app.py

import gradio as gr
import whisper
import os

model = whisper.load_model("tiny")

# main processing
def main(URL):
    video_path = youtube_dl(URL)
    text = transcript(video_path)
    return text

# Transcribe text using Whisper
def transcript(video_path):
    result = model.transcribe(video_path)
    return result["text"]

# Download the video
def youtube_dl(URL):
    # Download the video
    os.system(f"yt-dlp -f best -v {URL} -o target.mp4")
    # Path of downloaded video
    video_path = os.path.join(os.path.dirname(__file__), "target.mp4")
    return video_path

demo = gr.Interface(fn = main,
                    inputs = "text", outputs = "text")

if __name__ == "__main__":
    demo.launch()