vh
1a67370138
Two new speech stacks on irv-ml1, both on the /worktank/<stack>/
pattern, no tnet (irv-ml1 is local-endpoints-only for now).
parakeet — ASR via Shadowfita/parakeet-tdt-0.6b-v2-fastapi:
- docker buildx git context pinned to SHA 31c5652; no source
vendored. Rebuild on SHA bump.
- GPU-capable FastAPI + Silero VAD + WS streaming.
- API: POST /transcribe, WS /ws/transcribe, GET /healthz. Not the
literal OpenAI `/v1/audio/transcriptions` path — note in README.
- HF cache at /worktank/parakeet/models/ (excluded from restic).
- Build ~158s first time; steady-state start ~40s.
cosyvoice — TTS via neosun/cosyvoice:v1.3.2 shipping
Fun-CosyVoice3-0.5B-2512 (CosyVoice 3, chosen over v2 for the
expanded 5,000-hour instruction-following data covering emotions,
speed, tones, dialects, accents, role-playing; ~150ms streaming
TTFB matches v2). API: /v1/audio/speech (OpenAI drop-in),
/v1/voices/create (cloning), /health.
- Host port 8190 (container 8188; host 8188 already taken by comfyui).
- /worktank/cosyvoice/{voices,input,output}/; voices include in
restic (precious — reproducing a clone needs the original ref
audio), input+output excluded (scratch).
- Model weights (~2-3 GB) live inside image layer; re-download on
tag bump, persist across `compose up -d`.
Both healthy on first deploy.
61 lines
2.4 KiB
YAML
61 lines
2.4 KiB
YAML
# CosyVoice — multilingual expressive TTS with voice cloning.
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#
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# Ships the Fun-CosyVoice3-0.5B-2512 model from FunAudioLLM (latest
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# as of 2026-04). Streaming PCM chunks with ~150 ms TTFB. Emotional
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# control via either XML tags (<angry>text</angry>) or instruction
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# prompts (`You are a helpful assistant. <|endofprompt|>` syntax).
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#
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# Runs on irv-ml1 (dual GPU). Both GPUs exposed via
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# NVIDIA_VISIBLE_DEVICES=all; image reads CUDA_VISIBLE_DEVICES if
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# you later want to pin.
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#
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# Path split:
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# /worktank/cosyvoice/voices → /data/voices cloned speaker profiles
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# /worktank/cosyvoice/input → /data/input scratch for uploaded source audio
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# /worktank/cosyvoice/output → /data/output synthesized clips
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#
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# Models (~2–3 GB) download on first run into the image's internal
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# pretrained_models/ path. Not bind-mounted (the image expects an
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# exact layout we don't have authoritative docs for); recreating the
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# container without the cached image will re-download. Cached image
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# layer persists through `compose up -d` recreates.
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#
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# API routes (OpenAI-compatible where marked):
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# POST /v1/audio/speech — OpenAI drop-in for TTS
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# POST /v1/voices/create — voice cloning (reference audio in)
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# GET /v1/voices — list cloned voices
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# GET /health — health probe
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#
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# All tunables live in .env — edit that, not this file.
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services:
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cosyvoice:
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image: neosun/cosyvoice:${COSYVOICE_VERSION}
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container_name: cosyvoice
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restart: unless-stopped
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runtime: nvidia
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ports:
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- "${COSYVOICE_BIND:-0.0.0.0}:${COSYVOICE_PORT}:8188"
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environment:
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- NVIDIA_VISIBLE_DEVICES=all
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- MODEL_DIR=${COSYVOICE_MODEL_DIR:-pretrained_models/Fun-CosyVoice3-0.5B}
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- PORT=8188
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- GPU_IDLE_TIMEOUT=${COSYVOICE_GPU_IDLE_TIMEOUT:-600}
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volumes:
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- ${COSYVOICE_VOICES_DIR}:/data/voices
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- ${COSYVOICE_INPUT_DIR}:/data/input
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- ${COSYVOICE_OUTPUT_DIR}:/data/output
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healthcheck:
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test: ["CMD-SHELL", "curl -fsS http://localhost:8188/health >/dev/null || exit 1"]
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interval: 30s
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timeout: 10s
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retries: 3
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# First boot pulls ~2–3 GB of model weights.
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start_period: 300s
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labels:
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- homepage.group=AI Systems
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- homepage.name=CosyVoice
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- homepage.icon=mdi-account-voice
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- homepage.description=Expressive multilingual TTS + cloning (irv-ml1)
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- homepage.href=http://10.100.79.3:${COSYVOICE_PORT}
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