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Add cpu ci #15

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44 changes: 44 additions & 0 deletions .github/workflows/build-and-push-to-ghcr.yml
Original file line number Diff line number Diff line change
Expand Up @@ -93,3 +93,47 @@ jobs:
cache-to: type=registry,ref=ghcr.io/coqui-ai/xtts-streaming-server:cache-latest-cuda121
tags: ghcr.io/coqui-ai/xtts-streaming-server:latest-cuda121, ghcr.io/coqui-ai/xtts-streaming-server:main-cuda121-${{ github.sha }}
#build-args:
build-and-push-to-ghcr-cpu:
runs-on: ubuntu-22.04
steps:
-
name: Checkout
uses: actions/checkout@v3

-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3

- name: 'Login to GitHub Container Registry'
run: |
set -xe
docker login --username ${{ github.actor }} --password ${{ secrets.GITHUB_TOKEN }} ghcr.io

- name: 'Remove cache'
run: |
sudo rm -rf /usr/share/dotnet
sudo rm -rf /opt/ghc
sudo rm -rf "/usr/local/share/boost"
sudo rm -rf "$AGENT_TOOLSDIRECTORY"

- name: Build only for PR CPU
if: github.ref != 'refs/heads/main'
uses: docker/build-push-action@v5
with:
context: "{{defaultContext}}:server"
file: Dockerfile.cpu
push: false # Do not push image for PR
cache-from: type=registry,ref=ghcr.io/coqui-ai/xtts-streaming-server:cache-latest-cpu; type=registry,ref=ghcr.io/coqui-ai/xtts-streaming-server:cache-pr-cuda121-${{ github.event.number }}
cache-to: type=registry,ref=ghcr.io/coqui-ai/xtts-streaming-server:cache-pr-cpu-${{ github.event.number }}

- name: Build and Push image CPU
if: github.ref == 'refs/heads/main'
uses: docker/build-push-action@v5
with:
context: "{{defaultContext}}:server"
file: Dockerfile.cpu
push: true # Push if merged
cache-from: type=registry,ref=ghcr.io/coqui-ai/xtts-streaming-server:cache-latest-cpu
cache-to: type=registry,ref=ghcr.io/coqui-ai/xtts-streaming-server:cache-latest-cpu
tags: ghcr.io/coqui-ai/xtts-streaming-server:latest-cpu, ghcr.io/coqui-ai/xtts-streaming-server:main-cpu-${{ github.sha }}
#build-args:
81 changes: 45 additions & 36 deletions README.md
Original file line number Diff line number Diff line change
@@ -1,70 +1,79 @@
# XTTS streaming server

## Running the server
## 1) Run the server

To run a pre-built container (CUDA 11.8):
### Use a pre-built image

CUDA 12.1:

```bash
$ 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):

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

CUDA 12.1 version (for newer cards)
CPU (not recommended):

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

Run with a custom XTTS v2 model (FT or previous versions):
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`

```bash
$ 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](https://coqui.ai/cpml).
the terms of the [CPML license](https://coqui.ai/cpml). (Fine-tuned XTTS models also are under the [CPML license](https://coqui.ai/cpml))

(Fine-tuned XTTS models also are under the [CPML license](https://coqui.ai/cpml))
### Build the image yourself

## Testing the server
To build the Docker container Pytorch 2.1 and CUDA 11.8 :

### Using the gradio demo
`DOCKERFILE` may be `Dockerfile`, `Dockerfile.cpu`, `Dockerfile.cuda121`, or your own custom Dockerfile.

```bash
$ python -m pip install -r test/requirements.txt
$ python demo.py
$ 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
```

### Using the test script
Setting the `COQUI_TOS_AGREED` environment variable to `1` indicates you have read and agreed to
the terms of the [CPML license](https://coqui.ai/cpml). (Fine-tuned XTTS models also are under the [CPML license](https://coqui.ai/cpml))

```bash
$ cd test
$ python -m pip install -r requirements.txt
$ python test_streaming.py
```
## 2) Testing the running server

## Building the container
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.

1. To build the Docker container Pytorch 2.1 and CUDA 11.8 :
### Clone `xtts-streaming-server` if you haven't already

```bash
$ cd server
$ docker build -t xtts-stream .
$ git clone [email protected]:coqui-ai/xtts-streaming-server.git
```
For Pytorch 2.1 and CUDA 12.1 :
```bash
$ cd server
docker build -t xtts-stream . -f Dockerfile.cuda121
```
2. Run the server container:

### Using the gradio demo

```bash
$ docker run --gpus all -e COQUI_TOS_AGREED=1 --rm -p 8000:80 xtts-stream
$ cd xtts-streaming-server
$ python -m pip install -r test/requirements.txt
$ python demo.py
```

Setting the `COQUI_TOS_AGREED` environment variable to `1` indicates you have read and agreed to
the terms of the [CPML license](https://coqui.ai/cpml).


Make sure the model folder contains the following files:
- `config.json`
- `model.pth`
- `vocab.json`
### Using the test script

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