Update src/streamlit_app.py

src/streamlit_app.py

@@ -1279,37 +1279,46 @@ if uploaded_file is not None:
                             aligned_segments = align_transcription_with_speakers(result["segments"], speaker_segments)
                 
                 # SECOND-BY-SECOND SENTIMENT ANALYSIS
-                st.subheader("📊 Second-by-Second Sentiment Analysis")
+                # Skip for very long videos to avoid timeout
+                MAX_VIDEO_DURATION_FOR_DETAILED_ANALYSIS = 300  # 5 minutes
                 
-                # 1. Text Sentiment Analysis (Second-by-Second)
                 text_sentiment_per_second = []
-                if sentiment_analyzer:
-                    with st.spinner("Analyzing text sentiment second-by-second..."):
-                        text_sentiment_per_second = analyze_text_sentiment_second_by_second(
-                            result["segments"], 
-                            sentiment_analyzer, 
-                            video_duration
-                        )
-                
-                # 2. Audio Tone Sentiment Analysis (Second-by-Second)
                 audio_sentiment_per_second = []
-                if audio_sentiment_analyzer:
-                    with st.spinner("Analyzing audio tone sentiment second-by-second (based on voice tone, not words)..."):
-                        audio_sentiment_per_second = analyze_audio_sentiment_second_by_second(
-                            tmp_video_path,
-                            audio_sentiment_analyzer,
-                            video_duration
-                        )
-                
-                # 3. Visual Sentiment Analysis (Second-by-Second)
                 visual_sentiment_per_second = []
-                if visual_sentiment_analyzer:
-                    with st.spinner("Analyzing visual sentiment second-by-second from facial expressions..."):
-                        visual_sentiment_per_second = analyze_visual_sentiment_second_by_second(
-                            tmp_video_path,
-                            visual_sentiment_analyzer,
-                            video_duration
-                        )
+                
+                if video_duration > 0 and video_duration <= MAX_VIDEO_DURATION_FOR_DETAILED_ANALYSIS:
+                    st.subheader("📊 Second-by-Second Sentiment Analysis")
+                    
+                    # 1. Text Sentiment Analysis (Second-by-Second)
+                    if sentiment_analyzer:
+                        with st.spinner("Analyzing text sentiment second-by-second..."):
+                            try:
+                                text_sentiment_per_second = analyze_text_sentiment_second_by_second(
+                                    result["segments"], 
+                                    sentiment_analyzer, 
+                                    video_duration
+                                )
+                            except Exception as e:
+                                st.warning(f"⚠️ Text sentiment analysis skipped: {str(e)}")
+                    
+                    # 2. Audio Tone Sentiment Analysis (Second-by-Second)
+                    if audio_sentiment_analyzer:
+                        with st.spinner("Analyzing audio tone sentiment second-by-second..."):
+                            try:
+                                audio_sentiment_per_second = analyze_audio_sentiment_second_by_second(
+                                    tmp_video_path,
+                                    audio_sentiment_analyzer,
+                                    video_duration
+                                )
+                            except Exception as e:
+                                st.warning(f"⚠️ Audio sentiment analysis skipped: {str(e)}")
+                    
+                    # 3. Visual Sentiment Analysis (Second-by-Second) - SKIP for performance
+                    # This is very slow, disable it
+                    st.info("ℹ️ Visual sentiment analysis disabled for faster processing")
+                    
+                elif video_duration > MAX_VIDEO_DURATION_FOR_DETAILED_ANALYSIS:
+                    st.info(f"ℹ️ Video is {video_duration:.0f}s long. Second-by-second analysis is disabled for videos longer than {MAX_VIDEO_DURATION_FOR_DETAILED_ANALYSIS}s to prevent timeout.")
                 
                 # Create and display timeline graphs
                 if text_sentiment_per_second or audio_sentiment_per_second or visual_sentiment_per_second:
@@ -1323,17 +1332,20 @@ if uploaded_file is not None:
                     )
                     
                     # Display graphs
-                    if fig_text:
-                        st.pyplot(fig_text)
-                        plt.close(fig_text)
-                    
-                    if fig_audio:
-                        st.pyplot(fig_audio)
-                        plt.close(fig_audio)
-                    
-                    if fig_visual:
-                        st.pyplot(fig_visual)
-                        plt.close(fig_visual)
+                    try:
+                        if fig_text:
+                            st.pyplot(fig_text)
+                            plt.close(fig_text)
+                        
+                        if fig_audio:
+                            st.pyplot(fig_audio)
+                            plt.close(fig_audio)
+                        
+                        if fig_visual:
+                            st.pyplot(fig_visual)
+                            plt.close(fig_visual)
+                    except Exception as e:
+                        st.warning(f"⚠️ Could not display graphs: {str(e)}")
                     
                     # Summary statistics
                     st.markdown("### 📊 Sentiment Summary")
@@ -1360,16 +1372,12 @@ if uploaded_file is not None:
                             visual_neu = sum(1 for s in visual_sentiment_per_second if s["sentiment"] == "NEUTRAL")
                             st.metric("🎥 Visual Sentiment", f"Pos: {visual_pos}s | Neg: {visual_neg}s | Neu: {visual_neu}s")
                 
-                # Legacy emotion analysis (keep for backward compatibility)
+                # Legacy emotion analysis (DISABLED for performance - too slow)
                 visual_emotions = []
-                if visual_emotion_analyzer:
-                    with st.spinner("Analyzing emotions from video frames..."):
-                        visual_emotions = analyze_visual_emotions(tmp_video_path, visual_emotion_analyzer, max_frames=30)
-                
                 audio_tone_result = None
-                if audio_emotion_analyzer:
-                    with st.spinner("Analyzing audio tone and prosody..."):
-                        audio_tone_result = analyze_audio_tone_emotions(tmp_video_path, audio_emotion_analyzer)
+                
+                # Skip these for faster processing
+                st.info("ℹ️ Visual and audio emotion analysis disabled for faster results. Focus on transcription and text sentiment.")
                 
                 # Display results
                 # Main transcription text