u/Synthetic451

I can finally have a completely rootless container stack inside a custom podman network where the only ingress is through a reverse proxy container. The inability for my service containers to see the true source IP was literally the only thing holding me back from going rootless and it is finally HERE! 🎉

I simply added:

[network]
rootless_port_forwarder = "pasta"

into a drop-in conf file in /etc/containers/containers.conf.d and now my Nextcloud and Jellyfin can see where requests are actually coming from instead of my proxy container's internal IP. That means proper brute-force protection in Nextcloud and the ability to do IP banning.

I could not be happier with this setup. Huge thanks to the wonderful human beings who made this possible!

Upgraded to steam 1.0.0.86-1 today and realized that my Steam controller 2 (paired over Bluetooth) stopped working. KDE didn't even recognize it as a gamepad in the System Settings. Downgraded to 1.0.0.85-7 and it restored functionality.

Anybody else seeing the same?

I am using the 6.7 plasma packages that just rolled out in Arch extra-testing. I enabled HDR but when I launched into a game, the showcomposition kwin debug effect still showed that the game was being composited.

I am extremely sensitive to input latency so I prefer direct scanout but I do miss HDR. Anyone know what the current status is and what's left to do?

Qwen and Unsloth docs suggest that chat_template_kwargs: {"preserve_thinking": true} can increase accuracy for long conversations, but every time I enable it, Roo starts getting API errors. Is it just not recommended to use preserve_thinking in Roo or am I doing something wrong?

I have Roocode connecting through OpenWebUI to llama.cpp, which hosts the model using the following

[qwen3.6:27b]
hf-repo = unsloth/Qwen3.6-27B-GGUF
hf-file = Qwen3.6-27B-Q4_K_M.gguf
ctx-size = 128000
load-on-startup = false
temperature = 1
top-p = 0.95
top-k = 20
min-p = 0.0
presence-penalty = 1.5
repeat-penalty = 1.0
cache-type-k = q8_0
cache-type-v = q8_0

and then I override top-p, top-k, min-p, etc. with the recommended values for coding tasks via a custom model in OpenWebUI

temperature = 0.6
top_p = 0.95
top_k = 20
min_p = 0.0
presence_penalty = 0.0
repeat penalty = disabled or 1.0

I am relatively new to this so any help appreciated.