Ask HN: Best on device LLM tooling for PDFs?

I've got very used to using the "big" LLMs for analysing PDFs

Now llama.cpp has vision support; I tried out PDFs with it locally (via LM Studio) but the results weren't as good as I hoped for. One time it insisted it couldn't do "OCR", but gave me an example of what the data _could_ look like - which was the data.

The other major problem is sometimes PDFs are actually made up of images; and it got super confused on those as well.

Given this is so new I'm struggling to find any tools which make this easier.

4 points | by martinald 13 days ago

2 comments

  • raymond_goo 13 days ago
    Try something like this

      !pip install pytesseract pdf2image pillow
  !apt install poppler-utils
  #!apt install tesseract-ocr
  from pdf2image import convert_from_path
  import pytesseract

  pages = convert_from_path('k.pdf', dpi=300)

  all_text = ""
  for page_num, img in enumerate(pages, start=1):
      text = pytesseract.image_to_string(img)
      all_text += f"\n--- Page {page_num} ---\n{text}"

  print(all_text)
  • constantinum 10 days ago
    give https://pg.llmwhisperer.unstract.com/ a try