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 installed (required for audio format conversion and playback speed adjustments)

⚡️ 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/your-username/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=1.0

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-tts voice (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 1.0.

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-tts voices for a given language / locale.
• POST/GET /v1/voices/all: Lists all edge-tts voices, 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=1.0 \
  -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

🎙️ Voice Samples

Play voice samples and see all available Edge TTS voices