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:::warning This tutorial is a community contribution and is not supported by the OpenWebUI team. It serves only as a demonstration on how to customize OpenWebUI for your specific use case. Want to contribute? Check out the contributing tutorial. :::
Integrating openai-edge-tts 🗣️ with Open WebUI
What is openai-edge-tts, and how is it different from openedai-speech?
Similar to openedai-speech, openai-edge-tts is a text-to-speech API endpoint that mimics the OpenAI API endpoint, allowing for a direct substitute in scenarios where the OpenAI Speech endpoint is callable and the server endpoint URL can be configured.
openedai-speech is a more comprehensive option that allows for entirely offline generation of speech with many modalities to choose from.
openai-edge-tts is a simpler option that uses a Python package called edge-tts to generate the audio.
edge-tts (repo) leverages the Edge browser's free "Read Aloud" feature to emulate a request to Microsoft / Azure in order to receive very high quality text-to-speech for free.
Requirements
- Docker installed on your system
- Open WebUI running
- ffmpeg (Optional - Only required if opting to not use
mp3format)
⚡️ Quick start
The simplest way to get started without having to configure anything is to run the command below
docker run -d -p 5050:5050 travisvn/openai-edge-tts:latest
This will run the service at port 5050 with all the default configs
Setting up Open WebUI to use openai-edge-tts
- Open the Admin Panel and go to Settings -> Audio
- Set your TTS Settings to match the screenshot below
- Note: you can specify the TTS Voice here
:::info
The default API key is the string your_api_key_here. You do not have to change that value if you do not need the added security.
:::
And that's it! You can end here
See the Usage section for request examples.
Please ⭐️ star the repo on GitHub if you find OpenAI Edge TTS useful
:::tip
You can define the environment variables directly in the docker run command. See Quick Config for Docker below.
:::
Alternative Options
🐍 Running with Python
If you prefer to run this project directly with Python, follow these steps to set up a virtual environment, install dependencies, and start the server.
1. Clone the Repository
git clone https://github.com/travisvn/openai-edge-tts.git
cd openai-edge-tts
2. Set Up a Virtual Environment
Create and activate a virtual environment to isolate dependencies:
# For macOS/Linux
python3 -m venv venv
source venv/bin/activate
# For Windows
python -m venv venv
venv\Scripts\activate
3. Install Dependencies
Use pip to install the required packages listed in requirements.txt:
pip install -r requirements.txt
4. Configure Environment Variables
Create a .env file in the root directory and set the following variables:
API_KEY=your_api_key_here
PORT=5050
DEFAULT_VOICE=en-US-AndrewNeural
DEFAULT_RESPONSE_FORMAT=mp3
DEFAULT_SPEED=1.2
DEFAULT_LANGUAGE=en-US
REQUIRE_API_KEY=True
5. Run the Server
Once configured, start the server with:
python app/server.py
The server will start running at http://localhost:5050.
6. Test the API
You can now interact with the API at http://localhost:5050/v1/audio/speech and other available endpoints. See the Usage section for request examples.
Usage
Endpoint: /v1/audio/speech
Generates audio from the input text. Available parameters:
Required Parameter:
- input (string): The text to be converted to audio (up to 4096 characters).
Optional Parameters:
- model (string): Set to "tts-1" or "tts-1-hd" (default:
"tts-1"). - voice (string): One of the OpenAI-compatible voices (alloy, echo, fable, onyx, nova, shimmer) or any valid
edge-ttsvoice (default:"en-US-AndrewNeural"). - response_format (string): Audio format. Options:
mp3,opus,aac,flac,wav,pcm(default:mp3). - speed (number): Playback speed (0.25 to 4.0). Default is
1.2.
:::tip You can browse available voices and listen to sample previews at tts.travisvn.com :::
Example request with curl and saving the output to an mp3 file:
curl -X POST http://localhost:5050/v1/audio/speech \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your_api_key_here" \
-d '{
"input": "Hello, I am your AI assistant! Just let me know how I can help bring your ideas to life.",
"voice": "echo",
"response_format": "mp3",
"speed": 1.0
}' \
--output speech.mp3
Or, to be in line with the OpenAI API endpoint parameters:
curl -X POST http://localhost:5050/v1/audio/speech \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your_api_key_here" \
-d '{
"model": "tts-1",
"input": "Hello, I am your AI assistant! Just let me know how I can help bring your ideas to life.",
"voice": "alloy"
}' \
--output speech.mp3
And an example of a language other than English:
curl -X POST http://localhost:5050/v1/audio/speech \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your_api_key_here" \
-d '{
"model": "tts-1",
"input": "じゃあ、行く。電車の時間、調べておくよ。",
"voice": "ja-JP-KeitaNeural"
}' \
--output speech.mp3
Additional Endpoints
- POST/GET /v1/models: Lists available TTS models.
- POST/GET /v1/voices: Lists
edge-ttsvoices for a given language / locale. - POST/GET /v1/voices/all: Lists all
edge-ttsvoices, with language support information.
🐳 Quick Config for Docker
You can configure the environment variables in the command used to run the project
docker run -d -p 5050:5050 \
-e API_KEY=your_api_key_here \
-e PORT=5050 \
-e DEFAULT_VOICE=en-US-AndrewNeural \
-e DEFAULT_RESPONSE_FORMAT=mp3 \
-e DEFAULT_SPEED=1.2 \
-e DEFAULT_LANGUAGE=en-US \
-e REQUIRE_API_KEY=True \
travisvn/openai-edge-tts:latest
Additional Resources
For more information on openai-edge-tts, you can visit the GitHub repo
For direct support, you can visit the Voice AI & TTS Discord