import gradio as gr
import yt_dlp
import whisper
import os

# Load Whisper model
model = whisper.load_model("base")

def download_audio(url):
    ydl_opts = {
        'format': 'bestaudio/best',
        'outtmpl': '/tmp/audio.%(ext)s',  # Use /tmp directory for outputs
        'postprocessors': [{
            'key': 'FFmpegExtractAudio',
            'preferredcodec': 'mp3',
            'preferredquality': '192',
        }],
    }
    try:
        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
            info_dict = ydl.extract_info(url, download=True)
            audio_file = ydl.prepare_filename(info_dict).replace('.webm', '.mp3').replace('.m4a', '.mp3')
        return audio_file
    except yt_dlp.utils.DownloadError as e:
        return f"Download Error: {str(e)}"
    except Exception as e:
        return f"An unexpected error occurred: {str(e)}"

def transcribe_audio(audio_file):
    result = model.transcribe(audio_file)
    return result["text"]

def process_video(url):
    try:
        audio_file = download_audio(url)
        if "Error" in audio_file:
            return audio_file  # Return error message if download failed
        transcript = transcribe_audio(audio_file)
        os.remove(audio_file)  # Clean up the audio file
        return transcript
    except Exception as e:
        return f"An error occurred: {str(e)}"

# Gradio Interface
iface = gr.Interface(
    fn=process_video,
    inputs=gr.Textbox(value="https://www.youtube.com/watch?v=RiI1NkaDXlQ", label="YouTube Video URL"),
    outputs=gr.Textbox(label="Transcript"),
    title="YouTube Video Transcriber",
    description="Enter a YouTube video URL to get a transcript of its content."
)

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