256 lines
8.5 KiB
Python
256 lines
8.5 KiB
Python
"""SiliconFlow TTS Service with streaming support.
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Uses SiliconFlow's CosyVoice2 or MOSS-TTSD models for low-latency
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text-to-speech synthesis with streaming.
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API Docs: https://docs.siliconflow.cn/cn/api-reference/audio/create-speech
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"""
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import os
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import asyncio
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import aiohttp
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from typing import AsyncIterator, Optional
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from loguru import logger
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from services.base import BaseTTSService, TTSChunk, ServiceState
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class SiliconFlowTTSService(BaseTTSService):
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"""
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SiliconFlow TTS service with streaming support.
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Supports CosyVoice2-0.5B and MOSS-TTSD-v0.5 models.
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"""
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# Available voices
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VOICES = {
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"alex": "FunAudioLLM/CosyVoice2-0.5B:alex",
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"anna": "FunAudioLLM/CosyVoice2-0.5B:anna",
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"bella": "FunAudioLLM/CosyVoice2-0.5B:bella",
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"benjamin": "FunAudioLLM/CosyVoice2-0.5B:benjamin",
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"charles": "FunAudioLLM/CosyVoice2-0.5B:charles",
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"claire": "FunAudioLLM/CosyVoice2-0.5B:claire",
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"david": "FunAudioLLM/CosyVoice2-0.5B:david",
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"diana": "FunAudioLLM/CosyVoice2-0.5B:diana",
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}
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def __init__(
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self,
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api_key: Optional[str] = None,
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voice: str = "anna",
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model: str = "FunAudioLLM/CosyVoice2-0.5B",
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sample_rate: int = 16000,
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speed: float = 1.0
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):
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"""
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Initialize SiliconFlow TTS service.
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Args:
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api_key: SiliconFlow API key (defaults to SILICONFLOW_API_KEY env var)
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voice: Voice name (alex, anna, bella, benjamin, charles, claire, david, diana)
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model: Model name
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sample_rate: Output sample rate (8000, 16000, 24000, 32000, 44100)
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speed: Speech speed (0.25 to 4.0)
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"""
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# Resolve voice name
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if voice in self.VOICES:
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full_voice = self.VOICES[voice]
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else:
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full_voice = voice
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super().__init__(voice=full_voice, sample_rate=sample_rate, speed=speed)
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self.api_key = api_key or os.getenv("SILICONFLOW_API_KEY")
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self.model = model
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self.api_url = "https://api.siliconflow.cn/v1/audio/speech"
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self._session: Optional[aiohttp.ClientSession] = None
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self._cancel_event = asyncio.Event()
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async def connect(self) -> None:
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"""Initialize HTTP session."""
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if not self.api_key:
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raise ValueError("SiliconFlow API key not provided. Set SILICONFLOW_API_KEY env var.")
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self._session = aiohttp.ClientSession(
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headers={
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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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)
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self.state = ServiceState.CONNECTED
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logger.info(f"SiliconFlow TTS service ready: voice={self.voice}, model={self.model}")
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async def disconnect(self) -> None:
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"""Close HTTP session."""
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if self._session:
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await self._session.close()
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self._session = None
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self.state = ServiceState.DISCONNECTED
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logger.info("SiliconFlow TTS service disconnected")
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async def synthesize(self, text: str) -> bytes:
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"""Synthesize complete audio for text."""
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audio_data = b""
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async for chunk in self.synthesize_stream(text):
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audio_data += chunk.audio
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return audio_data
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async def synthesize_stream(self, text: str) -> AsyncIterator[TTSChunk]:
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"""
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Synthesize audio in streaming mode.
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Args:
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text: Text to synthesize
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Yields:
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TTSChunk objects with PCM audio
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"""
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if not self._session:
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raise RuntimeError("TTS service not connected")
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if not text.strip():
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return
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self._cancel_event.clear()
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payload = {
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"model": self.model,
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"input": text,
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"voice": self.voice,
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"response_format": "pcm",
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"sample_rate": self.sample_rate,
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"stream": True,
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"speed": self.speed
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}
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try:
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async with self._session.post(self.api_url, json=payload) as response:
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if response.status != 200:
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error_text = await response.text()
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logger.error(f"SiliconFlow TTS error: {response.status} - {error_text}")
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return
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# Stream audio chunks
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chunk_size = self.sample_rate * 2 // 10 # 100ms chunks
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buffer = b""
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async for chunk in response.content.iter_any():
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if self._cancel_event.is_set():
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logger.info("TTS synthesis cancelled")
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return
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buffer += chunk
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# Yield complete chunks
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while len(buffer) >= chunk_size:
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audio_chunk = buffer[:chunk_size]
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buffer = buffer[chunk_size:]
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yield TTSChunk(
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audio=audio_chunk,
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sample_rate=self.sample_rate,
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is_final=False
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)
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# Yield remaining buffer
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if buffer:
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yield TTSChunk(
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audio=buffer,
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sample_rate=self.sample_rate,
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is_final=True
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)
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except asyncio.CancelledError:
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logger.info("TTS synthesis cancelled via asyncio")
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raise
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except Exception as e:
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logger.error(f"TTS synthesis error: {e}")
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raise
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async def cancel(self) -> None:
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"""Cancel ongoing synthesis."""
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self._cancel_event.set()
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class StreamingTTSAdapter:
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"""
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Adapter for streaming LLM text to TTS with sentence-level chunking.
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This reduces latency by starting TTS as soon as a complete sentence
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is received from the LLM, rather than waiting for the full response.
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"""
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# Sentence delimiters
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SENTENCE_ENDS = {'.', '!', '?', '。', '！', '？', '；', '\n'}
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def __init__(self, tts_service: BaseTTSService, transport, session_id: str):
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self.tts_service = tts_service
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self.transport = transport
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self.session_id = session_id
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self._buffer = ""
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self._cancel_event = asyncio.Event()
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self._is_speaking = False
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async def process_text_chunk(self, text_chunk: str) -> None:
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"""
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Process a text chunk from LLM and trigger TTS when sentence is complete.
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Args:
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text_chunk: Text chunk from LLM streaming
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"""
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if self._cancel_event.is_set():
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return
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self._buffer += text_chunk
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# Check for sentence completion
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for i, char in enumerate(self._buffer):
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if char in self.SENTENCE_ENDS:
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# Found sentence end, synthesize up to this point
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sentence = self._buffer[:i+1].strip()
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self._buffer = self._buffer[i+1:]
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if sentence:
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await self._speak_sentence(sentence)
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break
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async def flush(self) -> None:
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"""Flush remaining buffer."""
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if self._buffer.strip() and not self._cancel_event.is_set():
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await self._speak_sentence(self._buffer.strip())
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self._buffer = ""
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async def _speak_sentence(self, text: str) -> None:
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"""Synthesize and send a sentence."""
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if not text or self._cancel_event.is_set():
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return
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self._is_speaking = True
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try:
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async for chunk in self.tts_service.synthesize_stream(text):
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if self._cancel_event.is_set():
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break
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await self.transport.send_audio(chunk.audio)
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await asyncio.sleep(0.01) # Prevent flooding
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except Exception as e:
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logger.error(f"TTS speak error: {e}")
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finally:
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self._is_speaking = False
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def cancel(self) -> None:
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"""Cancel ongoing speech."""
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self._cancel_event.set()
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self._buffer = ""
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def reset(self) -> None:
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"""Reset for new turn."""
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self._cancel_event.clear()
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self._buffer = ""
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self._is_speaking = False
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@property
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def is_speaking(self) -> bool:
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return self._is_speaking
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