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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.
- raymond_goo 1y agoTry 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 1y agogive https://pg.llmwhisperer.unstract.com/ https://pg.llmwhisperer.unstract.com/ a try