v0.10.0:0 - speaker diarization via Sortformer + merged transcribe-with-speakers

Adds a new pipeline for diarized transcription that any client (recap-relay,
ad-hoc curl, future Mac-side tools) can call. Pure data pipeline, no LLM
or UI included — name resolution / analysis happen downstream where prompts
and rendering are configurable.

Architecture:
  Spark 2 / parakeet-asr container:
    + /opt/parakeet/app/diarizer.py        (new: SortformerDiarizer class)
    + /opt/parakeet/app/main.py            (patched: loads diarizer, adds
                                            /v1/audio/diarize endpoint)
    Model: nvidia/diar_sortformer_4spk-v1  (~150 MB, ungated, NeMo native)

  Spark Control:
    + POST /api/audio/transcribe-with-speakers
      Body: multipart file
      Returns: {
        duration, language, speakers_detected,
        segments: [{start_ms, end_ms, speaker, text}, ...],
        models: {transcription, diarization}
      }
      Runs Parakeet ASR + Sortformer in parallel, merges words to speaker
      turns by timestamp, groups into speaker-change blocks (breaks also
      on >1.5s silence gaps).
    + If Parakeet 500s mid-pipeline, kicks deep-health probe and returns
      503/Retry-After: 60 — same wedge-recovery pattern as v0.9.0:2.

Apply Sortformer patches to the running Parakeet container with:
  bash image/parakeet_patches/apply.sh <spark2-host> <ssh-user>

Patches are reversible — apply.sh backs up the original main.py inside the
container at main.py.pre-sortformer before overwriting. Restore by copying
that file back and removing diarizer.py, then docker restart.

v0.11 follow-up: dashboard "Speech Models" panel to swap/update model
versions from the UI instead of needing to re-run apply.sh.

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

package/startos/versions/v0_1_0.ts

@@ -1,10 +1,10 @@
 import { VersionInfo, IMPOSSIBLE } from '@start9labs/start-sdk'
 
 export const v0_1_0 = VersionInfo.of({
-  version: '0.9.0:2',
+  version: '0.10.0:0',
   releaseNotes: {
     en_US:
-      'v0.9.0:2 — Open WebUI voice mode UX fix. Parakeet has a recurring CUDA wedge (CUBLAS_STATUS_*_ERROR mid-attention) that fires reliably on Open WebUI\'s WebM/Opus→MP3 audio. Previously the proxy just relayed the upstream 500, Open WebUI showed "Server connection error", and you had to wait up to 5 min for the periodic deep-health probe to detect+restart Parakeet. Now: when Parakeet returns 500, the proxy fires deep-health\'s probe immediately in the background (which contains the same wedge-detect + rate-limited auto-restart logic) and returns 503 with Retry-After: 60 instead. The client gets a clear retry signal and the auto-restart kicks in within seconds. Retrying ~60s later should succeed reliably.',
+      'v0.10.0 — Speaker diarization. Spark Control now offers a merged transcription + diarization endpoint at POST /api/audio/transcribe-with-speakers. Returns the spoken text broken into blocks with anonymous speaker labels (Speaker_0, Speaker_1, ...) and millisecond timestamps — designed as input for downstream apps (recap-relay, custom UIs) that handle speaker→name mapping and LLM analysis with their own configurable prompts. Diarization runs via NVIDIA NeMo Sortformer (nvidia/diar_sortformer_4spk-v1), loaded alongside Parakeet ASR inside the existing parakeet-asr container on Spark 2 — no new infrastructure, ~150 MB model addition. A new /v1/audio/diarize endpoint is also exposed on Parakeet directly for clients that just want speaker turns. Apply Sortformer patches via image/parakeet_patches/apply.sh after install. v0.11 will add a Speech Models dashboard panel for in-UI model swap/update.',
   },
   migrations: {
     up: async ({ effects }) => {},