mirror of
https://github.com/val1813/kwcode.git
synced 2026-09-08 17:08:51 +08:00
d9b51b4b29
- Add macOS GPU detection using sysctl hw.model - Display "Apple Silicon GPU" for Mac users - Preserve NVIDIA GPU detection for Windows/Linux - Add macOS installation guide in README - Document Apple Silicon unified memory architecture Fixes platform compatibility issue where Mac users see no GPU info. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
120 lines
3.6 KiB
Python
120 lines
3.6 KiB
Python
"""
|
||
硬件信息采集模块。
|
||
- psutil 获取 RAM/CPU（跨平台）
|
||
- nvidia-smi 获取 GPU VRAM（graceful fallback）
|
||
- VRAMWatcher 后台线程每10秒刷新 VRAM
|
||
"""
|
||
|
||
import platform
|
||
import subprocess
|
||
import threading
|
||
from dataclasses import dataclass
|
||
|
||
import psutil
|
||
|
||
|
||
@dataclass
|
||
class SysInfo:
|
||
gpu_name: str = "N/A"
|
||
vram_used_gb: float = 0.0
|
||
vram_total_gb: float = 0.0
|
||
ram_used_gb: float = 0.0
|
||
ram_total_gb: float = 0.0
|
||
cpu_name: str = "N/A"
|
||
|
||
|
||
def get_sysinfo() -> SysInfo:
|
||
"""采集一次完整硬件信息（启动时调用）。"""
|
||
info = SysInfo()
|
||
|
||
# RAM（psutil，跨平台）
|
||
vm = psutil.virtual_memory()
|
||
info.ram_total_gb = vm.total / 1024**3
|
||
info.ram_used_gb = vm.used / 1024**3
|
||
|
||
# CPU
|
||
try:
|
||
info.cpu_name = platform.processor() or "Unknown CPU"
|
||
if len(info.cpu_name) > 20:
|
||
info.cpu_name = info.cpu_name[:20] + "…"
|
||
except Exception:
|
||
pass
|
||
|
||
# GPU VRAM（平台特定检测）
|
||
if platform.system() == "Darwin":
|
||
# macOS: Apple Silicon 或 AMD GPU
|
||
try:
|
||
out = subprocess.check_output(
|
||
["sysctl", "hw.model"],
|
||
timeout=2,
|
||
stderr=subprocess.DEVNULL,
|
||
).decode(encoding="utf-8").strip()
|
||
if "Mac" in out:
|
||
info.gpu_name = "Apple Silicon GPU"
|
||
# macOS 使用统一内存架构，VRAM 信息不适用
|
||
except Exception:
|
||
pass
|
||
else:
|
||
# Windows/Linux: NVIDIA GPU（nvidia-smi）
|
||
try:
|
||
out = subprocess.check_output(
|
||
[
|
||
"nvidia-smi",
|
||
"--query-gpu=name,memory.used,memory.total",
|
||
"--format=csv,noheader,nounits",
|
||
],
|
||
timeout=2,
|
||
stderr=subprocess.DEVNULL,
|
||
).decode(encoding="utf-8").strip().split("\n")[0]
|
||
parts = [p.strip() for p in out.split(",")]
|
||
if len(parts) == 3:
|
||
info.gpu_name = parts[0][:20]
|
||
info.vram_used_gb = int(parts[1]) / 1024
|
||
info.vram_total_gb = int(parts[2]) / 1024
|
||
except Exception:
|
||
pass # 非NVIDIA或未安装驱动，显示 N/A
|
||
|
||
return info
|
||
|
||
|
||
class VRAMWatcher:
|
||
"""
|
||
后台守护线程，每10秒刷新一次 VRAM 使用量到 status_bar.vram_used。
|
||
daemon=True 随主进程退出自动销毁。
|
||
"""
|
||
|
||
INTERVAL = 10 # 秒
|
||
|
||
def __init__(self, status_bar):
|
||
self._status = status_bar
|
||
self._stop = threading.Event()
|
||
self._thread = threading.Thread(
|
||
target=self._run, daemon=True, name="vram-watcher"
|
||
)
|
||
|
||
def start(self):
|
||
self._thread.start()
|
||
|
||
def stop(self):
|
||
self._stop.set()
|
||
|
||
def _run(self):
|
||
while not self._stop.wait(timeout=self.INTERVAL):
|
||
try:
|
||
out = subprocess.check_output(
|
||
[
|
||
"nvidia-smi",
|
||
"--query-gpu=memory.used",
|
||
"--format=csv,noheader,nounits",
|
||
],
|
||
timeout=2,
|
||
stderr=subprocess.DEVNULL,
|
||
).decode(encoding="utf-8").strip()
|
||
# 只取第一行第一个数字，防止多GPU或格式变化
|
||
first_line = out.split("\n")[0].strip()
|
||
val = int("".join(c for c in first_line if c.isdigit()) or "0")
|
||
if val > 0:
|
||
self._status.vram_used = val / 1024
|
||
except Exception:
|
||
pass # nvidia-smi 不可用时静默跳过
|