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Ask HN: Best on device LLM tooling for PDFs?

4 балловавтор: martinald7 дней назад
I&#x27;ve got very used to using the &quot;big&quot; LLMs for analysing PDFs<p>Now llama.cpp has vision support; I tried out PDFs with it locally (via LM Studio) but the results weren&#x27;t as good as I hoped for. One time it insisted it couldn&#x27;t do &quot;OCR&quot;, but gave me an example of what the data _could_ look like - which was the data.<p>The other major problem is sometimes PDFs are actually made up of images; and it got super confused on those as well.<p>Given this is so new I&#x27;m struggling to find any tools which make this easier.

2 comments

raymond_goo7 дней назад
Try something like this<p><pre><code> !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(&#x27;k.pdf&#x27;, dpi=300) all_text = &quot;&quot; for page_num, img in enumerate(pages, start=1): text = pytesseract.image_to_string(img) all_text += f&quot;\n--- Page {page_num} ---\n{text}&quot; print(all_text)</code></pre>
constantinum4 дня назад
give <a href="https:&#x2F;&#x2F;pg.llmwhisperer.unstract.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;pg.llmwhisperer.unstract.com&#x2F;</a> a try