Update app.py

app.py

@@ -43,6 +43,15 @@ class VideoRetrieval:
             "A quiet moment of reflection before a life-changing decision"
         ]
         
+        # Sample YouTube clips (famous movie scenes)
+        youtube_clips = [
+            "https://www.youtube.com/watch?v=kcsNbQRU5TI",  # Matrix - Red Pill Blue Pill
+            "https://www.youtube.com/watch?v=YoHD9XEInc0",  # Inception - Hallway Fight
+            "https://www.youtube.com/watch?v=ZWCAf-xLV2k",  # Dark Knight - Interrogation
+            "https://www.youtube.com/watch?v=Jomr9SAjcyw",  # Pulp Fiction - Restaurant
+            "https://www.youtube.com/watch?v=SQ7_5MMbPYs",  # Shawshank - Hope Speech
+        ]
+        
         data = []
         for i in range(n_clips):
             data.append({
@@ -50,7 +59,8 @@ class VideoRetrieval:
                 'movie_title': movie_titles[i % len(movie_titles)],
                 'description': descriptions[i % len(descriptions)],
                 'timestamp': f'{(i*5):02d}:00 - {(i*5+3):02d}:00',
-                'duration': '3:00'
+                'duration': '3:00',
+                'youtube_url': youtube_clips[i % len(youtube_clips)]
             })
         
         self.clips_df = pd.DataFrame(data)
@@ -110,6 +120,7 @@ class VideoRetrieval:
                 'movie_title': self.clips_df.iloc[idx]['movie_title'],
                 'description': self.clips_df.iloc[idx]['description'],
                 'timestamp': self.clips_df.iloc[idx]['timestamp'],
+                'youtube_url': self.clips_df.iloc[idx]['youtube_url'],
                 'similarity_score': float(combined_similarities[idx])  # Convert to float for JSON serialization
             })
         
@@ -165,12 +176,20 @@ def main():
                             st.markdown(f"**Scene Description:**")
                             st.write(result['description'])
                             st.text(f"⏱️ Timestamp: {result['timestamp']}")
+                            
+                            # Add video player
+                            if result['youtube_url']:
+                                st.video(result['youtube_url'])
                         
                         with cols[1]:
                             st.markdown("**Relevance Score:**")
                             score = min(1.0, max(0.0, result['similarity_score']))
                             st.progress(score)
                             st.text(f"{score:.2%} match")
+                            
+                            # Add direct YouTube link
+                            st.markdown(f"[🔗 Watch on YouTube]({result['youtube_url']})")
+                            st.text("Click to open in a new tab")
                         
                         st.divider()