fix: resolve all audit findings — e2e coverage, feature system hardening, visual baselines

- Add 8 new E2E specs for AI tools (upscale, enhance-faces, colorize,
  restore-photo, erase-object, smart-crop, passport-photo, red-eye-removal)
  closing all HIGH/MEDIUM coverage gaps from the test matrix audit
- Fix ensureAiDirs() crash on non-Docker environments by gating on
  isDockerEnvironment() — prevents ENOENT when /data doesn't exist
- Bump torch 2.6.0→2.7.0 and torchvision 0.21.0→0.22.0 in feature
  manifest for broader Python version compatibility
- Add Python 3.14 version guard warning in install_feature.py
- Remove duplicate torchvision shims from upscale.py and enhance_faces.py
  (dispatcher.py already handles this at startup)
- Remove orphaned tools.batch i18n key and dead pipeline-builder filter
- Regenerate 4 visual regression baselines for current UI state
- Add data-testid to passport-photo generate button for E2E testability

packages/ai/python/install_feature.py

@@ -72,7 +72,7 @@ def cpu_fallback_packages(packages: list[str]) -> list[str]:
     result = []
     for pkg in packages:
         # Handle multi-package CUDA torch entries like:
-        # "torch==2.6.0+cu126 torchvision==0.21.0+cu126 --index-url ..."
+        # "torch==2.7.0+cu126 torchvision==0.22.0+cu126 --index-url ..."
         first_token = pkg.split()[0] if pkg.strip() else ""
         if first_token.startswith("torch==") and "+cu" in first_token:
             # Extract torch and torchvision versions, strip CUDA suffix
@@ -423,6 +423,11 @@ def write_installed_atomic(ai_dir: str, data: dict) -> None:
 
 
 def main() -> None:
+    if sys.version_info >= (3, 14):
+        print(f"[WARN] Python {sys.version_info.major}.{sys.version_info.minor} detected. "
+              f"Some packages may not have pre-built wheels. Build from source may be attempted.",
+              file=sys.stderr, flush=True)
+
     if len(sys.argv) < 4:
         fail(
             f"Usage: {sys.argv[0]} <bundleId> <manifestPath> <modelsDir>\n"