NGC PyTorch (the only base with working torch on Spark's ARM64 + sm_120
Blackwell) doesn't ship torchaudio. Stock pip wheels are amd64-only AND
ABI-incompatible with NGC's custom torch 2.10.0a anyway. Pip install
just fails or crashes at runtime.
Real fix:
- apt install git cmake build-essential ninja-build
- pip install git+https://github.com/pytorch/audio.git@v2.5.1
with TORCH_CUDA_ARCH_LIST="9.0;10.0;12.0" (sm_120 for Blackwell GB10)
- this compiles torchaudio against the torch already in the image, so
ABI matches by construction
Then constraints.txt locks torch + torchvision + torchaudio so the later
`pip install whisperx` can't swap any of them.
Cost: +3-5 min to the first install. Docker layer cache reuses the
built torchaudio on every subsequent rebuild.
Torchaudio v2.5.1 is the last tag that builds cleanly against
torch 2.5-2.10 — main branch is too volatile against NGC's alpha torch.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
WhisperX docker build was crashing at the model-prewarm step:
OSError: undefined symbol: torch_library_impl
Root cause: the NGC PyTorch base ships custom builds of torch +
torchaudio + torchvision matched together for Blackwell (sm_120). When
pip installed whisperx, it pulled the latest stock torchaudio wheel as
a transitive dep, which was compiled against a different libtorch and
won't load against NGC's.
Fix: at build time, capture NGC's actual torch/torchaudio/torchvision
versions into /tmp/torch-constraints.txt, then `pip install -c` that
constraint for all subsequent installs. pip can't swap torch out, so
the ABI stays consistent. whisperx and pyannote are happy with
torch>=2.0 — NGC's 2.10.0a0 satisfies that easily.
The pinned versions print to the build log so you can see them.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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>
Keysat