Add GPU memory monitoring and update interval settings in MainWindow
This commit is contained in:
@@ -44,6 +44,399 @@ perf_logger.setLevel(logging.WARNING) # Only log warnings and errors for perfor
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logger = logging.getLogger(__name__)
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def get_gpu_memory_info():
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"""
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Get GPU memory information using multiple methods.
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Supports both discrete and integrated GPUs across Windows, Linux, and macOS.
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Returns dict with GPU memory info or basic info if no GPU found.
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"""
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gpu_info = {'has_gpu': False, 'total_mb': 0, 'used_mb': 0, 'free_mb': 0, 'utilization_percent': 0, 'gpu_name': 'Unknown'}
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# Try nvidia-ml-py (NVIDIA GPUs - most detailed info)
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try:
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import pynvml
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pynvml.nvmlInit()
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handle = pynvml.nvmlDeviceGetHandleByIndex(0) # Get first GPU
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# Get memory info
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mem_info = pynvml.nvmlDeviceGetMemoryInfo(handle)
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total_mb = mem_info.total / 1024 / 1024
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used_mb = mem_info.used / 1024 / 1024
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free_mb = mem_info.free / 1024 / 1024
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utilization_percent = (used_mb / total_mb) * 100
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# Get GPU name
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gpu_name = pynvml.nvmlDeviceGetName(handle).decode('utf-8')
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gpu_info.update({
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'has_gpu': True,
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'total_mb': total_mb,
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'used_mb': used_mb,
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'free_mb': free_mb,
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'utilization_percent': utilization_percent,
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'gpu_name': gpu_name,
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'method': 'pynvml'
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})
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logger.debug(f"GPU detected via pynvml: {gpu_name}, {total_mb:.0f}MB total")
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return gpu_info
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except (ImportError, Exception) as e:
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logger.debug(f"pynvml not available or failed: {e}")
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# Try GPUtil (NVIDIA GPUs alternative)
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try:
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import GPUtil
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gpus = GPUtil.getGPUs()
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if gpus:
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gpu = gpus[0] # Get first GPU
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total_mb = gpu.memoryTotal
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used_mb = gpu.memoryUsed
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free_mb = gpu.memoryFree
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utilization_percent = (used_mb / total_mb) * 100
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gpu_info.update({
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'has_gpu': True,
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'total_mb': total_mb,
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'used_mb': used_mb,
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'free_mb': free_mb,
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'utilization_percent': utilization_percent,
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'gpu_name': gpu.name,
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'method': 'GPUtil'
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})
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logger.debug(f"GPU detected via GPUtil: {gpu.name}, {total_mb:.0f}MB total")
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return gpu_info
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except (ImportError, Exception) as e:
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logger.debug(f"GPUtil not available or failed: {e}")
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# Try psutil for basic GPU info (limited)
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try:
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import psutil
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# Check if there are any GPU-related processes
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for proc in psutil.process_iter(['pid', 'name']):
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try:
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proc_name = proc.info['name'].lower()
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if any(gpu_process in proc_name for gpu_process in ['nvidia', 'amd', 'intel', 'gpu']):
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gpu_info.update({
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'has_gpu': True,
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'total_mb': 0, # Can't get detailed info with psutil
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'used_mb': 0,
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'free_mb': 0,
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'utilization_percent': 0,
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'gpu_name': 'Detected via process',
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'method': 'psutil_detection'
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})
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logger.debug(f"GPU detected via psutil process detection: {proc_name}")
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return gpu_info
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except (psutil.NoSuchProcess, psutil.AccessDenied):
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continue
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except ImportError:
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pass
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# Try Windows-specific methods
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try:
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import subprocess
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import re
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# Try nvidia-smi command for NVIDIA GPUs
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try:
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result = subprocess.run(['nvidia-smi', '--query-gpu=name,memory.total,memory.used,memory.free', '--format=csv,noheader,nounits'],
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capture_output=True, text=True, timeout=5)
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if result.returncode == 0 and result.stdout.strip():
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lines = result.stdout.strip().split('\n')
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if lines:
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parts = lines[0].split(', ')
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if len(parts) >= 4:
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gpu_name = parts[0].strip()
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total_mb = float(parts[1].strip())
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used_mb = float(parts[2].strip())
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free_mb = float(parts[3].strip())
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utilization_percent = (used_mb / total_mb) * 100
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gpu_info.update({
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'has_gpu': True,
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'total_mb': total_mb,
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'used_mb': used_mb,
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'free_mb': free_mb,
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'utilization_percent': utilization_percent,
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'gpu_name': gpu_name,
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'method': 'nvidia-smi'
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})
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return gpu_info
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except (subprocess.TimeoutExpired, subprocess.CalledProcessError, FileNotFoundError):
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pass
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# Try Intel GPU detection via Windows Management Instrumentation (WMI)
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try:
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# Query for Intel integrated graphics
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wmi_result = subprocess.run([
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'powershell', '-Command',
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"Get-WmiObject -Class Win32_VideoController | Where-Object {$_.Name -like '*Intel*' -or $_.Name -like '*UHD*' -or $_.Name -like '*Iris*' -or $_.Name -like '*HD Graphics*'} | Select-Object Name, AdapterRAM | ConvertTo-Json"
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], capture_output=True, text=True, timeout=10)
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if wmi_result.returncode == 0 and wmi_result.stdout.strip():
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import json
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wmi_data = json.loads(wmi_result.stdout.strip())
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# Handle both single GPU and multiple GPUs
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if isinstance(wmi_data, dict):
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wmi_data = [wmi_data]
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for gpu_data in wmi_data:
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if gpu_data.get('Name') and gpu_data.get('AdapterRAM'):
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gpu_name = gpu_data['Name']
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# AdapterRAM is in bytes, convert to MB
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total_mb = int(gpu_data['AdapterRAM']) / (1024 * 1024)
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gpu_info.update({
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'has_gpu': True,
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'total_mb': total_mb,
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'used_mb': 0, # WMI doesn't provide usage info
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'free_mb': total_mb, # Assume all free since we can't get usage
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'utilization_percent': 0,
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'gpu_name': gpu_name,
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'method': 'WMI_Intel'
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})
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logger.debug(f"Intel GPU detected via WMI: {gpu_name}, {total_mb:.0f}MB")
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return gpu_info
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except (subprocess.TimeoutExpired, subprocess.CalledProcessError, FileNotFoundError, json.JSONDecodeError):
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pass
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# Try AMD GPU detection via WMI
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try:
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wmi_result = subprocess.run([
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'powershell', '-Command',
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"Get-WmiObject -Class Win32_VideoController | Where-Object {$_.Name -like '*AMD*' -or $_.Name -like '*Radeon*' -or $_.Name -like '*ATI*'} | Select-Object Name, AdapterRAM | ConvertTo-Json"
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], capture_output=True, text=True, timeout=10)
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if wmi_result.returncode == 0 and wmi_result.stdout.strip():
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import json
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wmi_data = json.loads(wmi_result.stdout.strip())
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# Handle both single GPU and multiple GPUs
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if isinstance(wmi_data, dict):
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wmi_data = [wmi_data]
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for gpu_data in wmi_data:
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if gpu_data.get('Name') and gpu_data.get('AdapterRAM'):
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gpu_name = gpu_data['Name']
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# AdapterRAM is in bytes, convert to MB
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total_mb = int(gpu_data['AdapterRAM']) / (1024 * 1024)
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gpu_info.update({
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'has_gpu': True,
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'total_mb': total_mb,
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'used_mb': 0, # WMI doesn't provide usage info
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'free_mb': total_mb, # Assume all free since we can't get usage
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'utilization_percent': 0,
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'gpu_name': gpu_name,
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'method': 'WMI_AMD'
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})
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return gpu_info
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except (subprocess.TimeoutExpired, subprocess.CalledProcessError, FileNotFoundError, json.JSONDecodeError):
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pass
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# Generic WMI query for any video controller
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try:
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wmi_result = subprocess.run([
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'powershell', '-Command',
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"Get-WmiObject -Class Win32_VideoController | Where-Object {$_.AdapterRAM -gt 0} | Select-Object Name, AdapterRAM | ConvertTo-Json"
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], capture_output=True, text=True, timeout=10)
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if wmi_result.returncode == 0 and wmi_result.stdout.strip():
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import json
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wmi_data = json.loads(wmi_result.stdout.strip())
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# Handle both single GPU and multiple GPUs
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if isinstance(wmi_data, dict):
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wmi_data = [wmi_data]
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# Find the first GPU with significant memory (>= 512MB)
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for gpu_data in wmi_data:
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if gpu_data.get('Name') and gpu_data.get('AdapterRAM'):
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total_mb = int(gpu_data['AdapterRAM']) / (1024 * 1024)
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# Only consider GPUs with at least 512MB
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if total_mb >= 512:
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gpu_name = gpu_data['Name']
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gpu_info.update({
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'has_gpu': True,
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'total_mb': total_mb,
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'used_mb': 0, # WMI doesn't provide usage info
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'free_mb': total_mb, # Assume all free since we can't get usage
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'utilization_percent': 0,
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'gpu_name': gpu_name,
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'method': 'WMI_Generic'
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})
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return gpu_info
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except (subprocess.TimeoutExpired, subprocess.CalledProcessError, FileNotFoundError, json.JSONDecodeError):
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pass
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except Exception as e:
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logger.debug(f"Windows GPU detection methods failed: {e}")
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# Try DirectX DXGI detection (Windows 10+)
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try:
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import subprocess
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# Use PowerShell to query DirectX information
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dxdiag_result = subprocess.run([
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'powershell', '-Command',
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"""
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Add-Type -AssemblyName System.Windows.Forms
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$dxdiag = Get-WmiObject -Class Win32_VideoController | Where-Object {$_.AdapterRAM -gt 536870912} | Select-Object Name, AdapterRAM, DriverVersion
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$dxdiag | ConvertTo-Json
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"""
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], capture_output=True, text=True, timeout=15)
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if dxdiag_result.returncode == 0 and dxdiag_result.stdout.strip():
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import json
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dx_data = json.loads(dxdiag_result.stdout.strip())
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if isinstance(dx_data, dict):
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dx_data = [dx_data]
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for gpu_data in dx_data:
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if gpu_data.get('Name') and gpu_data.get('AdapterRAM'):
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gpu_name = gpu_data['Name']
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total_mb = int(gpu_data['AdapterRAM']) / (1024 * 1024)
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gpu_info.update({
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'has_gpu': True,
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'total_mb': total_mb,
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'used_mb': 0,
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'free_mb': total_mb,
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'utilization_percent': 0,
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'gpu_name': gpu_name,
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'method': 'DirectX_DXGI'
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})
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return gpu_info
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except (subprocess.TimeoutExpired, subprocess.CalledProcessError, FileNotFoundError, json.JSONDecodeError):
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pass
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# Try Linux/macOS methods for integrated GPUs
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try:
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import subprocess
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import platform
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system = platform.system().lower()
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if system == 'linux':
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# Try lspci for GPU detection on Linux
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try:
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lspci_result = subprocess.run(['lspci', '-v'], capture_output=True, text=True, timeout=10)
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if lspci_result.returncode == 0:
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output = lspci_result.stdout.lower()
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# Look for VGA/Display controllers
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if any(keyword in output for keyword in ['vga', 'display', 'gpu', 'graphics']):
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# Extract GPU names
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lines = lspci_result.stdout.split('\n')
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for line in lines:
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if any(keyword in line.lower() for keyword in ['vga', 'display controller', '3d controller']):
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# Try to extract GPU name from the line
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if 'intel' in line.lower():
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gpu_name = 'Intel Integrated Graphics (detected via lspci)'
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elif 'amd' in line.lower() or 'ati' in line.lower():
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gpu_name = 'AMD Integrated Graphics (detected via lspci)'
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elif 'nvidia' in line.lower():
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gpu_name = 'NVIDIA GPU (detected via lspci)'
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else:
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gpu_name = 'GPU detected via lspci'
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gpu_info.update({
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'has_gpu': True,
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'total_mb': 0, # Can't get memory info from lspci
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'used_mb': 0,
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'free_mb': 0,
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'utilization_percent': 0,
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'gpu_name': gpu_name,
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'method': 'lspci_linux'
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})
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return gpu_info
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except (subprocess.TimeoutExpired, subprocess.CalledProcessError, FileNotFoundError):
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pass
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# Try checking /sys/class/drm for Intel iGPU on Linux
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try:
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import os
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drm_path = '/sys/class/drm'
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if os.path.exists(drm_path):
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drm_devices = os.listdir(drm_path)
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intel_devices = [d for d in drm_devices if 'i915' in d or 'intel' in d.lower()]
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if intel_devices:
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gpu_info.update({
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'has_gpu': True,
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'total_mb': 0,
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'used_mb': 0,
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'free_mb': 0,
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'utilization_percent': 0,
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'gpu_name': 'Intel Integrated Graphics (detected via /sys/class/drm)',
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'method': 'linux_drm'
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})
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return gpu_info
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except Exception:
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pass
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elif system == 'darwin': # macOS
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# Try system_profiler for macOS GPU detection
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try:
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profiler_result = subprocess.run([
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'system_profiler', 'SPDisplaysDataType', '-json'
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], capture_output=True, text=True, timeout=15)
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if profiler_result.returncode == 0:
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import json
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display_data = json.loads(profiler_result.stdout)
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displays = display_data.get('SPDisplaysDataType', [])
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for display in displays:
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gpu_name = display.get('sppci_model', 'Unknown GPU')
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vram = display.get('spdisplays_vram', '0 MB')
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# Extract VRAM size
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vram_mb = 0
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if 'MB' in vram:
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try:
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vram_mb = float(vram.replace(' MB', ''))
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except:
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pass
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elif 'GB' in vram:
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try:
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vram_mb = float(vram.replace(' GB', '')) * 1024
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except:
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pass
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gpu_info.update({
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'has_gpu': True,
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'total_mb': vram_mb,
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'used_mb': 0,
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'free_mb': vram_mb,
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'utilization_percent': 0,
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'gpu_name': gpu_name,
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'method': 'macos_system_profiler'
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})
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return gpu_info
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except (subprocess.TimeoutExpired, subprocess.CalledProcessError, FileNotFoundError, json.JSONDecodeError):
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pass
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except Exception as e:
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logger.debug(f"Linux/macOS GPU detection failed: {e}")
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return gpu_info
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CONFIG_DIR = 'scenarios'
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if not os.path.exists(CONFIG_DIR):
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os.makedirs(CONFIG_DIR)
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@@ -473,10 +866,7 @@ class MainWindow(QtWidgets.QMainWindow):
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if len(self._loop_times) > self._max_loop_time_samples:
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self._loop_times.pop(0)
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# Log performance warnings
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avg_time = sum(self._loop_times) / len(self._loop_times)
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if avg_time > 0.5: # If average loop time exceeds 500ms
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logger.warning(f"Performance warning: Average loop time: {avg_time:.3f}s")
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# Performance warnings are now handled by _monitor_performance with deduplication
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def _periodic_cleanup(self):
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"""
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@@ -597,7 +987,7 @@ class MainWindow(QtWidgets.QMainWindow):
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def get_memory_usage(self):
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"""
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Get current memory usage information for monitoring.
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Get current memory usage information for monitoring, including GPU memory.
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"""
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try:
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import psutil
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@@ -608,6 +998,9 @@ class MainWindow(QtWidgets.QMainWindow):
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# Get system info
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system_memory = psutil.virtual_memory()
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# Get GPU information
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gpu_info = get_gpu_memory_info()
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return {
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'process_memory_mb': memory_info.rss / 1024 / 1024, # MB
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'process_memory_percent': process.memory_percent(),
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@@ -616,22 +1009,19 @@ class MainWindow(QtWidgets.QMainWindow):
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'system_memory_available_gb': system_memory.available / 1024 / 1024 / 1024, # GB
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'template_cache_size': len(template_cache._cache) if hasattr(template_cache, '_cache') else 0,
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'cooldown_entries': len(self._step_cooldown) if hasattr(self, '_step_cooldown') else 0,
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'has_psutil': True
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'has_psutil': True,
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# GPU information
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'gpu_has_gpu': gpu_info['has_gpu'],
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'gpu_total_mb': gpu_info['total_mb'],
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'gpu_used_mb': gpu_info['used_mb'],
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'gpu_free_mb': gpu_info['free_mb'],
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'gpu_utilization_percent': gpu_info['utilization_percent'],
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'gpu_name': gpu_info['gpu_name'],
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'gpu_method': gpu_info.get('method', 'none')
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}
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except ImportError:
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# psutil not available, return basic info
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return {
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'process_memory_mb': 0,
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'process_memory_percent': 0,
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'cpu_percent': 0,
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'system_memory_percent': 0,
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'system_memory_available_gb': 0,
|
||||
'template_cache_size': len(template_cache._cache) if hasattr(template_cache, '_cache') else 0,
|
||||
'cooldown_entries': len(self._step_cooldown) if hasattr(self, '_step_cooldown') else 0,
|
||||
'has_psutil': False
|
||||
}
|
||||
except Exception as e:
|
||||
logger.warning(f"Error getting memory usage: {e}")
|
||||
# psutil not available, get GPU info anyway
|
||||
gpu_info = get_gpu_memory_info()
|
||||
return {
|
||||
'process_memory_mb': 0,
|
||||
'process_memory_percent': 0,
|
||||
@@ -641,7 +1031,37 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
'template_cache_size': len(template_cache._cache) if hasattr(template_cache, '_cache') else 0,
|
||||
'cooldown_entries': len(self._step_cooldown) if hasattr(self, '_step_cooldown') else 0,
|
||||
'has_psutil': False,
|
||||
'error': str(e)
|
||||
# GPU information
|
||||
'gpu_has_gpu': gpu_info['has_gpu'],
|
||||
'gpu_total_mb': gpu_info['total_mb'],
|
||||
'gpu_used_mb': gpu_info['used_mb'],
|
||||
'gpu_free_mb': gpu_info['free_mb'],
|
||||
'gpu_utilization_percent': gpu_info['utilization_percent'],
|
||||
'gpu_name': gpu_info['gpu_name'],
|
||||
'gpu_method': gpu_info.get('method', 'none')
|
||||
}
|
||||
except Exception as e:
|
||||
logger.warning(f"Error getting memory usage: {e}")
|
||||
# Try to get GPU info even if psutil fails
|
||||
gpu_info = get_gpu_memory_info()
|
||||
return {
|
||||
'process_memory_mb': 0,
|
||||
'process_memory_percent': 0,
|
||||
'cpu_percent': 0,
|
||||
'system_memory_percent': 0,
|
||||
'system_memory_available_gb': 0,
|
||||
'template_cache_size': len(template_cache._cache) if hasattr(template_cache, '_cache') else 0,
|
||||
'cooldown_entries': len(self._step_cooldown) if hasattr(self, '_step_cooldown') else 0,
|
||||
'has_psutil': False,
|
||||
'error': str(e),
|
||||
# GPU information
|
||||
'gpu_has_gpu': gpu_info['has_gpu'],
|
||||
'gpu_total_mb': gpu_info['total_mb'],
|
||||
'gpu_used_mb': gpu_info['used_mb'],
|
||||
'gpu_free_mb': gpu_info['free_mb'],
|
||||
'gpu_utilization_percent': gpu_info['utilization_percent'],
|
||||
'gpu_name': gpu_info['gpu_name'],
|
||||
'gpu_method': gpu_info.get('method', 'none')
|
||||
}
|
||||
|
||||
def stop_automation(self):
|
||||
@@ -728,7 +1148,10 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
# Setup periodic monitoring timer
|
||||
self.monitor_timer = QtCore.QTimer()
|
||||
self.monitor_timer.timeout.connect(self._monitor_performance)
|
||||
self.monitor_timer.start(2000) # Monitor every 2 seconds for responsive UI updates
|
||||
|
||||
# Get initial interval from dropdown (default is 2 seconds)
|
||||
initial_interval = self.update_interval_combo.currentData() or 2000
|
||||
self.monitor_timer.start(initial_interval)
|
||||
|
||||
# Initial resource display update
|
||||
QtCore.QTimer.singleShot(100, self._monitor_performance)
|
||||
@@ -749,7 +1172,7 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
|
||||
# Warning thresholds with duplicate prevention
|
||||
if avg_loop_time > 1.0:
|
||||
warning_msg = f"Performance issue: Average loop time {avg_loop_time:.3f}s"
|
||||
warning_msg = f"Performance warning: Average loop time {avg_loop_time:.3f}s"
|
||||
self._log_warning_once("performance_slow", warning_msg)
|
||||
|
||||
# Memory warning for cache-based monitoring
|
||||
@@ -767,6 +1190,11 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
cpu_msg = f"High CPU usage: {memory_info['cpu_percent']:.1f}%"
|
||||
self._log_warning_once("cpu_high", cpu_msg)
|
||||
|
||||
# GPU memory usage warning
|
||||
if memory_info.get('gpu_has_gpu', False) and memory_info.get('gpu_utilization_percent', 0) > 90:
|
||||
gpu_msg = f"High GPU memory usage: {memory_info['gpu_utilization_percent']:.1f}%"
|
||||
self._log_warning_once("gpu_high", gpu_msg)
|
||||
|
||||
except Exception as e:
|
||||
logger.debug(f"Performance monitoring error: {e}")
|
||||
|
||||
@@ -839,6 +1267,50 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
self.cache_label.setText(cache_text)
|
||||
self.cache_label.setStyleSheet(f'font-size: 9pt; color: {cache_color};')
|
||||
|
||||
# GPU memory info
|
||||
if memory_info.get('gpu_has_gpu', False):
|
||||
gpu_used_mb = memory_info.get('gpu_used_mb', 0)
|
||||
gpu_total_mb = memory_info.get('gpu_total_mb', 0)
|
||||
gpu_utilization = memory_info.get('gpu_utilization_percent', 0)
|
||||
gpu_method = memory_info.get('gpu_method', 'unknown')
|
||||
|
||||
if gpu_total_mb > 0:
|
||||
gpu_text = f"GPU: {gpu_used_mb:.0f}/{gpu_total_mb:.0f}MB ({gpu_utilization:.1f}%)"
|
||||
gpu_color = '#d9534f' if gpu_utilization > 80 else '#f0ad4e' if gpu_utilization > 60 else '#5cb85c'
|
||||
|
||||
# Add GPU name as tooltip
|
||||
gpu_name = memory_info.get('gpu_name', 'Unknown GPU')
|
||||
self.gpu_label.setToolTip(f"GPU: {gpu_name} (detected via {gpu_method})")
|
||||
else:
|
||||
gpu_text = f"GPU: Detected ({gpu_method})"
|
||||
gpu_color = '#5bc0de'
|
||||
gpu_name = memory_info.get('gpu_name', 'Unknown GPU')
|
||||
self.gpu_label.setToolTip(f"GPU: {gpu_name} (limited info via {gpu_method})")
|
||||
else:
|
||||
gpu_text = "GPU: Not detected"
|
||||
gpu_color = '#777'
|
||||
self.gpu_label.setToolTip(
|
||||
"No GPU detected or GPU monitoring libraries not available.\n\n"
|
||||
"For enhanced GPU monitoring:\n"
|
||||
"• NVIDIA GPUs: pip install pynvml or GPUtil\n"
|
||||
"• Integrated GPUs: Built-in Windows WMI support\n"
|
||||
"• Linux: lspci and DRM detection\n"
|
||||
"• macOS: system_profiler integration\n\n"
|
||||
"Click for more information about GPU monitoring."
|
||||
)
|
||||
|
||||
self.gpu_label.setText(gpu_text)
|
||||
self.gpu_label.setStyleSheet(f'font-size: 9pt; color: {gpu_color};')
|
||||
|
||||
# Make GPU label clickable to show GPU info when no GPU detected
|
||||
if not memory_info.get('gpu_has_gpu', False):
|
||||
self.gpu_label.mousePressEvent = lambda event: self._show_gpu_info()
|
||||
self.gpu_label.setCursor(QtGui.QCursor(QtCore.Qt.CursorShape.PointingHandCursor))
|
||||
else:
|
||||
# Remove click handler if GPU is detected
|
||||
self.gpu_label.mousePressEvent = None
|
||||
self.gpu_label.setCursor(QtGui.QCursor(QtCore.Qt.CursorShape.ArrowCursor))
|
||||
|
||||
# Performance info
|
||||
if hasattr(self, '_loop_times') and self._loop_times:
|
||||
avg_time = sum(self._loop_times) / len(self._loop_times)
|
||||
@@ -863,6 +1335,7 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
self.cpu_label.setText("CPU: Error")
|
||||
self.system_memory_label.setText("System: Error")
|
||||
self.cache_label.setText("Cache: Error")
|
||||
self.gpu_label.setText("GPU: Error")
|
||||
self.performance_label.setText(f"Display Error: {str(e)[:30]}...")
|
||||
|
||||
def stop_monitoring(self):
|
||||
@@ -878,7 +1351,10 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
self.cpu_label.hide()
|
||||
self.system_memory_label.hide()
|
||||
self.cache_label.hide()
|
||||
self.gpu_label.hide()
|
||||
self.performance_label.hide()
|
||||
self.interval_label.hide()
|
||||
self.update_interval_combo.hide()
|
||||
self.toggle_resources_btn.setText('Show Resources')
|
||||
self.resource_widgets_visible = False
|
||||
else:
|
||||
@@ -887,7 +1363,10 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
self.cpu_label.show()
|
||||
self.system_memory_label.show()
|
||||
self.cache_label.show()
|
||||
self.gpu_label.show()
|
||||
self.performance_label.show()
|
||||
self.interval_label.show()
|
||||
self.update_interval_combo.show()
|
||||
self.toggle_resources_btn.setText('Hide Resources')
|
||||
self.resource_widgets_visible = True
|
||||
|
||||
@@ -910,6 +1389,50 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
msg.setStandardButtons(QtWidgets.QMessageBox.StandardButton.Ok)
|
||||
msg.exec()
|
||||
|
||||
def _show_gpu_info(self):
|
||||
"""Show information about installing GPU monitoring libraries."""
|
||||
msg = QtWidgets.QMessageBox(self)
|
||||
msg.setWindowTitle("GPU Memory Monitoring")
|
||||
msg.setIcon(QtWidgets.QMessageBox.Icon.Information)
|
||||
msg.setText("GPU monitoring supports both discrete and integrated GPUs")
|
||||
msg.setInformativeText(
|
||||
"GPU Memory Monitoring Support:\n\n"
|
||||
"NVIDIA GPUs (Discrete):\n"
|
||||
"• pip install pynvml (recommended)\n"
|
||||
"• pip install GPUtil (alternative)\n"
|
||||
"• nvidia-smi command line tool\n\n"
|
||||
"Integrated GPUs (Intel/AMD):\n"
|
||||
"• Windows: WMI queries (built-in)\n"
|
||||
"• Linux: lspci and /sys/class/drm\n"
|
||||
"• macOS: system_profiler\n\n"
|
||||
"Features enabled:\n"
|
||||
"• GPU detection and identification\n"
|
||||
"• VRAM/memory size (where available)\n"
|
||||
"• Real-time usage (NVIDIA with libraries)\n"
|
||||
"• Cross-platform support\n\n"
|
||||
"Note: Integrated GPUs may show limited information\n"
|
||||
"compared to discrete GPUs due to system limitations.\n"
|
||||
"NVIDIA GPUs with proper libraries provide the most\n"
|
||||
"detailed monitoring including real-time usage."
|
||||
)
|
||||
msg.setStandardButtons(QtWidgets.QMessageBox.StandardButton.Ok)
|
||||
msg.exec()
|
||||
|
||||
def _on_update_interval_changed(self):
|
||||
"""Handle resource monitoring update interval change."""
|
||||
interval = self.update_interval_combo.currentData()
|
||||
if interval and hasattr(self, 'monitor_timer'):
|
||||
# Stop current timer
|
||||
self.monitor_timer.stop()
|
||||
|
||||
# Start timer with new interval
|
||||
self.monitor_timer.start(interval)
|
||||
|
||||
logger.debug(f"Resource monitoring interval changed to {interval}ms")
|
||||
|
||||
# Immediately update display to show the change is active
|
||||
QtCore.QTimer.singleShot(50, self._monitor_performance)
|
||||
|
||||
def _save_window_geometry(self):
|
||||
"""Save the current window size and position to a config file."""
|
||||
try:
|
||||
@@ -931,13 +1454,14 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
except (json.JSONDecodeError, IOError):
|
||||
existing_config = {}
|
||||
|
||||
# Update with window geometry
|
||||
# Update with window geometry and settings
|
||||
existing_config['main_window'] = geometry_data
|
||||
existing_config['update_interval'] = self.update_interval_combo.currentData()
|
||||
|
||||
with open(config_path, 'w') as f:
|
||||
json.dump(existing_config, f, indent=2)
|
||||
|
||||
logger.debug(f"Saved window geometry: {geometry_data}")
|
||||
logger.debug(f"Saved window geometry and settings: {geometry_data}")
|
||||
|
||||
except Exception as e:
|
||||
logger.debug(f"Error saving window geometry: {e}")
|
||||
@@ -983,6 +1507,16 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
if geometry_data.get('maximized', False):
|
||||
self.showMaximized()
|
||||
|
||||
# Restore update interval if saved
|
||||
saved_interval = config.get('update_interval')
|
||||
if saved_interval:
|
||||
# Find the index of the saved interval in the combo box
|
||||
for i in range(self.update_interval_combo.count()):
|
||||
if self.update_interval_combo.itemData(i) == saved_interval:
|
||||
self.update_interval_combo.setCurrentIndex(i)
|
||||
break
|
||||
logger.debug(f"Restored update interval: {saved_interval}ms")
|
||||
|
||||
logger.debug(f"Restored window geometry: x={x}, y={y}, w={width}, h={height}")
|
||||
|
||||
except (json.JSONDecodeError, IOError, KeyError) as e:
|
||||
@@ -1191,6 +1725,33 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
self.toggle_resources_btn.clicked.connect(self._toggle_resource_display)
|
||||
resource_layout.addWidget(self.toggle_resources_btn, 0, 2, 1, 1)
|
||||
|
||||
# Update interval dropdown
|
||||
self.interval_label = QtWidgets.QLabel('Update:')
|
||||
self.interval_label.setStyleSheet('font-size: 9pt; color: #333;')
|
||||
self.update_interval_combo = QtWidgets.QComboBox()
|
||||
self.update_interval_combo.setMaximumWidth(80)
|
||||
self.update_interval_combo.setToolTip('Set resource monitoring update interval')
|
||||
|
||||
# Add interval options (in milliseconds)
|
||||
intervals = [
|
||||
('0.5s', 500),
|
||||
('1s', 1000),
|
||||
('2s', 2000),
|
||||
('3s', 3000),
|
||||
('5s', 5000),
|
||||
('10s', 10000)
|
||||
]
|
||||
|
||||
for text, value in intervals:
|
||||
self.update_interval_combo.addItem(text, value)
|
||||
|
||||
# Set default to 2 seconds (index 2)
|
||||
self.update_interval_combo.setCurrentIndex(2)
|
||||
self.update_interval_combo.currentIndexChanged.connect(self._on_update_interval_changed)
|
||||
|
||||
resource_layout.addWidget(self.interval_label, 0, 3, 1, 1)
|
||||
resource_layout.addWidget(self.update_interval_combo, 0, 4, 1, 1)
|
||||
|
||||
# Memory usage
|
||||
self.memory_label = QtWidgets.QLabel('Memory: --')
|
||||
self.memory_label.setStyleSheet('font-size: 9pt; color: #333;')
|
||||
@@ -1211,6 +1772,11 @@ class MainWindow(QtWidgets.QMainWindow):
|
||||
self.cache_label.setStyleSheet('font-size: 9pt; color: #333;')
|
||||
resource_layout.addWidget(self.cache_label, 1, 1)
|
||||
|
||||
# GPU memory info
|
||||
self.gpu_label = QtWidgets.QLabel('GPU: --')
|
||||
self.gpu_label.setStyleSheet('font-size: 9pt; color: #333;')
|
||||
resource_layout.addWidget(self.gpu_label, 1, 2)
|
||||
|
||||
# Performance info
|
||||
self.performance_label = QtWidgets.QLabel('Performance: --')
|
||||
self.performance_label.setStyleSheet('font-size: 9pt; color: #333;')
|
||||
|
||||
Reference in New Issue
Block a user