Omnivoice

VoiceStudio — local TTS & STT

The user runs VoiceStudio, a fully-local voice app exposing an OpenAI-compatible audio API at http://localhost:3900/v1. Use it whenever the user asks to generate speech, narrate text, clone a voice, or transcribe audio — it costs nothing, works offline, and their audio never leaves the machine.

Before the first call

Check the backend is up:

curl -sf http://localhost:3900/health

If it fails, tell the user to launch VoiceStudio (or bun run desktop-prod from a source checkout) — don't fall back to a cloud API without asking; local-first is why they installed it.

Text-to-speech

curl -s http://localhost:3900/v1/audio/speech \
  -H "Content-Type: application/json" \
  -d '{"model": "tts-1", "voice": "alloy", "input": "TEXT HERE", "response_format": "wav"}' \
  --output speech.wav

• model: tts-1 or tts-1-hd — both map to the user's active TTS engine.
• voice: OpenAI names (alloy, echo, nova, …) work, but the real power is the user's own cloned voice-profile IDs — discover them first (below) and prefer a named clone when the user says "my voice" / "the narrator voice" / a profile by name.
• response_format: wav, mp3, flac, opus, or pcm.
• Long texts are fine — the engine chunks at sentence boundaries internally.

Discover the user's voices

curl -s http://localhost:3900/v1/audio/voices

Lists every cloned/designed voice profile (id + name) and the installed engines. Use a profile's id as the voice value in /speech.

Speech-to-text

curl -s http://localhost:3900/v1/audio/transcriptions \
  -F file=@clip.wav -F model=whisper-1 -F response_format=json

• model: whisper-1 maps to the active ASR engine (WhisperX by default; the user picks in Model Catalogue → Engines).
• response_format: json, text, verbose_json (per-segment timestamps), srt, or vtt — use srt/vtt directly when the user wants subtitles.

Python (openai SDK)

from openai import OpenAI
client = OpenAI(base_url="http://localhost:3900/v1", api_key="none")  # any string; nothing checks it

audio = client.audio.speech.create(model="tts-1", voice="alloy", input="Hello!", response_format="wav")
text = client.audio.transcriptions.create(model="whisper-1", file=open("clip.wav", "rb")).text

Notes

• No API key, no rate limits, no billing — it's the user's own hardware. First synthesis after a cold start may take longer (model loading); subsequent calls are fast.
• Anything beyond speech/transcription (video dubbing, batch jobs, voice design, audiobooks) lives in the full REST API — the interactive reference is embedded in the app at Settings → OpenAPI Reference, or ask the user to open it.
• If a call errors with an engine/model message, the actionable detail is usually in the response body — surface it to the user verbatim; VoiceStudio's errors are written to be user-fixable (e.g. which Settings toggle to flip).