nlm-ingestor

Data

pdf parsing for rag

SHOW HN2024

293points
32comments
#214of 3,515 in 2024
Top 7%of 2024 by points

How HN took it

MixedNo clear lean

9 positive, 9 neutral or asking, 2 mixed, 3 critical, out of 23 comments about the project. Thread score +0.20.

Execution: 2 for, 2 againstIdea: 2 for, 0 againstDocs: 0 for, 1 against

The thread, comment by comment

Each row is a top-level comment and its replies, in HN's order. Select a cell to open that comment on HN.

positive neutral or mixed critical about another commenter or something else the maker

What HN said

What people liked

  • Chunking keeps context together and table parsing is good

    From 1 comment
    • Thanks, I always forget I can do that! I've given it a go and it's really impressive – the default chunker is very smart and manages to keep most of the chunk context together…
      mpeg on HN
  • Fills a need for better RAG document loading

    From 2 comments
    • We've been looking for something exactly like this, thanks for sharing!
      xfalcox on HN
    • Last time I tried Langchain (admittedly, that was ~6 months ago) the implementations for content extraction from PDFs and HTML files were very basic. Enough to get a prototype…
      rmsaksida on HN

Objections

  • Docker image does not build natively on Apple silicon

    From 1 comment
    • I couldn't try this tool as it doesn't build on apple silicon (and there's no ARM docker image) However, I have a PDF parsing use-case that I tried those RAG tools for, but the…
      mpeg on HN
  • Hard to evaluate without example PDFs or input/output pairs in the repo

    From 2 comments
    • Do you ave any examples? There doesn't seem to be a single PDF file in the repo.
      jvdvegt on HN
    • Thank you for sharing. Are there some example input output pairs somewhere?
      firtoz on HN
  • Tesseract OCR makes mistakes

    From 1 comment
    • I am also curious about this. ADI is reliable but does have edge case issues on malformed PDF I fear tesseract OCR is a potential limitation though. I’ve seen it make so many…
      cdolan on HN

Requests

  • Provide example inputs and outputs

    From 2 comments
    • Thank you for sharing. Are there some example input output pairs somewhere?
      firtoz on HN
    • Do you ave any examples? There doesn't seem to be a single PDF file in the repo.
      jvdvegt on HN
  • Benchmark comparison against other loaders

    From 1 comment
    • Tesseract OCR fallback sounds great! There are now a lot of file loaders for RAG (langchain, LLMindex, unstructured, ...), any reasons, like a leading benchmark score, to prefer…
      lmeyerov on HN

Questions

  • How does it compare to Azure Document Intelligence

    From 1 comment
    • How does this differ from Azure Document Intelligence, or are they effectively the same thing?
      guidedlight on HN
  • How does it compare to PaddleOCR

    From 1 comment
    • How does this compare to PaddleOCR? Looks like Apache 2 license which is nice.
      ilaksh on HN

Alternatives named

  • llmsherpa

    From 1 comment
    • Thanks for the post. Please use this server with the llmsherpa LayoutPDFReader to get optimal chunks for your LLM/RAG project: https://github.com/nlmatics/llmsherpa. See examples…
      asukla on HN
  • Azure Document Intelligence

    From 1 comment
    • How does this differ from Azure Document Intelligence, or are they effectively the same thing?
      guidedlight on HN
  • PyMuPDF/fitz

    From 1 comment
    • For me, PyMuPDF/fitz has been the best way to retain natural reading order and set dynamic enough rules to extract text in complex layouts. None of the mentioned tools did this…
      ramoz on HN
  • pdfminer.six

    From 1 comment
    • Off-topic, but do you know how Tika compares to other pdf parsing libraries? I was very unimpressed by pdfminer.six (what unstructured uses) as the layout detection seems pretty…
      mpeg on HN
  • Tabula

    From 1 comment
    • Tika uses PDFBox under the hood, using its built-in text extractor (which is "ok"). If you're looking for table extraction specifically, check out Tabula…
      jahewson on HN

Category, keywords, summaries and labels on this page were made by AI (Thread Reader v2) and not checked by hand. Each point links to the comments it came from.

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