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Create openai-edge-tts-integration.md
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Timothy Jaeryang Baek
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docs/tutorials/integrations/openai-edge-tts-integration.md
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docs/tutorials/integrations/openai-edge-tts-integration.md
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---
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sidebar_position: 18
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title: "Edge TTS"
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---
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# Integrating `openai-edge-tts` with Open WebUI
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## What is `openai-edge-tts`, and how is it different from `openedai-speech`?
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Similar to [openedai-speech](https://github.com/matatonic/openedai-speech), [openai-edge-tts](https://github.com/travisvn/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.
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`openedai-speech` is a more comprehensive option that allows for entirely offline generation of speech with many modalities to choose from.
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`openai-edge-tts` is a simpler option that uses a Python package called `edge-tts` to generate the audio.
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`edge-tts` 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.
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## Requirements
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- Docker installed on your system
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- Open WebUI running
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- ffmpeg installed (required for audio format conversion and playback speed adjustments)
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## Quick start
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The simplest way to get started without having to configure anything is to run the command below
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```bash
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docker run -d -p 5050:5050 travisvn/openai-edge-tts:latest
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```
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This will run the service at port 5050 with all the default configs
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## Setting up Open WebUI to use `openai-edge-tts`
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- Open the Admin Panel and go to Settings -> Audio
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- Set your TTS Settings to match the screenshot below
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- _Note: you can specify the TTS Voice here_
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:::info
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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.
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:::
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**And that's it! You can end here**
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See the [Usage](#usage) section for request examples.
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## Alternative Options
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### Running with Python
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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.
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#### 1. Clone the Repository
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```bash
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git clone https://github.com/your-username/openai-edge-tts.git
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cd openai-edge-tts
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```
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#### 2. Set Up a Virtual Environment
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Create and activate a virtual environment to isolate dependencies:
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```bash
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# For macOS/Linux
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python3 -m venv venv
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source venv/bin/activate
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# For Windows
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python -m venv venv
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venv\Scripts\activate
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```
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#### 3. Install Dependencies
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Use `pip` to install the required packages listed in `requirements.txt`:
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```bash
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pip install -r requirements.txt
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```
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#### 4. Configure Environment Variables
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Create a `.env` file in the root directory and set the following variables:
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```plaintext
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API_KEY=your_api_key_here
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PORT=5050
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DEFAULT_VOICE=en-US-AndrewNeural
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DEFAULT_RESPONSE_FORMAT=mp3
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DEFAULT_SPEED=1.0
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DEFAULT_LANGUAGE=en-US
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REQUIRE_API_KEY=True
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```
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#### 5. Run the Server
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Once configured, start the server with:
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```bash
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python app/server.py
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```
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The server will start running at `http://localhost:5050`.
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#### 6. Test the API
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You can now interact with the API at `http://localhost:5050/v1/audio/speech` and other available endpoints. See the [Usage](#usage) section for request examples.
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#### Usage
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##### Endpoint: `/v1/audio/speech`
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Generates audio from the input text. Available parameters:
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**Required Parameter:**
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- **input** (string): The text to be converted to audio (up to 4096 characters).
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**Optional Parameters:**
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- **model** (string): Set to "tts-1" or "tts-1-hd" (default: `"tts-1"`).
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- **voice** (string): One of the OpenAI-compatible voices (alloy, echo, fable, onyx, nova, shimmer) or any valid `edge-tts` voice (default: `"en-US-AndrewNeural"`).
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- **response_format** (string): Audio format. Options: `mp3`, `opus`, `aac`, `flac`, `wav`, `pcm` (default: `mp3`).
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- **speed** (number): Playback speed (0.25 to 4.0). Default is `1.0`.
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Example request with `curl` and saving the output to an mp3 file:
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```bash
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curl -X POST http://localhost:5050/v1/audio/speech \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer your_api_key_here" \
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-d '{
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"input": "Hello, I am your AI assistant! Just let me know how I can help bring your ideas to life.",
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"voice": "echo",
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"response_format": "mp3",
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"speed": 1.0
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}' \
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--output speech.mp3
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```
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Or, to be in line with the OpenAI API endpoint parameters:
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```bash
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curl -X POST http://localhost:5050/v1/audio/speech \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer your_api_key_here" \
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-d '{
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"model": "tts-1",
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"input": "Hello, I am your AI assistant! Just let me know how I can help bring your ideas to life.",
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"voice": "alloy"
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}' \
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--output speech.mp3
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```
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And an example of a language other than English:
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```bash
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curl -X POST http://localhost:5050/v1/audio/speech \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer your_api_key_here" \
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-d '{
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"model": "tts-1",
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"input": "じゃあ、行く。電車の時間、調べておくよ。",
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"voice": "ja-JP-KeitaNeural"
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}' \
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--output speech.mp3
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```
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##### Additional Endpoints
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- **GET /v1/models**: Lists available TTS models.
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- **GET /v1/voices**: Lists `edge-tts` voices for a given language / locale.
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- **GET /v1/voices/all**: Lists all `edge-tts` voices, with language support information.
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## Additional Resources
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For more information on `openai-edge-tts`, you can visit the [GitHub repo](https://github.com/travisvn/openai-edge-tts)
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