60 lines
1.5 KiB
Python
60 lines
1.5 KiB
Python
#encoding = utf8
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import logging
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from asr import AsrObserver
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from utils import AsyncTaskQueue
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logger = logging.getLogger(__name__)
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class NLPBase(AsrObserver):
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def __init__(self, context, split, callback=None):
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self._ask_queue = AsyncTaskQueue()
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self._context = context
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self._split_handle = split
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self._callback = callback
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self._is_running = False
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@property
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def callback(self):
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return self._callback
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@callback.setter
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def callback(self, value):
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self._callback = value
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def _on_callback(self, txt: str):
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if self._callback is not None and self._is_running:
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self._callback.on_message(txt)
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async def _request(self, question):
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pass
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async def _on_close(self):
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pass
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def process(self, message: str):
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pass
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def completed(self, message: str):
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logger.info(f'complete:{message}')
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# self._context.pause_talk()
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self.ask(message)
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def ask(self, question):
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logger.info(f'ask:{question}')
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self._is_running = True
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self._ask_queue.add_task(self._request, question)
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logger.info(f'ask:{question} completed')
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def stop(self):
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logger.info('NLPBase stop')
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self._is_running = False
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self._ask_queue.add_task(self._on_close)
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self._ask_queue.stop()
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def pause_talk(self):
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logger.info('NLPBase pause_talk')
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self._is_running = False
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self._ask_queue.clear()
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