vh
e0d1c44137
The 2026-09-06 headscale cutover retired irv-ml1's wg0 tunnel IP 10.100.79.3 (now 10.6.110.50). Repointed all LIVE canonical refs to the DNS NAME so the next move can't re-break them: homepage.href/siteMonitor labels across 25 stack composes, load-bearing env defaults (asset-engine INFERENCE_HOST, open-webui AUDIO_TTS_OPENAI_API_BASE_URL, skaldsong SKALDSONG_TTS_BASE_URL, zonos-gateway ZONOS_URL, dia), homepage services.yaml manual cards (Voice Design Studio, IRV-ML1), and servers/irv-ml1/ssh-target. Updated the stale 'WG tunnel' comment to the mesh reality. Left as-is: README curl-examples and .env.example comments (docs), and historical mentions in CLAUDE.md/persistent-memory. NOTE: applying the label repoints to the RUNNING irv-ml1 containers needs a recreate per service (labels read at creation); deployed .env values are separate from these canonical defaults.
59 lines
2.6 KiB
YAML
59 lines
2.6 KiB
YAML
# Kyutai TTS — 1.6B / 2B-class streaming TTS from Kyutai (the Moshi /
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# Mimi team), trained on 2.5M hours. 220 ms latency in solo setup; up
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# to 32 simultaneous streams under 350 ms on an L40-class GPU.
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#
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# Served via the NillPointer/Kyutai-TTS-Server community wrapper —
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# Kyutai's official deployment is Rust + websockets only, which doesn't
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# fit our OpenAI-compat fleet. The community wrapper bridges Kyutai's
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# native streaming to the OpenAI /v1/audio/speech contract.
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#
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# Why this stack alongside the existing TTS:
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# * Kyutai's claim is the lowest streaming latency in this size
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# class (220 ms on a single GPU). Worth bench-comparing against
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# Chatterbox (~1.2 s) and Fish S2-Pro (~150 ms claimed).
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# * Trained on 2.5M hours — a different scaling regime from the
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# others (CosyVoice 5k hrs, Fish 10M hrs).
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# * Designed for full-duplex dialogue (Moshi heritage) — may surface
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# conversational quality the others lack.
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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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kyutai-tts:
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image: local/kyutai-tts:${KYUTAI_TTS_TAG}
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build:
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context: https://github.com/NillPointer/Kyutai-TTS-Server.git#${KYUTAI_TTS_SHA}
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dockerfile: Dockerfile
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container_name: kyutai-tts
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restart: unless-stopped
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runtime: nvidia
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ports:
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- "${KYUTAI_TTS_BIND:-0.0.0.0}:${KYUTAI_TTS_PORT}:8000"
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environment:
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- NVIDIA_VISIBLE_DEVICES=${KYUTAI_TTS_GPU_DEVICES:-0}
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# Kyutai's en/fr bilingual model on HF. Switch to a different
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# checkpoint via .env without rebuilding.
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- KYUTAI_MODEL=${KYUTAI_TTS_MODEL:-kyutai/tts-1.6b-en_fr}
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- HF_HOME=/app/hf_cache
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volumes:
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- ${KYUTAI_TTS_CACHE_DIR}:/app/hf_cache
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- ${KYUTAI_TTS_VOICES_DIR}:/app/voices:ro
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healthcheck:
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# NillPointer wrapper's actual endpoints (verified at runtime via
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# /openapi.json): just /health (root) and /v1/audio/speech (POST).
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# No /v1/models, no /v1/audio/voices — those 404. /health is the
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# liveness signal. 127.0.0.1 explicit to dodge IPv4/IPv6 localhost
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# race.
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test: ["CMD-SHELL", "python3 -c \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://127.0.0.1:8000/health', timeout=5).status==200 else 1)\""]
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interval: 30s
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timeout: 10s
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retries: 3
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# First boot pulls the Kyutai checkpoint (~3-6 GB) + warms.
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start_period: 600s
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labels:
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- homepage.group=AI Systems
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- homepage.name=Kyutai TTS
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- homepage.icon=mdi-radio-tower
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- homepage.description=Ultra-low-latency streaming TTS — 220 ms on solo GPU, EN/FR (irv-ml1)
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- homepage.href=http://irv-ml1.nh3.internal:${KYUTAI_TTS_PORT}
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