mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
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71 lines
2.3 KiB
Python
71 lines
2.3 KiB
Python
import time
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import os
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from config.logger import setup_logging
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from typing import Optional, Tuple, List
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from core.providers.asr.dto.dto import InterfaceType
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from core.providers.asr.base import ASRProviderBase
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import requests
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TAG = __name__
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logger = setup_logging()
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class ASRProvider(ASRProviderBase):
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def __init__(self, config: dict, delete_audio_file: bool):
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self.interface_type = InterfaceType.NON_STREAM
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self.api_key = config.get("api_key")
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self.api_url = config.get("base_url")
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self.model = config.get("model_name")
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self.output_dir = config.get("output_dir")
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self.delete_audio_file = delete_audio_file
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os.makedirs(self.output_dir, exist_ok=True)
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def requires_file(self) -> bool:
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return True
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async def speech_to_text(self, opus_data: List[bytes], session_id: str, artifacts=None) -> Tuple[Optional[str], Optional[str]]:
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file_path = None
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try:
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if artifacts is None:
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return "", None
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file_path = artifacts.file_path
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logger.bind(tag=TAG).info(f"file path: {file_path}")
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headers = {
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"Authorization": f"Bearer {self.api_key}",
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}
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# 使用data参数传递模型名称
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data = {
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"model": self.model
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}
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with open(file_path, "rb") as audio_file: # 使用with语句确保文件关闭
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files = {
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"file": audio_file
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}
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start_time = time.time()
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response = requests.post(
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self.api_url,
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files=files,
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data=data,
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headers=headers
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)
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logger.bind(tag=TAG).debug(
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f"语音识别耗时: {time.time() - start_time:.3f}s | 结果: {response.text}"
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)
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if response.status_code == 200:
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text = response.json().get("text", "")
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return text, file_path
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else:
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raise Exception(f"API请求失败: {response.status_code} - {response.text}")
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except Exception as e:
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logger.bind(tag=TAG).error(f"语音识别失败: {e}")
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return "", None
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