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from .pipelines import WhisperPipe, MetaItem, WhisperChinese, Translate7BPipe, FunASRPipe, VadPipe, TranslatePipe
from .utils import timer
class ProcessingPipes:
def __init__(self) -> None:
self._process = []
# whisper 转录
self._whisper_pipe_en = self._launch_process(WhisperPipe())
# self._whisper_pipe_zh = self._launch_process(WhisperChinese())
self._funasr_pipe = self._launch_process(FunASRPipe())
# llm 翻译
self._translate_pipe = self._launch_process(TranslatePipe())
self._translate_7b_pipe = self._launch_process(Translate7BPipe())
# vad
self._vad_pipe = self._launch_process(VadPipe())
def _launch_process(self, process_obj):
process_obj.daemon = True
process_obj.start()
self._process.append(process_obj)
return process_obj
def wait_ready(self):
for p in self._process:
p.wait()
@timer(name="🐧 Translate")
def translate(self, text, src_lang, dst_lang) -> MetaItem:
item = MetaItem(
transcribe_content=text,
source_language=src_lang,
destination_language=dst_lang)
self._translate_pipe.input_queue.put(item)
return self._translate_pipe.output_queue.get()
@timer(name="🐧 Translate-large")
def translate_large(self, text, src_lang, dst_lang) -> MetaItem:
item = MetaItem(
transcribe_content=text,
source_language=src_lang,
destination_language=dst_lang)
self._translate_7b_pipe.input_queue.put(item)
return self._translate_7b_pipe.output_queue.get()
def get_transcription_model(self, lang: str = 'en'):
if lang == 'zh':
return self._funasr_pipe
return self._whisper_pipe_en
@timer(name="📝 transcribe")
def transcribe(self, audio_buffer: bytes, src_lang: str) -> MetaItem:
transcription_model = self.get_transcription_model(src_lang)
item = MetaItem(audio=audio_buffer, source_language=src_lang)
transcription_model.input_queue.put(item)
return transcription_model.output_queue.get()
def voice_detect(self, audio_buffer: bytes) -> MetaItem:
item = MetaItem(source_audio=audio_buffer)
self._vad_pipe.input_queue.put(item)
return self._vad_pipe.output_queue.get()
if __name__ == "__main__":
import soundfile
tp = TranslatePipes()
# result = tp.translate("你好，今天天气怎么样?", src_lang="zh", dst_lang="en")
mel, _, = soundfile.read("assets/jfk.flac")
# result = tp.transcribe(mel, 'en')
result = tp.voice_detect(mel)
print(result)
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