VitsServer
v
⚡ A VITS ONNX server designed for fast inference, supporting streaming and additional inference settings to enable model preference settings and optimize performance.
We offer out-of-the-box call systems.
client = VITS ( "http://127.0.0.1:9557" )
res = client . generate_voice ( model_id = "model_01" , text = "你好，世界！" , speaker_id = 0 , audio_type = "wav" ,
length_scale = 1.0 , noise_scale = 0.5 , noise_scale_w = 0.5 , auto_parse = True )
with open ( "output.wav" , "wb" ) as f :
for chunk in res . iter_content ( chunk_size = 1024 ):
if chunk :
f . write ( chunk ) We recommend using a virtual environment to isolate the runtime environment. Because this project's dependencies may potentially disrupt your dependency library, we recommend using pipenv to manage the dependency package.
Configuration is in .env , including the following fields:
VITS_SERVER_HOST = 0.0.0.0
VITS_SERVER_PORT = 9557
VITS_SERVER_RELOAD = false
# VITS_SERVER_WORKERS=1
# VITS_SERVER_INIT_CONFIG="https://....json"
# VITS_SERVER_INIT_MODEL="https://.....pth or onnx"or you can use the following command to set the environment variable:
export VITS_SERVER_HOST= " 0.0.0.0 "
export VITS_SERVER_PORT= " 9557 "
export VITS_SERVER_RELOAD= " false "
export VITS_DISABLE_GPU= " false "
VITS_SERVER_RELOAD means auto restart server when file changed.
apt-get update &&
apt-get install -y build-essential libsndfile1 vim gcc g++ cmake
apt install python3-pip
pip3 install pipenv
pipenv install # Create and install dependency packages
pipenv shell # Activate the virtual environment
python3 main.py # Run
# then ctrl+c exit apt install npm
npm install pm2 -g
pm2 start pm2.json
# then the server will run in the background
and we have a one-click script to install pipenv and npm :
curl -LO https://raw.githubusercontent.com/LlmKira/VitsServer/main/deploy_script.sh && chmod +x deploy_script.sh && ./deploy_script.sh
we have docker pull sudoskys/vits-server:main to docker hub.
you can also build from Dockerfile.
docker build -t < image-name > . where <image-name> is the name you want to give to the image. Then, use the following command to start the container:
docker run -d -p 9557:9557 -v < local-path > /vits_model:/app/model < image-name > where <local-path> is the local folder path you want to map to the /app/model directory in the container.
In the model folder, place the model.pth / model.onnx and corresponding model.json files. If it is .pth , it will be automatically converted to .onnx !
you can use .env to set VITS_SERVER_INIT_CONFIG and VITS_SERVER_INIT_MODEL to download model files.
VITS_SERVER_INIT_CONFIG = " https://....json "
VITS_SERVER_INIT_MODEL = " https://.....pth?trace=233 or onnx?trace=233 " model folder structure:
.
├── 1000_epochs.json
├── 1000_epochs.onnx
├── 1000_epochs.pth
├── 233_epochs.json
├── 233_epochs.onnx
└── 233_epochs.pth
Model ID is 1000_epochs and 233_epochs .
When you put model files in the model folder, you should restart the server.
You can add extra fields in the model configuration to obtain information such as the model name corresponding to the model ID through the API.
{
//...
"info" : {
"name" : "coco" ,
"description" : "a vits model" ,
"author" : "someone" ,
"cover" : "https://xxx.com/xxx.jpg" ,
"email" : "[email protected]"
} ,
"infer" : {
"noise_scale" : 0.667 ,
"length_scale" : 1.0 ,
"noise_scale_w" : 0.8
}
//....
} infer is the default(prefer) inference settings for the model.
info is the model information.
You can access {your_base_url}/model/list?show_speaker=True&show_ms_config=True to obtain detailed information about model roles and configurations.
We would like to acknowledge the contributions of the following projects in the development of this project:
