Update app.py

app.py

@@ -1,60 +1,3 @@
-# app.py
-
-import gradio as gr
-from backend import fetch_video_metadata, fetch_transcript, split_long_sentences, match_keywords_in_sentences, read_keywords
-import pandas as pd
-
-# Gradio interface function to call the backend functions
-def analyze_sentiment(video_url, excel_file_path):
-    # Fetch video metadata
-    metadata, metadata_error = fetch_video_metadata(video_url)
-    if metadata_error:
-        return f"Error: {metadata_error}"
-
-    # Fetch transcript
-    transcript, transcript_error = fetch_transcript(video_url)
-    if transcript_error:
-        return f"Error: {transcript_error}"
-
-    # Process sentences from transcript
-    sentences = split_long_sentences(transcript)
-
-    # Read keywords from uploaded Excel file
-    keywords, attributes = read_keywords(excel_file_path)
-
-    # Match keywords in sentences
-    matched_keywords = match_keywords_in_sentences(sentences, keywords)
-
-    # Prepare the report for Gradio display
-    report = {
-        "Metadata": metadata,
-        "Matched Keywords": matched_keywords,
-        "Sentences": sentences
-    }
-
-    return report
-
-# Gradio interface setup
-interface = gr.Interface(
-    fn=analyze_sentiment,
-    inputs=[
-        gr.inputs.Textbox(label="YouTube Video URL"),
-        gr.inputs.File(label="Upload Keywords Excel File")  # User uploads keywords file
-    ],
-    outputs=[
-        gr.outputs.JSON(label="Metadata and Sentiment Analysis Results"),
-        gr.outputs.Textbox(label="Sentences from Transcript")  # Display sentences detected in transcript
-    ]
-)
-
-# Launch Gradio interface
-interface.launch()
-
-
-
-
-
-