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Joined 1 year ago
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Cake day: September 9th, 2023

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  • pirat@lemmy.worldtoSelfhosted@lemmy.worldLow Cost Mini PCs
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    2 days ago

    I’m in the same situation as you, more or less… I have three new 22TB drives that need an enclosure, preferably for JBOD (no hardware RAID needed) but I can’t figure out which ones are actually good products… I don’t mind using a random-brand product if it’s actually solid.

    I find it very difficult to figure out which ones will support my 22TB drives. And for some of them, it seems, it’s impossible to add new drives to empty slots later (because of hardware RAID, I guess?), which has made me hesitant in buying one with more slots than I have drives, in case they can’t be utilized later on anyway…

    I was looking at the QNAP TR-004 which was mentioned by someone else somewhere on Lemmy some months ago, but IIRC it would be impossible to use the fourth slot later if the drive isn’t included in the hardware RAID configuration…

    EDIT: I have also been looking into so-called “backplanes” as an alternative, since they seem to do the job and are cheaper, but I’m unsure if I’ll need a PC chassis/case/tower for that to actually work?

    If you find something good (products or relevant info), feel free to share it with me.



  • If you connect to Jellyfin through Kodi with the JellyCon add-on, you can sync audio, subtitles etc. when it’s playing.

    While it’s possible to navigate through your Jellyfin libraries from within the Jellycon add-on in Kodi, I usually find it quicker to just use the Jellyfin app or webapp on phone/pc to find the desired media, then “cast” it to the active Kodi client. The Kodi client will then play it directly from the server, no video data is going through the casting device.












  • In Liftoff, the Lemmy app I use, you can easily add a picture when writing the post/comment, which will then be hosted on the instance. It’s probably the same for other Lemmy apps. The websites I’m not sure about, since every instance can have multiple web frontends.

    I know I’m replying to a month-old post, but I hope you’ll figure out a solution, since we very much still need to see this.

    Also, if at all possible, please include some proof of those super creamy eels?!

    Thank you very much!

    Example - it works:

    Picture example

    (Made with JS Paint, a retro MS Paint clone in the browser! Remember this brilliant technique for making “art”?)



  • a “tl,dr” bot would probably not even need high end hardware, because it does not matter if it takes ten minutes for a summary.

    True, that’s a good take. Tl;dr for the masses! Do you think an internal or external tl;dr bot would be embraced by the Paperless community?

    It could either process the (entire or selected) collection, adding the new tl;dr entries to the files “behind the scenes”, just based on some general settings/prompt to optimize for the desired output – or it could do the work on-demand on a per-document basis, either based on the general settings or custom settings, though this could be a flow-breaking bottleneck in situations where the hardware isn’t powerful enough to keep up with you. However, that only seems like a temporary problem to me, since hardware, LLMs etc. will keep advancing and getting more powerful/efficient/cheap/noice.

    a chat bot do not belong into paperless

    Right – but, opposingly to that, Paperless definitely do belong into some chatbots!


  • I’m not interest in sending my documents to open AI.

    You wouldn’t have to. There are plenty of well-performing open-source models that work with an API similar to the Open AI standard, with which you can simply substitute OpenAI models by using a different URL and API-key.

    You can run these models in the cloud, either selfhosted or “as a service”.

    Or you can run them locally on high-end consumer-grade hardware, some even on smartphones, and the models are only getting smaller and more performant with very frequent advancements regarding training, tuning and prompting. Some of these open-source models are already claiming to be outperforming GPT-4 in some regards, so this solution seems viable too.

    Hell, you can even build and automate your own specialized agents in collaborating “crews” using frameworks, and so much more…

    Though, I’m unsure if the LLM functionality should be integrated into Paperless, or rather implemented by calling the Paperless API from the LLM agent. I see how both ways could fit some specific uses.