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KokoroTTSService: use kokoro-onnx instead of kokoro

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This commit is contained in:
Aleix Conchillo Flaqué
2026-01-31 17:18:34 -08:00
parent bdc9e7e2e4
commit 95689cc81c
6 changed files with 89 additions and 679 deletions
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1
changelog/3612.changed.md Normal file
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@@ -0,0 +1 @@
- Changed `KokoroTTSService` to use `kokoro-onnx` instead of `kokoro` as the underlying TTS engine.

2
pyproject.toml
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@@ -75,7 +75,7 @@ heygen = [ "livekit>=1.0.13", "pipecat-ai[websockets-base]" ]
hume = [ "hume>=0.11.2" ]
inworld = []
koala = [ "pvkoala~=2.0.3" ]
kokoro = [ "kokoro>=0.9.4,<1", "requests>=2.32.5,<3" ]
kokoro = [ "kokoro-onnx>=0.5.0,<1", "requests>=2.32.5,<3" ]
krisp = [ "pipecat-ai-krisp~=0.4.0" ]
langchain = [ "langchain~=0.3.20", "langchain-community~=0.3.20", "langchain-openai~=0.3.9" ]
livekit = [ "livekit~=1.0.13", "livekit-api~=1.0.5", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.10.1" ]

3
scripts/evals/run-release-evals.py
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@@ -144,8 +144,7 @@ TESTS_07 = [
("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH),
("07zh-interruptible-hathora.py", EVAL_SIMPLE_MATH),
("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH),
# Some issue with loguru.
# ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH),
("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH),
# Needs a local XTTS docker instance running.
# ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH),
# Needs a Krisp license.

128
src/pipecat/services/kokoro/tts.py
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@@ -4,10 +4,11 @@
# SPDX-License-Identifier: BSD 2-Clause License
#
"""Kokoro TTS service implementation."""
"""Kokoro TTS service implementation using kokoro-onnx."""
import asyncio
from typing import AsyncGenerator, AsyncIterator, Optional
import os
from pathlib import Path
from typing import AsyncGenerator, Optional
import numpy as np
from loguru import logger
@@ -17,6 +18,7 @@ from pipecat.audio.utils import create_stream_resampler
from pipecat.frames.frames import (
ErrorFrame,
Frame,
TTSAudioRawFrame,
TTSStartedFrame,
TTSStoppedFrame,
)
@@ -25,33 +27,61 @@ from pipecat.transcriptions.language import Language, resolve_language
from pipecat.utils.tracing.service_decorators import traced_tts
try:
from kokoro import KPipeline
import requests
from kokoro_onnx import Kokoro
except ModuleNotFoundError as e:
logger.error(f"Exception: {e}")
logger.error("In order to use Kokoro, you need to `pip install pipecat-ai[kokoro]`.")
raise Exception(f"Missing module: {e}")
KOKORO_CACHE_DIR = Path(os.path.expanduser("~/.cache/kokoro-onnx"))
KOKORO_MODEL_URL = "https://github.com/thewh1teagle/kokoro-onnx/releases/download/model-files-v1.0/kokoro-v1.0.onnx"
KOKORO_VOICES_URL = (
"https://github.com/thewh1teagle/kokoro-onnx/releases/download/model-files-v1.0/voices-v1.0.bin"
)
def _download_file(url: str, dest: Path):
"""Download a file from a URL to a destination path."""
logger.debug(f"Downloading {url} to {dest}...")
dest.parent.mkdir(parents=True, exist_ok=True)
resp = requests.get(url, stream=True, timeout=300)
resp.raise_for_status()
with open(dest, "wb") as f:
for chunk in resp.iter_content(chunk_size=8192):
f.write(chunk)
logger.debug(f"Downloaded {dest}")
def _ensure_model_files(model_path: Path, voices_path: Path):
"""Download model files if they don't exist."""
if not model_path.exists():
_download_file(KOKORO_MODEL_URL, model_path)
if not voices_path.exists():
_download_file(KOKORO_VOICES_URL, voices_path)
def language_to_kokoro_language(language: Language) -> str:
"""Convert a Language enum to Kokoro language code.
"""Convert a Language enum to kokoro-onnx language code.
Args:
language: The Language enum value to convert.
Returns:
The corresponding Kokoro language code, or None if not supported.
The corresponding kokoro-onnx locale code.
"""
LANGUAGE_MAP = {
Language.EN: "a",
Language.EN_US: "a",
Language.EN_GB: "b",
Language.ES: "e",
Language.FR: "f",
Language.HI: "h",
Language.IT: "i",
Language.JA: "j",
Language.PT: "p",
Language.ZH: "z",
Language.EN: "en-us",
Language.EN_US: "en-us",
Language.EN_GB: "en-gb",
Language.ES: "es",
Language.FR: "fr",
Language.HI: "hi",
Language.IT: "it",
Language.JA: "ja",
Language.PT: "pt",
Language.ZH: "zh",
}
return resolve_language(language, LANGUAGE_MAP, use_base_code=True)
@@ -60,8 +90,8 @@ def language_to_kokoro_language(language: Language) -> str:
class KokoroTTSService(TTSService):
"""Kokoro TTS service implementation.
Provides local text-to-speech synthesis using the Kokoro-82M model.
Automatically downloads the model on first use.
Provides local text-to-speech synthesis using kokoro-onnx.
Automatically downloads model files on first use.
"""
class InputParams(BaseModel):
@@ -77,7 +107,8 @@ class KokoroTTSService(TTSService):
self,
*,
voice_id: str,
repo_id="hexgrad/Kokoro-82M",
model_path: Optional[str] = None,
voices_path: Optional[str] = None,
params: Optional[InputParams] = None,
**kwargs,
):
@@ -85,10 +116,11 @@ class KokoroTTSService(TTSService):
Args:
voice_id: Voice identifier to use for synthesis.
repo_id: Hugging Face repository ID for the Kokoro model.
Defaults to "hexgrad/Kokoro-82M".
model_path: Path to the kokoro ONNX model file. Defaults to auto-downloaded file.
voices_path: Path to the voices binary file. Defaults to auto-downloaded file.
params: Configuration parameters for synthesis.
**kwargs: Additional arguments passed to parent `TTSService`.
"""
super().__init__(**kwargs)
@@ -96,7 +128,13 @@ class KokoroTTSService(TTSService):
self._voice_id = voice_id
self._lang_code = language_to_kokoro_language(params.language)
self._pipeline = KPipeline(lang_code=self._lang_code, repo_id=repo_id)
model = Path(model_path) if model_path else KOKORO_CACHE_DIR / "kokoro-v1.0.onnx"
voices = Path(voices_path) if voices_path else KOKORO_CACHE_DIR / "voices-v1.0.bin"
_ensure_model_files(model, voices)
self._kokoro = Kokoro(str(model), str(voices))
self._resampler = create_stream_resampler()
@@ -106,50 +144,38 @@ class KokoroTTSService(TTSService):
@traced_tts
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
"""Synthesize speech from text using the Kokoro pipeline.
"""Synthesize speech from text using kokoro-onnx.
Runs the Kokoro pipeline in a background thread and streams audio
frames as they become available.
Uses the async streaming API to generate audio frames.
Args:
text: The text to synthesize.
"""
logger.debug(f"{self}: Generating TTS [{text}]")
def async_next(it):
try:
return next(it)
except StopIteration:
return None
async def async_iterator(iterator) -> AsyncIterator[bytes]:
while True:
item = await asyncio.to_thread(async_next, iterator)
if item is None:
return
(_, _, audio) = item
# Kokoro outputs a PyTorch tensor at 24kHz, convert to int16 bytes
audio_np = np.array(audio)
audio_int16 = (audio_np * 32767).astype(np.int16).tobytes()
yield audio_int16
try:
await self.start_ttfb_metrics()
await self.start_tts_usage_metrics(text)
yield TTSStartedFrame()
async for frame in self._stream_audio_frames_from_iterator(
async_iterator(self._pipeline(text, voice=self._voice_id)),
in_sample_rate=24000,
):
stream = self._kokoro.create_stream(
text, voice=self._voice_id, lang=self._lang_code, speed=1.0
)
async for samples, sample_rate in stream:
await self.stop_ttfb_metrics()
yield frame
audio_int16 = (samples * 32767).astype(np.int16).tobytes()
audio_data = await self._resampler.resample(
audio_int16, sample_rate, self.sample_rate
)
yield TTSAudioRawFrame(
audio=audio_data, sample_rate=self.sample_rate, num_channels=1
)
except Exception as e:
yield ErrorFrame(error=f"Unknown error occurred: {e}")
finally:
logger.debug(f"{self}: Finished TTS [{text}]")
await self.stop_ttfb_metrics()
yield TTSStoppedFrame()

1
src/pipecat/services/piper/tts.py
View File

@@ -227,6 +227,5 @@ class PiperHttpTTSService(TTSService):
except Exception as e:
yield ErrorFrame(error=f"Unknown error occurred: {e}")
finally:
logger.debug(f"{self}: Finished TTS [{text}]")
await self.stop_ttfb_metrics()
yield TTSStoppedFrame()

633
uv.lock generated
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