app.py

import gradio as gr

def process_keywords_and_video(url, excel_file):
    metadata, error = fetch_video_metadata(url)
    if error:
        return error, None

    transcript, error = fetch_transcript(url)
    if error:
        return error, None

    sentences = split_long_sentences(transcript)
    keywords, attributes = read_keywords(excel_file)
    matched_keywords = match_keywords_in_sentences(sentences, keywords)
    sentiment_results = analyze_sentiment_for_keywords(matched_keywords, sentences)
    wordclouds = generate_word_clouds(matched_keywords)
    pdf_file = generate_pdf_with_sections(metadata, sentiment_results, wordclouds)

    return "Processing completed successfully!", pdf_file

# Gradio App
with gr.Blocks() as iface:
    gr.Markdown("<h1>Auto-Insight: YouTube Video Analyzer for Automobiles</h1>")
    video_url = gr.Textbox(label="YouTube Video URL", placeholder="Enter the YouTube video URL")
    excel_file = gr.File(label="Upload Excel File with Keywords")
    process_button = gr.Button("Analyze Video")
    processing_status = gr.Textbox(label="Processing Status", interactive=False)
    pdf_output = gr.File(label="Download Sentiment Report (PDF)")

    process_button.click(
        process_keywords_and_video,
        inputs=[video_url, excel_file],
        outputs=[processing_status, pdf_output]
    )

iface.launch(share=True)