Linux Mint 22, 64GB DDR5, AMD RYZEN 9 7950X , AMD Radeon 6900 XT w/16gb VRAM.
I know it's not my system because in older iterations 1.6.4 and 1.6.5 I was just fine.
Selected local GPU, but it seems like it attempts to connect to an external LLM service and errors out with:
The LLM service has encountered an Error: An error occurred while sending the request.
Below is what I pulled from the log as it ran.
I assume it's attempting to use a 3rd party LLM service instead of my local GPU because of the Tokens, but I'll eat humble pie if I'm wrong.
Tokens: 797
<CheckMemoryCompression>d__163:MoveNext()
System.Threading.ExecutionContext:RunInternal(ExecutionContext, ContextCallback, Object, Boolean)
System.Runtime.CompilerServices.MoveNextRunner:Run()
System.Threading.Tasks.AwaitTaskContinuation:RunCallback(ContextCallback, Object, Task&)
System.Threading.Tasks.Task:FinishContinuations()
System.Threading.Tasks.Task`1:TrySetResult(TResult)
System.Runtime.CompilerServices.AsyncTaskMethodBuilder`1:SetResult(TResult)
KoboldSharp.<GetTokenCount>d__7:MoveNext()
System.Threading.ExecutionContext:RunInternal(ExecutionContext, ContextCallback, Object, Boolean)
System.Runtime.CompilerServices.MoveNextRunner:Run()
UnityEngine.WorkRequest:Invoke()
UnityEngine.UnitySynchronizationContext:Exec()
System.Net.Http.HttpRequestException: An error occurred while sending the request ---> System.Net.WebException: Error getting response stream (ReadDoneAsync2): ReceiveFailure
I'm not trying to run it via 3rd Party Vendors, is there a setting I can change in the .config files to force it to utilize my GPU?
Steps to reproduce:
Download 1.6.6b without having run any other versions of Silverpine. Launch. After AI Model loads, attempt to talk to any NPC. Error should appear.
I'm pretty sure I'm not doing anything out of the ordinary for this.
Edit: Loading the Demo Server things behave as expected, but attempting to load via GPU using the Demo program ALSO triggers this LLM Warning.
Edit 02: Loading older QWEN-3.5 works. I Didn't both with Gemma-4-Dense-Large, I don't have the VRAM for it, but since the Sparse isn't behaving I doubt it's larger brother would either.