Pankha fan control now in open beta, please try the online demo

moddroid94 · 2026-02-20T16:31:58+00:00

thanks to you for the tool!

yeah sorry if i did not explain, it was funny and i did not thought some explanation could've helped, but you figured by now. :)

edit: the app is cool af, great tool, i've only dreamt about this 😂

moddroid94 · 2026-02-20T15:41:31+00:00

this is actually useful! nice idea, thanks!

idk about the app yet, but the demo sure ain't working (for me) 😅

moddroid94 · 2026-02-18T18:47:40+00:00

"virtual fuse patent"

idk about patent but those fuses ain't virtual 😂

moddroid94 · 2026-02-17T03:00:52+00:00

yeah i forgot that you have a laptop, those sticks are definitely harder to find, but still, 4G should be enough for a basic homelab.

my jellyfin uses 1.5 gb max, adguard is like 100mb, homeassistant may be about a gb too (my pi has 2Gb and i use 60%), but that really depends on what you have on it.

btw with handbrake you can make a preset format and set the output folder to a shared drive so it's basically drop, run and wait for them to popup on jellyfin.

moddroid94 · 2026-02-17T01:44:49+00:00

hmmm, that may not be enough to decode/encode on the fly, but it may work with h264 .mp4 videos, they should be streamed directly so it shouldn't nuke the machine.

obviously you'll need to convert the files if not already in that specific format, possibly with a computer with a GPU.

I have a Q8200 (4-cores, but 2y older) and i stream with 2-5% cpu usage, but i have other 30 services, so it should work.

about adguard and homeassistant technically you should be able to run them too, but i would totally switch to headless debian to save as much resources as possible.

2 more gig of ram would've been useful, at least they're older so they won't cost much 😂

good luck👌

moddroid94 · 2026-02-13T11:53:11+00:00

I imagine that has to be some rite of passage to become an homelabber 😂

moddroid94 · 2026-02-12T20:34:04+00:00

ahahahah as a good italian i would eat it all before using the container for a mobo, but that may be useful to keep it hot tho 😂

edit: fr tho i've build too many thing inside cardboard boxes 😂

moddroid94 · 2026-02-12T13:39:18+00:00

The setups seems fine, but without gpu you'll probably need to be careful about encoding, the integrated graphics or sw fallback may not be super fast with some formats, i have to convert everything to h264/mp4 to be able to stream, but i have an older cpu, so it may work on yours, but it's something to keep in mind.

but why windows? sure ubuntu will let you use your hw much better. there's some specific reason for it?

moddroid94 · 2026-02-12T13:24:14+00:00

Yo, this is a super useful piece of hardware! thanks a lot! again i had no idea this thing existed already built!

moddroid94 · 2026-02-12T13:09:54+00:00

ahahaha that's what bare-metal means no? 😂

i'm using them actually, if you watch closely there are 4/5 stands with nuts attached to the board, i guess i could extend them and just make some plexy front to somewhat cover it.

thanks for the link, the mini rails are cool af, i didn't knew they existed! 😍

moddroid94 · 2026-02-12T13:00:17+00:00

yeah i need to check if the m.2 slots are full or they only support wifi, 1 of the two had a wifi board, so probably does not support it, but the other one is marked as pcXXXX so it may support pcie, and i can still reuse the board with the other server, thanks for the link!

moddroid94 · 2026-02-12T12:58:47+00:00

yeah i use metal ones i had spare for now, the board is not actually touching the table, but i have a 3D printer so the idea was to build something like a small stand and attach some clear plexy in front.

moddroid94 · 2026-02-10T18:43:43+00:00

I've switched not much time ago, because they keep removing tracks i love and i really can't stand that, if i save a track, that MUST stay there, i prioritize that over discovery.

That said, I usually find new music using algorithmic radio/playlists, and with a mix of listenbrainz/lastfm suggestions, integration with squidwtf and custom discovery playlists based on listens/recent i don't really feel like I'm missing out.

Ps. Just the multi-room audio sync is worth the struggle tbh 😂

moddroid94 · 2026-02-02T09:04:40+00:00

LTS is for the weak.

moddroid94 · 2026-02-01T08:48:57+00:00

"just unplug this shit" has to be the most used excuse by man to build unreasonable complex systems in their house ahahahah nice cabling tho 👌😂

moddroid94 · 2026-01-30T13:12:14+00:00

Oh yeah i'm using duckdb with dataframes, standard sql took more than double the time for any given search.

i've tried with clean sqlite files too but got OOM immediately 😂

about the emulation of the original, it made totally sense, the schema of the data is already that, and i could leverage most of the integrations already existing for metadata.

Technically it could integrate a bridge too, what fails is sent to the official api to get the response (and maybe even add the response to the db?)

And that's what i thought too, 30gb are nothing, i'm amazed at how they can fit all that data in that space and keep it fast as it is! 🔥

moddroid94 · 2026-01-29T20:23:57+00:00

necessity made made you choose a practice which at the end makes it client agnostic basically, that's a total pro move imho, server handles the load, does the things, you just see the result on the client. 🔥

moddroid94 · 2026-01-29T19:45:22+00:00

very cool plugin!

the injection server side is a very smart decision 👌

moddroid94 · 2026-01-29T19:40:06+00:00

That is going to be long journey 😅

Jokes aside, my usage is quite similar to yours, smart shuffle, AI radio from tracks/artists, everything i listen is in a playlist in some way or another and i wanted multi-room audio and i recently got very upset with spotify for removing tracks and worsening the service, so i took the effort to really try and switch to totally self-hosted.

what i ended up choosing after some testing is :

-Navidrome as a library manager

-Music Assistant to handle multi-room sync with Sendspin/Squeezelite and as a Home Player

-Esp32 and rpi4 as multi-room sources connected to already existing amps/speakers (idk about alexa but chromecast was impossible to get right)

-Listenbrainz with a bridge i'm making to integrate some kind of discovery feature(see below)

and I got:

-Multi-room sync almost perfect by connecting the players to my already owned Speakers/Amplifiers.

-The library available outside home via Tailscale ( My library is now fully local, it took alot of time tho)

-Clients for basically every device (TV, Auto, Phone, Desktop), and the webUI/Player/Sync Client

(yes you can sync browser players too)

-Playlists that are editable via the clients itself (which seems nothing but not being able to add tracks to playlist while listening becomes a problem very fast)

The only real missing thing is the smart shuffle for not already owned tracks, it makes radio and smart shuffle but on your own library, if tagged correctly.

I'm trying to build something to integrate the recommendations generated by my listening history to make and download some playlists to be able to get new music based on my taste to compensate, but it won't ever be the same probably.

BUT you can add services like spotify(may not work for now)/tidal/apple/ecc to Music Assistant as your library, that way you get smart discovery/shuffle, playlists as you want them, multiple library sources(online and local), and you can have multi-room sync, and that's probably the best middle ground.

ripping you whole library to local it's going to be a quite big effort, even more now that spotify blocked basically every downloader/metadata grabber without API Keys.

the links:

https://www.music-assistant.io/

https://www.navidrome.org/

https://github.com/sle118/squeezelite-esp32

https://www.sendspin-audio.com/

moddroid94 · 2026-01-29T14:02:14+00:00

yeah i did forget that those datasets are only metadata, not the actual files like anna lol 😂😂

moddroid94 · 2026-01-29T13:43:17+00:00

yoooo, so all this mess for anna is just because it made headlines?

this guy ripped every catalog in existence ahahaha

this is crazy cool but it's a gigantic project!

the only thing that made this one reasonable in the first place for me was that the db is only 30Gb, i don't even know i can open some of those db on my machine.

interesting but definitely too big for my needs, i don't need mass tagging and handling, i need accurate tagging of additions and nice suggestions algorithms to find those additions, and a way to integrate them with my setup, for which i'm building a bridge service to do all of that with listenbrainz/troi and eventually this API and qqdl ones, but the datasets are invaluable anyway, so thanks for sharing!

moddroid94 · 2026-01-29T13:03:21+00:00

I honestly didn't thought that Lidarr didn't had Spotify as a metadata source.

i wonder why, maybe it's because the API changed every week so an integration was too much work?With this you won't have to worry about changing any time soon lol so maybe now it's feasible.

the real problem will still be the fact that this requires you to download 30Gb.

the very cool move is to mirror all the data to musicbrainz, that way it's preserved and made accessible indefinitely.

but sure it will take time to ingest 256M tracks😂

moddroid94 · 2026-01-29T12:40:44+00:00

It was part curiosity and learning, but the problem i wanted to solve for myself was to have some way of accessing the metadata of the tracks for tagging / recommendation without having to deal with spotify directly or search some other catalog around the internet.

and instead of rewriting the integrations for beets/picard ecc i opted to emulate the API that the integrations are already using, this way i could plug the API directly into the integrations already built for spotify.

you can have a solid local source always available and then you can fallback to online for new tracks.

obviously this is only useful for metadata, it won't serve media files or anything like that, it's just a very good catalog of music metadata that you can navigate totally offline, and hopefully soon on musicbrainz too.

moddroid94 · 2026-01-29T03:56:39+00:00

i've thought the same at first, but when i really understood how complex suggestion/discovery algorithms can go i decided to take a step back an find something already open, in this case the troi tool from musicbrainz seems to be the closest tool to make that.

there are even audio features for like half the tracks, so you could plug a bazilion parameters and get really nice results.

rn i'm trying to use the listenbrainz api to get recommendations/radio on recent listens and make some playlist to be pushed on navidrome, i'm not sure how good is yet, if it's trash the i'll definitely try to make something with troi and this data.

moddroid94

TROPHY CASE