Refactor duplicate stream tts adapter
This commit is contained in:
Xin Wang
@@ -17,6 +17,7 @@ from services.tts import EdgeTTSService, MockTTSService
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from services.asr import BufferedASRService, MockASRService
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from services.siliconflow_asr import SiliconFlowASRService
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from services.siliconflow_tts import SiliconFlowTTSService
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from services.streaming_tts_adapter import StreamingTTSAdapter
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from services.realtime import RealtimeService, RealtimeConfig, RealtimePipeline
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__all__ = [
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@@ -40,6 +41,7 @@ __all__ = [
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"SiliconFlowASRService",
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# TTS (SiliconFlow)
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"SiliconFlowTTSService",
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"StreamingTTSAdapter",
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# Realtime
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"RealtimeService",
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"RealtimeConfig",
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@@ -13,6 +13,7 @@ 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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from services.streaming_tts_adapter import StreamingTTSAdapter # backward-compatible re-export
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class SiliconFlowTTSService(BaseTTSService):
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@@ -192,119 +193,3 @@ class SiliconFlowTTSService(BaseTTSService):
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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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def _is_non_sentence_period(self, text: str, idx: int) -> bool:
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"""Check whether '.' should NOT be treated as a sentence delimiter."""
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if text[idx] != ".":
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return False
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# Decimal/version segment: 1.2, v1.2.3
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if idx > 0 and idx < len(text) - 1 and text[idx - 1].isdigit() and text[idx + 1].isdigit():
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return True
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# Number abbreviations: No.1 / No. 1
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left_start = idx - 1
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while left_start >= 0 and text[left_start].isalpha():
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left_start -= 1
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left_token = text[left_start + 1:idx].lower()
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if left_token == "no":
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j = idx + 1
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while j < len(text) and text[j].isspace():
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j += 1
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if j < len(text) and text[j].isdigit():
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return True
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return 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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while True:
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split_idx = -1
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for i, char in enumerate(self._buffer):
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if char == "." and self._is_non_sentence_period(self._buffer, i):
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continue
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if char in self.SENTENCE_ENDS:
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split_idx = i
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break
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if split_idx < 0:
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break
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end_idx = split_idx + 1
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while end_idx < len(self._buffer) and self._buffer[end_idx] in self.SENTENCE_ENDS:
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end_idx += 1
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sentence = self._buffer[:end_idx].strip()
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self._buffer = self._buffer[end_idx:]
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if sentence and any(ch.isalnum() for ch in sentence):
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await self._speak_sentence(sentence)
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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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86
engine/services/streaming_text.py
Normal file
86
engine/services/streaming_text.py
Normal file
@@ -0,0 +1,86 @@
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"""Shared text chunking helpers for streaming TTS."""
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from typing import Optional
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def is_non_sentence_period(text: str, idx: int) -> bool:
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"""Check whether '.' should NOT be treated as a sentence delimiter."""
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if idx < 0 or idx >= len(text) or text[idx] != ".":
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return False
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# Decimal/version segment: 1.2, v1.2.3
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if idx > 0 and idx < len(text) - 1 and text[idx - 1].isdigit() and text[idx + 1].isdigit():
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return True
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# Number abbreviations: No.1 / No. 1
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left_start = idx - 1
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while left_start >= 0 and text[left_start].isalpha():
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left_start -= 1
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left_token = text[left_start + 1:idx].lower()
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if left_token == "no":
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j = idx + 1
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while j < len(text) and text[j].isspace():
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j += 1
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if j < len(text) and text[j].isdigit():
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return True
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return False
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def has_spoken_content(text: str) -> bool:
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"""Check whether text contains pronounceable content (not punctuation-only)."""
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return any(char.isalnum() for char in text)
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def extract_tts_sentence(
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text_buffer: str,
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*,
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end_chars: frozenset[str],
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trailing_chars: frozenset[str],
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closers: frozenset[str],
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min_split_spoken_chars: int = 0,
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hold_trailing_at_buffer_end: bool = False,
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force: bool = False,
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) -> Optional[tuple[str, str]]:
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"""Extract one TTS sentence from text buffer."""
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if not text_buffer:
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return None
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search_start = 0
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while True:
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split_idx = -1
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for idx in range(search_start, len(text_buffer)):
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char = text_buffer[idx]
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if char == "." and is_non_sentence_period(text_buffer, idx):
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continue
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if char in end_chars:
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split_idx = idx
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break
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if split_idx == -1:
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return None
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end_idx = split_idx + 1
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while end_idx < len(text_buffer) and text_buffer[end_idx] in trailing_chars:
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end_idx += 1
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while end_idx < len(text_buffer) and text_buffer[end_idx] in closers:
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end_idx += 1
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if hold_trailing_at_buffer_end and not force and end_idx >= len(text_buffer):
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return None
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sentence = text_buffer[:end_idx].strip()
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spoken_chars = sum(1 for ch in sentence if ch.isalnum())
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if (
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not force
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and min_split_spoken_chars > 0
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and 0 < spoken_chars < min_split_spoken_chars
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and end_idx < len(text_buffer)
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):
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search_start = end_idx
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continue
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remainder = text_buffer[end_idx:]
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return sentence, remainder
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95
engine/services/streaming_tts_adapter.py
Normal file
95
engine/services/streaming_tts_adapter.py
Normal file
@@ -0,0 +1,95 @@
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"""Backend-agnostic streaming adapter from LLM text to TTS audio."""
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import asyncio
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from loguru import logger
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from services.base import BaseTTSService
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from services.streaming_text import extract_tts_sentence, has_spoken_content
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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_ENDS = {"。", "！", "？", ".", "!", "?", "\n"}
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SENTENCE_CLOSERS = frozenset()
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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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while True:
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split_result = extract_tts_sentence(
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self._buffer,
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end_chars=frozenset(self.SENTENCE_ENDS),
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trailing_chars=frozenset(self.SENTENCE_ENDS),
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closers=self.SENTENCE_CLOSERS,
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force=False,
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)
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if not split_result:
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break
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sentence, self._buffer = split_result
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if sentence and has_spoken_content(sentence):
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await self._speak_sentence(sentence)
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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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