Turning a pile of documents into a searchable useable knowledge base

I learned a solution is to turn the documents into vectors in say PostgreSQL (with pgvector) and do a cosine similarity search with a search vector. Doing a search for embed models on HuggingFace shows nomic-ai/nomic-embed-text-v1.5 and Qwen/Qwen3-Embedding-0.6B. I might have used a larger one like Qwen/Qwen3-Embedding-4B.

There's some info for AnythingLLM[0] which supports RAG. AnythingLLM has LanceDB out of the box but also supports others including pgvector.

[0] https://docs.anythingllm.com/features/embedding-models

I had an issue. A documents folder with over 12k objects in it. A hodgepodge of folders and sub-folders. That over time had created a mess that no amount of file movement was ever going to make it usable. I wanted: 1) To keep my data local 2) be able to filter out PII and other data 3) Be able to find and delete duplicates 4) Get short synopsis of what a document is 5) Semantic and keyword search 6) All of this kept local to me requiring no internet access and no tokens spent to train someone elses AI.

The result I call DocuBrowser and in it's current form is FOSS (GPL-3) licensed for your personal use. The UI is in your browser. The AI models used are held local and are tiny, Available for Linux(RPM,Deb, and tgz) Windows and Mac. Let me know what you think and thanks for taking the time to try it out.

We need projects like this. Automatically classifying the files is smart.

I'm working on a similar application called Hister (https://github.com/asciimoo/hister). I should borrow some of your ideas. =]

The hardest part of these projects is usually not making documents searchable

Looks good, definitely going to try it. Extra thanks for creating something fully local, we need more projects like this one!

Nice, what are you hoping to accomplish with this project?

I'm a huge fan of recall, going to test this out. This looks very interesting.

I just installed this and, after a few hiccups, got it up and running on my Ubuntu system. Works great, looks great. Thank you for this. Half of my documents are OpenDocument format. Is there any chance you'll be supporting ODF in the future?

How do you feel about supporting an S3 compatible target as a feature request?