Hi, I’m looking for some recommendations, mostly looking for pointers of where to go and look at/research stuff as I have no idea what is good and what is just well advertised.
Intro:
I have finally entered the world of (almost) Gigabit internet, which is opening up options with what I can host.
I currently have:
Pi hole on an actual RP (will probably remain there because its easy)
Inbound Wireguard VPN on my old router (will stop working when my old ISP stops service) EDIT: my new ISB gave me a router, but it doesn’t have VPN functionality
Foundry VTT that I run up on my gaming machine when needed
I will probably also be upgrading my gaming PC in the next few months, so my current rig will probably be put behind the TV to use as a server and for couch gaming.
Info/recommendations I would like:
VPN software (I want to VPN INTO my network) My goto would be wireguard, is that still a good option? (I assume I just port forward the VPN ports to the server?)
Private cloud/File server: I both want to be able to occasionally (but permamently) host files publicly, but still have the main store be available on the local network only. Is that going to be two pieces of software, or just one?
Is a local video streaming app actually useful for a rare watcher of movies etc, or can they be streamed directly from the file server? its something that I see a lot of people talk about, but don’t really understand why…
Is Docker the way to go for everything? or just install on the machine directly?
Piracy VM - Enabling the virtualisation stuff for Docker mostly breaks virtualbox (at least on windows) any recommendations for how to nicely run a VM alongside docker (if that’s the recommendation)?
Should/Could I be hosting anything else? Foundry will probably be on there. I don’t feel like I have a use for smart home stuff, so home assistant wouldn’t be much use etc.
Interesting approach with the ASN — haven’t started using that feature yet. If I understand correctly, you add a QR ASN to each document you need to keep a physical copy of? And that sticker also has the ASN in human readable form?
So you would then add many documents at once to the feeder, and Paperless will read the QR and also split documents whenever a new code appears?
What about documents you don’t want to keep physically? Is there a way to get Paperless to split them automatically as well if you add many to the feeder?
And that sticker also has the ASN in human readable form?
Yes! They look like this:
So you would then add many documents at once to the feeder, and Paperless will read the QR and also split documents whenever a new code appears?
What about documents you don’t want to keep physically? Is there a way to get Paperless to split them automatically as well if you add many to the feeder?
Paperless supports two different splitting methods:
If it encounters an ASN QR code, it’ll split at that point and keep the page with the barcode
If it encounters a special barcode that’s used as a separator sheet, it’ll split at that point and delete the page with the barcode. By default it looks for a “Patch T” barcode, and you can a page with a Patch T barcode from https://www.alliancegroup.co.uk/patch-codes.htm
so all you need to do is have a “Patch T” page between each document and it’ll split them automatically.
I’m also using paperless-ai to automatically tag and set a title for scanned documents. Very useful. I’d love to run my own AI locally using ollama, but I don’t have good enough hardware so for now I’m using Google’s Gemini 2.0 Flash. I trust Google’s privacy policy far more than OpenAI’s, Google Gemini is very cheap, and if you use the paid version they don’t retain any of your data nor use it for training.
Thanks, this sounds really useful. Patch T sounds like some manual sorting work, but I guess with the option to reuse those separator pages it is still better than manual splitting or - worse - single scanning.
I haven’t looked into paperless-ai yet, but I hope my machine would be beefy enough for this task — worst case I guess it might take a little longer to process all docs.
Now I only still need to decide on a good archiving method. I read some article a long time ago about the pros and cons of different document archiving methods used by professional archivers. Some prefer horizontal stacking in boxes, while others prefer vertical stacks in vertical boxes. Pretty interesting nerdy topic 😀
I haven’t looked into paperless-ai yet, but I hope my machine would be beefy enough for this task
You need a GPU with a decent amount of VRAM to get LLMs working well locally. I don’t have a new enough GPU to be useful - my server just has the Intel iGPU, and my desktop PC only has a GTX1080, which is from before Nvidia added Tensor cores for AI.
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Interesting approach with the ASN — haven’t started using that feature yet. If I understand correctly, you add a QR ASN to each document you need to keep a physical copy of? And that sticker also has the ASN in human readable form? So you would then add many documents at once to the feeder, and Paperless will read the QR and also split documents whenever a new code appears?
What about documents you don’t want to keep physically? Is there a way to get Paperless to split them automatically as well if you add many to the feeder?
Yes! They look like this:
Paperless supports two different splitting methods:
so all you need to do is have a “Patch T” page between each document and it’ll split them automatically.
Docs: https://docs.paperless-ngx.com/advanced_usage/#document-splitting
I’m also using
paperless-aito automatically tag and set a title for scanned documents. Very useful. I’d love to run my own AI locally using ollama, but I don’t have good enough hardware so for now I’m using Google’s Gemini 2.0 Flash. I trust Google’s privacy policy far more than OpenAI’s, Google Gemini is very cheap, and if you use the paid version they don’t retain any of your data nor use it for training.Thanks, this sounds really useful. Patch T sounds like some manual sorting work, but I guess with the option to reuse those separator pages it is still better than manual splitting or - worse - single scanning.
I haven’t looked into paperless-ai yet, but I hope my machine would be beefy enough for this task — worst case I guess it might take a little longer to process all docs.
Now I only still need to decide on a good archiving method. I read some article a long time ago about the pros and cons of different document archiving methods used by professional archivers. Some prefer horizontal stacking in boxes, while others prefer vertical stacks in vertical boxes. Pretty interesting nerdy topic 😀
You need a GPU with a decent amount of VRAM to get LLMs working well locally. I don’t have a new enough GPU to be useful - my server just has the Intel iGPU, and my desktop PC only has a GTX1080, which is from before Nvidia added Tensor cores for AI.
Thanks, I’ll look into it. For completionists: This is the article about how to properly archive paper: https://peelarchivesblog.com/2024/09/10/how-do-archivists-package-things-the-battle-of-the-boxes/