Keysat
5a0bfba6a3
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
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* 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
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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)
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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
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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>
14 lines
1.4 KiB
TypeScript
14 lines
1.4 KiB
TypeScript
import { VersionInfo, IMPOSSIBLE } from '@start9labs/start-sdk'
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export const v0_1_0 = VersionInfo.of({
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version: '0.12.0:0',
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releaseNotes: {
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en_US:
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'v0.12.0 — WhisperX as a one-click dashboard install. The Audio / Speech tab now shows an "Add WhisperX" banner the first time you open it (when WhisperX isn\'t installed). Clicking it ships the build context to Spark 2 over SSH, runs docker build (~10–15 min first time), runs docker run with a 40 GB memory cap (so a long-audio pathological case gets OOM-killed cleanly instead of swap-thrashing the whole Spark — what bit us with Sortformer on a 90-min file), and polls /health until both Whisper + pyannote 3.1 report loaded. Progress streams live in a build-log dialog with phase + elapsed timer. Once installed, WhisperX auto-appears as a managed service alongside Parakeet and Magpie (Start/Restart/Stop, deep-check, auto-restart on wedge — same lifecycle as the others). The /api/audio/transcribe-with-speakers endpoint now prefers WhisperX when it\'s healthy and falls back to the legacy Parakeet + Sortformer path otherwise — clean cutover, no client-side changes, easy rollback. New endpoints: GET /api/whisperx/status, POST /api/whisperx/install, GET /api/whisperx/install/{job_id}, GET /api/whisperx/install/{job_id}/stream (SSE).',
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},
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migrations: {
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up: async ({ effects }) => {},
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down: IMPOSSIBLE,
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},
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})
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