Is there a way to run an LLM as a better local search engine?

15 hours agoby oblio

Basically, I was thinking that a way I could actually use LLMs would be to point them at my hard drive, with hundreds of images, PDFs, XLS' and other random files, and start asking it questions to easily find things in there. Can a local LLM run OCR software on its own?

I'm on Windows, if it matters. Is there anything like that out there, already (mostly) built?

What you described would be a great solution for plenty of tasks, but maybe solving some fallacies one at a time would also be great. For example, when we're sure by placing a properly named file at a directory location, we will find it by recalling the folder name or the name of the file itself while in reality we're often surprised that after months or years this won't work, the expected path to the file either not exists or doesn't contain what we're looking for. The same fallacy is true also for different hierarchical notes organizers.

In this case LLMs with their ability to find semantic equivalence might be a great help. And with the current state of affairs I even think that an LLM with a sufficiently large context window might absorb some kind of the file system dump with directory paths and file names and answer a question about some obscure file from the past.

12 hours agoby Agraillo

You need to provide more information.

Is your data organized or is just a dump of unrelated content?

- If you have a bag of files without any metadata the best option is to create something like a RAG, with a pre OCR step for image files (or even some multimodal model call).

- If the content is well organized with a logic structure an agent could extract information with a little look around.

Is static or varies day by day?

- If is static you could index all at once, if not, an agent that pick what to reindex would be a better call.

I'm not aware of a solution like this, but seems doable as an MCP server. But the cost will scale quiclky.

15 hours agoby DHRicoF

Multimodal Qwen is pretty good at OCR although it's pretty slow without a GPU.

For pure search you're almost certainly better off building an index of CLIP embeddings and then doing cosine similarity with a query embedding to find things. I have gigabytes of reaction images and memes I've been thinking about doing this with.

11 hours agoby msgodel

Seems that you're looking for a RAG System, and you may have a try RAGFlow

14 hours agoby aliasmaya

Have you tried asking this question at an LLM? :p

14 hours agoby Iolaum

local as in on your filesystem?

14 hours agoby cranberryturkey