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.github/workflows/build-docker.yml

@@ -0,0 +1,196 @@
+name: Build and Publish Docker Image
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - 'main'
+  release:
+    types: [published]
+
+jobs:
+  build-and-push-image:
+    runs-on: ubuntu-latest
+
+    permissions:
+      contents: read
+      packages: write
+
+    env:
+      # Set up environment variables for the job
+      DOCKER_REGISTRY: ghcr.io
+      IMAGE_NAME: ${{ github.repository }}
+      TAG: ${{ github.sha }}
+
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+        with:
+          install: true
+
+      # Log in to the GitHub Container Registry only when not running on a pull request event
+      - name: Login to Docker Registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.DOCKER_REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: ${{ env.DOCKER_REGISTRY }}/${{ env.IMAGE_NAME }}
+
+      # Build and push the Docker image to GHCR for the main branch or specific tags
+      - name: Build and Push Docker Image
+        if: github.ref == 'refs/heads/main'
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          file: Dockerfile
+          push: true
+          tags: ${{ env.DOCKER_REGISTRY }}/${{ env.IMAGE_NAME }}:latest
+          labels: version=${{ github.run_id }}
+          platforms: linux/amd64,linux/arm64
+
+      # For tagged releases, build and push the Docker image with the corresponding tag
+      - name: Build and Push Docker Image (Tagged)
+        if: startsWith(github.ref, 'refs/tags/')
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          file: Dockerfile
+          push: true
+          tags: ${{ env.DOCKER_REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.ref_name }}
+          labels: version=${{ github.run_id }}
+          platforms: linux/amd64,linux/arm64
+
+  build-and-push-min-image:
+    runs-on: ubuntu-latest
+
+    permissions:
+      contents: read
+      packages: write
+
+    env:
+      # Set up environment variables for the job
+      DOCKER_REGISTRY: ghcr.io
+      IMAGE_NAME: ${{ github.repository }}-min
+      TAG: ${{ github.sha }}
+
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+        with:
+          install: true
+
+      # Log in to the GitHub Container Registry only when not running on a pull request event
+      - name: Login to Docker Registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.DOCKER_REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: ${{ env.DOCKER_REGISTRY }}/${{ env.IMAGE_NAME }}
+
+      # Build and push the Docker image to GHCR for the main branch or specific tags
+      - name: Build and Push Docker Image
+        if: github.ref == 'refs/heads/main'
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          file: Dockerfile.min
+          push: true
+          tags: ${{ env.DOCKER_REGISTRY }}/${{ env.IMAGE_NAME }}:latest
+          labels: version=${{ github.run_id }}
+          platforms: linux/amd64,linux/arm64
+
+      # For tagged releases, build and push the Docker image with the corresponding tag
+      - name: Build and Push Docker Image (Tagged)
+        if: startsWith(github.ref, 'refs/tags/')
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          file: Dockerfile.min
+          push: true
+          tags: ${{ env.DOCKER_REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.ref_name }}
+          labels: version=${{ github.run_id }}
+          platforms: linux/amd64,linux/arm64
+
+  build-and-push-rocm-image:
+    runs-on: ubuntu-latest
+
+    permissions:
+      contents: read
+      packages: write
+
+    env:
+      # Set up environment variables for the job
+      USE_ROCM: 1
+      DOCKER_REGISTRY: ghcr.io
+      IMAGE_NAME: ${{ github.repository }}-rocm
+      TAG: ${{ github.sha }}
+
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+        with:
+          install: true
+
+      # Log in to the GitHub Container Registry only when not running on a pull request event
+      - name: Login to Docker Registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.DOCKER_REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: ${{ env.DOCKER_REGISTRY }}/${{ env.IMAGE_NAME }}
+
+      # Build and push the Docker image to GHCR for the main branch or specific tags
+      - name: Build and Push Docker Image
+        if: github.ref == 'refs/heads/main'
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          file: Dockerfile
+          push: true
+          tags: ${{ env.DOCKER_REGISTRY }}/${{ env.IMAGE_NAME }}:latest
+          labels: version=${{ github.run_id }}
+          platforms: linux/amd64,linux/arm64
+          build-args: |
+            USE_ROCM=1
+
+      # For tagged releases, build and push the Docker image with the corresponding tag
+      - name: Build and Push Docker Image (Tagged)
+        if: startsWith(github.ref, 'refs/tags/')
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          file: Dockerfile
+          push: true
+          tags: ${{ env.DOCKER_REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.ref_name }}
+          labels: version=${{ github.run_id }}
+          platforms: linux/amd64,linux/arm64
+          build-args: |
+            USE_ROCM=1
+

.gitignore

@@ -0,0 +1,166 @@
+voices/
+.env
+speech.env
+config/pre_process_map.yaml
+config/voice_to_speaker.yaml
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

Dockerfile

@@ -0,0 +1,35 @@
+FROM python:3.11-slim
+
+RUN --mount=type=cache,target=/root/.cache/pip pip install -U pip
+
+ARG TARGETPLATFORM
+RUN apt-get update && apt-get install --no-install-recommends -y curl ffmpeg
+RUN if [ "$TARGETPLATFORM" != "linux/amd64" ]; then apt-get install --no-install-recommends -y build-essential ; fi
+RUN if [ "$TARGETPLATFORM" != "linux/amd64" ]; then curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y ; fi
+ENV PATH="/root/.cargo/bin:${PATH}"
+# for deepspeed support - doesn't seem worth it, image +7.5GB, over the 10GB ghcr.io limit, and no noticable gain in speed or VRAM usage?
+#RUN curl -O https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/cuda-keyring_1.1-1_all.deb
+#RUN dpkg -i cuda-keyring_1.1-1_all.deb && rm cuda-keyring_1.1-1_all.deb
+#RUN apt-get update && apt-get install --no-install-recommends -y libaio-dev build-essential cuda-toolkit
+#ENV CUDA_HOME=/usr/local/cuda
+RUN apt-get clean && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+RUN mkdir -p voices config
+
+ARG USE_ROCM
+ENV USE_ROCM=${USE_ROCM}
+
+COPY requirements*.txt /app/
+RUN if [ "${USE_ROCM}" = "1" ]; then mv /app/requirements-rocm.txt /app/requirements.txt; fi
+RUN --mount=type=cache,target=/root/.cache/pip pip install -r requirements.txt
+
+COPY *.py *.sh *.default.yaml README.md LICENSE /app/
+
+ARG PRELOAD_MODEL
+ENV PRELOAD_MODEL=${PRELOAD_MODEL}
+ENV TTS_HOME=voices
+ENV HF_HOME=voices
+ENV COQUI_TOS_AGREED=1
+
+CMD bash startup.sh

Dockerfile.min

@@ -0,0 +1,20 @@
+FROM python:3.11-slim
+
+ARG TARGETPLATFORM
+RUN apt-get update && apt-get install --no-install-recommends -y curl ffmpeg
+RUN if [ "$TARGETPLATFORM" != "linux/amd64" ]; then apt-get install --no-install-recommends -y build-essential ; fi
+RUN if [ "$TARGETPLATFORM" != "linux/amd64" ]; then curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y ; fi
+ENV PATH="/root/.cargo/bin:${PATH}"
+RUN apt-get clean && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+RUN mkdir -p voices config
+
+COPY requirements*.txt /app/
+RUN --mount=type=cache,target=/root/.cache/pip pip install -r requirements-min.txt
+COPY *.py *.sh *.default.yaml README.md LICENSE /app/
+
+ENV TTS_HOME=voices
+ENV HF_HOME=voices
+
+CMD bash startup.min.sh

LICENSE

@@ -0,0 +1,661 @@
+                    GNU AFFERO GENERAL PUBLIC LICENSE
+                       Version 3, 19 November 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+                            Preamble
+
+  The GNU Affero General Public License is a free, copyleft license for
+software and other kinds of works, specifically designed to ensure
+cooperation with the community in the case of network server software.
+
+  The licenses for most software and other practical works are designed
+to take away your freedom to share and change the works.  By contrast,
+our General Public Licenses are intended to guarantee your freedom to
+share and change all versions of a program--to make sure it remains free
+software for all its users.
+
+  When we speak of free software, we are referring to freedom, not
+price.  Our General Public Licenses are designed to make sure that you
+have the freedom to distribute copies of free software (and charge for
+them if you wish), that you receive source code or can get it if you
+want it, that you can change the software or use pieces of it in new
+free programs, and that you know you can do these things.
+
+  Developers that use our General Public Licenses protect your rights
+with two steps: (1) assert copyright on the software, and (2) offer
+you this License which gives you legal permission to copy, distribute
+and/or modify the software.
+
+  A secondary benefit of defending all users' freedom is that
+improvements made in alternate versions of the program, if they
+receive widespread use, become available for other developers to
+incorporate.  Many developers of free software are heartened and
+encouraged by the resulting cooperation.  However, in the case of
+software used on network servers, this result may fail to come about.
+The GNU General Public License permits making a modified version and
+letting the public access it on a server without ever releasing its
+source code to the public.
+
+  The GNU Affero General Public License is designed specifically to
+ensure that, in such cases, the modified source code becomes available
+to the community.  It requires the operator of a network server to
+provide the source code of the modified version running there to the
+users of that server.  Therefore, public use of a modified version, on
+a publicly accessible server, gives the public access to the source
+code of the modified version.
+
+  An older license, called the Affero General Public License and
+published by Affero, was designed to accomplish similar goals.  This is
+a different license, not a version of the Affero GPL, but Affero has
+released a new version of the Affero GPL which permits relicensing under
+this license.
+
+  The precise terms and conditions for copying, distribution and
+modification follow.
+
+                       TERMS AND CONDITIONS
+
+  0. Definitions.
+
+  "This License" refers to version 3 of the GNU Affero General Public License.
+
+  "Copyright" also means copyright-like laws that apply to other kinds of
+works, such as semiconductor masks.
+
+  "The Program" refers to any copyrightable work licensed under this
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+<https://www.gnu.org/licenses/>.

add_voice.py

@@ -0,0 +1,63 @@
+#!/usr/bin/env python
+
+import argparse
+import os
+import shutil
+import yaml
+
+print("!! WARNING EXPERIMENTAL !! - THIS TOOL WILL ERASE ALL COMMENTS FROM THE CONFIG FILES .. OR WORSE!!")
+
+parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+
+parser.add_argument('sample', action='store', help="Set the wav sample file")
+parser.add_argument('-n', '--name', action='store', help="Set the name for the voice (by default will use the WAV file name)")
+parser.add_argument('-l', '--language', action='store', default="auto", help="Set the language for the voice",
+                    choices=['auto', 'en', 'es', 'fr', 'de', 'it', 'pt', 'pl', 'tr', 'ru', 'nl', 'cs', 'ar', 'zh-cn', 'ja', 'hu', 'ko', 'hi'])
+parser.add_argument('--openai-model', action='store', default="tts-1-hd", help="Set the openai model for the voice")
+parser.add_argument('--xtts-model', action='store', default="xtts", help="Set the xtts model for the voice (if using a custom model, also set model_path)")
+parser.add_argument('--model-path', action='store', default=None, help="Set the path for a custom xtts model")
+parser.add_argument('--config-path', action='store', default="config/voice_to_speaker.yaml", help="Set the config file path")
+parser.add_argument('--voice-path', action='store', default="voices", help="Set the default voices file path")
+parser.add_argument('--default-path', action='store', default="voice_to_speaker.default.yaml", help="Set the default config file path")
+
+args = parser.parse_args()
+
+basename = os.path.basename(args.sample)
+name_noext, ext = os.path.splitext(basename)
+
+if not args.name:
+    args.name = name_noext
+else:
+    basename = f"{args.name}.wav"
+
+dest_file = os.path.join(args.voice_path, basename)
+if args.sample != dest_file:
+    shutil.copy2(args.sample, dest_file)
+
+if not os.path.exists(args.config_path):
+    shutil.copy2(args.default_path, args.config_path)
+
+with open(args.config_path, 'r', encoding='utf8') as file:
+    voice_map = yaml.safe_load(file)
+
+model_conf = voice_map.get(args.openai_model, {})
+model_conf[args.name] = {
+    'model': args.xtts_model,
+    'speaker': os.path.join(args.voice_path, basename),
+    'language': args.language,
+}
+if args.model_path:
+    model_conf[args.name]['model_path'] = args.model_path
+voice_map[args.openai_model] = model_conf
+
+with open(args.config_path, 'w', encoding='utf8') as ofile:
+    yaml.safe_dump(voice_map, ofile, default_flow_style=False, allow_unicode=True)
+
+print(f"Updated: {args.config_path}")
+print(f"Added voice: {args.openai_model}/{args.name}")
+print(f"Added section:")
+print(f"{args.openai_model}:")
+print(f"  {args.name}:")
+print(f"    model: {model_conf[args.name]['model']}")
+print(f"    speaker: {model_conf[args.name]['speaker']}")
+print(f"    language: {model_conf[args.name]['language']}")

audio_reader.py

@@ -0,0 +1,127 @@
+#!/usr/bin/env python3
+try:
+    import dotenv
+    dotenv.load_dotenv()
+except ImportError:
+    pass
+
+import argparse
+import os
+import pysbd
+import queue
+import sys
+import tempfile
+import threading
+import shutil
+import sys
+import tempfile
+import contextlib
+
+import openai
+
+try:
+    from playsound import playsound
+except ImportError:
+    print("Error: missing required package 'playsound'. !pip install playsound")
+    sys.exit(1)
+
+@contextlib.contextmanager
+def tempdir():
+    path = tempfile.mkdtemp()
+    try:
+        yield path
+    finally:
+        try:
+            shutil.rmtree(path)
+        except IOError:
+            sys.stderr.write('Failed to clean up temp dir {}'.format(path))
+
+class SimpleAudioPlayer:
+    def __init__(self):
+        self._queue = queue.Queue()
+        self.running = True
+        self._thread = threading.Thread(target=self.__play_audio_loop, daemon=True)
+        self._thread.start()
+
+    def put(self, file):
+        self._queue.put(file)
+
+    def stop(self):
+        self.running = False
+        self._thread.join()
+        try:
+            while True:
+                file = self._queue.get_nowait()
+                if os.path.exists(file):
+                    os.unlink(file)
+        except queue.Empty as e:
+            pass
+
+    def __play_audio_loop(self):
+        while self.running:
+            try:
+                while True:
+                    file = self._queue.get(block=True, timeout=0.01)
+
+                    try:
+                        playsound(file)
+                    finally:
+                        os.unlink(file)
+
+            except queue.Empty as e:
+                continue
+
+class OpenAI_tts:
+    def __init__(self, model, voice, speed, base_dir):
+        self.base_dir = base_dir
+        self.openai_client = openai.OpenAI(
+            # export OPENAI_API_KEY=sk-11111111111
+            # export OPENAI_BASE_URL=http://localhost:8000/v1
+            api_key = os.environ.get("OPENAI_API_KEY", "sk-ip"),
+            base_url = os.environ.get("OPENAI_BASE_URL", "http://localhost:8000/v1"),
+        )
+        
+        self.params = {
+            'model': model,
+            'voice': voice,
+            'speed': speed
+        }
+
+    def speech_to_file(self, text: str) -> None:
+        with self.openai_client.audio.speech.with_streaming_response.create(
+                input=text, response_format='opus', **self.params
+            ) as response:
+            tf, output_filename = tempfile.mkstemp(suffix='.wav', prefix="audio_reader_", dir=self.base_dir)
+            response.stream_to_file(output_filename)
+            return output_filename
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description='Text to speech player',
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+
+    parser.add_argument('-m', '--model', action='store', default="tts-1", help="The OpenAI model")
+    parser.add_argument('-v', '--voice', action='store', default="alloy", help="The voice to use")
+    parser.add_argument('-s', '--speed', action='store', default=1.0, help="How fast to read the audio")
+
+    args = parser.parse_args()
+
+    try:
+        with tempdir() as base_dir:
+            player = SimpleAudioPlayer()
+            reader = OpenAI_tts(voice=args.voice, model=args.model, speed=args.speed, base_dir=base_dir)
+            seg = pysbd.Segmenter(language='en', clean=True) # text is dirty, clean it up.
+
+            for raw_line in sys.stdin:
+                for line in seg.segment(raw_line):
+                    if not line:
+                        continue
+
+                    print(line)
+                    player.put(reader.speech_to_file(line))
+
+            player.stop()
+
+    except KeyboardInterrupt:
+        pass

docker-compose.min.yml

@@ -0,0 +1,13 @@
+services:
+  server:
+    build:
+      dockerfile: Dockerfile.min # piper for all models, no gpu/nvidia required, ~1GB
+    image: ghcr.io/matatonic/openedai-speech-min
+    env_file: speech.env
+    ports:
+      - "8000:8000"
+    volumes:
+      - ./voices:/app/voices
+      - ./config:/app/config
+    # To install as a service
+    restart: unless-stopped

docker-compose.rocm.yml

@@ -0,0 +1,27 @@
+services:
+  server:
+    build:
+      dockerfile: Dockerfile
+      args:
+        - USE_ROCM=1
+    image: ghcr.io/matatonic/openedai-speech-rocm
+    env_file: speech.env
+    ports:
+      - "8000:8000"
+    volumes:
+      - ./voices:/app/voices
+      - ./config:/app/config
+    # To install as a service
+    restart: unless-stopped
+    # For AMD GPU (ROCm) Support
+    cap_add:
+      - SYS_PTRACE
+    devices:
+      - /dev/kfd
+      - /dev/dri
+    security_opt:
+      - seccomp=unconfined
+    group_add:
+      - video
+      - audio
+    ipc: host

docker-compose.yml

@@ -0,0 +1,21 @@
+services:
+  server:
+    build:
+      dockerfile: Dockerfile
+    image: ghcr.io/matatonic/openedai-speech
+    env_file: speech.env
+    ports:
+      - "8000:8000"
+    volumes:
+      - ./voices:/app/voices
+      - ./config:/app/config
+    # To install as a service
+    restart: unless-stopped
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              #device_ids: ['0', '1'] # Select a gpu, or
+              count: all
+              capabilities: [gpu]

download_samples.bat

@@ -0,0 +1,6 @@
+@echo off
+for %%i in (alloy echo fable onyx nova shimmer) do (
+    if not exist "voices\%%i.wav" (
+        curl -s https://cdn.openai.com/API/docs/audio/%%i.wav | ffmpeg -loglevel error -i - -ar 22050 -ac 1 voices\%%i.wav
+    )
+)

download_samples.sh

@@ -0,0 +1,4 @@
+#!/bin/sh
+for i in alloy echo fable onyx nova shimmer; do
+	[ ! -e "voices/$i.wav" ] && curl -s https://cdn.openai.com/API/docs/audio/$i.wav | ffmpeg -loglevel error -i - -ar 22050 -ac 1 voices/$i.wav
+done

download_voices_tts-1-hd.bat

@@ -0,0 +1,8 @@
+@echo off
+set COQUI_TOS_AGREED=1
+set TTS_HOME=voices
+
+for %%i in (%*) do (
+    python -c "from TTS.utils.manage import ModelManager; ModelManager().download_model('%%i')"
+)
+call download_samples.bat

download_voices_tts-1-hd.sh

@@ -0,0 +1,8 @@
+#!/bin/sh
+export COQUI_TOS_AGREED=1
+export TTS_HOME=voices
+
+for model in $*; do
+	python -c "from TTS.utils.manage import ModelManager; ModelManager().download_model('$model')"
+done
+./download_samples.sh

download_voices_tts-1.bat

@@ -0,0 +1,8 @@
+@echo off
+set models=%* 
+if "%models%" == "" set models=en_GB-northern_english_male-medium en_US-libritts_r-medium
+
+piper --update-voices --data-dir voices --download-dir voices --model x 2> nul
+for %%i in (%models%) do (
+    if not exist "voices\%%i.onnx" piper --data-dir voices --download-dir voices --model %%i > nul
+)

download_voices_tts-1.sh

@@ -0,0 +1,6 @@
+#!/bin/sh
+models=${*:-"en_GB-northern_english_male-medium en_US-libritts_r-medium"} # en_US-ryan-high
+piper --update-voices --data-dir voices --download-dir voices --model x 2> /dev/null
+for i in $models ; do
+    [ ! -e "voices/$i.onnx" ] && piper --data-dir voices --download-dir voices --model $i < /dev/null > /dev/null
+done

openedai.py

@@ -0,0 +1,181 @@
+from fastapi import FastAPI, Request
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import PlainTextResponse, JSONResponse
+from loguru import logger
+
+class OpenAIError(Exception):
+    pass
+
+class APIError(OpenAIError):
+    message: str
+    code: str = None
+    param: str = None
+    type: str = None
+
+    def __init__(self, message: str, code: int = 500, param: str = None, internal_message: str = ''):
+        super().__init__(message)
+        self.message = message
+        self.code = code
+        self.param = param
+        self.type = self.__class__.__name__,
+        self.internal_message = internal_message
+
+    def __repr__(self):
+        return "%s(message=%r, code=%d, param=%s)" % (
+            self.__class__.__name__,
+            self.message,
+            self.code,
+            self.param,
+        )
+
+class InternalServerError(APIError):
+    pass
+
+class ServiceUnavailableError(APIError):
+    def __init__(self, message="Service unavailable, please try again later.", code=503, internal_message=''):
+        super().__init__(message, code, internal_message)
+
+class APIStatusError(APIError):
+    status_code: int = 400
+    
+    def __init__(self, message: str, param: str = None, internal_message: str = ''):
+        super().__init__(message, self.status_code, param, internal_message)
+
+class BadRequestError(APIStatusError):
+    status_code: int = 400
+
+class AuthenticationError(APIStatusError):
+    status_code: int = 401
+
+class PermissionDeniedError(APIStatusError):
+    status_code: int = 403
+
+class NotFoundError(APIStatusError):
+    status_code: int = 404
+
+class ConflictError(APIStatusError):
+    status_code: int = 409
+
+class UnprocessableEntityError(APIStatusError):
+    status_code: int = 422
+
+class RateLimitError(APIStatusError):
+    status_code: int = 429
+
+class OpenAIStub(FastAPI):
+    def __init__(self, **kwargs) -> None:
+        super().__init__(**kwargs)
+        self.models = {}
+
+        self.add_middleware(
+            CORSMiddleware,
+            allow_origins=["*"],
+            allow_credentials=True,
+            allow_methods=["*"],
+            allow_headers=["*"]
+        )
+
+        @self.exception_handler(Exception)
+        def openai_exception_handler(request: Request, exc: Exception) -> JSONResponse:
+            # Generic server errors
+            #logger.opt(exception=exc).error("Logging exception traceback")
+
+            return JSONResponse(status_code=500, content={
+                'message': 'InternalServerError',
+                'code': 500,
+            })
+
+        @self.exception_handler(APIError)
+        def openai_apierror_handler(request: Request, exc: APIError) -> JSONResponse:
+            # Server error
+            logger.opt(exception=exc).error("Logging exception traceback")
+
+            if exc.internal_message:
+                logger.info(exc.internal_message)
+
+            return JSONResponse(status_code = exc.code, content={
+                'message': exc.message,
+                'code': exc.code,
+                'type': exc.__class__.__name__,
+                'param': exc.param,
+            })
+
+        @self.exception_handler(APIStatusError)
+        def openai_statuserror_handler(request: Request, exc: APIStatusError) -> JSONResponse:
+            # Client side error
+            logger.info(repr(exc))
+
+            if exc.internal_message:
+                logger.info(exc.internal_message)
+
+            return JSONResponse(status_code = exc.code, content={
+                'message': exc.message,
+                'code': exc.code,
+                'type': exc.__class__.__name__,
+                'param': exc.param,
+            })
+
+        @self.middleware("http")
+        async def log_requests(request: Request, call_next):
+            logger.debug(f"Request path: {request.url.path}")
+            logger.debug(f"Request method: {request.method}")
+            logger.debug(f"Request headers: {request.headers}")
+            logger.debug(f"Request query params: {request.query_params}")
+            logger.debug(f"Request body: {await request.body()}")
+
+            response = await call_next(request)
+
+            logger.debug(f"Response status code: {response.status_code}")
+            logger.debug(f"Response headers: {response.headers}")
+
+            return response
+
+        @self.get('/v1/billing/usage')
+        @self.get('/v1/dashboard/billing/usage')
+        async def handle_billing_usage():
+            return { 'total_usage': 0 }
+
+        @self.get("/", response_class=PlainTextResponse)
+        @self.head("/", response_class=PlainTextResponse)
+        @self.options("/", response_class=PlainTextResponse)
+        async def root():
+            return PlainTextResponse(content="", status_code=200 if self.models else 503)
+
+        @self.get("/health")
+        async def health():
+            return {"status": "ok" if self.models else "unk" }
+
+        @self.get("/v1/models")
+        async def get_model_list():
+            return self.model_list()
+
+        @self.get("/v1/models/{model}")
+        async def get_model_info(model_id: str):
+            return self.model_info(model_id)
+
+    def register_model(self, name: str, model: str = None) -> None:
+        self.models[name] = model if model else name
+
+    def deregister_model(self, name: str) -> None:
+        if name in self.models:
+            del self.models[name]
+
+    def model_info(self, model: str) -> dict:
+        result = {
+            "id": model,
+            "object": "model",
+            "created": 0,
+            "owned_by": "user"
+        }
+        return result
+
+    def model_list(self) -> dict:
+        if not self.models:
+            return {}
+        
+        result = {
+            "object": "list",
+            "data": [ self.model_info(model) for model in list(set(self.models.keys() | self.models.values())) if model ]
+        }
+
+        return result

pre_process_map.default.yaml

@@ -0,0 +1,37 @@
+# regex pairs to clean the text before speaking
+- - ([^.])\.$
+  - \1
+- - '&'
+  - '&'
+- - '<'
+  - <
+- - '&gt;'
+  - '>'
+- - '&quot;'
+  - '"'
+- - '&#x27;'
+  - ''''
+- - '&copy;'
+  - '©'
+- - '&reg;'
+  - '®'
+- - '&nbsp;'
+  - ' '
+- - '"'
+  - ''
+- - ' biases '
+  - ' bias''s '
+- - ex\.
+  - for example
+- - e\.g\.
+  - for example
+- - ' ESG '
+  - ' E.S.G. '
+- - ' FY '
+  - ' F.Y. '
+- - ([0-9]+)-([0-9]+)
+  - \1 to \2
+- - '\*\*\*'
+  - '*'
+- - '\*\*'
+  - '*'

requirements-min.txt

@@ -0,0 +1,5 @@
+fastapi
+uvicorn
+loguru
+numpy<2
+piper-tts

requirements-rocm.txt

@@ -0,0 +1,10 @@
+fastapi
+uvicorn
+loguru
+piper-tts
+coqui-tts
+langdetect
+# Creating an environment where deepspeed works is complex, for now it will be disabled by default.
+#deepspeed
+torch; --index-url https://download.pytorch.org/whl/rocm5.7; sys_platform == "linux"
+torchaudio; --index-url https://download.pytorch.org/whl/rocm5.7; sys_platform == "linux"

requirements.txt

@@ -0,0 +1,16 @@
+fastapi
+uvicorn
+loguru
+piper-tts
+coqui-tts[languages]
+langdetect
+# Creating an environment where deepspeed works is complex, for now it will be disabled by default.
+#deepspeed
+
+torch; sys_platform != "darwin"
+torchaudio; sys_platform != "darwin"
+# for MPS accelerated torch on Mac - doesn't work yet, incomplete support in torch and torchaudio
+torch; --index-url https://download.pytorch.org/whl/cpu; sys_platform == "darwin"
+torchaudio; --index-url https://download.pytorch.org/whl/cpu; sys_platform == "darwin"
+
+# ROCM (Linux only) - use requirements.amd.txt

sample.env

@@ -0,0 +1,6 @@
+TTS_HOME=voices
+HF_HOME=voices
+#PRELOAD_MODEL=xtts
+#PRELOAD_MODEL=xtts_v2.0.2
+#EXTRA_ARGS=--log-level DEBUG --unload-timer 300
+#USE_ROCM=1

say.py

@@ -0,0 +1,96 @@
+#!/usr/bin/env python
+
+import sys
+import os
+import atexit
+import tempfile
+import argparse
+
+try:
+    import dotenv
+    dotenv.load_dotenv(override=True)
+except ImportError:
+    pass
+
+try:
+    from playsound import playsound
+except ImportError:
+    playsound = None
+
+import openai
+
+
+def parse_args(argv):
+    parser = argparse.ArgumentParser(
+        description='Text to speech using the OpenAI API',
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+    )
+    parser.add_argument("-m", "--model", type=str, default="tts-1", help="The model to use")#, choices=["tts-1", "tts-1-hd"])
+    parser.add_argument("-v", "--voice", type=str, default="alloy", help="The voice of the speaker")#, choices=["alloy", "echo", "fable", "onyx", "nova", "shimmer"])
+    parser.add_argument("-f", "--format", type=str, default="mp3", choices=["mp3", "aac", "opus", "flac"], help="The output audio format")
+    parser.add_argument("-s", "--speed", type=float, default=1.0, help="playback speed, 0.25-4.0")
+    parser.add_argument("-t", "--text", type=str, default=None, help="Provide text to read on the command line")
+    parser.add_argument("-i", "--input", type=str, default=None, help="Read text from a file (default is to read from stdin)")
+    
+    if playsound is None:
+        parser.add_argument("-o", "--output", type=str, help="The filename to save the output to") # required
+        parser.add_argument("-p", "--playsound", type=None, default=None, help="python playsound not found. pip install playsound")
+    else:
+        parser.add_argument("-o", "--output", type=str, default=None, help="The filename to save the output to") # not required
+        parser.add_argument("-p", "--playsound", action="store_true", help="Play the audio")
+
+    args = parser.parse_args(argv)
+
+    return args
+
+
+if __name__ == "__main__":
+    args = parse_args(sys.argv[1:])
+
+    if args.playsound and playsound is None:
+        print("playsound module not found, audio will not be played, use -o <filename> to save output to a file. pip install playsound")
+        sys.exit(1)
+
+    if not args.playsound and not args.output:
+        print("Must select one of playsound (-p) or output file name (-o)")
+        sys.exit(1)
+
+    if args.input is None and args.text is None:
+        text = sys.stdin.read()
+    elif args.text:
+        text = args.text
+    elif args.input:
+        if os.path.exists(args.input):
+            with open(args.input, 'r') as f:
+                text = f.read()
+        else:
+            print(f"Warning! File not found: {args.input}\nFalling back to old behavior for -i")
+            text = args.input
+
+    client = openai.OpenAI(
+        # This part is not needed if you set these environment variables before import openai
+        # export OPENAI_API_KEY=sk-11111111111
+        # export OPENAI_BASE_URL=http://localhost:8000/v1
+        api_key = os.environ.get("OPENAI_API_KEY", "sk-ip"),
+        base_url = os.environ.get("OPENAI_BASE_URL", "http://localhost:8000/v1"),
+    )
+
+    if args.playsound and args.output is None:
+        _, args.output = tempfile.mkstemp(suffix='.wav')
+        
+        def cleanup():
+            os.unlink(args.output)
+
+        atexit.register(cleanup)
+
+    with client.audio.speech.with_streaming_response.create(
+        model=args.model,
+        voice=args.voice,
+        speed=args.speed,
+        response_format=args.format,
+        input=text,
+    ) as response:
+        response.stream_to_file(args.output)
+
+        if args.playsound:
+            playsound(args.output)

speech.py

@@ -0,0 +1,415 @@
+#!/usr/bin/env python3
+import argparse
+import contextlib
+import gc
+import os
+import queue
+import re
+import subprocess
+import sys
+import threading
+import time
+import yaml
+
+from fastapi.responses import StreamingResponse
+from loguru import logger
+from openedai import OpenAIStub, BadRequestError, ServiceUnavailableError
+from pydantic import BaseModel
+import uvicorn
+
+@contextlib.asynccontextmanager
+async def lifespan(app):
+    yield
+    gc.collect()
+    try:
+        import torch
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+            torch.cuda.ipc_collect()
+    except:
+        pass
+
+app = OpenAIStub(lifespan=lifespan)
+xtts = None
+args = None
+
+def unload_model():
+    import torch, gc
+    global xtts
+    if xtts:
+        logger.info("Unloading model")
+        xtts.xtts.to('cpu') # this was required to free up GPU memory... 
+        del xtts
+        xtts = None
+        gc.collect()
+        torch.cuda.empty_cache()
+        torch.cuda.ipc_collect()
+
+class xtts_wrapper():
+    check_interval: int = 1 # too aggressive?
+
+    def __init__(self, model_name, device, model_path=None, unload_timer=None):
+        self.model_name = model_name
+        self.unload_timer = unload_timer
+        self.last_used = time.time()
+        self.timer = None
+        self.lock = threading.Lock()
+
+        logger.info(f"Loading model {self.model_name} to {device}")
+
+        if model_path is None:
+            model_path = ModelManager().download_model(model_name)[0]
+
+        config_path = os.path.join(model_path, 'config.json')
+        config = XttsConfig()
+        config.load_json(config_path)
+        self.xtts = Xtts.init_from_config(config)
+        self.xtts.load_checkpoint(config, checkpoint_dir=model_path, use_deepspeed=args.use_deepspeed)  # XXX there are no prebuilt deepspeed wheels??
+        self.xtts = self.xtts.to(device=device)
+        self.xtts.eval()
+
+        if self.unload_timer:
+            logger.info(f"Setting unload timer to {self.unload_timer} seconds")
+            self.last_used = time.time()
+            self.check_idle()
+
+    def check_idle(self):
+        with self.lock:
+            if time.time() - self.last_used >= self.unload_timer:
+                print("Unloading TTS model due to inactivity")
+                unload_model()
+            else:
+                # Reschedule the check
+                self.timer = threading.Timer(self.check_interval, self.check_idle)
+                self.timer.daemon = True
+                self.timer.start()
+
+    def tts(self, text, language, speaker_wav, **hf_generate_kwargs):
+        with torch.no_grad():
+            self.last_used = time.time()
+            tokens = 0
+            try:
+                with self.lock:
+                    gpt_cond_latent, speaker_embedding = self.xtts.get_conditioning_latents(audio_path=[speaker_wav]) # not worth caching calls, it's < 0.001s after model is loaded
+                    pcm_stream = self.xtts.inference_stream(text, language, gpt_cond_latent, speaker_embedding, **hf_generate_kwargs)
+                    self.last_used = time.time()
+
+                while True:
+                    with self.lock:
+                        yield next(pcm_stream).cpu().numpy().tobytes()
+                        self.last_used = time.time()
+                    tokens += 1
+
+            except StopIteration:
+                pass
+
+            finally:
+                logger.debug(f"Generated {tokens} tokens in {time.time() - self.last_used:.2f}s @ {tokens / (time.time() - self.last_used):.2f} T/s")
+                self.last_used = time.time()
+
+def default_exists(filename: str):
+    if not os.path.exists(filename):
+        fpath, ext = os.path.splitext(filename)
+        basename = os.path.basename(fpath)
+        default = f"{basename}.default{ext}"
+        
+        logger.info(f"{filename} does not exist, setting defaults from {default}")
+
+        with open(default, 'r', encoding='utf8') as from_file:
+            with open(filename, 'w', encoding='utf8') as to_file:
+                to_file.write(from_file.read())
+
+# Read pre process map on demand so it can be changed without restarting the server
+def preprocess(raw_input):
+    #logger.debug(f"preprocess: before: {[raw_input]}")
+    default_exists('config/pre_process_map.yaml')
+    with open('config/pre_process_map.yaml', 'r', encoding='utf8') as file:
+        pre_process_map = yaml.safe_load(file)
+        for a, b in pre_process_map:
+            raw_input = re.sub(a, b, raw_input)
+    
+    raw_input = raw_input.strip()
+    #logger.debug(f"preprocess: after: {[raw_input]}")
+    return raw_input
+
+# Read voice map on demand so it can be changed without restarting the server
+def map_voice_to_speaker(voice: str, model: str):
+    default_exists('config/voice_to_speaker.yaml')
+    with open('config/voice_to_speaker.yaml', 'r', encoding='utf8') as file:
+        voice_map = yaml.safe_load(file)
+        try:
+            return voice_map[model][voice]
+
+        except KeyError as e:
+            raise BadRequestError(f"Error loading voice: {voice}, KeyError: {e}", param='voice')
+
+class GenerateSpeechRequest(BaseModel):
+    model: str = "tts-1" # or "tts-1-hd"
+    input: str
+    voice: str = "alloy"  # alloy, echo, fable, onyx, nova, and shimmer
+    response_format: str = "mp3" # mp3, opus, aac, flac
+    speed: float = 1.0 # 0.25 - 4.0
+
+def build_ffmpeg_args(response_format, input_format, sample_rate):
+    # Convert the output to the desired format using ffmpeg
+    if input_format == 'WAV':
+        ffmpeg_args = ["ffmpeg", "-loglevel", "error", "-f", "WAV", "-i", "-"]
+    else:
+        ffmpeg_args = ["ffmpeg", "-loglevel", "error", "-f", input_format, "-ar", sample_rate, "-ac", "1", "-i", "-"]
+    
+    if response_format == "mp3":
+        ffmpeg_args.extend(["-f", "mp3", "-c:a", "libmp3lame", "-ab", "64k"])
+    elif response_format == "opus":
+        ffmpeg_args.extend(["-f", "ogg", "-c:a", "libopus"])
+    elif response_format == "aac":
+        ffmpeg_args.extend(["-f", "adts", "-c:a", "aac", "-ab", "64k"])
+    elif response_format == "flac":
+        ffmpeg_args.extend(["-f", "flac", "-c:a", "flac"])
+    elif response_format == "wav":
+        ffmpeg_args.extend(["-f", "wav", "-c:a", "pcm_s16le"])
+    elif response_format == "pcm": # even though pcm is technically 'raw', we still use ffmpeg to adjust the speed
+        ffmpeg_args.extend(["-f", "s16le", "-c:a", "pcm_s16le"])
+
+    return ffmpeg_args
+
+@app.post("/v1/audio/speech", response_class=StreamingResponse)
+async def generate_speech(request: GenerateSpeechRequest):
+    global xtts, args
+    if len(request.input) < 1:
+        raise BadRequestError("Empty Input", param='input')
+
+    input_text = preprocess(request.input)
+
+    if len(input_text) < 1:
+        raise BadRequestError("Input text empty after preprocess.", param='input')
+
+    model = request.model
+    voice = request.voice
+    response_format = request.response_format.lower()
+    speed = request.speed
+
+    # Set the Content-Type header based on the requested format
+    if response_format == "mp3":
+        media_type = "audio/mpeg"
+    elif response_format == "opus":
+        media_type = "audio/ogg;codec=opus" # codecs?
+    elif response_format == "aac":
+        media_type = "audio/aac"
+    elif response_format == "flac":
+        media_type = "audio/x-flac"
+    elif response_format == "wav":
+        media_type = "audio/wav"
+    elif response_format == "pcm":
+        if model == 'tts-1': # piper
+            media_type = "audio/pcm;rate=22050"
+        elif model == 'tts-1-hd': # xtts
+            media_type = "audio/pcm;rate=24000"
+    else:
+        raise BadRequestError(f"Invalid response_format: '{response_format}'", param='response_format')
+
+    ffmpeg_args = None
+
+    # Use piper for tts-1, and if xtts_device == none use for all models.
+    if model == 'tts-1' or args.xtts_device == 'none':
+        voice_map = map_voice_to_speaker(voice, 'tts-1')
+        try:
+            piper_model = voice_map['model']
+
+        except KeyError as e:
+            raise ServiceUnavailableError(f"Configuration error: tts-1 voice '{voice}' is missing 'model:' setting. KeyError: {e}")
+
+        speaker = voice_map.get('speaker', None)
+
+        tts_args = ["piper", "--model", str(piper_model), "--data-dir", "voices", "--download-dir", "voices", "--output-raw"]
+        if speaker:
+            tts_args.extend(["--speaker", str(speaker)])
+        if speed != 1.0:
+            tts_args.extend(["--length-scale", f"{1.0/speed}"])
+
+        tts_proc = subprocess.Popen(tts_args, stdin=subprocess.PIPE, stdout=subprocess.PIPE)
+        tts_proc.stdin.write(bytearray(input_text.encode('utf-8')))
+        tts_proc.stdin.close()
+
+        ffmpeg_args = build_ffmpeg_args(response_format, input_format="s16le", sample_rate="22050")
+
+        # Pipe the output from piper/xtts to the input of ffmpeg
+        ffmpeg_args.extend(["-"])
+        ffmpeg_proc = subprocess.Popen(ffmpeg_args, stdin=tts_proc.stdout, stdout=subprocess.PIPE)
+
+        return StreamingResponse(content=ffmpeg_proc.stdout, media_type=media_type)
+    # Use xtts for tts-1-hd
+    elif model == 'tts-1-hd':
+        voice_map = map_voice_to_speaker(voice, 'tts-1-hd')
+        try:
+            tts_model = voice_map.pop('model')
+            speaker = voice_map.pop('speaker')
+
+        except KeyError as e:
+            raise ServiceUnavailableError(f"Configuration error: tts-1-hd voice '{voice}' is missing setting. KeyError: {e}")
+
+        if xtts and xtts.model_name != tts_model:
+            unload_model()
+
+        tts_model_path = voice_map.pop('model_path', None) # XXX changing this on the fly is ignored if you keep the same name
+
+        if xtts is None:
+            xtts = xtts_wrapper(tts_model, device=args.xtts_device, model_path=tts_model_path, unload_timer=args.unload_timer)
+
+        ffmpeg_args = build_ffmpeg_args(response_format, input_format="f32le", sample_rate="24000")
+
+        # tts speed doesn't seem to work well
+        speed = voice_map.pop('speed', speed)
+        if speed < 0.5:
+            speed = speed / 0.5
+            ffmpeg_args.extend(["-af", "atempo=0.5"]) 
+        if speed > 1.0:
+            ffmpeg_args.extend(["-af", f"atempo={speed}"]) 
+            speed = 1.0
+
+        # Pipe the output from piper/xtts to the input of ffmpeg
+        ffmpeg_args.extend(["-"])
+
+        language = voice_map.pop('language', 'auto')
+        if language == 'auto':
+            try:
+                language = detect(input_text)
+                if language not in [
+                    'en', 'es', 'fr', 'de', 'it', 'pt', 'pl', 'tr',
+                    'ru', 'nl', 'cs', 'ar', 'zh-cn', 'hu', 'ko', 'ja', 'hi'
+                ]:
+                    logger.debug(f"Detected language {language} not supported, defaulting to en")
+                    language = 'en'
+                else:
+                    logger.debug(f"Detected language: {language}")
+            except:
+                language = 'en'
+                logger.debug(f"Failed to detect language, defaulting to en")
+
+        comment = voice_map.pop('comment', None) # ignored.
+
+        hf_generate_kwargs = dict(
+            speed=speed,
+            **voice_map,
+        )
+
+        hf_generate_kwargs['enable_text_splitting'] = hf_generate_kwargs.get('enable_text_splitting', True) # change the default to true
+
+        if hf_generate_kwargs['enable_text_splitting']:
+            if language == 'zh-cn':
+                split_lang = 'zh'
+            else:
+                split_lang = language
+            all_text = split_sentence(input_text, split_lang, xtts.xtts.tokenizer.char_limits[split_lang])
+        else:
+            all_text = [input_text]
+
+        ffmpeg_proc = subprocess.Popen(ffmpeg_args, stdin=subprocess.PIPE, stdout=subprocess.PIPE)
+
+        in_q = queue.Queue() # speech pcm 
+        ex_q = queue.Queue() # exceptions
+
+        def exception_check(exq: queue.Queue):
+            try:
+                e = exq.get_nowait()
+            except queue.Empty:
+                return
+            
+            raise e
+
+        def generator():
+            # text -> in_q
+            try:
+                for text in all_text:
+                    for chunk in xtts.tts(text=text, language=language, speaker_wav=speaker, **hf_generate_kwargs):
+                        exception_check(ex_q)
+                        in_q.put(chunk)
+
+            except BrokenPipeError as e: # client disconnect lands here
+                logger.info("Client disconnected - 'Broken pipe'")
+
+            except Exception as e:
+                logger.error(f"Exception: {repr(e)}")
+                raise e
+        
+            finally:
+                in_q.put(None) # sentinel
+
+        def out_writer(): 
+            # in_q -> ffmpeg
+            try:
+                while True:
+                    chunk = in_q.get()
+                    if chunk is None: # sentinel
+                        break
+                    ffmpeg_proc.stdin.write(chunk) # BrokenPipeError from here on client disconnect
+
+            except Exception as e: # BrokenPipeError
+                ex_q.put(e)  # we need to get this exception into the generation loop
+                ffmpeg_proc.kill()
+                return
+            
+            finally:
+                ffmpeg_proc.stdin.close()
+
+        generator_worker = threading.Thread(target=generator, daemon=True)
+        generator_worker.start()
+
+        out_writer_worker = threading.Thread(target=out_writer, daemon=True)
+        out_writer_worker.start()
+
+        def cleanup():
+            ffmpeg_proc.kill()
+            del generator_worker
+            del out_writer_worker
+
+        return StreamingResponse(content=ffmpeg_proc.stdout, media_type=media_type, background=cleanup)
+    else:
+        raise BadRequestError("No such model, must be tts-1 or tts-1-hd.", param='model')
+
+
+# We return 'mps' but currently XTTS will not work with mps devices as the cuda support is incomplete
+def auto_torch_device():
+    try:
+        import torch
+        return 'cuda' if torch.cuda.is_available() else 'mps' if ( torch.backends.mps.is_available() and torch.backends.mps.is_built() ) else 'cpu'
+    
+    except:
+        return 'none'
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description='OpenedAI Speech API Server',
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+
+    parser.add_argument('--xtts_device', action='store', default=auto_torch_device(), help="Set the device for the xtts model. The special value of 'none' will use piper for all models.")
+    parser.add_argument('--preload', action='store', default=None, help="Preload a model (Ex. 'xtts' or 'xtts_v2.0.2'). By default it's loaded on first use.")
+    parser.add_argument('--unload-timer', action='store', default=None, type=int, help="Idle unload timer for the XTTS model in seconds, Ex. 900 for 15 minutes")
+    parser.add_argument('--use-deepspeed', action='store_true', default=False, help="Use deepspeed with xtts (this option is unsupported)")
+    parser.add_argument('--no-cache-speaker', action='store_true', default=False, help="Don't use the speaker wav embeddings cache")
+    parser.add_argument('-P', '--port', action='store', default=8000, type=int, help="Server tcp port")
+    parser.add_argument('-H', '--host', action='store', default='0.0.0.0', help="Host to listen on, Ex. 0.0.0.0")
+    parser.add_argument('-L', '--log-level', default="INFO", choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"], help="Set the log level")
+
+    args = parser.parse_args()
+
+    default_exists('config/pre_process_map.yaml')
+    default_exists('config/voice_to_speaker.yaml')
+
+    logger.remove()
+    logger.add(sink=sys.stderr, level=args.log_level)
+
+    if args.xtts_device != "none":
+        import torch
+        from TTS.tts.configs.xtts_config import XttsConfig
+        from TTS.tts.models.xtts import Xtts
+        from TTS.utils.manage import ModelManager
+        from TTS.tts.layers.xtts.tokenizer import split_sentence
+        from langdetect import detect
+
+    if args.preload:
+        xtts = xtts_wrapper(args.preload, device=args.xtts_device, unload_timer=args.unload_timer)
+
+    app.register_model('tts-1')
+    app.register_model('tts-1-hd')
+
+    uvicorn.run(app, host=args.host, port=args.port)

startup.bat

@@ -0,0 +1,8 @@
+@echo off
+
+set /p < speech.env
+
+call download_voices_tts-1.bat
+call download_voices_tts-1-hd.bat %PRELOAD_MODEL%
+
+python speech.py %PRELOAD_MODEL:+--preload %PRELOAD_MODEL% %EXTRA_ARGS%

startup.min.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+
+[ -f speech.env ] && . speech.env
+
+bash download_voices_tts-1.sh
+
+python speech.py --xtts_device none $EXTRA_ARGS $@

startup.sh

@@ -0,0 +1,10 @@
+#!/bin/bash
+
+[ -f speech.env ] && . speech.env
+
+echo "First startup may download 2GB of speech models. Please wait."
+
+bash download_voices_tts-1.sh
+bash download_voices_tts-1-hd.sh $PRELOAD_MODEL
+
+python speech.py ${PRELOAD_MODEL:+--preload $PRELOAD_MODEL} $EXTRA_ARGS $@

test_voices.sh

@@ -0,0 +1,67 @@
+#!/bin/bash
+
+URL=${1:-http://localhost:8000/v1/audio/speech}
+
+curl -s $URL -H "Content-Type: application/json" -d "{
+    \"model\": \"tts-1\",
+    \"input\": \"I'm going to play you the original voice, followed by the piper voice and finally the X T T S version 2 voice\",
+    \"voice\": \"echo\",
+    \"speed\": 1.0
+  }" | mpv --really-quiet -
+
+for voice in alloy echo fable onyx nova shimmer ; do
+
+echo $voice
+
+curl -s $URL -H "Content-Type: application/json" -d "{
+    \"model\": \"tts-1\",
+    \"input\": \"original\",
+    \"voice\": \"echo\",
+    \"speed\": 1.0
+  }" | mpv --really-quiet -
+
+curl -s https://cdn.openai.com/API/docs/audio/$voice.wav | mpv --really-quiet -
+
+curl -s $URL -H "Content-Type: application/json" -d "{
+    \"model\": \"tts-1\",
+    \"input\": \"The quick brown fox jumped over the lazy dog. This voice is called $voice, how do you like this voice?\",
+    \"voice\": \"$voice\",
+    \"speed\": 1.0
+  }" | mpv --really-quiet -
+
+curl -s $URL -H "Content-Type: application/json" -d "{
+    \"model\": \"tts-1-hd\",
+    \"input\": \"The quick brown fox jumped over the lazy dog. This HD voice is called $voice, how do you like this voice?\",
+    \"voice\": \"$voice\",
+    \"speed\": 1.0
+  }" | mpv --really-quiet -
+
+done
+
+curl -s $URL -H "Content-Type: application/json" -d "{
+    \"model\": \"tts-1\",
+    \"input\": \"the slowest voice\",
+    \"voice\": \"onyx\",
+    \"speed\": 0.25
+  }" | mpv --really-quiet -
+
+curl -s $URL -H "Content-Type: application/json" -d "{
+    \"model\": \"tts-1-hd\",
+    \"input\": \"the slowest HD voice\",
+    \"voice\": \"onyx\",
+    \"speed\": 0.25
+  }" | mpv --really-quiet -
+
+curl -s $URL -H "Content-Type: application/json" -d "{
+    \"model\": \"tts-1\",
+    \"input\": \"And this is how fast it can go, the fastest voice\",
+    \"voice\": \"nova\",
+    \"speed\": 4.0
+  }" | mpv --really-quiet -
+
+curl -s $URL -H "Content-Type: application/json" -d "{
+    \"model\": \"tts-1-hd\",
+    \"input\": \"And this is how fast it can go, the fastest HD voice\",
+    \"voice\": \"nova\",
+    \"speed\": 4.0
+  }" | mpv --really-quiet -

voice_to_speaker.default.yaml

@@ -0,0 +1,59 @@
+tts-1:
+  some_other_voice_name_you_want:
+    model: voices/choose your own model.onnx
+    speaker: set your own speaker
+  alloy:
+    model: voices/en_US-libritts_r-medium.onnx
+    speaker: 79 # 64, 79, 80, 101, 130
+  echo:
+    model: voices/en_US-libritts_r-medium.onnx
+    speaker: 134 # 52, 102, 134
+  echo-alt:
+    model: voices/en_US-ryan-high.onnx
+    speaker: # default speaker
+  fable:
+    model: voices/en_GB-northern_english_male-medium.onnx
+    speaker: # default speaker
+  onyx:
+    model: voices/en_US-libritts_r-medium.onnx
+    speaker: 159 # 55, 90, 132, 136, 137, 159
+  nova:
+    model: voices/en_US-libritts_r-medium.onnx
+    speaker: 107 # 57, 61, 107, 150, 162
+  shimmer:
+    model: voices/en_US-libritts_r-medium.onnx
+    speaker: 163
+tts-1-hd:
+  alloy-alt:
+    model: xtts
+    speaker: voices/alloy-alt.wav
+  alloy:
+    model: xtts
+    speaker: voices/alloy.wav
+  echo:
+    model: xtts
+    speaker: voices/echo.wav
+  fable:
+    model: xtts
+    speaker: voices/fable.wav
+  onyx:
+    model: xtts
+    speaker: voices/onyx.wav
+  nova:
+    model: xtts
+    speaker: voices/nova.wav
+  shimmer:
+    model: xtts
+    speaker: voices/shimmer.wav
+  me:
+    model: xtts_v2.0.2 # you can specify an older xtts version
+    speaker: voices/me.wav # this could be you
+    language: auto
+    enable_text_splitting: True
+    length_penalty: 1.0
+    repetition_penalty: 10
+    speed: 1.0
+    temperature: 0.75
+    top_k: 50
+    top_p: 0.85
+    comment: You can add a comment here also, which will be persistent and otherwise ignored.