import time import os from config.logger import setup_logging from typing import Optional, Tuple, List from core.providers.asr.dto.dto import InterfaceType from core.providers.asr.base import ASRProviderBase import requests TAG = __name__ logger = setup_logging() class ASRProvider(ASRProviderBase): def __init__(self, config: dict, delete_audio_file: bool): self.interface_type = InterfaceType.NON_STREAM self.api_key = config.get("api_key") self.api_url = config.get("base_url") self.model = config.get("model_name") self.output_dir = config.get("output_dir") self.delete_audio_file = delete_audio_file os.makedirs(self.output_dir, exist_ok=True) async def speech_to_text(self, opus_data: List[bytes], session_id: str, audio_format="opus") -> Tuple[Optional[str], Optional[str]]: file_path = None try: start_time = time.time() if audio_format == "pcm": pcm_data = opus_data else: pcm_data = self.decode_opus(opus_data) file_path = self.save_audio_to_file(pcm_data, session_id) logger.bind(tag=TAG).debug( f"音频文件保存耗时: {time.time() - start_time:.3f}s | 路径: {file_path}" ) logger.bind(tag=TAG).info(f"file path: {file_path}") headers = { "Authorization": f"Bearer {self.api_key}", } # 使用data参数传递模型名称 data = { "model": self.model } with open(file_path, "rb") as audio_file: # 使用with语句确保文件关闭 files = { "file": audio_file } start_time = time.time() response = requests.post( self.api_url, files=files, data=data, headers=headers ) logger.bind(tag=TAG).debug( f"语音识别耗时: {time.time() - start_time:.3f}s | 结果: {response.text}" ) if response.status_code == 200: text = response.json().get("text", "") return text, file_path else: raise Exception(f"API请求失败: {response.status_code} - {response.text}") except Exception as e: logger.bind(tag=TAG).error(f"语音识别失败: {e}") return "", None finally: # 文件清理逻辑 if self.delete_audio_file and file_path and os.path.exists(file_path): try: os.remove(file_path) logger.bind(tag=TAG).debug(f"已删除临时音频文件: {file_path}") except Exception as e: logger.bind(tag=TAG).error(f"文件删除失败: {file_path} | 错误: {e}")