feat(multimodal): 完成阶段F运行管理与收尾验收

backend/scripts/install-model-runtime.ps1

@@ -1,9 +1,12 @@
 param(
-    [ValidateSet('cpu', 'cuda')][string]$Device = 'cpu'
+    [ValidateSet('cpu', 'cuda')][string]$Device = 'cpu',
+    [string]$RuntimeDirectory = '',
+    [switch]$QuietProgress
 )
 $ErrorActionPreference = 'Stop'
+$uvOptions = if ($QuietProgress) { @('--quiet') } else { @() }
 $backendRoot = Split-Path $PSScriptRoot -Parent
-$runtimeRoot = Join-Path $backendRoot '.venv-models'
+$runtimeRoot = if ($RuntimeDirectory) { [IO.Path]::GetFullPath($RuntimeDirectory) } else { Join-Path $backendRoot '.venv-models' }
 $runtimePython = Join-Path $runtimeRoot 'Scripts/python.exe'
 if (!(Test-Path -LiteralPath $runtimePython)) {
     & uv venv --python 3.12 $runtimeRoot
@@ -11,9 +14,14 @@ if (!(Test-Path -LiteralPath $runtimePython)) {
 }
 # CPU is the default. CUDA wheels include the runtime, not the NVIDIA driver.
 $torchIndex = if ($Device -eq 'cuda') { 'https://download.pytorch.org/whl/cu128' } else { 'https://download.pytorch.org/whl/cpu' }
-& uv pip install --python $runtimePython --index-url $torchIndex 'torch==2.9.1' 'torchaudio==2.9.1'
+$wheelVariant = if ($Device -eq 'cuda') { 'cu128' } else { 'cpu' }
+# Pin the local version too: ==2.9.1 alone also accepts an already-installed CPU wheel.
+Write-Output 'COMPONENT:torch'
+& uv @uvOptions pip install --python $runtimePython --index-url $torchIndex "torch==2.9.1+$wheelVariant" "torchaudio==2.9.1+$wheelVariant"
 if ($LASTEXITCODE -ne 0) { throw 'PyTorch 安装失败' }
-& uv pip install --python $runtimePython -r (Join-Path $PSScriptRoot 'model-requirements.lock') -c (Join-Path $PSScriptRoot 'model-requirements.txt')
+Write-Output 'COMPONENT:dependencies'
+& uv @uvOptions pip install --python $runtimePython -r (Join-Path $PSScriptRoot 'model-requirements.lock') -c (Join-Path $PSScriptRoot 'model-requirements.txt')
 if ($LASTEXITCODE -ne 0) { throw '模型依赖安装失败' }
+Write-Output 'COMPONENT:verify'
 & $runtimePython -c 'import torch; print({"torch":torch.__version__,"cuda_available":torch.cuda.is_available()})'
 if ($LASTEXITCODE -ne 0) { throw '模型运行环境检查失败' }