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Skald-Circle/docs/plugins/orpheus_tts_3b.md
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docs overhaul: agent-facing doc bundle, read-only docs mount in containers
- Strip ~55 stale upstream docs (dev docs never meant for the agents)
- Write new slim index.md as an agent-facing guide to the app's features
- Add new plugin docs: comfyui, elevenlabs, kokoro_tts, orpheus_tts_3b,
  remote_connectivity, whisper_local (replacing old names)
- Add docs_host to UserFs: docs/… and ~/docs/… resolve to {WD}/docs,
  mounted read-only at /root/docs in every user's container
- Instruct assistant/kid/project-coordinator agents to read docs/index.md
  when users ask how the software works
2026-07-22 10:20:21 +01:00

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Orpheus TTS 3B

  • Plugin id: orpheus_tts_3b
  • Category: Text-to-speech, local
  • Runs: on this machine, as a Python subprocess this plugin manages — needs a real GPU for reasonable speed

What it does

Expressive, high-quality local text-to-speech using the 3-billion-parameter Orpheus model. Heavier than Kokoro TTS, but supports inline emotion tags for much more natural-sounding speech: <laugh>, <chuckle>, <sigh>, <cough>, <sniffle>, <groan>, <yawn>, <gasp> — placed directly in the text where the effect should occur, e.g. "He showed up at noon. <chuckle> Classic."

The model is gated on HuggingFace, so it requires a personal access token before it can download.

Requirements

  • A HuggingFace account and access token: create one at https://huggingface.co/settings/tokens. It must be stored as a secret named HUGGINGFACE_TOKEN — this is not a plugin config field. If you (the assistant) are helping set this up, activate the config tools and call set_secret("HUGGINGFACE_TOKEN", "hf_...") with the token the user gives you; do not ask them to find a settings page for it. The plugin refuses to start without it.
  • GPU VRAM, depending on the quantization level chosen: roughly 7 GB (none/fp16), 4 GB (int8, the default), or 2.5 GB (int4).
  • python3 on the host; the model itself downloads automatically from HuggingFace on first run and is cached locally.

Enabling & configuring (admin)

  1. Get a HuggingFace token and store it as the secret HUGGINGFACE_TOKEN (see above).
  2. Plugin catalog → Orpheus TTS 3B → enable, then Configure.
  3. Fields:
    • quantization (none | int8 | int4, default int8) — lower precision uses less VRAM at some quality cost.
    • voice (tara | dan | leah | zac | zoe | mia | julia | leo, default tara).
  4. No separate "add provider" step — it appears directly in the Models hub's TTS section once running.

Notes

  • Meaningfully heavier than Kokoro TTS: only worth choosing when the machine has a real GPU and the extra expressiveness (emotion tags) matters.
  • If the plugin won't start, the most common cause is a missing or invalid HUGGINGFACE_TOKEN secret, or the model being gated and requiring the HuggingFace account to accept its license on the model page first.