Update app.py

app.py

@@ -344,163 +344,148 @@ def main():
             progress_bar.progress(40)
             st.subheader("Speech Trajectory Analysis")
             
-            compare_mode = st.toggle("Enable Side-by-Side Comparison", value=False)
-            
             viz_options = st.multiselect(
                 "Select visualizations to display:",
                 ["Sentiment Flow", "Moral Foundations Flow", "Basic Emotions Flow"],
                 default=["Sentiment Flow"]
             )
             
-            if len(viz_options) > 1 and compare_mode:
-                cols = st.columns(len(viz_options))
-            else:
-                cols = [st]  # Single column mode
-            
             # Create consistent segments for analyses
             segments = analyzer.split_text(text, max_length=512)
             num_segments = len(segments)
             segment_labels = [f"{i+1}" for i in range(num_segments)]
             
-            current_col = 0
-            
             if "Sentiment Flow" in viz_options:
-                with cols[current_col]:
-                    sentiment_scores = analyzer.analyze_emotional_trajectory(text)
-                    
-                    trajectory_fig = go.Figure(data=go.Scatter(
-                        x=segment_labels,
-                        y=sentiment_scores,
-                        mode='lines+markers',
-                        line=dict(color='#1f77b4', width=3),
-                        marker=dict(
-                            size=8, 
-                            color=['#ff4444' if score < -0.3 else '#44ff44' if score > 0.3 else '#888888' for score in sentiment_scores],
-                            symbol='circle'
-                        )
-                    ))
-                    
-                    trajectory_fig.update_layout(
-                        title='Emotional Flow Throughout the Speech',
-                        xaxis_title='Speech Segments',
-                        yaxis_title='Emotional Tone',
-                        yaxis=dict(
-                            ticktext=['Very Negative', 'Negative', 'Neutral', 'Positive', 'Very Positive'],
-                            tickvals=[-1, -0.5, 0, 0.5, 1],
-                            range=[-1.1, 1.1],
-                            gridcolor='lightgray'
-                        ),
-                        hovermode='x unified',
-                        showlegend=False,
-                        plot_bgcolor='white',
-                        height=500
-                    )
-                    
-                    trajectory_fig.update_traces(
-                        hovertemplate="Segment: %{x}<br>Score: %{y:.2f}<extra></extra>"
+                st.write("### Sentiment Flow")
+                sentiment_scores = analyzer.analyze_emotional_trajectory(text)
+                
+                trajectory_fig = go.Figure(data=go.Scatter(
+                    x=segment_labels,
+                    y=sentiment_scores,
+                    mode='lines+markers',
+                    line=dict(color='#1f77b4', width=3),
+                    marker=dict(
+                        size=8, 
+                        color=['#ff4444' if score < -0.3 else '#44ff44' if score > 0.3 else '#888888' for score in sentiment_scores],
+                        symbol='circle'
                     )
-                    
-                    st.plotly_chart(trajectory_fig, use_container_width=True)
-                    if compare_mode:
-                        current_col += 1
+                ))
+                
+                trajectory_fig.update_layout(
+                    title='Emotional Flow Throughout the Speech',
+                    xaxis_title='Speech Segments',
+                    yaxis_title='Emotional Tone',
+                    yaxis=dict(
+                        ticktext=['Very Negative', 'Negative', 'Neutral', 'Positive', 'Very Positive'],
+                        tickvals=[-1, -0.5, 0, 0.5, 1],
+                        range=[-1.1, 1.1],
+                        gridcolor='lightgray'
+                    ),
+                    hovermode='x unified',
+                    showlegend=False,
+                    plot_bgcolor='white',
+                    height=500
+                )
+                
+                trajectory_fig.update_traces(
+                    hovertemplate="Segment: %{x}<br>Score: %{y:.2f}<extra></extra>"
+                )
+                
+                st.plotly_chart(trajectory_fig, use_container_width=True)
             
             if "Moral Foundations Flow" in viz_options:
-                with cols[current_col]:
-                    moral_trajectories = {
-                        'care': [], 'fairness': [], 'loyalty': [],
-                        'authority': [], 'sanctity': []
-                    }
-                    
-                    for segment in segments:
-                        moral_scores = analyzer.analyze_moral_foundations(segment)
-                        for foundation in moral_trajectories.keys():
-                            moral_trajectories[foundation].append(moral_scores[foundation])
-                    
-                    moral_fig = go.Figure()
-                    colors = px.colors.qualitative.Set3[:5]
-                    
-                    for idx, (foundation, scores) in enumerate(moral_trajectories.items()):
-                        moral_fig.add_trace(go.Scatter(
-                            x=segment_labels,
-                            y=scores,
-                            name=MORAL_FOUNDATIONS[foundation],
-                            mode='lines+markers',
-                            line=dict(color=colors[idx], width=2),
-                            marker=dict(size=6, color=colors[idx])
-                        ))
-                    
-                    moral_fig.update_layout(
-                        title='Moral Foundations Flow',
-                        xaxis_title='Speech Segments',
-                        yaxis_title='Foundation Strength',
-                        yaxis=dict(range=[0, 1]),
-                        hovermode='x unified',
-                        plot_bgcolor='white',
-                        showlegend=True,
-                        height=500,
-                        legend=dict(
-                            orientation="h",
-                            yanchor="bottom",
-                            y=1.02,
-                            xanchor="right",
-                            x=1
-                        )
-                    )
-                    
-                    moral_fig.update_traces(
-                        hovertemplate="Segment: %{x}<br>Strength: %{y:.2f}<extra></extra>"
+                st.write("### Moral Foundations Flow")
+                moral_trajectories = {
+                    'care': [], 'fairness': [], 'loyalty': [],
+                    'authority': [], 'sanctity': []
+                }
+                
+                for segment in segments:
+                    moral_scores = analyzer.analyze_moral_foundations(segment)
+                    for foundation in moral_trajectories.keys():
+                        moral_trajectories[foundation].append(moral_scores[foundation])
+                
+                moral_fig = go.Figure()
+                colors = px.colors.qualitative.Set3[:5]
+                
+                for idx, (foundation, scores) in enumerate(moral_trajectories.items()):
+                    moral_fig.add_trace(go.Scatter(
+                        x=segment_labels,
+                        y=scores,
+                        name=MORAL_FOUNDATIONS[foundation],
+                        mode='lines+markers',
+                        line=dict(color=colors[idx], width=2),
+                        marker=dict(size=6, color=colors[idx])
+                    ))
+                
+                moral_fig.update_layout(
+                    title='Moral Foundations Flow',
+                    xaxis_title='Speech Segments',
+                    yaxis_title='Foundation Strength',
+                    yaxis=dict(range=[0, 1]),
+                    hovermode='x unified',
+                    plot_bgcolor='white',
+                    showlegend=True,
+                    height=500,
+                    legend=dict(
+                        orientation="h",
+                        yanchor="bottom",
+                        y=1.02,
+                        xanchor="right",
+                        x=1
                     )
-                    
-                    st.plotly_chart(moral_fig, use_container_width=True)
-                    if compare_mode:
-                        current_col += 1
+                )
+                
+                moral_fig.update_traces(
+                    hovertemplate="Segment: %{x}<br>Strength: %{y:.2f}<extra></extra>"
+                )
+                
+                st.plotly_chart(moral_fig, use_container_width=True)
         
             if "Basic Emotions Flow" in viz_options:
-                with cols[current_col]:
-                    emotions = []
-                    for segment in segments:
-                        try:
-                            result = analyzer.emotion_classifier(segment[:512])[0]
-                            emotions.append(result['label'])
-                        except:
-                            emotions.append('neutral')
-                    
-                    emotions_df = pd.DataFrame({
-                        'Segment': segment_labels,
-                        'Emotion': emotions
-                    })
-                    
-                    emotions_fig = px.bar(
-                        emotions_df,
-                        x='Segment',
-                        y='Emotion',
-                        color='Emotion',
-                        title='Basic Emotions Flow',
-                        color_discrete_sequence=px.colors.qualitative.Set2
-                    )
-                    
-                    emotions_fig.update_layout(
-                        xaxis_title='Speech Segments',
-                        yaxis_title='Emotion',
-                        showlegend=True,
-                        plot_bgcolor='white',
-                        height=500,
-                        legend=dict(
-                            orientation="h",
-                            yanchor="bottom",
-                            y=1.02,
-                            xanchor="right",
-                            x=1
-                        )
-                    )
-                    
-                    emotions_fig.update_traces(
-                        hovertemplate="Segment: %{x}<br>Emotion: %{y}<extra></extra>"
+                st.write("### Basic Emotions Flow")
+                emotions = []
+                for segment in segments:
+                    try:
+                        result = analyzer.emotion_classifier(segment[:512])[0]
+                        emotions.append(result['label'])
+                    except:
+                        emotions.append('neutral')
+                
+                emotions_df = pd.DataFrame({
+                    'Segment': segment_labels,
+                    'Emotion': emotions
+                })
+                
+                emotions_fig = px.bar(
+                    emotions_df,
+                    x='Segment',
+                    y='Emotion',
+                    color='Emotion',
+                    title='Basic Emotions Flow',
+                    color_discrete_sequence=px.colors.qualitative.Set2
+                )
+                
+                emotions_fig.update_layout(
+                    xaxis_title='Speech Segments',
+                    yaxis_title='Emotion',
+                    showlegend=True,
+                    plot_bgcolor='white',
+                    height=500,
+                    legend=dict(
+                        orientation="h",
+                        yanchor="bottom",
+                        y=1.02,
+                        xanchor="right",
+                        x=1
                     )
-                    
-                    st.plotly_chart(emotions_fig, use_container_width=True)
-                    if compare_mode:
-                        current_col += 1
+                )
+                
+                emotions_fig.update_traces(
+                    hovertemplate="Segment: %{x}<br>Emotion: %{y}<extra></extra>"
+                )
+                
+                st.plotly_chart(emotions_fig, use_container_width=True)
         
             # Add download button
             if viz_options: