Fix Windows memory budget detection

packages/node/meshnet_node/hardware.py

@@ -1,5 +1,6 @@
 """GPU hardware detection with graceful CPU fallback."""
 
+import json
 import os
 import subprocess
 import time
@@ -12,7 +13,96 @@ def _detect_ram_mb() -> int:
         page_size = os.sysconf("SC_PAGE_SIZE")
         return int((pages * page_size) // (1024 * 1024))
     except (AttributeError, OSError, ValueError):
-        return 0
+        pass
+    return _detect_windows_ram_mb()
+
+
+def _detect_windows_ram_mb() -> int:
+    """Return Windows physical RAM in MB, or 0."""
+    try:
+        import ctypes
+
+        class _MemoryStatusEx(ctypes.Structure):
+            _fields_ = [
+                ("dwLength", ctypes.c_ulong),
+                ("dwMemoryLoad", ctypes.c_ulong),
+                ("ullTotalPhys", ctypes.c_ulonglong),
+                ("ullAvailPhys", ctypes.c_ulonglong),
+                ("ullTotalPageFile", ctypes.c_ulonglong),
+                ("ullAvailPageFile", ctypes.c_ulonglong),
+                ("ullTotalVirtual", ctypes.c_ulonglong),
+                ("ullAvailVirtual", ctypes.c_ulonglong),
+                ("ullAvailExtendedVirtual", ctypes.c_ulonglong),
+            ]
+
+        status = _MemoryStatusEx()
+        status.dwLength = ctypes.sizeof(_MemoryStatusEx)
+        if ctypes.windll.kernel32.GlobalMemoryStatusEx(ctypes.byref(status)):
+            return int(status.ullTotalPhys // (1024 * 1024))
+    except (AttributeError, OSError, ValueError):
+        pass
+
+    try:
+        result = subprocess.run(
+            [
+                "powershell",
+                "-NoProfile",
+                "-Command",
+                "(Get-CimInstance Win32_ComputerSystem).TotalPhysicalMemory",
+            ],
+            capture_output=True,
+            text=True,
+            timeout=5,
+        )
+        if result.returncode == 0 and result.stdout.strip():
+            return int(result.stdout.strip()) // (1024 * 1024)
+    except (FileNotFoundError, subprocess.TimeoutExpired, ValueError):
+        pass
+    return 0
+
+
+def _detect_windows_gpu_memory() -> dict | None:
+    """Return Windows GPU memory metadata from Win32_VideoController, if available."""
+    try:
+        result = subprocess.run(
+            [
+                "powershell",
+                "-NoProfile",
+                "-Command",
+                (
+                    "Get-CimInstance Win32_VideoController | "
+                    "Select-Object Name,AdapterRAM | ConvertTo-Json -Compress"
+                ),
+            ],
+            capture_output=True,
+            text=True,
+            timeout=5,
+        )
+    except (FileNotFoundError, subprocess.TimeoutExpired):
+        return None
+
+    if result.returncode != 0 or not result.stdout.strip():
+        return None
+    try:
+        raw = json.loads(result.stdout)
+    except json.JSONDecodeError:
+        return None
+    entries = raw if isinstance(raw, list) else [raw]
+    best: dict | None = None
+    for entry in entries:
+        if not isinstance(entry, dict):
+            continue
+        name = str(entry.get("Name") or "").strip()
+        if not name:
+            continue
+        try:
+            adapter_ram = int(entry.get("AdapterRAM") or 0)
+        except (TypeError, ValueError):
+            adapter_ram = 0
+        vram_mb = max(0, adapter_ram // (1024 * 1024))
+        if best is None or vram_mb > best["vram_mb"]:
+            best = {"gpu_name": name, "vram_mb": vram_mb}
+    return best
 
 
 def detect_hardware() -> dict:
@@ -25,7 +115,15 @@ def detect_hardware() -> dict:
             name = torch.cuda.get_device_name(idx)
             props = torch.cuda.get_device_properties(idx)
             vram_mb = props.total_memory // (1024 * 1024)
-            return {"device": "cuda", "gpu_name": name, "vram_mb": vram_mb, "ram_mb": ram_mb}
+            shared_vram_mb = max(0, ram_mb // 2)
+            return {
+                "device": "cuda",
+                "gpu_name": name,
+                "vram_mb": vram_mb,
+                "dedicated_vram_mb": vram_mb,
+                "shared_vram_mb": shared_vram_mb,
+                "ram_mb": ram_mb,
+            }
     except ImportError:
         pass
 
@@ -39,11 +137,37 @@ def detect_hardware() -> dict:
             parts = line.split(",", 1)
             gpu_name = parts[0].strip()
             vram_mb = int(parts[1].strip()) if len(parts) > 1 else 0
-            return {"device": "cuda", "gpu_name": gpu_name, "vram_mb": vram_mb, "ram_mb": ram_mb}
+            shared_vram_mb = max(0, ram_mb // 2)
+            return {
+                "device": "cuda",
+                "gpu_name": gpu_name,
+                "vram_mb": vram_mb,
+                "dedicated_vram_mb": vram_mb,
+                "shared_vram_mb": shared_vram_mb,
+                "ram_mb": ram_mb,
+            }
     except (FileNotFoundError, subprocess.TimeoutExpired, ValueError, IndexError):
         pass
 
-    return {"device": "cpu", "gpu_name": None, "vram_mb": 0, "ram_mb": ram_mb}
+    windows_gpu = _detect_windows_gpu_memory()
+    if windows_gpu is not None:
+        return {
+            "device": "cpu",
+            "gpu_name": windows_gpu["gpu_name"],
+            "vram_mb": windows_gpu["vram_mb"],
+            "dedicated_vram_mb": windows_gpu["vram_mb"],
+            "shared_vram_mb": max(0, ram_mb // 2),
+            "ram_mb": ram_mb,
+        }
+
+    return {
+        "device": "cpu",
+        "gpu_name": None,
+        "vram_mb": 0,
+        "dedicated_vram_mb": 0,
+        "shared_vram_mb": 0,
+        "ram_mb": ram_mb,
+    }
 
 
 def benchmark_throughput(device_str: str = "cpu") -> float: