VoiceStudio/deploy/dockerhub-overview.md

OmniVoice Studio

The open-source ElevenLabs alternative. Real-time dictation, zero-shot voice cloning, and cinematic video dubbing — fully local, no API keys, no accounts. 646 languages.

OmniVoice runs entirely on your own hardware (CUDA / MPS / ROCm / CPU auto-detect) — nothing is sent to the cloud. This image is the headless web-server build: a FastAPI backend serving a pre-built React UI over HTTP, so you can run it on a homelab box, a GPU server, or anywhere Docker runs and open the UI in a browser.

The Tauri desktop app's auto-updater and update-channel toggle are desktop-only and do not apply to this image — to update, pull a newer tag and recreate the container.

What you need: 8 GB RAM (16 GB+ recommended), ~10 GB free disk for model weights + cache (20 GB+ comfortable), and optionally a GPU — 4 GB VRAM works (TTS auto-offloads to CPU), 8 GB+ is comfortable. No GPU at all is fine too: the entire pipeline runs on CPU, just slower. Pull size: ~5 GB compressed (CUDA/CPU image), ~15 GB for the :rocm variant.

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Quick start (CPU)

docker run -d --name omnivoice \
  -p 127.0.0.1:3900:3900 \
  -v omnivoice-data:/app/omnivoice_data \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  palashdeb/omnivoice-studio:latest

Open http://localhost:3900. The first run downloads a few GB of model weights — follow docker logs -f omnivoice to watch progress.

Quick start (NVIDIA GPU)

docker run -d --name omnivoice --gpus all \
  -p 127.0.0.1:3900:3900 \
  -v omnivoice-data:/app/omnivoice_data \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  palashdeb/omnivoice-studio:latest

GPU mode needs the NVIDIA Container Toolkit on the host.

Quick start (AMD GPU / ROCm)

AMD GPUs use the dedicated :rocm image variant (the default image is CUDA-only and runs on CPU on AMD hardware). No toolkit needed — pass the GPU through as device nodes; the host only needs the amdgpu kernel driver:

docker run -d --name omnivoice \
  --device /dev/kfd --device /dev/dri \
  -p 127.0.0.1:3900:3900 \
  -v omnivoice-data:/app/omnivoice_data \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  palashdeb/omnivoice-studio:rocm

Podman users: same two --device flags (Quadlet: AddDevice=/dev/kfd + AddDevice=/dev/dri). On RDNA3 consumer cards (RX 7900 XTX/XT), add -e HSA_OVERRIDE_GFX_VERSION=11.0.0 if the GPU isn't detected — details in the Docker install guide.

There's also a Compose file in the repo with cpu / gpu / rocm profiles — see the Docker install guide.

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Image tags

Tag	What you get
:latest	Rolling preview — latest commit on main, at or ahead of the last release. This is the preview channel; pin :stable for production.
:stable	Most recent versioned release (updated on every v* git tag)
:0.4.0	Exact release version
:0.4	Latest patch within the 0.4 minor
:main	Alias of the same rolling main build as :latest
:sha-xxxxxxx	A specific commit (produced by manual workflow dispatch)
:rocm	AMD GPU (ROCm) build of the rolling preview — the ROCm analogue of :latest
:stable-rocm, :0.4.0-rocm, :0.4-rocm, :sha-xxxxxxx-rocm	ROCm builds of the corresponding tags above

Preview builds always come from main and never version-sort below :stable, so upgrades flow naturally. The same images and tags are mirrored on GHCR at ghcr.io/debpalash/omnivoice-studio.

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What's inside

• 🎙️ Voice Cloning — a 3-second clip mirrors any voice, zero-shot, in 646 languages.
• 🎨 Voice Design — dial in gender, age, accent, pitch, speed, emotion, and dialect.
• 🎬 Video Dubbing — YouTube URL or file → transcribe → translate → re-voice → MP4.
• 📖 Audiobook & long-form — script → plan → loudness-normalized M4B with chapters, metadata, and cover art.
• 🔊 Vocal Isolation — Demucs splits speech from music and keeps the background.
• 👥 Speaker Diarization — Pyannote + WhisperX auto-identify who said what.
• 📦 Batch Queue — drop 50 videos and walk away; per-job progress.
• 🤖 MCP Server — drive OmniVoice from Claude, Cursor, or any MCP client.
• 🛡️ AI Watermark — invisible AudioSeal (Meta) marking that survives compression.
• ⚡ GPU Auto-Detect — CUDA · MPS · ROCm · CPU, with auto-offload on ≤8 GB cards.
• 🧩 Extensible — subclass TTSBackend to add any engine in ~50 lines.

Multiple TTS engines ship out of the box (IndexTTS, CosyVoice, Supertonic-3, and more), auto-detected and selectable in Settings.

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Volumes worth persisting

Mount	Purpose
omnivoice-data:/app/omnivoice_data	Project DB, user voices, settings, encrypted HF token — survives upgrades
~/.cache/huggingface:/root/.cache/huggingface	HF model cache — reuse the host cache to skip multi-GB re-downloads

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Configuration & networking

• The container binds uvicorn to 0.0.0.0 internally; the host-side 127.0.0.1:3900:3900 mapping is what keeps it loopback-only. Change the mapping to 0.0.0.0:3900:3900 for LAN access.
• Behind a reverse proxy on a different origin, set -e OMNIVOICE_PUBLIC_API_BASE=https://api.your-host.example so the UI targets the right API base (works on the prebuilt image; no rebuild needed).
• The image ships with OMNIVOICE_SERVER_MODE=1, which relaxes the desktop-only loopback-origin gate so the admin UI works through Docker's NAT. Set it to 0 if you front the container with your own loopback auth proxy.

Security: OmniVoice ships no authentication. Anything that can reach the URL can use the app. Before exposing it beyond localhost, put it behind a reverse proxy with auth (Caddy basic_auth, nginx + htpasswd) or a private overlay (Tailscale, ZeroTier).

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Links

• Source & full install docs: https://github.com/debpalash/OmniVoice-Studio
• Docker guide: https://github.com/debpalash/OmniVoice-Studio/blob/main/docs/install/docker.md
• Troubleshooting: https://github.com/debpalash/OmniVoice-Studio/blob/main/docs/install/troubleshooting.md
• Community / support: Discord

OmniVoice Studio is in active beta and licensed under AGPL-3.0.