import gradio as gr
import whisper
import ffmpeg
import streamlit.components.v1 as components


def transcribe_audio(audio_file):
    model = whisper.load_model("small")
    result = model.transcribe(audio_file, fp16=False)
    return result["text"]



# def inference():
#     html = (
#             "<div >"
#             "<img  src='file/logo-digitalix.png' alt='image One'>"
#             + "</div>"
#     )
#     return html

def main():
    audio_input = gr.inputs.Audio(source="upload", type="filepath")
    output_text = gr.outputs.Textbox()
    logo_html = '<img src="logo-digitalix.png" alt="Logo" width="50px">'  # Balise HTML pour le logo

    # Créer un composant Streamlit avec le logo
    components.html(logo_html)
    iface = gr.Interface(fn=transcribe_audio, inputs=audio_input, 
                         outputs=output_text, title="Transciption Audio DIGITALIXSA",
                         description="Charger l'audio")
    
    iface.launch(auth=("admin", "pass1234"))


if __name__ == '__main__':
    main()

#