108 lines
3.3 KiB
Python
108 lines
3.3 KiB
Python
#
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# Copyright (c) 2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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from typing import AsyncGenerator, Optional
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import aiohttp
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from loguru import logger
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from pydantic import BaseModel
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from pipecat.frames.frames import (
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ErrorFrame,
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Frame,
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TTSAudioRawFrame,
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TTSStartedFrame,
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TTSStoppedFrame,
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)
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from pipecat.services.ai_services import TTSService
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class RimeHttpTTSService(TTSService):
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class InputParams(BaseModel):
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pause_between_brackets: Optional[bool] = False
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phonemize_between_brackets: Optional[bool] = False
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inline_speed_alpha: Optional[str] = None
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speed_alpha: Optional[float] = 1.0
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reduce_latency: Optional[bool] = False
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def __init__(
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self,
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*,
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api_key: str,
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voice_id: str = "eva",
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model: str = "mist",
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sample_rate: int = 24000,
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params: InputParams = InputParams(),
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**kwargs,
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):
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super().__init__(sample_rate=sample_rate, **kwargs)
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self._api_key = api_key
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self._base_url = "https://users.rime.ai/v1/rime-tts"
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self._settings = {
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"speaker": voice_id,
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"modelId": model,
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"samplingRate": sample_rate,
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"speedAlpha": params.speed_alpha,
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"reduceLatency": params.reduce_latency,
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"pauseBetweenBrackets": params.pause_between_brackets,
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"phonemizeBetweenBrackets": params.phonemize_between_brackets,
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}
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if params.inline_speed_alpha:
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self._settings["inlineSpeedAlpha"] = params.inline_speed_alpha
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def can_generate_metrics(self) -> bool:
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return True
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async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
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logger.debug(f"Generating TTS: [{text}]")
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headers = {
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"Accept": "audio/pcm",
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"Authorization": f"Bearer {self._api_key}",
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"Content-Type": "application/json",
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}
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payload = self._settings.copy()
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payload["text"] = text
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try:
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await self.start_ttfb_metrics()
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await self.start_tts_usage_metrics(text)
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yield TTSStartedFrame()
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async with aiohttp.ClientSession() as session:
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async with session.post(self._base_url, json=payload, headers=headers) as response:
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if response.status != 200:
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error_message = f"Rime TTS error: HTTP {response.status}"
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logger.error(error_message)
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yield ErrorFrame(error=error_message)
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return
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# Process the streaming response
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chunk_size = 8192
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first_chunk = True
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async for chunk in response.content.iter_chunked(chunk_size):
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if first_chunk:
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await self.stop_ttfb_metrics()
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first_chunk = False
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if chunk:
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frame = TTSAudioRawFrame(chunk, self._settings["samplingRate"], 1)
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yield frame
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yield TTSStoppedFrame()
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except Exception as e:
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logger.exception(f"Error generating TTS: {e}")
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yield ErrorFrame(error=f"Rime TTS error: {str(e)}")
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finally:
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yield TTSStoppedFrame()
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