import gradio as gr
from utils import SpeechRecognition

sp = SpeechRecognition()

sp.load_model()

#sample_file = "assets/samples/sample1378.flac"

def recognition(audio_file):
    print("audio_file", audio_file.name)
    speech, rate = sp.load_speech_with_file(audio_file.name)
    
    result = sp.predict_audio_file(speech)
    print(result)

    return result

inputs = gr.inputs.Audio(label="Input Audio", type="file")

outputs = "text"
title = "Turkish Automatic Speech Recognition"
description = "Demo for Turkish Automatic Speech Recognition with Huggingface wav2vec Turkish Model. To use it, simply upload your audio, or click one of the examples to load them."
article = "<p style='text-align: center'>This is the model for <a href='https://huggingface.co/m3hrdadfi/wav2vec2-large-xlsr-turkish' target='_blank'>m3hrdadfi/wav2vec2-large-xlsr-turkish</a>, a fine-tuned <a href='https://huggingface.co/facebook/wav2vec2-large-xlsr-53' target='_blank'>facebook/wav2vec2-large-xlsr-53</a> model on the <a href='https://commonvoice.mozilla.org/en/datasets' target='_blank'>Turkish Common Voice dataset</a>.<br/>When using this model, make sure that your speech input is sampled at 16kHz.</a></p>"
examples = [
    ['assets/samples/common_voice_sample_1378.flac'],
    ['assets/samples/common_voice_sample_1589.flac'],
    ['assets/samples/baris_ozcan_sample_1.m4a'],
    ['assets/samples/baris_ozcan_sample_2.wav'],
    ['assets/samples/baris_ozcan_sample_3.m4a']
]

gr.Interface(recognition, inputs, outputs, title=title, description=description, article=article, examples=examples).launch()