import time
from http import HTTPStatus
from dashscope.audio.asr import Recognition

# 若没有将API Key配置到环境变量中，需将下面这行代码注释放开，并将apiKey替换为自己的API Key
import dashscope
dashscope.api_key = "sk-92f2fec23dc94de49a31c9945d04e5f7"

# 使用本地已有的wav文件
audio_file = 'asr_example.wav'

print(f'开始识别文件: {audio_file}')
start_time = time.time()

recognition = Recognition(model='paraformer-realtime-v2',
                          format='wav',
                          sample_rate=16000,
                          # "language_hints"只支持paraformer-v2和paraformer-realtime-v2模型
                          language_hints=['zh', 'en'],
                          callback=None)
result = recognition.call(audio_file)

end_time = time.time()
elapsed_time = end_time - start_time

if result.status_code == HTTPStatus.OK:
    print('识别结果：')
    print(result.get_sentence())
    print(f'\n识别耗时: {elapsed_time:.3f} 秒')
    print(f'开始时间: {time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(start_time))}')
    print(f'结束时间: {time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(end_time))}')
else:
    print('Error: ', result.message)
    print(f'识别失败，耗时: {elapsed_time:.3f} 秒')