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TTS WebUI

TTS WebUI

Web UI for running multiple text-to-speech, music generation, and audio tools
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Source
collected from the steven2358/awesome-generative-ai list · type: MCP server
Harvest history
first seen 2026-10-14 · last seen 2026-10-16 · seen 4× · listed by 3 sources
Score
score 303 · 3 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
first catalogued 2026-10-14;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Third-party quality signals

TTS WebUI

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

Download Installer ||
Installation ||
Docker Setup ||
Silly Tavern ||
Extensions ||
Feedback / Bug reports
Videos
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Examples
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| :-----------------------------------------: | :-----------------------------------------: | :-------------------------------: |
Screenshots
| .png) | .png) | .png) |
| :-----------------------------------------: | :-----------------------------------------: | :-------------------------------: |
| .png) | .png) | .png) |
| :-----------------------------------------: | :-----------------------------------------: | :-------------------------------: |
Supported Models
| Text-to-speech | Audio/Music Generation | Audio Conversion/Tools |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- |
| Bark | MusicGen | RVC |
| Tortoise | MAGNeT | Demucs |
| Maha TTS | Stable Audio | Vocos |
| MMS | Riffusion\* | Whisper |
| Vall-E X | AudioCraft Mac\* | AP BWE |
| StyleTTS2 | AudioCraft Plus\* | Resemble Enhance |
| SeamlessM4T | ACE-Step\* | Audio Separator |
| XTTSv2\* | Song Bloom\* | PyRNNoise\* |
| MARS5\* | | MiMo Audio\* |
| F5-TTS\* | | |
| Parler TTS\* | | |
| OpenVoice\* | | |
| OpenVoice V2\* | | |
| Kokoro TTS\* | | |
| DIA\* | | |
| CosyVoice\* | | |
| GPT-SoVITS\* | | |
| Piper TTS\* | | |
| Kimi Audio 7B Instruct\* | | |
| Chatterbox\* | | |
| VibeVoice\* | | |
| Kitten TTS\* | | |
| Index-TTS2\* | | |
| VoxCPM\* | | |
| FireRedTTS2\* | | |
| MegaTTS3\* | | |
| MiniMax Cloud TTS (built-in) | | |
\* These models are not installed by default, instead they are available as extensions.
Installation
Using TTS WebUI Ignition (Recommended)
TTS WebUI Ignition is the new installer and launcher for TTS WebUI.
On Windows:
For other platforms, download the latest release from the releases page or build it from source using the instructions in the repository.
Using the Installer (Legacy)
Current base installation size is around 10.7 GB. Each model will require 2-8 GB of space in addition.
* Download the latest version and extract it.
* Run start_tts_webui.bat or start_tts_webui.sh to start the server. It will ask you to select the GPU/Chip you are using. Once everything has installed, it will start the Gradio server at http://localhost:7770 and the React UI at http://localhost:3000.
* Output log will be available in the installer_scripts/output.log file.
* Note: The start script sets up a conda environment and a python virtual environment. Thus you don't need to make a venv before that, and in fact, launching from another venv might break this script.
Manual installation
Prerequisites:
* git
* Python 3.10 or 3.11 (3.12 not supported yet)
* PyTorch
* ffmpeg (with vorbis support)
* (Optional) NodeJS 22.9.0 for React UI
* SQLite (bundled with Python) for database support
1. Clone the repository:
2. Install required packages:
3. Run the server:
4. For React UI:
For detailed manual installation instructions, please refer to the Manual Installation Guide.
Docker Setup
tts-webui can also be ran inside of a Docker container. Using CUDA inside of docker requires NVIDIA Container Toolkit. To get started, pull the image from GitHub Container Registry:
Once the image has been pulled it can be started with Docker Compose:
The ports are 7770 (env:TTS_PORT) for the Gradio backend and 3000 (env:UI_PORT) for the React front end.
The container will take some time to generate the first output while models are downloaded in the background. The status of this download can be verified by checking the container logs:
Source
awesome · https://github.com/rsxdalv/TTS-WebUI
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