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Zero-shot, massively-multilingual (600+ language) voice-cloning + voice-design TTS (diffusion-LM, Apache-2.0). No official image, so a thin CUDA container around the pip package running upstream's own Gradio demo (no FastAPI wrapper). Pinned to GPU 0 (3090) — the A6000 is ComfyUI-exclusive — port 8199. Built + verified live on irv-ml1 (Gradio 200, container healthy). Surface is the Gradio UI + Gradio API, NOT OpenAI-compat /v1/audio/speech (wrap later if asset-engine should consume it). deploy-omnivoice.yaml builds local + verifies.
21 lines
824 B
Bash
21 lines
824 B
Bash
# OmniVoice (k2-fsa/OmniVoice) — irv-ml1 stack tunables.
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# Copy to .env on the host (/opt/docker/compose/omnivoice/.env). The deploy
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# playbook seeds .env from this template on first run only.
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# Host port (container always listens on 8001). 8199 is free in the irv-ml1
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# audio range (8190-8198 + 8765/919x taken; 8201 reserved for voxtral).
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OMNIVOICE_PORT=8199
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OMNIVOICE_BIND=0.0.0.0
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# GPU: device 0 = RTX 3090 on irv-ml1 (device 1 / A6000 is ComfyUI-exclusive).
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# OmniVoice runs in <5 GB; the 3090 had ~18 GB free.
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OMNIVOICE_GPU_DEVICES=0
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# Image tag + optional upstream pin (empty = latest omnivoice on PyPI).
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OMNIVOICE_TAG=latest
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OMNIVOICE_VERSION=
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# Persistent HF weight cache + reference-voice staging on /worktank.
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OMNIVOICE_CACHE_DIR=/worktank/omnivoice/hf_cache
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OMNIVOICE_VOICES_DIR=/worktank/omnivoice/voices
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