import gradio as gr import pandas as pd import logging from multilingual_sentiment_model import * # === Setup Logging === logging.basicConfig( level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s", ) # Gradio Function with Logging def youtube_sentiment_analysis(url, num_of_comments): try: video_id = extract_video_id(url) if not video_id: logging.warning("Invalid YouTube URL entered in UI.") return "Error: Invalid YouTube URL", None, None video_title = get_video_title(video_id) # Fetch video title comments, error = get_comments(video_id, int(num_of_comments)) if error: logging.error(f"Error fetching comments: {error}") return f"Error fetching comments: {error}", None, None if not comments: logging.warning("No comments found for the video.") return "Error: No comments found.", None, None sentiment_results, sentiment_counts = analyze_sentiment(comments) chart = plot_pie_chart(sentiment_counts, video_title) # Pass title to the chart summary = get_overall_sentiment(sentiment_counts) return summary, chart, pd.DataFrame(sentiment_results).head(5) except Exception as e: logging.exception(f"Unexpected Error: {str(e)}") return f"Unexpected Error: {str(e)}", None, None # Example YouTube URLs example_urls = [ ["https://www.youtube.com/watch?v=0e9WuB0Ua98"], ["https://www.youtube.com/watch?v=3JZ_D3ELwOQ"], ["https://youtu.be/dQw4w9WgXcQ"], ["https://www.youtube.com/watch?v=9bZkp7q19f0"], ["https://www.youtube.com/watch?v=2Vv-BfVoq4g"] ] # Gradio Interface with gr.Blocks() as demo: # Centered Title with gr.Row(): gr.HTML("
Enter a YouTube video URL and specify the number of comments to analyze.
") with gr.Row(): with gr.Column(): youtube_url = gr.Textbox(label="YouTube Video URL") num_comments = gr.Slider(minimum=10, maximum=1000, step=1, value=100, label="Number of Comments to Fetch") submit_btn = gr.Button("Submit") gr.Markdown("### Example YouTube Video URLs for Testing") gr.Examples(examples=example_urls, inputs=youtube_url, label="Click an example to autofill") with gr.Column(): output_summary = gr.Textbox(label="Overall Sentiment Summary") output_chart = gr.Plot(label="Sentiment Chart") output_table = gr.Dataframe(label="Comment Sentiment Analysis") submit_btn.click( youtube_sentiment_analysis, inputs=[youtube_url, num_comments], outputs=[output_summary, output_chart, output_table], ) # Launch App if __name__ == "__main__": demo.launch()