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version: 2
enable-beta-ecosystems: true
updates:
- package-ecosystem: "docker"
directory: "/"
schedule:
interval: "weekly"
- package-ecosystem: "github-actions"
directory: "/"
schedule:
interval: "weekly"
- package-ecosystem: "uv"
directory: "/"
schedule:
interval: "weekly"

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name: Build and Publish Docker Image
on:
push:
branches:
- "**"
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build-and-push:
runs-on: ubuntu-latest
steps:
- name: Check out repository
uses: actions/checkout@v4
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Log in to GitHub Container Registry
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Determine image metadata
id: meta
uses: docker/metadata-action@v5
with:
images: ghcr.io/tcpipuk/chatterbox-proxy
tags: |
# Tag every branch push by its branch name
type=ref,event=branch,format={{ref_name}}
# Also tag "latest" if this is the main branch
type=ref,event=branch,if=ref==refs/heads/main,format=latest
- name: Build and push Docker image
uses: docker/build-push-action@v4
with:
context: .
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}

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# 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
# UV
# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
#uv.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/latest/usage/project/#working-with-version-control
.pdm.toml
.pdm-python
.pdm-build/
# 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/
# Abstra
# Abstra is an AI-powered process automation framework.
# Ignore directories containing user credentials, local state, and settings.
# Learn more at https://abstra.io/docs
.abstra/
# Visual Studio Code
# Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore
# that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
# and can be added to the global gitignore or merged into this file. However, if you prefer,
# you could uncomment the following to ignore the enitre vscode folder
# .vscode/
# Ruff stuff:
.ruff_cache/
# PyPI configuration file
.pypirc
# Cursor
# Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to
# exclude from AI features like autocomplete and code analysis. Recommended for sensitive data
# refer to https://docs.cursor.com/context/ignore-files
.cursorignore
.cursorindexingignore

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# Stage 1: Build dependencies using uv
FROM ghcr.io/astral-sh/uv:python3.13-bookworm-slim AS builder
WORKDIR /app
# Set uv environment variables for optimized linking and bytecode compilation
ENV UV_COMPILE_BYTECODE=1 \
UV_LINK_MODE=copy
# Install dependencies into a virtual environment using uv
COPY pyproject.toml uv.lock ./
RUN --mount=type=cache,target=/root/.cache/uv \
uv sync --frozen --no-dev --no-editable --no-install-project
# Stage 2: Create the runtime image
FROM python:3.13-slim-bookworm AS runtime
WORKDIR /app
# Copy the virtual environment with dependencies from the builder stage
COPY --from=builder /app/.venv ./.venv
# Add the virtual environment's bin directory to the PATH
ENV PATH="/app/.venv/bin:${PATH}" \
PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1
# Copy the adapter application code and default voices file
COPY adapter.py voices.yml ./
# Expose the port the app runs on
EXPOSE 8004
# Run Uvicorn on container start
CMD ["uvicorn", "adapter:app", "--host", "0.0.0.0", "--port", "8004"]

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MIT License
Copyright (c) 2025 Tom Foster
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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# 🎙️ Chatterbox TTS Proxy
Ever wanted to use ChatGPT's voice features with your own custom voices? This proxy makes it happen!
It's a simple bridge that lets any app using OpenAI's TTS API tap into Chatterbox's awesome voice
cloning powers. No code changes needed - just point your app at this proxy and you're good to go! 🚀
## ✨ Why Use This Proxy?
* Drop-in Replacement - Works with any OpenAI TTS client - just swap the endpoint URL
* Zero-shot Voice Cloning - Clone any voice from a single audio sample
* Emotional Control - Make your AI sound happy, sad, or anywhere in between
* Production Ready - High-quality audio that's ready for real-world use
* Easy Deployment - One command to get everything running
## 🎯 Chatterbox TTS
Chatterbox is Resemble AI's open-source TTS engine that's seriously impressive:
* Clone any voice from a single audio sample (yes, really)
* Control how emotional the voice sounds
* Generate studio-quality audio
* Works with WAV, MP3, and FLAC files
This project uses [bhimrazy's Chatterbox TTS server](https://github.com/bhimrazy/litserve-examples/tree/main/chatterbox-tts)
from [Docker Hub](https://hub.docker.com/r/bhimrazy/chatterbox-tts). It's the perfect starting point
for voice cloning experiments!
## 🔄 Adapter Proxy
The adapter translates between OpenAI's TTS API format and Chatterbox's more powerful capabilities:
* Converts OpenAI requests to Chatterbox format
* Manages voice presets and settings
* Handles errors gracefully
* Makes everything just work™
Here's how it works:
**Your app sends this** (standard OpenAI format):
```json5
{
"model": "tts-1", #this value is ignored
"voice": "en-uk-heart",
"input": "Hello, this is a test."
}
```
**The proxy converts it to this** (Chatterbox format):
```json5
{
"text": "Hello, this is a test.",
"audio_prompt": "reference/voice_sample.wav",
"cfg": 0.4, # Controls generation quality
"exaggeration": 0.6, # Controls emotional intensity
"temperature": None, # Only needed when an audio prompt isn't provided
}
```
The magic happens with these settings:
* **`audio_prompt`** - Your reference audio file (WAV, FLAC, or MP3)
* **`exaggeration`** - How emotional the voice should be (0.0-1.0)
* **`cfg`** - How closely to match the reference voice (0.0-1.0)
* **`temperature`** - If you have no reference file, this controls the randomness of the voice
## 🎭 Voice Cloning
Want to add your own voice? It's super easy! Here's how:
1. Drop your audio file in the `reference/` folder
(5-45 seconds will work, but I recommend at least 15-20 seconds for accuracy)
2. Add a new preset to `adapter.py`
3. Tweak the settings:
* `exaggeration`: Crank it up (0.8-1.0) for more dramatic speech
* `cfg`: Higher values (0.7-0.9) for better voice matching
That's it! The proxy handles all the complicated stuff behind the scenes. 🎯
## 🚀 Setup & Run
### Docker Compose
Fire it up with one command:
```bash
docker-compose up -d
```
### 📁 Folder Structure
```bash
.
├── models/ # Hugging Face models (cached)
├── reference/ # Your voice samples go here
├── voices.yml # Voice preset configurations
└── docker-compose.yml
```
### 🎭 Voice Configuration
The `voices.yml` file lets you configure your voice presets. Each preset can use either:
* An audio sample for voice cloning (recommended)
* Temperature-based generation (when no audio sample is available)
Example configuration:
```yaml
# Voice with audio sample
stewie:
name: Stewie
audio_prompt: stewie.mp3
exaggeration: 0.8 # How emotional (0.0-1.0)
cfg: 0.4 # Voice matching quality (0.0-1.0)
# Voice without audio sample
random-voice:
name: Random Voice
temperature: 0.7 # Voice randomness (0.0-1.0)
exaggeration: 0.5
cfg: 0.5
```
To use your own voice configuration:
1. Create a `voices.yml` file in your project directory
2. Mount it in the container using the volume in `docker-compose.yml`
3. Optionally override the path using the `VOICES_FILE` environment variable
The proxy will automatically reload the voice presets when the container starts.
### 🧪 Quick Test
You can test the proxy directly using curl:
```bash
curl -X POST http://your-server:8004/v1/audio/speech \
-H "Content-Type: application/json" \
-d '{
"model": "tts-1",
"voice": "stewie",
"input": "How does it feel to be the least cultured person at a bus station?"
}' \
--output test.wav
```
This will:
1. Send a request to the proxy
2. Use the "stewie" voice preset
3. Save the generated audio as `test.wav`
You can then play the file to hear the result. Try different voices and text to experiment!
## ⚖️ Ethical Considerations
We strongly encourage responsible use of this technology:
* Use your own voice or public domain voices for personal projects
* Get explicit permission before cloning someone else's voice
* Be transparent when using AI-generated voices
* Consider the impact on voice actors and content creators
While we can't control how others use this tool, we don't condone:
* Impersonating others without consent
* Creating misleading or harmful content
* Using cloned voices for fraud or deception
* Any other malicious or unethical purposes
Remember: With great power comes great responsibility! 🕷️
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

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"""FastAPI adapter for Chatterbox TTS API, providing OpenAI-compatible endpoints.
This adapter lets any app using OpenAI's TTS API tap into Chatterbox's awesome voice cloning powers.
It's like a smart translator that converts OpenAI's simple requests into Chatterbox's more powerful
format, handling all the voice settings behind the scenes.
What makes this cool:
- Clone any voice from a single audio sample (yes, really! 🎯)
- Control how emotional the voice sounds
- Generate studio-quality audio
- Works with any OpenAI TTS client - no code changes needed
- Easy to add new voices or tweak existing ones
The adapter keeps track of all your voice presets and their settings, making it super simple to
experiment with different voices and emotional styles.
"""
from __future__ import annotations
import logging
import os
from pathlib import Path
import httpx
import yaml
from fastapi import FastAPI, HTTPException, Response
from pydantic import BaseModel, Field
app = FastAPI()
logger = logging.getLogger("uvicorn.error")
CHATTERBOX_URL = f"http://{os.getenv('CHATTER_HOST', 'localhost')}:{os.getenv('CHATTER_PORT', '8000')}/speech"
MAX_INPUT_LENGTH = 500
VOICES_FILE = os.getenv("VOICES_FILE", "voices.yml")
DEFAULT_CONTENT_TYPE = "application/octet-stream"
class VoicePreset(BaseModel):
"""Voice preset configuration."""
name: str
audio_prompt: str | None = Field(default=None)
exaggeration: float = Field(default=0.5, ge=0.0, le=1.0)
cfg: float = Field(default=0.5, ge=0.0, le=1.0)
temperature: float | None = Field(default=None, ge=0.0, le=1.0)
class TTSRequest(BaseModel):
"""OpenAI-compatible TTS request model.
This is what your app sends to the proxy. The model field is ignored (we always use Chatterbox),
but we keep it to maintain compatibility with OpenAI's API.
"""
model: str | None = "tts-1"
voice: str
input: str
def load_voice_presets() -> dict[str, VoicePreset]:
"""Load voice presets from YAML file.
Returns:
Dictionary of voice presets with their settings.
Raises:
FileNotFoundError: If the voices file doesn't exist.
yaml.YAMLError: If the YAML file is invalid.
"""
try:
with Path(VOICES_FILE).open(encoding="utf-8") as f:
raw_presets = yaml.safe_load(f)
presets: dict[str, VoicePreset] = {}
for voice_id, preset in raw_presets.items():
# Ensure audio_prompt is relative to reference/ directory if provided
if preset.get("audio_prompt") and not preset["audio_prompt"].startswith("reference/"):
preset["audio_prompt"] = f"reference/{preset['audio_prompt']}"
# Validate and convert to VoicePreset model
presets[voice_id] = VoicePreset(**preset)
except FileNotFoundError:
logger.exception("Voices file not found: %s", VOICES_FILE)
raise
except yaml.YAMLError:
logger.exception("Invalid YAML in voices file")
raise
else:
return presets
# Load voice presets at startup
try:
VOICE_PRESETS = load_voice_presets()
except (FileNotFoundError, yaml.YAMLError, ValueError):
logger.exception("Failed to load voice presets")
VOICE_PRESETS = {} # Fallback to empty dict if loading fails
@app.get("/health")
async def health_check() -> dict[str, str]:
"""Health check endpoint.
Returns:
Status message indicating the service is healthy.
"""
return {"status": "healthy"}
@app.get("/v1/audio/voices")
async def list_voices() -> list[dict[str, str]]:
"""List all available voice presets.
Returns:
A list of voice presets, each with an ID and display name. These are the voices
your app can use when making TTS requests.
"""
return [{"id": k, "name": v.name} for k, v in VOICE_PRESETS.items()]
@app.get("/v1/audio/models")
async def list_models() -> list[dict[str, str | int]]:
"""List available TTS models.
Returns:
A list containing the Chatterbox model info to maintain compatibility with OpenAI's API.
We always use Chatterbox under the hood, but this endpoint lets your app check
what's available.
"""
return [{"id": "chatterbox", "created": 1713956629}]
@app.post("/v1/audio/speech")
async def openai_tts(req: TTSRequest) -> Response:
"""Generate speech from text using Chatterbox TTS.
This is where the magic happens! The function:
1. Checks if your request is valid
2. Finds the right voice preset
3. Converts the request to Chatterbox format
4. Sends it to Chatterbox
5. Returns the generated audio
Args:
req: Your TTS request with the text to speak and which voice to use.
Returns:
The generated audio file, ready to play.
Raises:
HTTPException: If the text is too long or the voice isn't found.
"""
logger.info(
"Received TTS request: model=%s, voice=%s, input_length=%d", req.model, req.voice, len(req.input)
)
if len(req.input) > MAX_INPUT_LENGTH:
logger.warning("Input text too long: %d > %d", len(req.input), MAX_INPUT_LENGTH)
raise HTTPException(
status_code=400,
detail=f"Input text exceeds {MAX_INPUT_LENGTH} characters; please shorten.",
)
if req.voice not in VOICE_PRESETS:
logger.warning("Unknown voice preset: %s (available: %s)", req.voice, ", ".join(VOICE_PRESETS.keys()))
raise HTTPException(
status_code=400,
detail=f"Unknown voice preset: {req.voice}",
)
preset = VOICE_PRESETS[req.voice]
logger.info(
"Using voice preset: %s (audio_prompt=%s, exaggeration=%.1f, cfg=%.1f, temperature=%s)",
preset.name,
preset.audio_prompt,
preset.exaggeration,
preset.cfg,
preset.temperature,
)
# Build payload with required fields
payload = {
"text": req.input,
"exaggeration": preset.exaggeration,
"cfg": preset.cfg,
}
# Only include audio_prompt or temperature, not both
if preset.audio_prompt:
payload["audio_prompt"] = preset.audio_prompt
elif preset.temperature is not None:
payload["temperature"] = preset.temperature
logger.info("Sending request to Chatterbox: %s", payload)
async with httpx.AsyncClient(timeout=30.0) as client:
try:
chatterbox_response = await client.post(CHATTERBOX_URL, json=payload)
chatterbox_response.raise_for_status()
except httpx.HTTPStatusError as e:
status = e.response.status_code
detail = f"Chatterbox error: {e.response.text}"
logger.exception("Chatterbox request failed: %s (status=%d)", detail, status)
raise HTTPException(status_code=status, detail=detail) from e
except httpx.RequestError as e:
logger.exception("Failed to connect to Chatterbox")
raise HTTPException(
status_code=503,
detail="Chatterbox service unavailable",
) from e
except Exception as e:
logger.exception("Unexpected error during TTS request")
raise HTTPException(
status_code=500,
detail="Internal server error",
) from e
content_type = chatterbox_response.headers.get("content-type", DEFAULT_CONTENT_TYPE)
logger.info("Successfully generated audio (content-type: %s)", content_type)
return Response(content=chatterbox_response.content, media_type=content_type)

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services:
chatterbox:
deploy:
resources:
limits:
cpus: 4
memory: 2G
reservations:
devices:
- capabilities:
- gpu
count: 1
driver: nvidia
environment:
- HF_HOME=/app/models
- NVIDIA_VISIBLE_DEVICES=all
- NVIDIA_DRIVER_CAPABILITIES=compute,utility
image: bhimrazy/chatterbox-tts:v0.1.0
restart: unless-stopped
volumes:
- ./models:/app/models
adapter:
depends_on:
- chatterbox
deploy:
resources:
limits:
cpus: 2
memory: 1G
environment:
- CHATTER_HOST=chatterbox
- CHATTER_PORT=8000
- VOICES_FILE=/app/voices.yml
image: ghcr.io/tcpipuk/chatterbox-proxy:latest
ports:
- "8004:8004"
restart: unless-stopped
volumes:
- ./voices.yml:/app/voices.yml

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[project]
name = "chatterbox-proxy"
version = "0.1.0"
description = "A proxy for the Chatterbox TTS API"
readme = "README.md"
license = { text = "MIT" }
authors = [{ name = "Tom Foster", email = "tom@tcpip.uk" }]
maintainers = [{ name = "Tom Foster", email = "tom@tcpip.uk" }]
requires-python = ">=3.13"
classifiers = [
"Development Status :: 4 - Beta",
"License :: OSI Approved :: MIT License",
"Topic :: Communications :: Chat",
"Framework :: AsyncIO",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.13",
]
dependencies = ["fastapi>=0.115", "httpx>=0.28", "uvicorn[standard]>=0.34"]
[project.urls]
Homepage = "https://github.com/tcpipuk/chatterbox-proxy"
[dependency-groups]
dev = ["ruff>=0.9"]
[tool.uv]
package = true
[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"
[tool.ruff]
cache-dir = "/tmp/.ruff_cache"
fix = true
line-length = 110
preview = true
show-fixes = false
target-version = "py313"
unsafe-fixes = true
[tool.ruff.format]
line-ending = "auto"
skip-magic-trailing-comma = false
[tool.ruff.lint]
fixable = ["ALL"]
ignore = [
"ANN401", # use of Any type
"BLE001", # blind Exception usage
"COM812", # missing trailing comma
"CPY", # flake8-copyright
"FBT", # boolean arguments
"PLR0912", # too many branches
"PLR0913", # too many arguments
"PLR0915", # too many statements
"PLR0917", # too many positional arguments
"RUF029", # async methods that don't await
"S104", # binding to all interfaces
"S110", # passed exceptions
"TRY301", # raise inside try block
]
select = ["ALL"]
unfixable = [
"F841", # local variable assigned but never used
"RUF100", # unused noqa comments
"T201", # don't strip print statement
]
[tool.ruff.lint.isort]
combine-as-imports = true
required-imports = ["from __future__ import annotations"]
[tool.ruff.lint.per-file-ignores]
"tests/**" = [
"ANN", # Ignore missing type annotations
"ARG", # Ignore argument issues
"C901", # Ignore complex methods
"DOC201", # Ignore "return" in docstrings
"DOC402", # Ignore "yield" in docstrings
"PLR2004", # Ignore magic values
"RET", # Ignore return issues
"S404", # Ignore subprocess module
"S603", # Ignore subprocess usage
"S607", # Ignore subprocess with relative path
"SLF001", # private member access
]
[tool.ruff.lint.pydocstyle]
convention = "google"

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revision = 2
requires-python = ">=3.13"
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version = "0.7.0"
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52
voices.yml Normal file
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# Voice presets for Chatterbox TTS
# Each preset defines a voice that can be used with the OpenAI-compatible API
#
# Fields:
# name: Display name for the voice
# audio_prompt: Path to the reference audio file (relative to reference/ directory)
# exaggeration: Emotional intensity (0.0-1.0)
# cfg: Voice matching quality (0.0-1.0)
# temperature: Optional. Only used if no audio_prompt is provided (0.0-1.0)
# Controls voice randomness when no reference audio is available
stewie:
name: Stewie
audio_prompt: stewie.mp3
exaggeration: 0.8
cfg: 0.4
shadowheart:
name: Shadowheart
audio_prompt: shadowheart.flac
exaggeration: 0.6
cfg: 0.4
rick:
name: Rick
audio_prompt: rick.mp3
exaggeration: 0.6
cfg: 0.3
glados:
name: GLaDOS
audio_prompt: glados.wav
exaggeration: 0.3
cfg: 0.2
american-normal:
name: American Female
audio_prompt: female_american.flac
exaggeration: 0.6
cfg: 0.8
american-whisper:
name: American Whisper
audio_prompt: american_whisper.wav
exaggeration: 0.2
cfg: 0.3
british-whisper:
name: British Whisper
audio_prompt: british_whisper.wav
exaggeration: 0.3
cfg: 0.4