import gradio as gr
import whisper
from pytube import YouTube

loaded_model = whisper.load_model("base")

def inference(link):
  yt = YouTube(link)
  path = yt.streams.filter(only_audio=True)[0].download(filename="audio.mp4")
  options = whisper.DecodingOptions(without_timestamps=True)
  results = loaded_model.transcribe(path)
  return results['text']

def change_model(size):
  loaded_model = whisper.load_model(size)

title="Youtube Whisperer"
description="Speech to text transcription of Youtube videos using OpenAI's Whisper"
block = gr.Blocks()

with block:
    gr.HTML(
        """
            <div style="text-align: center; max-width: 500px; margin: 0 auto;">
              <div>
                <h1>Youtube Whisperer</h1>
              </div>
              <p style="margin-bottom: 10px; font-size: 94%">
                Speech to text transcription of Youtube videos using OpenAI's Whisper
              </p>
            </div>
        """
    )
    with gr.Group():
        with gr.Box():
          sz = gr.Dropdown(label="Model Size", choices=['base','small', 'medium', 'large'], value='base')
          sz.change(change_model, inputs=[sz], outputs=[])
          link = gr.Textbox(label="YouTube Link")
          text = gr.Textbox(
              label="Transcription", 
              placeholder="Transcription Output",
              lines=5)
          with gr.Row().style(mobile_collapse=False, equal_height=True): 
              btn = gr.Button("Transcribe")       
              btn.click(inference, inputs=[link], outputs=[text])

block.launch()