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import soundfile as sf
import torch
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
import gradio as gr
import sox

def convert(inputfile, outfile):
    sox_tfm = sox.Transformer()
    sox_tfm.set_output_format(
        file_type="wav", channels=1, encoding="signed-integer", rate=16000, bits=16
    )
    sox_tfm.build(inputfile, outfile)
    
    
    
processor = Wav2Vec2Processor.from_pretrained("facebook/wav2vec2-base-960h")
model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-base-960h")

def parse_transcription(wav_file):
    filename = wav_file.name.split('.')[0]
    convert(wav_file.name, filename + "16k.wav")
    speech, _ = sf.read(filename + "16k.wav")
    input_values = processor(speech, sampling_rate=16_000, return_tensors="pt").input_values
    logits = model(input_values).logits
    predicted_ids = torch.argmax(logits, dim=-1)
    transcription = processor.decode(predicted_ids[0], skip_special_tokens=True)
    return transcription,



output1 = gr.outputs.Textbox(label="Transcription in English: ")
output2 = gr.outputs.Textbox(label="Validated Transcription in English")
    
input_ = gr.inputs.Audio(source="microphone", type="file") 
#gr.Interface(parse_transcription, inputs = input_,  outputs="text", 
#             analytics_enabled=False, show_tips=False, enable_queue=True).launch(inline=False);
             
gr.Interface(parse_transcription, inputs = input_,  outputs=[output1, output2], analytics_enabled=False, 
                                                                            show_tips=False, 
                                                                            theme='huggingface',
                                                                            layout='vertical',
                                                                            title="Piecurus Test on Speech Transcription",
                                                                            description="This is a live demo for Speech to Text Translation. Models used: facebook/wav2vec2-base-960h", enable_queue=True).launch( inline=False)