import gradio as gr
import os
import pandas as pd
from googleapiclient.discovery import build
from transformers import pipeline

# Set up YouTube Data API credentials and initialize
api_key = "AIzaSyBUX6ak7fd2KEh-2aUM_aH26jVEw6Wj5V4"  # Replace with your own API key
youtube = build('youtube', 'v3', developerKey=api_key)

# Initialize sentiment analysis pipeline
sentiment_pipeline = pipeline("sentiment-analysis")

def get_video_comments(video_id, max_length=512):
    comments = []
    next_page_token = None
    
    while True:
        response = youtube.commentThreads().list(
            part='snippet',
            videoId=video_id,
            pageToken=next_page_token if next_page_token else ''
        ).execute()

        for item in response['items']:
            comment = item['snippet']['topLevelComment']['snippet']['textDisplay']
            # Truncate the comment if it exceeds the maximum length
            comment = comment[:max_length]
            comments.append(comment)

        next_page_token = response.get('nextPageToken')

        if not next_page_token:
            break

    return comments

def analyze_sentiment(comments):
    if comments:  # Ensure there are comments to analyze
        results = sentiment_pipeline(comments)
        return results
    else:
        return []

def process_video(yt_link):
    video_id = yt_link.split("=")[-1]  # Extract video ID from the link
    comments = get_video_comments(video_id)
    sentiment_results = analyze_sentiment(comments)

    # Create a DataFrame from the comments and sentiment analysis results
    df = pd.DataFrame({
        'Comments': comments,
        'Sentiment': [result['label'] for result in sentiment_results],
        'Score': [result['score'] for result in sentiment_results]
    })

    return df

# Define the Gradio interface
iface = gr.Interface(
    fn=process_video,
    inputs=gr.Textbox(lines=2, placeholder="Enter YouTube video URL here..."),
    outputs="dataframe",
    title="YouTube Video Comments Sentiment Analysis",
    description="Enter a YouTube video link to analyze the sentiment of its comments."
)

# Launch the interface
iface.launch(share=True)