import requests
import gradio as gr
import os
import time
from pytubefix import YouTube
from moviepy.editor import VideoFileClip
from transformers import pipeline

# Whisper model
asr = pipeline("automatic-speech-recognition", model="distil-whisper/distil-small.en")

# Summarization model
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")

# Function to fetch PO Token from the Node.js server
def get_po_token():
    try:
        response = requests.get("http://localhost:3001/get-token")  # Call Node.js API
        response.raise_for_status()
        return response.json().get("poToken")  # Extract token
    except Exception as e:
        print(f"Error fetching PO token: {e}")
        return None  # Return None if the request fails

def process_youtube_link(youtube_url):
    try:
        print(f"Received YouTube URL: {youtube_url}")  # Debugging

        po_token = get_po_token()
        if not po_token:
            return "Error: Unable to fetch PO token.", ""

        # Use the token with pytubefix
        yt = YouTube(youtube_url, po_token=po_token)
        title = yt.title
        print(f"Downloading: {title}")

        ys = yt.streams.get_highest_resolution()
        video_path = f"{title}.mp4"
        ys.download(filename=video_path)

        # Log download success
        if os.path.exists(video_path):
            print(f"Download successful: {video_path}")
            print("Files in current directory:", os.listdir("."))
        else:
            print("Download failed!")

        # Extract Audio
        audio_path = f"{title}.wav"
        video = VideoFileClip(video_path)
        video.audio.write_audiofile(audio_path, codec="pcm_s16le")

        # Transcribe Audio
        transcription = asr(audio_path, return_timestamps=True)
        transcribed_text = transcription["text"]

        # Summarize Transcription
        summary = summarizer(transcribed_text, max_length=150, min_length=50, do_sample=False)[0]["summary_text"]

        return transcribed_text, summary

    except Exception as e:
        print(f"Error: {str(e)}")  # Log errors
        return f"Error: {str(e)}", ""

# Gradio Interface
iface = gr.Interface(
    fn=process_youtube_link,
    inputs=gr.Textbox(label="Enter YouTube URL"),
    outputs=[gr.Textbox(label="Transcription"), gr.Textbox(label="Summary")],
    title="YouTube Video Summarizer",
    description="Enter a YouTube link, and this app will summarize the content of the video.",
)

iface.launch()