Awesome
<div align="center"> <h1 align="center">Serving XTTS with BentoML</h1> </div>XTTS is a voice generation model that lets you clone voices into different languages by using just a quick 6-second audio clip.
This is a BentoML example project, demonstrating how to build a text-to-speech inference API server using the XTTS model. See here for a full list of BentoML example projects.
Install dependencies
git clone https://github.com/bentoml/BentoXTTS.git
cd BentoXTTS
# Recommend Python 3.11
pip install -r requirements.txt
Run the BentoML Service
We have defined a BentoML Service in service.py
. Run bentoml serve
in your project directory to start the Service. You may also set the environment variable COQUI_TTS_AGREED=1
to agree to the terms of Coqui TTS.
$ COQUI_TOS_AGREED=1 bentoml serve .
2024-01-18T11:13:54+0800 [INFO] [cli] Starting production HTTP BentoServer from "service:XTTS" listening on http://localhost:3000 (Press CTRL+C to quit)
/workspace/codes/examples/xtts/venv/lib/python3.10/site-packages/TTS/api.py:70: UserWarning: `gpu` will be deprecated. Please use `tts.to(device)` instead.
warnings.warn("`gpu` will be deprecated. Please use `tts.to(device)` instead.")
> tts_models/multilingual/multi-dataset/xtts_v2 is already downloaded.
> Using model: xtts
The server is now active at http://localhost:3000. You can interact with it using the Swagger UI or in other different ways.
CURL
curl -X 'POST' \
'http://localhost:3000/synthesize' \
-H 'accept: */*' \
-H 'Content-Type: application/json' \
-d '{
"text": "It took me quite a long time to develop a voice and now that I have it I am not going to be silent.",
"lang": "en"
}' -o output.wav
Python client
This client returns the audio file as a Path
object. You can use it to access or process the file. See Clients for details.
import bentoml
with bentoml.SyncHTTPClient("http://localhost:3000") as client:
result = client.synthesize(
text="It took me quite a long time to develop a voice and now that I have it I am not going to be silent.",
lang="en"
)
For detailed explanations of the Service code, see XTTS: Text to speech.
Deploy to BentoCloud
After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. Sign up if you haven't got a BentoCloud account.
Make sure you have logged in to BentoCloud, then run the following command to deploy it.
bentoml deploy .
Once the application is up and running on BentoCloud, you can access it via the exposed URL.
Note: For custom deployment in your own infrastructure, use BentoML to generate an OCI-compliant image.