feat(health): warn when GPU arch isn't supported by PyTorch build

Applies the compatibility-checker portion of #367. Adds a
check_cuda_compatibility() helper that compares the current device's
compute capability against torch.cuda._get_arch_list() and returns a
human-readable warning if the PyTorch build doesn't support it.

Wired into three places:
  • HealthResponse gains a gpu_compatibility_warning field so clients
    can surface the issue in the UI
  • Startup logs the warning as WARN level
  • _get_gpu_status() appends "[UNSUPPORTED - see logs]" to the GPU
    label shown in settings

Skipped #367's other half — the switch from stable to nightly cu128
wheels across release.yml, build_binary.py, and justfile. That's
redundant with #401's TORCH_CUDA_ARCH_LIST=...12.0+PTX approach and
would introduce non-deterministic builds from shifting nightly
releases.

Co-Authored-By: nyzxor <[email protected]>
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

backend/backends/base.py

@@ -126,6 +126,44 @@ def get_torch_device(
     return "cpu"
 
 
+def check_cuda_compatibility() -> tuple[bool, str | None]:
+    """Check if the installed PyTorch supports the current GPU's compute capability.
+
+    Returns:
+        (compatible, warning_message) — compatible is True if OK or no CUDA GPU,
+        warning_message is a human-readable string if there's a problem.
+    """
+    import torch
+
+    if not torch.cuda.is_available():
+        return True, None
+
+    major, minor = torch.cuda.get_device_capability(0)
+    capability = f"{major}.{minor}"
+    device_name = torch.cuda.get_device_name(0)
+    sm_tag = f"sm_{major}{minor}"
+
+    # torch.cuda._get_arch_list() returns the SM architectures this build
+    # was compiled for (e.g. ["sm_50", "sm_60", ..., "sm_90"]).
+    try:
+        arch_list = torch.cuda._get_arch_list()
+        if arch_list:
+            # Check for both sm_XX and compute_XX (JIT-compiled) entries
+            compute_tag = f"compute_{major}{minor}"
+            if sm_tag not in arch_list and compute_tag not in arch_list:
+                return False, (
+                    f"{device_name} (compute capability {capability} / {sm_tag}) "
+                    f"is not supported by this PyTorch build. "
+                    f"Supported architectures: {', '.join(arch_list)}. "
+                    f"Install PyTorch nightly (cu128) for newer GPU support: "
+                    f"pip install torch --index-url https://download.pytorch.org/whl/nightly/cu128"
+                )
+    except AttributeError:
+        pass
+
+    return True, None
+
+
 def empty_device_cache(device: str) -> None:
     """
     Free cached memory on the given device (CUDA or XPU).