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Ask HN: I have many PDFs – what is the best local way to leverage AI for search?

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Re: Ask HN: I have many PDFs – what is the best local way to leverage AI for search?

#61

Post by nl »

rspoerri wrote: post #57
nl wrote: post #27

Earlier quoted context omitted.

Does the llamaindex PDF indexer correctly deal with multi-column PDFs? Most I've seen don't, and you get very odd results because of this.

i've made quite good conversions from pdf to markdown with https://github.com/VikParuchuri/marker . it's slow but worth a shot. Markdown should be easily parseable by a rag. i'm trying to get a similar system setup on my computer.

This looks worth exploring, so thanks. The author has done a bunch of work beyond what PyMuPDF does on multicolumn layouts.

Re: Ask HN: I have many PDFs – what is the best local way to leverage AI for search?

#62

Post by jesterson »

The best tool I found for myself for similar goal was Devonthink. Using it for many years since and quite happy with it.

There is no AI or any other modern fad, but fulltext search (including OCR for image files inside PDFs) works great

Re: Ask HN: I have many PDFs – what is the best local way to leverage AI for search?

#63

Post by hiq »

finack wrote: post #6

OCR and pattern matching on text are computationally cheap and incredibly easy to do. For example, tax documents often bear the name of your government's tax authority, which presumably you are familiar with and can search for. They also tend to have years on them.

This.

I wanted to convert some equations from some maths textbook back into latex, and I found that taking a screenshot and feeding the image into some LLM service supporting images was a good way to do that.

Re: Ask HN: I have many PDFs – what is the best local way to leverage AI for search?

#65

Post by jononor »

ravetcofx wrote: post #53
andai wrote: post #35

Earlier quoted context omitted.

I found that grep actually outperformed vector search for many queries. The only thing I was missing was when I didn't know how exactly to phrase something (the exact keyword to use). Do keyword search systems have workarounds for this? My own idea was for each keyword to generate a list of neighbor keywords in semantic space. I figured with such a dataset, I'd get something approximating vector search for free. I ma…

Do you know of any way to build a fast index you can run grep against? Would love to have something as instantaneous as "Everything" on windows for full text on Linux so I can just dump everything in a directory

Tracker is an open source project for that. It has been around for some 10+ years now. https://tracker.gnome.org/overview/

Re: Ask HN: I have many PDFs – what is the best local way to leverage AI for search?

#66

Post by datpiff »

SoftTalker wrote: post #38

If you haven’t given some serious thought to getting rid of most of the documents then consider it. There is very little need to keep most routine documents for more than a few years. If you think you need your electric bill for March 2006 at your fingertips, why?

I was hoping someone would make this point. A lot of digital archiving is just delaying tossing things - a hard drive is easier to deal with than boxes of paper. The contents can still be useless.

When it comes to a search solution - what kind of searches have you done in the past? What kind of problems did you come across? If the answer to either is "none" you are planning on building a useless system.

Re: Ask HN: I have many PDFs – what is the best local way to leverage AI for search?

#70

Post by theolivenbaum »

If you're looking for something local, we develop an app for macOS and Windows that let's you search and talk to local files and data from cloud apps: https://curiosity.ai For the AI features, you can use OpenAI or local models (the app uses llama.cpp in the background, it ships with llama3 and a few other models, and we're soon going to let you use any .gguf model)
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