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/audio_proxy.py

@@ -209,6 +209,17 @@ def build_router(settings: Settings, deep_health: Any = None) -> APIRouter:
             raise HTTPException(r.status_code, r.text[:500])
         return Response(content=r.content, media_type=r.headers.get("content-type", "application/json"))
 
+    def _whisperx_base() -> str:
+        return f"http://{settings.whisperx_host}:{settings.whisperx_port}"
+
+    async def _whisperx_healthy() -> bool:
+        try:
+            async with httpx.AsyncClient(timeout=2.0) as client:
+                r = await client.get(f"{_whisperx_base()}/health")
+            return r.status_code == 200 and bool(r.json().get("diarizer_loaded"))
+        except Exception:
+            return False
+
     # ---- /api/audio/transcribe-with-speakers (STT + diarization, merged) ----
     @router.post("/api/audio/transcribe-with-speakers")
     async def transcribe_with_speakers(
@@ -245,6 +256,23 @@ def build_router(settings: Settings, deep_health: Any = None) -> APIRouter:
         filename = file.filename or "audio.wav"
         content_type = file.content_type or "application/octet-stream"
 
+        # Prefer WhisperX (single-pipeline, handles long audio properly) when it's
+        # installed and healthy. Fall back to Parakeet + Sortformer otherwise.
+        if await _whisperx_healthy():
+            files = {"file": (filename, body, content_type)}
+            try:
+                async with httpx.AsyncClient(timeout=1800.0) as client:
+                    r = await client.post(
+                        f"{_whisperx_base()}/v1/audio/transcribe-with-speakers",
+                        files=files,
+                    )
+            except httpx.HTTPError as e:
+                raise HTTPException(502, f"whisperx unreachable: {e}")
+            if r.status_code != 200:
+                raise HTTPException(r.status_code, r.text[:500])
+            return r.json()
+
+        # ── Legacy fallback: Parakeet ASR + Sortformer diarizer in parallel ──
         async def _call_transcribe(client: httpx.AsyncClient) -> dict:
             files = {"file": (filename, body, content_type)}
             data = {"response_format": "verbose_json"}