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Enable ONNX GPU support in Docker configurations and refactor model file handling

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remsky 2025-01-22 05:00:38 -07:00
parent 4a24be1605
commit d50214d3be
19 changed files with 123 additions and 4321 deletions
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3
README.md
View file

@ -7,6 +7,9 @@
[![Coverage](https://img.shields.io/badge/coverage-60%25-grey)]()
[![Tested at Model Commit](https://img.shields.io/badge/last--tested--model--commit-a67f113-blue)](https://huggingface.co/hexgrad/Kokoro-82M/tree/c3b0d86e2a980e027ef71c28819ea02e351c2667) [![Try on Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Try%20on-Spaces-blue)](https://huggingface.co/spaces/Remsky/Kokoro-TTS-Zero)
> [!INFO]
> Pre-release. Not fully tested
Dockerized FastAPI wrapper for [Kokoro-82M](https://huggingface.co/hexgrad/Kokoro-82M) text-to-speech model
- OpenAI-compatible Speech endpoint, with inline voice combination functionality
- NVIDIA GPU accelerated or CPU Onnx inference

21
api/src/core/config.py
View file

@ -9,37 +9,22 @@ class Settings(BaseSettings):
host: str = "0.0.0.0"
port: int = 8880
# TTS Settings
# Application Settings
output_dir: str = "output"
output_dir_size_limit_mb: float = 500.0 # Maximum size of output directory in MB
default_voice: str = "af"
use_gpu: bool = False # Whether to use GPU acceleration if available
use_onnx: bool = True # Whether to use ONNX runtime
# Container absolute paths
model_dir: str = "/app/api/src/models" # Absolute path in container
voices_dir: str = "/app/api/src/voices" # Absolute path in container
# Model filenames
pytorch_model_file: str = "kokoro-v0_19.pth"
onnx_model_file: str = "kokoro-v0_19.onnx"
# Audio Settings
sample_rate: int = 24000
max_chunk_size: int = 300 # Maximum size of text chunks for processing
gap_trim_ms: int = 250 # Amount to trim from streaming chunk ends in milliseconds
# ONNX Optimization Settings
onnx_num_threads: int = 4 # Number of threads for intra-op parallelism
onnx_inter_op_threads: int = 4 # Number of threads for inter-op parallelism
onnx_execution_mode: str = "parallel" # parallel or sequential
onnx_optimization_level: str = "all" # all, basic, or disabled
onnx_memory_pattern: bool = True # Enable memory pattern optimization
onnx_arena_extend_strategy: str = "kNextPowerOfTwo" # Memory allocation strategy
# ONNX GPU Settings
onnx_device_id: int = 0 # GPU device ID to use
onnx_gpu_mem_limit: float = 0.7 # Limit GPU memory usage to 70%
onnx_cudnn_conv_algo_search: str = "EXHAUSTIVE" # CUDNN convolution algorithm search
onnx_do_copy_in_default_stream: bool = True # Copy in default CUDA stream
class Config:
env_file = ".env"

6
api/src/core/model_config.py
View file

@ -11,7 +11,7 @@ class ONNXCPUConfig(BaseModel):
instance_timeout: int = Field(300, description="Session timeout in seconds")
# Runtime settings
num_threads: int = Field(8, description="Number of threads for parallel operations")
num_threads: int = Field(4, description="Number of threads for parallel operations")
inter_op_threads: int = Field(4, description="Number of threads for operator parallelism")
execution_mode: str = Field("parallel", description="ONNX execution mode")
optimization_level: str = Field("all", description="ONNX optimization level")
@ -77,6 +77,10 @@ class ModelConfig(BaseModel):
cache_voices: bool = Field(True, description="Whether to cache voice tensors")
voice_cache_size: int = Field(2, description="Maximum number of cached voices")
# Model filenames
pytorch_model_file: str = Field("kokoro-v0_19.pth", description="PyTorch model filename")
onnx_model_file: str = Field("kokoro-v0_19.onnx", description="ONNX model filename")
# Backend-specific configs
onnx_cpu: ONNXCPUConfig = Field(default_factory=ONNXCPUConfig)
onnx_gpu: ONNXGPUConfig = Field(default_factory=ONNXGPUConfig)

25
api/src/inference/model_manager.py
View file

@ -17,26 +17,27 @@ from .pytorch_gpu import PyTorchGPUBackend
from .session_pool import CPUSessionPool, StreamingSessionPool
# Global singleton instance and state
# Global singleton instance and lock for thread-safe initialization
_manager_instance = None
_manager_lock = asyncio.Lock()
_loaded_models = {}
_backends = {}
class ModelManager:
"""Manages model loading and inference across backends."""
# Class-level state for shared resources
_loaded_models = {}
_backends = {}
def __init__(self, config: Optional[ModelConfig] = None):
"""Initialize model manager.
Args:
config: Optional configuration
Note:
This should not be called directly. Use get_manager() instead.
"""
self._config = config or model_config
global _loaded_models, _backends
self._loaded_models = _loaded_models
self._backends = _backends
# Initialize session pools
self._session_pools = {
@ -293,10 +294,20 @@ async def get_manager(config: Optional[ModelConfig] = None) -> ModelManager:
Returns:
ModelManager instance
Thread Safety:
This function is thread-safe and ensures only one instance is created
even under concurrent access.
"""
global _manager_instance
# Fast path - return existing instance without lock
if _manager_instance is not None:
return _manager_instance
# Slow path - create new instance with lock
async with _manager_lock:
# Double-check pattern
if _manager_instance is None:
_manager_instance = ModelManager(config)
await _manager_instance.initialize()

18
api/src/inference/session_pool.py
View file

@ -75,20 +75,16 @@ def create_provider_options(is_gpu: bool = False) -> Dict:
if is_gpu:
config = model_config.onnx_gpu
return {
"CUDAExecutionProvider": {
"device_id": config.device_id,
"arena_extend_strategy": config.arena_extend_strategy,
"gpu_mem_limit": int(config.gpu_mem_limit * torch.cuda.get_device_properties(0).total_memory),
"cudnn_conv_algo_search": config.cudnn_conv_algo_search,
"do_copy_in_default_stream": config.do_copy_in_default_stream
}
"device_id": config.device_id,
"arena_extend_strategy": config.arena_extend_strategy,
"gpu_mem_limit": int(config.gpu_mem_limit * torch.cuda.get_device_properties(0).total_memory),
"cudnn_conv_algo_search": config.cudnn_conv_algo_search,
"do_copy_in_default_stream": config.do_copy_in_default_stream
}
else:
return {
"CPUExecutionProvider": {
"arena_extend_strategy": model_config.onnx_cpu.arena_extend_strategy,
"cpu_memory_arena_cfg": "cpu:0"
}
"arena_extend_strategy": model_config.onnx_cpu.arena_extend_strategy,
"cpu_memory_arena_cfg": "cpu:0"
}

7
api/src/inference/voice_manager.py
View file

@ -73,12 +73,13 @@ class VoiceManager:
return voice
def _manage_cache(self) -> None:
"""Manage voice cache size."""
"""Manage voice cache size using simple LRU."""
if len(self._voice_cache) >= self._config.cache_size:
# Remove oldest voice
# Remove least recently used voice
oldest = next(iter(self._voice_cache))
del self._voice_cache[oldest]
logger.debug(f"Removed from voice cache: {oldest}")
torch.cuda.empty_cache() # Clean up GPU memory if needed
logger.debug(f"Removed LRU voice from cache: {oldest}")
async def combine_voices(self, voices: List[str], device: str = "cpu") -> str:
"""Combine multiple voices into a new voice.

6
api/src/main.py
View file

@ -1,4 +1,3 @@
"""
FastAPI OpenAI Compatible API
"""
@ -14,6 +13,7 @@ from fastapi.middleware.cors import CORSMiddleware
from loguru import logger
from .core.config import settings
from .core.model_config import model_config
from .routers.development import router as dev_router
from .routers.openai_compatible import router as openai_router
from .services.tts_service import TTSService
@ -63,8 +63,8 @@ async def lifespan(app: FastAPI):
# Get backend and initialize model
backend = model_manager.get_backend(backend_type)
# Use model path directly from settings
model_file = settings.pytorch_model_file if not settings.use_onnx else settings.onnx_model_file
# Use model path from model_config
model_file = model_config.pytorch_model_file if not settings.use_onnx else model_config.onnx_model_file
model_path = os.path.join(settings.model_dir, model_file)

75
api/src/routers/openai_compatible.py
View file

@ -130,12 +130,12 @@ async def create_speech(
},
)
else:
# Generate complete audio
audio, _ = tts_service._generate_audio(
# Generate complete audio using public interface
audio, _ = await tts_service.generate_audio(
text=request.input,
voice=voice_to_use,
speed=request.speed,
stitch_long_output=True,
stitch_long_output=True
)
# Convert to requested format
@ -153,14 +153,37 @@ async def create_speech(
)
except ValueError as e:
logger.error(f"Invalid request: {str(e)}")
# Handle validation errors
logger.warning(f"Invalid request: {str(e)}")
raise HTTPException(
status_code=400, detail={"error": "Invalid request", "message": str(e)}
status_code=400,
detail={
"error": "validation_error",
"message": str(e),
"type": "invalid_request_error"
}
)
except RuntimeError as e:
# Handle runtime/processing errors
logger.error(f"Processing error: {str(e)}")
raise HTTPException(
status_code=500,
detail={
"error": "processing_error",
"message": "Failed to process audio generation request",
"type": "server_error"
}
)
except Exception as e:
logger.error(f"Error generating speech: {str(e)}")
# Handle unexpected errors
logger.error(f"Unexpected error in speech generation: {str(e)}")
raise HTTPException(
status_code=500, detail={"error": "Server error", "message": str(e)}
status_code=500,
detail={
"error": "server_error",
"message": "An unexpected error occurred",
"type": "server_error"
}
)
@ -173,7 +196,14 @@ async def list_voices():
return {"voices": voices}
except Exception as e:
logger.error(f"Error listing voices: {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
raise HTTPException(
status_code=500,
detail={
"error": "server_error",
"message": "Failed to retrieve voice list",
"type": "server_error"
}
)
@router.post("/audio/voices/combine")
@ -199,13 +229,32 @@ async def combine_voices(request: Union[str, List[str]]):
return {"voices": voices, "voice": combined_voice}
except ValueError as e:
logger.error(f"Invalid voice combination request: {str(e)}")
logger.warning(f"Invalid voice combination request: {str(e)}")
raise HTTPException(
status_code=400, detail={"error": "Invalid request", "message": str(e)}
status_code=400,
detail={
"error": "validation_error",
"message": str(e),
"type": "invalid_request_error"
}
)
except RuntimeError as e:
logger.error(f"Voice combination processing error: {str(e)}")
raise HTTPException(
status_code=500,
detail={
"error": "processing_error",
"message": "Failed to process voice combination request",
"type": "server_error"
}
)
except Exception as e:
logger.error(f"Server error during voice combination: {str(e)}")
logger.error(f"Unexpected error in voice combination: {str(e)}")
raise HTTPException(
status_code=500, detail={"error": "Server error", "message": "Server error"}
status_code=500,
detail={
"error": "server_error",
"message": "An unexpected error occurred",
"type": "server_error"
}
)

7
api/src/services/tts_service.py
View file

@ -51,7 +51,7 @@ class TTSService:
return service
async def generate_audio(
self, text: str, voice: str, speed: float = 1.0
self, text: str, voice: str, speed: float = 1.0, stitch_long_output: bool = True
) -> Tuple[np.ndarray, float]:
"""Generate audio for text.
@ -59,9 +59,14 @@ class TTSService:
text: Input text
voice: Voice name
speed: Speed multiplier
stitch_long_output: Whether to stitch together long outputs
Returns:
Audio samples and processing time
Raises:
ValueError: If text is empty after preprocessing or no chunks generated
RuntimeError: If audio generation fails
"""
start_time = time.time()
voice_tensor = None

3
docker/cpu/Dockerfile
View file

@ -10,7 +10,7 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
# Install uv
# Install uv for speed and glory
COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
# Create non-root user
@ -44,6 +44,7 @@ ENV PYTHONPATH=/app
ENV PATH="/app/.venv/bin:$PATH"
ENV UV_LINK_MODE=copy
ENV USE_GPU=false
ENV USE_ONNX=true
# Run FastAPI server
CMD ["uv", "run", "python", "-m", "uvicorn", "api.src.main:app", "--host", "0.0.0.0", "--port", "8880", "--log-level", "debug"]

22
docker/cpu/pyproject.toml
View file

@ -1,22 +0,0 @@
[project]
name = "kokoro-fastapi-cpu"
version = "0.1.0"
description = "FastAPI TTS Service - CPU Version"
readme = "../README.md"
requires-python = ">=3.10"
dependencies = [
# Core ML/DL for CPU
"torch>=2.5.1",
"transformers==4.47.1",
]
[tool.uv.workspace]
members = ["../shared"]
[tool.uv.sources]
torch = { index = "pytorch-cpu" }
[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true

229
docker/cpu/requirements.lock
View file

@ -1,229 +0,0 @@
# This file was autogenerated by uv via the following command:
# uv pip compile pyproject.toml ../shared/pyproject.toml --output-file requirements.lock
aiofiles==23.2.1
# via kokoro-fastapi (../shared/pyproject.toml)
annotated-types==0.7.0
# via pydantic
anyio==4.8.0
# via starlette
attrs==24.3.0
# via
# clldutils
# csvw
# jsonschema
# phonemizer
# referencing
babel==2.16.0
# via csvw
certifi==2024.12.14
# via requests
cffi==1.17.1
# via soundfile
charset-normalizer==3.4.1
# via requests
click==8.1.8
# via
# kokoro-fastapi (../shared/pyproject.toml)
# uvicorn
clldutils==3.21.0
# via segments
colorama==0.4.6
# via
# click
# colorlog
# csvw
# loguru
# tqdm
coloredlogs==15.0.1
# via onnxruntime
colorlog==6.9.0
# via clldutils
csvw==3.5.1
# via segments
dlinfo==1.2.1
# via phonemizer
exceptiongroup==1.2.2
# via anyio
fastapi==0.115.6
# via kokoro-fastapi (../shared/pyproject.toml)
filelock==3.16.1
# via
# huggingface-hub
# torch
# transformers
flatbuffers==24.12.23
# via onnxruntime
fsspec==2024.12.0
# via
# huggingface-hub
# torch
greenlet==3.1.1
# via sqlalchemy
h11==0.14.0
# via uvicorn
huggingface-hub==0.27.1
# via
# tokenizers
# transformers
humanfriendly==10.0
# via coloredlogs
idna==3.10
# via
# anyio
# requests
isodate==0.7.2
# via
# csvw
# rdflib
jinja2==3.1.5
# via torch
joblib==1.4.2
# via phonemizer
jsonschema==4.23.0
# via csvw
jsonschema-specifications==2024.10.1
# via jsonschema
language-tags==1.2.0
# via csvw
loguru==0.7.3
# via kokoro-fastapi (../shared/pyproject.toml)
lxml==5.3.0
# via clldutils
markdown==3.7
# via clldutils
markupsafe==3.0.2
# via
# clldutils
# jinja2
mpmath==1.3.0
# via sympy
munch==4.0.0
# via kokoro-fastapi (../shared/pyproject.toml)
networkx==3.4.2
# via torch
numpy==2.2.1
# via
# kokoro-fastapi (../shared/pyproject.toml)
# onnxruntime
# scipy
# soundfile
# transformers
onnxruntime==1.20.1
# via kokoro-fastapi (../shared/pyproject.toml)
packaging==24.2
# via
# huggingface-hub
# onnxruntime
# transformers
phonemizer==3.3.0
# via kokoro-fastapi (../shared/pyproject.toml)
protobuf==5.29.3
# via onnxruntime
pycparser==2.22
# via cffi
pydantic==2.10.4
# via
# kokoro-fastapi (../shared/pyproject.toml)
# fastapi
# pydantic-settings
pydantic-core==2.27.2
# via pydantic
pydantic-settings==2.7.0
# via kokoro-fastapi (../shared/pyproject.toml)
pylatexenc==2.10
# via clldutils
pyparsing==3.2.1
# via rdflib
pyreadline3==3.5.4
# via humanfriendly
python-dateutil==2.9.0.post0
# via
# clldutils
# csvw
python-dotenv==1.0.1
# via
# kokoro-fastapi (../shared/pyproject.toml)
# pydantic-settings
pyyaml==6.0.2
# via
# huggingface-hub
# transformers
rdflib==7.1.2
# via csvw
referencing==0.35.1
# via
# jsonschema
# jsonschema-specifications
regex==2024.11.6
# via
# kokoro-fastapi (../shared/pyproject.toml)
# segments
# tiktoken
# transformers
requests==2.32.3
# via
# kokoro-fastapi (../shared/pyproject.toml)
# csvw
# huggingface-hub
# tiktoken
# transformers
rfc3986==1.5.0
# via csvw
rpds-py==0.22.3
# via
# jsonschema
# referencing
safetensors==0.5.2
# via transformers
scipy==1.14.1
# via kokoro-fastapi (../shared/pyproject.toml)
segments==2.2.1
# via phonemizer
six==1.17.0
# via python-dateutil
sniffio==1.3.1
# via anyio
soundfile==0.13.0
# via kokoro-fastapi (../shared/pyproject.toml)
sqlalchemy==2.0.27
# via kokoro-fastapi (../shared/pyproject.toml)
starlette==0.41.3
# via fastapi
sympy==1.13.1
# via
# onnxruntime
# torch
tabulate==0.9.0
# via clldutils
tiktoken==0.8.0
# via kokoro-fastapi (../shared/pyproject.toml)
tokenizers==0.21.0
# via transformers
torch==2.5.1+cpu
# via kokoro-fastapi-cpu (pyproject.toml)
tqdm==4.67.1
# via
# kokoro-fastapi (../shared/pyproject.toml)
# huggingface-hub
# transformers
transformers==4.47.1
# via kokoro-fastapi-cpu (pyproject.toml)
typing-extensions==4.12.2
# via
# anyio
# fastapi
# huggingface-hub
# phonemizer
# pydantic
# pydantic-core
# sqlalchemy
# torch
# uvicorn
uritemplate==4.1.1
# via csvw
urllib3==2.3.0
# via requests
uvicorn==0.34.0
# via kokoro-fastapi (../shared/pyproject.toml)
win32-setctime==1.2.0
# via loguru

1841
docker/cpu/uv.lock generated
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File diff suppressed because it is too large Load diff

13
docker/gpu/Dockerfile
View file

@ -1,8 +1,11 @@
FROM pytorch/pytorch:2.1.0-cuda11.8-cudnn8-runtime
FROM nvidia/cuda:12.3.2-cudnn9-runtime-ubuntu22.04
# Set non-interactive frontend
ENV DEBIAN_FRONTEND=noninteractive
# Install dependencies
# Install Python and other dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
python3.10 \
python3.10-venv \
espeak-ng \
git \
libsndfile1 \
@ -27,15 +30,15 @@ WORKDIR /app
# Copy dependency files
COPY --chown=appuser:appuser pyproject.toml ./pyproject.toml
# Install dependencies
# Install dependencies with GPU extras
RUN --mount=type=cache,target=/root/.cache/uv \
uv venv && \
uv sync --extra gpu --no-install-project
uv sync --extra gpu
# Copy project files
COPY --chown=appuser:appuser api ./api
# Install project
# Install project with GPU extras
RUN --mount=type=cache,target=/root/.cache/uv \
uv sync --extra gpu

22
docker/gpu/pyproject.toml
View file

@ -1,22 +0,0 @@
[project]
name = "kokoro-fastapi-gpu"
version = "0.1.0"
description = "FastAPI TTS Service - GPU Version"
readme = "../README.md"
requires-python = ">=3.10"
dependencies = [
# Core ML/DL for GPU
"torch==2.5.1+cu121",
"transformers==4.47.1",
]
[tool.uv.workspace]
members = ["../shared"]
[tool.uv.sources]
torch = { index = "pytorch-cuda" }
[[tool.uv.index]]
name = "pytorch-cuda"
url = "https://download.pytorch.org/whl/cu121"
explicit = true

229
docker/gpu/requirements.lock
View file

@ -1,229 +0,0 @@
# This file was autogenerated by uv via the following command:
# uv pip compile pyproject.toml ../shared/pyproject.toml --output-file requirements.lock
aiofiles==23.2.1
# via kokoro-fastapi (../shared/pyproject.toml)
annotated-types==0.7.0
# via pydantic
anyio==4.8.0
# via starlette
attrs==24.3.0
# via
# clldutils
# csvw
# jsonschema
# phonemizer
# referencing
babel==2.16.0
# via csvw
certifi==2024.12.14
# via requests
cffi==1.17.1
# via soundfile
charset-normalizer==3.4.1
# via requests
click==8.1.8
# via
# kokoro-fastapi (../shared/pyproject.toml)
# uvicorn
clldutils==3.21.0
# via segments
colorama==0.4.6
# via
# click
# colorlog
# csvw
# loguru
# tqdm
coloredlogs==15.0.1
# via onnxruntime
colorlog==6.9.0
# via clldutils
csvw==3.5.1
# via segments
dlinfo==1.2.1
# via phonemizer
exceptiongroup==1.2.2
# via anyio
fastapi==0.115.6
# via kokoro-fastapi (../shared/pyproject.toml)
filelock==3.16.1
# via
# huggingface-hub
# torch
# transformers
flatbuffers==24.12.23
# via onnxruntime
fsspec==2024.12.0
# via
# huggingface-hub
# torch
greenlet==3.1.1
# via sqlalchemy
h11==0.14.0
# via uvicorn
huggingface-hub==0.27.1
# via
# tokenizers
# transformers
humanfriendly==10.0
# via coloredlogs
idna==3.10
# via
# anyio
# requests
isodate==0.7.2
# via
# csvw
# rdflib
jinja2==3.1.5
# via torch
joblib==1.4.2
# via phonemizer
jsonschema==4.23.0
# via csvw
jsonschema-specifications==2024.10.1
# via jsonschema
language-tags==1.2.0
# via csvw
loguru==0.7.3
# via kokoro-fastapi (../shared/pyproject.toml)
lxml==5.3.0
# via clldutils
markdown==3.7
# via clldutils
markupsafe==3.0.2
# via
# clldutils
# jinja2
mpmath==1.3.0
# via sympy
munch==4.0.0
# via kokoro-fastapi (../shared/pyproject.toml)
networkx==3.4.2
# via torch
numpy==2.2.1
# via
# kokoro-fastapi (../shared/pyproject.toml)
# onnxruntime
# scipy
# soundfile
# transformers
onnxruntime==1.20.1
# via kokoro-fastapi (../shared/pyproject.toml)
packaging==24.2
# via
# huggingface-hub
# onnxruntime
# transformers
phonemizer==3.3.0
# via kokoro-fastapi (../shared/pyproject.toml)
protobuf==5.29.3
# via onnxruntime
pycparser==2.22
# via cffi
pydantic==2.10.4
# via
# kokoro-fastapi (../shared/pyproject.toml)
# fastapi
# pydantic-settings
pydantic-core==2.27.2
# via pydantic
pydantic-settings==2.7.0
# via kokoro-fastapi (../shared/pyproject.toml)
pylatexenc==2.10
# via clldutils
pyparsing==3.2.1
# via rdflib
pyreadline3==3.5.4
# via humanfriendly
python-dateutil==2.9.0.post0
# via
# clldutils
# csvw
python-dotenv==1.0.1
# via
# kokoro-fastapi (../shared/pyproject.toml)
# pydantic-settings
pyyaml==6.0.2
# via
# huggingface-hub
# transformers
rdflib==7.1.2
# via csvw
referencing==0.35.1
# via
# jsonschema
# jsonschema-specifications
regex==2024.11.6
# via
# kokoro-fastapi (../shared/pyproject.toml)
# segments
# tiktoken
# transformers
requests==2.32.3
# via
# kokoro-fastapi (../shared/pyproject.toml)
# csvw
# huggingface-hub
# tiktoken
# transformers
rfc3986==1.5.0
# via csvw
rpds-py==0.22.3
# via
# jsonschema
# referencing
safetensors==0.5.2
# via transformers
scipy==1.14.1
# via kokoro-fastapi (../shared/pyproject.toml)
segments==2.2.1
# via phonemizer
six==1.17.0
# via python-dateutil
sniffio==1.3.1
# via anyio
soundfile==0.13.0
# via kokoro-fastapi (../shared/pyproject.toml)
sqlalchemy==2.0.27
# via kokoro-fastapi (../shared/pyproject.toml)
starlette==0.41.3
# via fastapi
sympy==1.13.1
# via
# onnxruntime
# torch
tabulate==0.9.0
# via clldutils
tiktoken==0.8.0
# via kokoro-fastapi (../shared/pyproject.toml)
tokenizers==0.21.0
# via transformers
torch==2.5.1+cu121
# via kokoro-fastapi-gpu (pyproject.toml)
tqdm==4.67.1
# via
# kokoro-fastapi (../shared/pyproject.toml)
# huggingface-hub
# transformers
transformers==4.47.1
# via kokoro-fastapi-gpu (pyproject.toml)
typing-extensions==4.12.2
# via
# anyio
# fastapi
# huggingface-hub
# phonemizer
# pydantic
# pydantic-core
# sqlalchemy
# torch
# uvicorn
uritemplate==4.1.1
# via csvw
urllib3==2.3.0
# via requests
uvicorn==0.34.0
# via kokoro-fastapi (../shared/pyproject.toml)
win32-setctime==1.2.0
# via loguru

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pyproject.toml
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@ -16,7 +16,6 @@ dependencies = [
# ML/DL Base
"numpy>=1.26.0",
"scipy==1.14.1",
"onnxruntime==1.20.1",
# Audio processing
"soundfile==0.13.0",
# Text processing
@ -39,9 +38,11 @@ dependencies = [
[project.optional-dependencies]
gpu = [
"torch==2.5.1+cu121",
"onnxruntime-gpu==1.20.1",
]
cpu = [
"torch==2.5.1",
"onnxruntime==1.20.1",
]
test = [
"pytest==8.0.0",