76 lines
2.5 KiB
Python
76 lines
2.5 KiB
Python
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import asyncio
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from http import HTTPStatus
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from dashscope.audio.asr import Recognition
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import dashscope
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import logging
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from Config import Config
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# 初始化日志记录器
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logger = logging.getLogger(__name__)
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# 若没有配置环境变量，请用百炼API Key将下行替换为：dashscope.api_key = "sk-xxx"
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dashscope.api_key = Config.ALY_LLM_API_KEY
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class ASRClient:
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"""
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阿里云语音识别客户端，用于处理语音文件的转写任务
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使用 Recognition API 支持本地文件实时转写
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"""
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def __init__(self, api_key=None):
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"""
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初始化ASR客户端
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Args:
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api_key: 阿里云DashScope API密钥，若不提供则使用配置文件中的密钥
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"""
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logger.info("开始初始化ASR客户端")
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try:
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self.api_key = api_key or Config.ALY_LLM_API_KEY
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dashscope.api_key = self.api_key
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logger.info("ASR客户端初始化完成")
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except Exception as e:
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logger.error(f"初始化ASR客户端失败: {str(e)}", exc_info=True)
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raise
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async def transcribe_file(self, file_path):
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"""
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转写本地音频文件
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Args:
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file_path: 本地音频文件路径
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Returns:
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str: 转写后的文本，如果失败返回None
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"""
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logger.info(f"开始转写文件: {file_path}")
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try:
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recognition = Recognition(
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model='paraformer-realtime-v1',
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format='mp3',
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sample_rate=16000,
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callback=None
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)
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# Run blocking call in executor
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loop = asyncio.get_running_loop()
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result = await loop.run_in_executor(None, lambda: recognition.call(file_path))
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if result.status_code == HTTPStatus.OK:
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sentences = []
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if 'sentence' in result.output:
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for s in result.output['sentence']:
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sentences.append(s['text'])
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text = "".join(sentences)
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logger.info("转写成功")
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return text
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else:
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logger.error(f"转写失败: {result.code} - {result.message}")
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return None
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except Exception as e:
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logger.error(f"转写过程出错: {str(e)}", exc_info=True)
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return None
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