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48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
import os
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from openai import OpenAI
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from .ASRData import ASRDataSeg
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from .BaseASR import BaseASR
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class WhisperASR(BaseASR):
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def __init__(self, audio_path: [str, bytes], model: str = MODEL, use_cache: bool = False):
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super().__init__(audio_path, use_cache)
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self.base_url = os.getenv('OPENAI_BASE_URL')
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self.api_key = os.getenv('OPENAI_API_KEY')
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if not self.base_url or not self.api_key:
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raise ValueError("环境变量 OPENAI_BASE_URL 和 OPENAI_API_KEY 必须设置")
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self.model = model
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self.client = OpenAI(base_url=self.base_url, api_key=self.api_key)
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def _run(self) -> dict:
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return self._submit()
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def _make_segments(self, resp_data: dict) -> list[ASRDataSeg]:
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return [ASRDataSeg(u['text'], u['start'], u['end']) for u in resp_data['segments']]
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def _get_key(self) -> str:
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return f"{self.__class__.__name__}-{self.model}-{self.crc32_hex}-{self.model}"
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def _submit(self) -> dict:
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completion = self.client.audio.transcriptions.create(
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model=self.model,
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temperature=0,
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response_format="verbose_json",
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file=("test.mp3", self.file_binary, "audio/mp3"),
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prompt="",
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language="zh"
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)
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return completion.to_dict()
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if __name__ == '__main__':
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# Example usage
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audio_file = r"test.mp3"
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asr = WhisperASR(audio_file)
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asr_data = asr.run()
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print(asr_data)
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