chore(backend): repair test suite and bring ruff to green

The suite hadn't run green since the routes refactor:
- test_profile_duplicate_names.py imported the pre-refactor module
  layout and broke collection; now imports backend.services.profiles
- tests/conftest.py puts the repo root and backend dir on sys.path so
  files collect standalone instead of depending on run order
- test_cors.py tested a hand-copied mirror of the origin list that had
  drifted from app.py (missing http://tauri.localhost); it now builds
  the app via the real create_app() factory
- test_progress.py simulated a 1KB download, below the tracker's 1MB
  reporting threshold; simulation raised to 5MB
- slow/timeout markers registered in pyproject

Ruff: ~900 violations auto-fixed (typing modernization, import
sorting, unused imports, whitespace). The remaining rules are baselined
in pyproject.toml with per-rule counts to burn down, plus per-file
carve-outs for deliberate env-before-import ordering. ruff check is
now clean; suite is 134 passed, 2 skipped.

backend/utils/cache.py

@@ -4,9 +4,10 @@ Voice prompt caching utilities.
 
 import hashlib
 import logging
-import torch
 from pathlib import Path
-from typing import Optional, Union, Dict, Any
+from typing import Any, Union
+
+import torch
 
 from .. import config
 
@@ -19,7 +20,7 @@ def _get_cache_dir() -> Path:
 
 
 # In-memory cache - can store dict (voice prompt) or tensor (legacy)
-_memory_cache: dict[str, Union[torch.Tensor, Dict[str, Any]]] = {}
+_memory_cache: dict[str, Union[torch.Tensor, dict[str, Any]]] = {}
 
 
 def get_cache_key(audio_path: str, reference_text: str) -> str:
@@ -46,7 +47,7 @@ def get_cache_key(audio_path: str, reference_text: str) -> str:
 
 def get_cached_voice_prompt(
     cache_key: str,
-) -> Optional[Union[torch.Tensor, Dict[str, Any]]]:
+) -> Union[torch.Tensor, dict[str, Any]] | None:
     """
     Get cached voice prompt if available.
 
@@ -76,7 +77,7 @@ def get_cached_voice_prompt(
 
 def cache_voice_prompt(
     cache_key: str,
-    voice_prompt: Union[torch.Tensor, Dict[str, Any]],
+    voice_prompt: Union[torch.Tensor, dict[str, Any]],
 ) -> None:
     """
     Cache voice prompt to memory and disk.