fix(catalogue): harvest review findings on #2013

- SetupSummary: an installed engine whose routing is "unavailable" reads
  Needs setup, not Ready (select is refused for it too); a failed /engines
  or /dictation/models fetch renders as an error with Retry instead of
  posing as "Off" / "Needs setup".
- Bulk installs (summary, model store, recommendation card) wait for every
  request to settle before re-enabling, and report which repos failed —
  one early rejection can no longer re-arm the button mid-flight.
- The weights list stays mounted across family switches (hidden under LLM)
  so download progress and Retry/Dismiss state survive navigation.
- Settings search: Hugging Face mirror terms route to Network; the legacy
  "models" tab id resolves to Storage. "Manage models" opens the TTS tab.
- Locales: uk "Рушії", zh-TW "引擎", vi "Engine" for the Engines heading.
- Docs name the family tab wherever the instruction depends on it.

docs/install/macos.md

@@ -157,7 +157,7 @@ without the quarantine step.
 - **Apple Silicon (M-series):** VoiceStudio automatically picks the `mlx-whisper`
   and `mlx-audio` backends where available — these use the Apple Neural Engine
   and Metal Performance Shaders for ~2× the throughput of the CPU path.
-  Installing the **Parakeet TDT v3 (MLX)** model from **Model Catalogue → Downloaded weights**
+  Installing the **Parakeet TDT v3 (MLX)** model from **Model Catalogue** (ASR tab → **Downloaded weights**)
   additionally makes dictation/capture prefer the `parakeet-mlx` engine
   (25 European languages, word timestamps, ~2 GB unified memory) — it is never
   downloaded without that explicit install, and it is only auto-preferred when

docs/install/troubleshooting.md

@@ -89,7 +89,7 @@ uv pip install --reinstall transformers
 ```
 
 Or, as a quick workaround, switch ASR to **faster-whisper** in
-**Model Catalogue → Downloaded weights**. If it recurs, add the backend **`.venv`** to your
+**Model Catalogue** (ASR tab → **Use**). If it recurs, add the backend **`.venv`** to your
 antivirus exclusions (see §1). Newer builds classify this error and show the
 reinstall hint directly instead of a bare path + "try restarting".
 
@@ -408,7 +408,7 @@ Intel-Mac wheels, so this entry only applies to historical installs (see
 ## 10. Windows: `Could not locate cudnn_ops_infer64_8.dll` during transcription
 
 **Symptom:** on Windows + NVIDIA, transcription/dubbing fails and the backend
-log shows `Could not locate cudnn_ops_infer64_8.dll`. Model Catalogue → Downloaded weights shows
+log shows `Could not locate cudnn_ops_infer64_8.dll`. Model Catalogue (ASR tab) shows
 WhisperX or faster-whisper selected.
 
 On builds before this was fixed, the failure looked much worse than a failed
@@ -444,7 +444,7 @@ uv pip install --no-deps --python .venv\Scripts\python.exe --target .venv\Lib\si
 (On Linux the target is `.venv/lib/pythonX.Y/site-packages/cudnn8_compat`.)
 
 Or sidestep cuDNN 8 entirely: switch the ASR backend to **PyTorch Whisper** in
-**Model Catalogue → Downloaded weights**. It runs on PyTorch's own stack (cuDNN 9, bundled with
+**Model Catalogue** (ASR tab → **Use**). It runs on PyTorch's own stack (cuDNN 9, bundled with
 torch) and needs no cuDNN-8 DLL — it loads its Whisper pipeline on demand (no
 extra env var).
 
@@ -600,12 +600,12 @@ did was `generate:start (audio)`, a dub, or a dictation.
 
 **Fix — reduce ASR load (any one of these):**
 
-1. **Pick a smaller ASR model / engine** in **Model Catalogue → Downloaded weights** — e.g.
+1. **Pick a smaller ASR model / engine** in **Model Catalogue** (ASR tab: **Use** an engine, then a smaller model under **Downloaded weights**) — e.g.
    faster-whisper **medium** or **small**, instead of large-v3. Biggest win on
    low-VRAM GPUs.
 2. **Free VRAM**: **Flush the TTS model** before dubbing so ASR isn't competing
    for memory (top toolbar → Flush → "Unload all + flush", or per-model from
-   Model Catalogue → Downloaded weights — see [Flush caches / Unload resident model](../performance.md#flush-caches--unload-resident-model)
+   Model Catalogue → Downloaded weights under the engine's family tab — see [Flush caches / Unload resident model](../performance.md#flush-caches--unload-resident-model)
    for exactly what it frees and the API equivalents for scripts), or
 3. **Run ASR on CPU** (slower but reliable) if your GPU is small.
 4. **Test with a 10-second clip** first — if that returns quickly, it confirms a