Agreed that there’s no all-in-one solution to play local music and music on Spotify (if I’m a premium user). I vaguely recall there’s a solution to automate playing Spotify music and record it in real-time (since you cannot download music directly) but it seemed too troublesome, so I eventually chose spot-dl4 to download music from YouTube using Spotify playlist, then the folder got imported into Lidarr/Navidrome, then my Symfonium on Android connects to Navidrome to get the songs.
It’s quite a bit of manual work to add songs to a separate playlist if I like something on Spotify then use spot-dl4 to do the download. At least, I successfully keep a copy of my favourite songs on my server.
Between Tube Archivist (TA) and Pinchflat (PF), it seems TA is a better choice (because you want to delete the downloaded videos). TA has a built-in interface to watch and delete the video. But if you are like me, who watches the videos in Jellyfin and don’t plan to delete them afterwards, then PF is a solid archival application.
I suppose you are using the plugin at https://github.com/tubearchivist/tubearchivist-jf-plugin. Very rarely I had the same problem. But if I ignore it, the data sometimes fixes itself after another update. If not, you could try the manual trigger. Frankly I have no idea why it fails sometimes.
I purchased my first NAS a few months ago and I had zero knowledge of self hosting and zero knowledge of Linux. I did manage to install all of these applications but, as suggested by tutorials I read, also installed Portainer because using docker in a command line method was just way too difficult. I’m quite sure I wouldn’t be able to set up anything without a GUI.
I know this is not the theme of this post, but I wonder if there’s an LLM that doesn’t hallucinate when asked to summarize information of a group of documents. I tried Gpt4all for simple queries like finding out which documents mentioned a certain phrase. It often gave me filenames that didn’t actually exist. Hallucinating contents is one thing but making up data source is just horrible.