main.py

import whisper



def whisper_(input_audio):
    model = whisper.load_model("medium")
    
    # load audio and pad/trim it to fit 30 seconds
    audio = whisper.load_audio(input_audio)
    audio = whisper.pad_or_trim(audio)
    # make log-Mel spectrogram and move to the same device as the model
    mel = whisper.log_mel_spectrogram(audio, n_mels=model.dims.n_mels).to(model.device)
    
    # detect the spoken language
    _, probs = model.detect_language(mel)
    print(f"Detected language: {max(probs, key=probs.get)}")
    
    # decode the audio
    options = whisper.DecodingOptions()
    result = whisper.decode(model, mel, options)
    # print the recognized text
    
    text_result = result.text
    return text_result