Just to add an update to this: I was able to improve the "seam" in my seamless loop by manually setting the loop start to the priming frame count from afinfo, and the loop end to priming + valid. However, I'm now wondering whether a truly seamless loop is actually possible with compressed audio. Since the signal at any given point is always an approximation when encoded, the audio on both sides of a "cut" in the original wav must also be an approximation, meaning that the two sides won't necessarily be as "similar" as in the original. That seems reasonable to me, but is it correct? I'm talking about a "seamless" loop of an ambient soundscape recording, btw, so there's no actual silence (i.e., it's not a drum loop or anything like that).

Thanks for the response. Actually, it will pause and stay paused if I break in the main View, but in a service function I have for processing data it stops for a few seconds, then continues. It's a static function in a singleton, but I don't think that would make a difference. However, I actually just noticed a couple of things: 1) the app is actually detaching and continuing, and 2) it's posting an error that I hadn't noticed before (gulp): Message from debugger: The LLDB RPC server has crashed. You may need to manually terminate your process. The crash log is located in ~/Library/Logs/DiagnosticReports and has a prefix 'lldb-rpc-server'. Please file a bug and attach the most recent crash log.... It does the same breaking at various points in a custom package I'm developing alongside the app. I'll file a bug... I guess this should go to Swift, not necessarily Apple? EDIT: Actually, I see a similar unresolved issue from August at bugs.swift.org: https://bugs.swift.org/browse/SR-15110?jql=text%20~%20%22lldb%20crash%22 (In case anyone else is seeing the same issue.)

Thanks for the info @ConatusEng, but unfortunately I get a ModuleNotFound error when trying to import tensorflow_text. I've tried several different approaches, from various places on the internet, but no luck. I did notice that, for whatever reason, my conda install is miniconda3, not miniforge3, which a lot of people seem to have. I've running torchserve locally under a different env (for several months), and it works fine, so I don't really want to re-install conda if I can help it. Installing tensorflow-text from source does complete successfully, so I'm really not sure why the module won't load. Any thoughts?

I'm not sure that it's concerning, but it's annoying that we don't have anything yet. I have yet to try an LLM that's really good for Swift. Understandable. They're probably working to make sure they're substantively better than anything else out there.

Yeah, crazy... I could really use Swift Assist to deal with some SwiftUI problems I'm having. None of the LLMs are particularly good at SwiftUI, and seem to be wasting more of my time than they're saving. When, Apple???? You're the only ones with the data and the incentive to build a really knowledgeable Swift coding LLM.... super frustrating. This should be a no-brainer for Apple.

I hope WWDC gives us some news about Swift Assist. We really need a better LLM for Swift, imho.