import os
import gradio as gr
from dotenv import load_dotenv
import google.generativeai as genai
from youtube_transcript_api import YouTubeTranscriptApi

# Load environment variables
load_dotenv()
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
genai.configure(api_key=GEMINI_API_KEY)

def get_video_id(url):
    video_id = url.split("=")[-1]
    if "&" in video_id:
        video_id = video_id.split("&")[0]
    return video_id

def get_video_transcripts(video_id):
    try:
        transcription_list = YouTubeTranscriptApi.get_transcript(video_id)
        transcription = " ".join([transcript["text"] for transcript in transcription_list])
        return transcription
    except Exception as e:
        return str(e)

def summarize_video(youtube_url):
    video_id = get_video_id(youtube_url)
    transcriptions = get_video_transcripts(video_id)
    # Initialize the gemini-pro model and generate summary here (simplified)
    gemini_model = genai.GenerativeModel("gemini-pro")
    prompt = f"Summarize the following transcription:\n{transcriptions}"
    summary = gemini_model.generate_content(prompt).text
    return summary

iface = gr.Interface(fn=summarize_video, inputs="text", outputs="text", title="YouTube Video Summarizer", description="Enter a YouTube URL to get a summary.")

if __name__ == "__main__":
    iface.launch(share=True)  # Set share=True to get a public link