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plugins: merge the user Plugins page into per-plugin sidebar pages

The generic per-user #plugins page is gone: a plugin with per-user
settings hosts them in its own web_pages() sidebar page instead
(Telegram's pairing page is new; Honcho's opt-in page already existed).
The admin catalog moves from #plugin-catalog to #plugins (old hash
redirected), and user_config_schema is removed from the Plugin trait,
the API DTOs and both plugins — the my-config endpoint, the
plugin_user_configs store and the update_user_config hook stay, now
driven by each plugin's own page fragment.

2026-07-28 20:48:03 +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)

Get a HuggingFace token and store it as the secret HUGGINGFACE_TOKEN (see above).
Plugins page → Orpheus TTS 3B → enable, then Configure.
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).
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.

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