from transformers import WhisperProcessor, WhisperForConditionalGeneration
import torchaudio


# load model and processor
processor = WhisperProcessor.from_pretrained("openai/whisper-tiny")
model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny")
model.config.forced_decoder_ids = None


def audio_to_text(file_path_abs):
    # Load the audio and resample it
    waveform, sample_rate = torchaudio.load(file_path_abs)
    resampler = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=16000)
    waveform = resampler(waveform)
    waveform = waveform.squeeze().numpy()
    input_features = processor(waveform, sampling_rate=16000, return_tensors="pt").input_features

    # generate token ids
    predicted_ids = model.generate(input_features)
    # decode token ids to text
    transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
    return transcription