XTTS streaming server

movie.mp4

1) Run the server

Use a pre-built image

CUDA 12.1:

$ docker run --gpus=all -e COQUI_TOS_AGREED=1 --rm -p 8000:80 ghcr.io/coqui-ai/xtts-streaming-server:latest-cuda121

CUDA 11.8 (for older cards):

$ docker run --gpus=all -e COQUI_TOS_AGREED=1 --rm -p 8000:80 ghcr.io/coqui-ai/xtts-streaming-server:latest

CPU (not recommended):

$ docker run -e COQUI_TOS_AGREED=1 --rm -p 8000:80 ghcr.io/coqui-ai/xtts-streaming-server:latest-cpu

Run with a fine-tuned model:

Make sure the model folder /path/to/model/folder contains the following files:

config.json
model.pth
vocab.json

$ docker run -v /path/to/model/folder:/app/tts_models --gpus=all -e COQUI_TOS_AGREED=1  --rm -p 8000:80 ghcr.io/coqui-ai/xtts-streaming-server:latest`

Setting the COQUI_TOS_AGREED environment variable to 1 indicates you have read and agreed to the terms of the CPML license. (Fine-tuned XTTS models also are under the CPML license)

Build the image yourself

To build the Docker container Pytorch 2.1 and CUDA 11.8 :

DOCKERFILE may be Dockerfile, Dockerfile.cpu, Dockerfile.cuda121, or your own custom Dockerfile.

$ git clone [email protected]:coqui-ai/xtts-streaming-server.git
$ cd xtts-streaming-server/server
$ docker build -t xtts-stream . -f DOCKERFILE
$ docker run --gpus all -e COQUI_TOS_AGREED=1 --rm -p 8000:80 xtts-stream

Setting the COQUI_TOS_AGREED environment variable to 1 indicates you have read and agreed to the terms of the CPML license. (Fine-tuned XTTS models also are under the CPML license)

2) Testing the running server

Once your Docker container is running, you can test that it's working properly. You will need to run the following code from a fresh terminal.

Clone `xtts-streaming-server` if you haven't already

$ git clone [email protected]:coqui-ai/xtts-streaming-server.git

Using the gradio demo

$ cd xtts-streaming-server
$ python -m pip install -r test/requirements.txt
$ python demo.py

Using the test script

$ cd xtts-streaming-server/test
$ python -m pip install -r requirements.txt
$ python test_streaming.py

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