app.py

import gradio as gr
import whisper
import ffmpeg


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()
    
    iface = gr.Interface(fn=transcribe_audio, inputs=audio_input, 
                         outputs=output_text, title="Transciption Audio DIGITALIXSA",
                         description=inference)
    
    iface.launch(auth=("admin", "pass1234"))


if __name__ == '__main__':
    main()

# description="Charger l'audio")