96 lines
2.9 KiB
Python
96 lines
2.9 KiB
Python
"""Backend-agnostic streaming adapter from LLM text to TTS audio."""
|
||
|
||
import asyncio
|
||
|
||
from loguru import logger
|
||
|
||
from services.base import BaseTTSService
|
||
from services.streaming_text import extract_tts_sentence, has_spoken_content
|
||
|
||
|
||
class StreamingTTSAdapter:
|
||
"""
|
||
Adapter for streaming LLM text to TTS with sentence-level chunking.
|
||
|
||
This reduces latency by starting TTS as soon as a complete sentence
|
||
is received from the LLM, rather than waiting for the full response.
|
||
"""
|
||
|
||
SENTENCE_ENDS = {"。", "！", "？", ".", "!", "?", "\n"}
|
||
SENTENCE_CLOSERS = frozenset()
|
||
|
||
def __init__(self, tts_service: BaseTTSService, transport, session_id: str):
|
||
self.tts_service = tts_service
|
||
self.transport = transport
|
||
self.session_id = session_id
|
||
self._buffer = ""
|
||
self._cancel_event = asyncio.Event()
|
||
self._is_speaking = False
|
||
|
||
async def process_text_chunk(self, text_chunk: str) -> None:
|
||
"""
|
||
Process a text chunk from LLM and trigger TTS when sentence is complete.
|
||
|
||
Args:
|
||
text_chunk: Text chunk from LLM streaming
|
||
"""
|
||
if self._cancel_event.is_set():
|
||
return
|
||
|
||
self._buffer += text_chunk
|
||
|
||
# Check for sentence completion
|
||
while True:
|
||
split_result = extract_tts_sentence(
|
||
self._buffer,
|
||
end_chars=frozenset(self.SENTENCE_ENDS),
|
||
trailing_chars=frozenset(self.SENTENCE_ENDS),
|
||
closers=self.SENTENCE_CLOSERS,
|
||
force=False,
|
||
)
|
||
if not split_result:
|
||
break
|
||
|
||
sentence, self._buffer = split_result
|
||
if sentence and has_spoken_content(sentence):
|
||
await self._speak_sentence(sentence)
|
||
|
||
async def flush(self) -> None:
|
||
"""Flush remaining buffer."""
|
||
if self._buffer.strip() and not self._cancel_event.is_set():
|
||
await self._speak_sentence(self._buffer.strip())
|
||
self._buffer = ""
|
||
|
||
async def _speak_sentence(self, text: str) -> None:
|
||
"""Synthesize and send a sentence."""
|
||
if not text or self._cancel_event.is_set():
|
||
return
|
||
|
||
self._is_speaking = True
|
||
|
||
try:
|
||
async for chunk in self.tts_service.synthesize_stream(text):
|
||
if self._cancel_event.is_set():
|
||
break
|
||
await self.transport.send_audio(chunk.audio)
|
||
await asyncio.sleep(0.01) # Prevent flooding
|
||
except Exception as e:
|
||
logger.error(f"TTS speak error: {e}")
|
||
finally:
|
||
self._is_speaking = False
|
||
|
||
def cancel(self) -> None:
|
||
"""Cancel ongoing speech."""
|
||
self._cancel_event.set()
|
||
self._buffer = ""
|
||
|
||
def reset(self) -> None:
|
||
"""Reset for new turn."""
|
||
self._cancel_event.clear()
|
||
self._buffer = ""
|
||
self._is_speaking = False
|
||
|
||
@property
|
||
def is_speaking(self) -> bool:
|
||
return self._is_speaking
|