Turning a pile of documents into a searchable useable knowledge base

https://github.com/linuxrebel/DocuBrowser

by linuxrebe1 • 14 days ago

195 56 14 days ago

linuxrebe119• 14 days ago

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.

bobim2• 14 days ago

Could it be extended so it also extracts pictures from pptx and xlsx and run vision to get a description to be added to the text content before indexing?

linuxrebe119• 14 days ago

Let me look into this

seb1204• 14 days ago

Sounds similar to https://docs.paperless-ngx.com/

Key difference I see is that you point it to a folder instead of uploading to a system.

vsviridov• 14 days ago

I think paperless devs are working on AI integration, and there are 3rd party solutions. I'm holding out for an official one, so far.

It's pretty cool, I've set up a share where the scanner scans, and it automatically picks it up from there and ingests it into the system.

password43212• 14 days ago

Personal use? I need this at work, dragging useful info from tarpits like Teams and GitLab.

Also need to search git repos including all branches and history (TIL/xkcd#153'd GitLab's web search can basically only do one branch at a time).

linuxrebe119• 14 days ago

I creating DocuRepo as well. though not as fleshed out.

rukshn• 14 days ago

But how’d you access teams when it’s work teams and don’t have api access ?

gatnoodle• 14 days ago

This looks really cool. Can you tell me the minimum specs required to run this? It would nice if you could add it to the readme as well.

linuxrebe119• 14 days ago

I've run it on a VM with 4G ram and no GPU. It runs, But I really recommend 8G ram at least. If you have a GPU (like I do) with 4G vRAM that is ideal. Will get this in the readme. Thanks for the suggestion. I really tried to build this to minimal spec.

fnordian• 14 days ago

It’s either restricted to personal use, or it’s GPL-3. How can you have both?

linuxrebe119• 14 days ago

By restricted for personal use I mean it's not networked. It's running on your system only. It's not a networked commercial product able to do SSO etc. It's not an enterprise level product.

aucisson_masque2• 14 days ago

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

rahimnathwani• 14 days ago

Did you mean Recoll (https://www.recoll.org/)?

aucisson_masque2• 12 days ago

Indeed

asciimoo2• 14 days ago

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. =]

hankbond• 14 days ago

I have not set up Hister yet but it's on my list to try out. How would I do something like host it on my Unraid box but have it index/persist my local MacBook browsing history?

linuxrebe119• 14 days ago

I just had a wild thought. Combine Hister with my RepoSearch app. Point it at a companies Internal github/gitlab and have a searchable knowledge base of your git repos.

asciimoo2• 13 days ago

I like the idea. Could you share your RepoSearch app? Also, we have Discord & IRC channels, please join and start brainstorming.

NKosmatos• 14 days ago

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

linuxrebe119• 14 days ago

thankyou

toomuchtodo• 14 days ago

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

linuxrebe119• 14 days ago

I'm actually thinking of this for a commercial product feature. However, if you use a tool like Rclone on Windows, Linux or Mac. Mount the s3 bucket and you can then run DocuBrowse as if the s3 bucket were local.

subhobroto• 14 days ago

I love your project on many fronts. One, you're using Claude. Two, you used Python - but most importantly, you personally care about it.

I will be using this, and I will be making contributions to it as well.

I'm actually thinking of this for a commercial product feature

Would you consider writing down which features you would like to make commercial product features and how you would like to price them?

drizzler• 14 days ago

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?

linuxrebe119• 14 days ago

Yes, not supporting it is an oversight I will correct.

linuxrebe119• 14 days ago

Will have version 0.9.1 out later today to support ODF formats.

jphorism• 14 days ago

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

NamlchakKhandro• 14 days ago

A resume

passwordoops• 14 days ago

Care to elaborate?

linuxrebe119• 14 days ago

- Filling a need I personally have. - Learning how to leverage AI for real world use not just to fill up a data center. - Personal knowledge -developing skills

Pretty much in that order

Avery29• 14 days ago

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

karmakaze• 14 days ago

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

mune2gu-chan• 14 days ago

Not a fan of pushing every personal document to someone else's cloud. Nice to see a tool that keeps everything on disk instead.

nickweb• 14 days ago

Honestly. This with Paperless-NGX might be game changing if both pointed to the same folder.

kamranjon• 14 days ago

Wanted to share Antfly which I think serves a similar niche:

https://antfly.io/

https://github.com/antflydb/antfly

They’ve put a lot of effort into optimizing the local llm pipelines and I have a lot of faith in the devs working on it.

appstorelottery3• 14 days ago

Anyone getting a bunch of permission errors when running (e.g. Traceback (most recent call last): File "/Users/tron/Applications/DocuBrowse/venv/lib/python3.9/site-packages/psutil/_psosx.py", line 347, in wrapper return fun(self, args, *kwargs) File "/Users/tron/Applications/DocuBrowse/venv/lib/python3.9/site-packages/psutil/_psosx.py", line 508, in net_connections rawlist = cext.proc_net_connections(self.pid, families, types) PermissionError: [Errno 1] Operation not permitted (originated from proc_pidinfo(PROC_PIDLISTFDS) 1/2)

appstorelottery3• 14 days ago

Living in bizarro world of AI. Install open source project, fails, feed into OpenCode w/DeepSeekFlash 4 -> feed error into it get fixed.

The kill_port function only catches ImportError from the psutil block, so when psutil is installed but raises AccessDenied (common on macOS), it crashes instead of falling back to lsof.

In platform_paths.py - add two lines after line 250:

except psutil.Error: pass

Fixed. Now when psutil raises AccessDenied (as happens on macOS without elevated privileges), it falls through to the lsof/fuser fallback instead of crashing. Try docubrowser start again.

appstorelottery3• 14 days ago

Disappointed that it wasn't returning a list of paragraphs from eBooks that semantically match; search only appears to list the publications - not the actual match within the document.

linuxrebe119• 14 days ago

I fixed this in version 0.9.1 (just released) thanks for the bug (seriously)

linuxrebe119• 14 days ago

I was building for mac on a VM install of OSX. Will take this as a bug, Thanks.

Ozzie_osman• 14 days ago

This is really cool. Can it play nice with gdrive or Dropbox? For better or worse, that's just where my data lives now but I'd love this layer.

linuxrebe119• 14 days ago

I use rclone to "mount" them locally. Then it becomes searchable.

hunmernop2• 14 days ago

Can you make a dockerfile and docker compose file?

seba_dos1• 14 days ago

You can.

hunmernop2• 12 days ago

Ok, I made them, they work well.

LawrenceKerr• 13 days ago

Many such open source projects already (which is fantastic). I lose track of them.

Today it happened I needed a simple way to embed & query 1TB+ of documents, and I was looking at open source options. Can anyone tell me what their go-to solution is now? Could this be the one?

And what are the key differences vs. other open source RAG tools like kotaemon?

Turning a pile of documents into a searchable useable knowledge base

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