Clint Pearson (ckpearson)

   on Dec 16, 2024

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   PDFs are an absolute nightmare specifically for this reason, and we've had issues with reading order from direct file extraction because the order things are rendered in is not necessarily the order they're present in the file either.

   We've just gone down the route of using Azure's Document Intelligence system which does a much better job of extracting structural information (even tables!), but of course that's not an offline option and does lead to some cost / latency considerations.
3. dipam7 commented on Dec 16, 2024

   

   Dipam Vasani (dipam7)

   on Dec 16, 2024

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   Just tested this as well with a v simple table and found the output no better than raw pdf > txt.

   Btw why is the output txt and not markdown? I don't see titles or section headings with ###. The output seems plain text.
4. jvhgit commented on Dec 17, 2024

   

   Jens (jvhgit)

   on Dec 17, 2024

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   Hi, you might want to take a look at https://github.com/Filimoa/open-parse .

   👍React with 👍1Reacted by Ivan Shcheklein

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5. PeterStaar-IBM commented on Dec 17, 2024

   

   Peter W. J. Staar (PeterStaar-IBM)

   on Dec 17, 2024

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   Ivan Shcheklein (@shcheklein) You can use docling (https://github.com/DS4SD/docling), it is designed for that!

   👍React with 👍2Reacted by Panos Vagenas and Jabeur-Jaafar
6. gabrielstuff commented on Dec 19, 2024

   

   Gabriel (gabrielstuff)

   on Dec 19, 2024

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   This would be a great feature. Pymupdf is the only one I found doing it almost perfectly : https://pymupdf.readthedocs.io/en/latest/pymupdf4llm/index.html

   Docling manage to do it but it is not that good.

   👍React with 👍1Reacted by khalt00
7. PeterStaar-IBM commented on Dec 20, 2024

   

   Peter W. J. Staar (PeterStaar-IBM)

   on Dec 20, 2024

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   This would be a great feature. Pymupdf is the only one I found doing it almost perfectly : https://pymupdf.readthedocs.io/en/latest/pymupdf4llm/index.html

   Docling manage to do it but it is not that good.

   Gabriel (@gabrielstuff) What do you mean? Running the following command,

   docling --from pdf --to html --image-export-mode embedded /Users/taa/Downloads/4.General.Electric.Company.pdf
   

   I get the following (few screenshots)

   

   

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8. gabrielstuff commented on Jan 17, 2025

   

   Gabriel (gabrielstuff)

   on Jan 17, 2025

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   Peter W. J. Staar (@PeterStaar-IBM), I will share some pdf. What I mean is that the table rendered by docling were not to the level of the ones from the pymupdf.
   The tables from markitdown are simply bad.
9. deepdive101 commented on Jan 30, 2025

   

   deepdive101

   on Jan 30, 2025

   Last edited by deepdive101

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   We've just gone down the route of using Azure's Document Intelligence

   Clint Pearson (@ckpearson) Do you have code you can share for this?
10. ckpearson commented on Feb 5, 2025

    

    Clint Pearson (ckpearson)

    on Feb 5, 2025

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    We've just gone down the route of using Azure's Document Intelligence

    @ckpearson Do you have code you can share for this?

    So everything you need should be here: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/layout?view=doc-intel-4.0.0&tabs=rest%2Csample-code

    We're using the Layout extraction model as it's the most broadly capable, and does the structure analysis, though General goes as far as things like checkboxes etc.

    They've got SDKs available for different languages, but ultimately it's also just a REST API call away.

    Some interesting gotchas we ran into that might save you some time:

    • The raw text (named Content on the response objects) DOES NOT preserve visual new-lines
      • The top-level document text has new-lines between paragraphs, but not within them; this is to account for the fact that a new line might be legitimate, or it might be due to content wrapping
      • They leave the determination of that up to you, but you can find all of the lines that make up an element in the lines collection on a page
    • Content is indexed using spans where the index and length represent positions within the top-level document content string
    • Content theoretically can span multiple pages (paragraph, table etc) which is why boundingRegions can contain multiple entries over different pages
      • In practice though I've not seen this happen yet, but you might want to account for it in case you're interested in the coordinates of items in the document
    • Tables are numbered globally in sequence (1, 2, etc)
      • Tables that span multiple pages WILL get seen as separate tables, you'll need to do your own work for gluing them back together in some sort of post-process step
    • Text content inside tables are ALSO paragraphs in the paragraphs collection, so if you don't want to process them as independent from the table they're contained within, you'll want to do some processing to exclude content that is contained within other content
      • We used an interval tree for this, where we add the content items based on their smallest span index and total length
        • Then finding if a paragraph is inside a table is a pretty easy query of "find me tables where this paragraph's span overlaps"

    Happy hacking!

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11. cagdasyurekli commented on Aug 26, 2026

    

    Çağdaş Yürekli (cagdasyurekli)

    on Aug 26, 2026

    Contributor

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    I opened PR #2345 with an opt-in, plugin-scoped semantic PDF OCR path for the remaining structure-recovery cases described here and in #83.

    The deterministic core converter and default plugin behavior remain unchanged. When explicitly enabled, every page is rendered for vision-assisted Markdown extraction with instructions to preserve source text, headings, reading order, nested lists, and tables. Empty/error results fall back to deterministic whole-document extraction.

    The mechanism, fallback paths, option precedence, custom OCR-service compatibility, and PyMuPDF resource cleanup are covered by tests. Because semantic quality is model-dependent, the PR deliberately presents this as an opt-in alternative for stubborn PDFs rather than a universal deterministic fix.
12. artiz commented on Oct 16, 2026

    

    Artem Kustikov (artiz)

    on Oct 16, 2026

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    Following up on the docling suggestion above: docling.rs (https://github.com/docling-project/docling.rs) is a Rust port of docling with a MarkItDown-compatible Python API, so the headings and tables come through with the same call shape as MarkItDown, without the Python/PyTorch stack. I maintain it. Disclosure: its accuracy numbers are scored against docling’s own groundtruth, so treat them as a sanity check rather than an independent benchmark.