Keysat
713cd09cc2
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>
55 lines
2.4 KiB
Bash
Executable File
55 lines
2.4 KiB
Bash
Executable File
#!/bin/bash
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# Apply Sortformer diarization patches to a running parakeet-asr container.
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#
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# Run from the spark-control repo root on the laptop:
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# bash image/parakeet_patches/apply.sh <spark2-host> <ssh-user>
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#
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# What it does:
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# 1. Backs up the current /opt/parakeet/app/main.py inside the container
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# (writable layer; survives docker restart but NOT docker rm).
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# 2. Copies the patched main.py + new diarizer.py into the container.
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# 3. Restarts the container so the new code + Sortformer model load.
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#
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# Reversibility:
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# - The backup of main.py is at /opt/parakeet/app/main.py.pre-sortformer
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# inside the container. Restore with:
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# docker exec parakeet-asr cp /opt/parakeet/app/main.py.pre-sortformer /opt/parakeet/app/main.py
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# docker exec parakeet-asr rm -f /opt/parakeet/app/diarizer.py
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# docker restart parakeet-asr
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# - If the container is ever `docker rm`'d (volume rebuild), re-run this
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# script. We will eventually fold this into spark-control as an action.
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set -e
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HOST="${1:?usage: apply.sh <spark2-host> <ssh-user>}"
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USER="${2:?usage: apply.sh <spark2-host> <ssh-user>}"
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CONTAINER="${CONTAINER:-parakeet-asr}"
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REPO_DIR="$(cd "$(dirname "$0")" && pwd)"
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echo "→ Backing up current main.py inside ${CONTAINER}..."
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ssh "${USER}@${HOST}" "docker exec ${CONTAINER} sh -c \
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'test -f /opt/parakeet/app/main.py.pre-sortformer || cp /opt/parakeet/app/main.py /opt/parakeet/app/main.py.pre-sortformer'"
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echo "→ Copying diarizer.py into container..."
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ssh "${USER}@${HOST}" "docker exec -i ${CONTAINER} sh -c \
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'cat > /opt/parakeet/app/diarizer.py'" < "${REPO_DIR}/diarizer.py"
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echo "→ Copying patched main.py into container..."
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ssh "${USER}@${HOST}" "docker exec -i ${CONTAINER} sh -c \
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'cat > /opt/parakeet/app/main.py'" < "${REPO_DIR}/main.py"
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echo "→ Verifying syntax inside container..."
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ssh "${USER}@${HOST}" "docker exec ${CONTAINER} python3 -c \
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'import ast; ast.parse(open(\"/opt/parakeet/app/diarizer.py\").read()); ast.parse(open(\"/opt/parakeet/app/main.py\").read()); print(\"py OK\")'"
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echo "→ Restarting ${CONTAINER}..."
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ssh "${USER}@${HOST}" "docker restart ${CONTAINER}"
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echo
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echo "✔ Patches applied. Sortformer model (~150 MB) will download on first load — wait ~30s before testing."
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echo
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echo "Test once it's ready:"
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echo " curl -sS http://${HOST}:8000/health"
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echo " curl -sS -X POST http://${HOST}:8000/v1/audio/diarize -F file=@some-audio.mp3 | head -c 500"
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