engines: import f5-tts + kokoro + tortoise sidecars into the tree
The python FastAPI sidecars have lived ad-hoc at /srv/appdata/ <engine>/build/ on the host without version control. Bringing them into the skald repo so the engine code travels with the cross-engine routing it depends on. This commit lands the VANILLA version of each engine on main: engines/f5-tts/ SWivid F5-TTS (CC-BY-NC weights flagged) engines/kokoro/ hexgrad Kokoro-82M (Apache 2.0 top to bottom) engines/tortoise/ neonbjb Tortoise-TTS (Apache 2.0 top to bottom) Engine-specific kludges (question doubling, GPU coordination, pause-duration tuning) get layered on engine/* branches per the README. Main stays the safe-to-read baseline.
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engines/f5-tts/compose.yml
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engines/f5-tts/compose.yml
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# F5-TTS standalone stack on the host.
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#
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# License posture (acknowledged 2026-05-13): code is Apache 2.0, but
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# the pretrained model weights are CC-BY-NC (Emilia training data).
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# Personal listen is fine; public sharing is a flagged gray area.
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# Sulkta's call: ship anyway.
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#
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# Runtime: 8GB GPU is plenty (F5 inference ~4-6GB peak).
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#
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# First-run cost: ~2GB model download from HuggingFace into hf-cache,
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# happens on first inference request. Subsequent runs are warm.
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name: f5-tts
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services:
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f5-tts:
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image: registry.example.local:5000/f5-tts:0.3
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container_name: f5-tts
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restart: unless-stopped
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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ports:
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- "127.0.0.1:7792:7860"
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- "127.0.0.1:7792:7860"
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volumes:
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# HF model weights cache — persists ~2GB after first download.
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- /srv/appdata/f5-tts/hf-cache:/cache/hf
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# Reference voice clips (lj_speech.wav, etc).
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- /srv/appdata/f5-tts/voices:/voices:ro
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# Rendered audio output — skald writes story narrations here.
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- /srv/appdata/f5-tts/audio:/audio
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environment:
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HF_HOME: /cache/hf
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HF_HUB_DISABLE_TELEMETRY: "1"
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labels:
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org.sulkta.domain: "sulkta"
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org.sulkta.owner: "Sulkta"
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org.sulkta.managed-by: "compose"
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org.sulkta.role: "f5-tts"
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