fix(hwfit): detect unified-memory NVIDIA (Grace Blackwell GB10 / DGX Spark) instead of 'No GPU' (#1340) (#1372)

_detect_nvidia parsed nvidia-smi --query-gpu=memory.total,name and did
float(memory.total) per row, dropping the row on ValueError. Grace Blackwell
GB10 (DGX Spark, sm_121) reports memory.total as '[N/A]'/'Not Supported'
because the GPU shares the system LPDDR pool rather than carrying discrete VRAM
— so the only GPU row was dropped and a real GB10 (even with vLLM running on it)
was reported as 'No GPU', breaking Cookbook recommendations and model switching.

Keep a named device whose memory.total is non-numeric: when there are no
discrete-VRAM rows but such unified devices exist, report a unified-memory CUDA
GPU backed by the system RAM pool (has_gpu, name, backend=cuda, count,
unified_memory=True) — mirroring how Apple Silicon and AMD APUs are already
handled. Discrete GPUs are unchanged, and a box with a real discrete GPU keeps
the discrete path.

Adds tests/test_hwfit_unified_nvidia.py with a GB10 nvidia-smi fixture: the
device is detected (not dropped), surfaces through detect_system with
unified_memory propagated, discrete GPUs stay non-unified, and a discrete GPU
takes precedence over an N/A-memory row.

Co-authored-by: NubsCarson <nubs@nubs.site>

tests/test_hwfit_unified_nvidia.py

@@ -0,0 +1,73 @@
+"""Unified-memory NVIDIA detection — Grace Blackwell GB10 / DGX Spark (#1340).
+
+GB10 (and other unified-memory NVIDIA parts) report `nvidia-smi
+--query-gpu=memory.total` as "[N/A]"/"Not Supported" because the GPU shares the
+system LPDDR pool instead of carrying discrete VRAM. The detector did
+`float(memory.total)` and, on the ValueError, `continue`d — dropping the only
+GPU row, so a real GB10 running vLLM was reported as "No GPU" and Cookbook
+recommendations/model-switching broke. These pin that such a device is detected
+as a unified-memory CUDA GPU backed by system RAM, while discrete GPUs are
+unchanged.
+"""
+
+import pytest
+
+from services.hwfit import hardware
+
+
+@pytest.fixture(autouse=True)
+def _local(monkeypatch):
+    monkeypatch.setattr(hardware, "_remote_host", None)
+
+
+def test_gb10_unified_memory_detected_not_dropped(monkeypatch):
+    # Real GB10 nvidia-smi --query-gpu=memory.total,name output: memory is N/A.
+    monkeypatch.setattr(hardware, "_run", lambda cmd: "[N/A], NVIDIA GB10")
+    monkeypatch.setattr(hardware, "_get_ram_gb", lambda: 128.0)
+    info = hardware._detect_nvidia()
+    assert info is not None, "GB10 was dropped as 'No GPU'"
+    assert info["gpu_name"] == "NVIDIA GB10"
+    assert info["backend"] == "cuda"
+    assert info["gpu_count"] == 1
+    assert info["unified_memory"] is True
+    assert info["gpu_vram_gb"] == 128.0          # backed by the unified RAM pool
+    assert hardware._last_gpu_error is None
+
+
+def test_detect_system_reports_gb10_as_gpu(monkeypatch):
+    """End-to-end through detect_system: has_gpu True + unified_memory propagated."""
+    monkeypatch.setattr(hardware, "_run", lambda cmd: "[N/A], NVIDIA GB10")
+    monkeypatch.setattr(hardware, "_get_ram_gb", lambda: 128.0)
+    monkeypatch.setattr(hardware, "_get_available_ram_gb", lambda: 120.0)
+    monkeypatch.setattr(hardware, "_get_cpu_count", lambda: 20)
+    monkeypatch.setattr(hardware, "_get_cpu_name", lambda: "NVIDIA Grace")
+    monkeypatch.setattr(hardware, "_detect_apple_silicon", lambda: None)
+    s = hardware.detect_system(fresh=True)
+    assert s["has_gpu"] is True
+    assert s["gpu_name"] == "NVIDIA GB10"
+    assert s["backend"] == "cuda"
+    assert s.get("unified_memory") is True
+
+
+def test_discrete_gpu_unchanged_and_not_unified(monkeypatch):
+    monkeypatch.setattr(hardware, "_run", lambda cmd: "24576, NVIDIA GeForce RTX 4090")
+    info = hardware._detect_nvidia()
+    assert info["gpu_vram_gb"] == 24.0
+    assert info["gpu_count"] == 1
+    assert not info.get("unified_memory")
+
+
+def test_discrete_takes_precedence_over_unified_row(monkeypatch):
+    """A box with a real discrete-VRAM GPU keeps the discrete path; the
+    N/A-memory row is not conflated into a unified pool."""
+    monkeypatch.setattr(hardware, "_run", lambda cmd: "24576, NVIDIA RTX 4090\n[N/A], NVIDIA GB10")
+    info = hardware._detect_nvidia()
+    assert info["gpu_name"] == "NVIDIA RTX 4090"
+    assert info["gpu_count"] == 1
+    assert not info.get("unified_memory")
+
+
+def test_no_gpu_still_none(monkeypatch):
+    """No nvidia-smi output → still None, no spurious unified GPU."""
+    monkeypatch.setattr(hardware, "_run", lambda cmd: None)
+    assert hardware._detect_nvidia() is None