Warning: XTTS-streaming-server doesn't support concurrent streaming requests, it's a demo server, not meant for production.

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)

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)

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.

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

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

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