v0.12.0:0 - WhisperX as a one-click dashboard install + managed service

Replaces the manual rsync+build+run with a proper spark-control feature.
First in the audio path that doesn't require shell access on Spark 2.

What's in the box
─────────────────
* image/whisperx_container/   - the build context (Dockerfile, requirements,
  app/main.py FastAPI wrapper). Mainline pipeline: faster-whisper for STT +
  pyannote 3.1 for diarization + wav2vec2 forced alignment. Single endpoint
  /v1/audio/transcribe-with-speakers returns the exact same shape spark-
  control's existing endpoint does, so the recap-relay PR spec needs no
  changes when we cut over.

* image/app/whisperx_install.py - install manager. ships build context to
  Spark 2 over SSH, runs `docker build`, runs `docker run` with 40 GB
  memory cap (vs Sortformer's unbounded which thrashed Spark 2 on a 90-min
  file), polls /health until both Whisper + pyannote report loaded.

* Audio proxy: /api/audio/transcribe-with-speakers now prefers WhisperX
  when its /health reports diarizer_loaded=true, falls back to the legacy
  Parakeet + Sortformer path otherwise. Same response shape either way.
  Clean cutover, easy rollback (`docker rm whisperx-asr`).

* Dashboard (Audio / Speech tab):
  - "Add WhisperX" banner appears when not installed, with a primary
    "Install WhisperX" button. One click triggers the install.
  - Build progress dialog with phase + elapsed timer + live build log via
    SSE (`/api/whisperx/install/{job_id}/stream`).
  - After install, WhisperX auto-registers as a managed service alongside
    Parakeet and Magpie (Start/Restart/Stop, deep-check, auto-restart).
  - Banner self-hides once /api/whisperx/status reports healthy.

New endpoints
─────────────
  GET  /api/whisperx/status
  POST /api/whisperx/install
  GET  /api/whisperx/install/{job_id}
  GET  /api/whisperx/install/{job_id}/stream  (SSE phase + log)

Config additions (env)
──────────────────────
  WHISPERX_HOST       (defaults to spark2_host)
  WHISPERX_USER       (defaults to spark2_user)
  WHISPERX_CONTAINER  (default: whisperx-asr)
  WHISPERX_PORT       (default: 8002)
  WHISPERX_MODEL      (default: medium; tiny/base/small/medium/large-v3)

Dockerfile
──────────
Added COPY whisperx_container /app/whisperx_container so the runtime
install manager can read the build context from inside the spark-control
image and ship it over SSH.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

image/app/config.py

@@ -35,6 +35,11 @@ class Settings:
     magpie_host: str
     magpie_user: str
     magpie_container: str
+    whisperx_host: str
+    whisperx_user: str
+    whisperx_container: str
+    whisperx_port: int
+    whisperx_model: str
     ssh_key_path: str
     ssh_known_hosts: str
     models_yaml: str
@@ -49,7 +54,7 @@ class Settings:
     def from_env(cls) -> "Settings":
         spark2_host = _env("SPARK2_HOST")
         spark2_user = _env("SPARK2_USER")
-        # Parakeet and Magpie default to Spark 2 unless explicitly overridden.
+        # Parakeet, Magpie, and WhisperX all default to Spark 2 unless overridden.
         return cls(
             spark1_host=_env("SPARK1_HOST"),
             spark1_user=_env("SPARK1_USER"),
@@ -61,6 +66,11 @@ class Settings:
             magpie_host=_env("MAGPIE_HOST") or spark2_host,
             magpie_user=_env("MAGPIE_USER") or spark2_user,
             magpie_container=_env("MAGPIE_CONTAINER") or "magpie-tts",
+            whisperx_host=_env("WHISPERX_HOST") or spark2_host,
+            whisperx_user=_env("WHISPERX_USER") or spark2_user,
+            whisperx_container=_env("WHISPERX_CONTAINER") or "whisperx-asr",
+            whisperx_port=int(_env("WHISPERX_PORT", "8002")),
+            whisperx_model=_env("WHISPERX_MODEL", "medium"),
             ssh_key_path=_env("SSH_KEY_PATH"),
             ssh_known_hosts=_env("SSH_KNOWN_HOSTS"),
             models_yaml=_resolve_models_yaml(),