Update app.py

app.py

@@ -1,3 +1,63 @@
+# 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()
+
+
+
+
+
+
+
+
+
 import gradio as gr
 
 def process_keywords_and_video(url, excel_file):