Update app.py

app.py

@@ -662,7 +662,7 @@ def analyze_emotions(text):
 def create_visualization(result):
     """Create visualization of emotion analysis results"""
     # Create figure and axis
-    fig, ax = plt.subplots(figsize=(10, 6))
+    fig, ax = plt.subplots(figsize=(12, 8))
 
     # Extract emotion data
     emotions = [e[0] for e in result['emotion_scores']]
@@ -671,36 +671,39 @@ def create_visualization(result):
     # Get colors
     colors = [EMOTION_COLORS.get(emotion, '#CCCCCC') for emotion in emotions]
 
-    # Create bar chart
-    bars = ax.bar(emotions, scores, color=colors)
+    # Create horizontal bar chart
+    bars = ax.barh(emotions, scores, color=colors)
+
+    # Set x-axis to a static 100%
+    ax.set_xlim(0, 100)
+    ax.set_xticks(range(0, 101, 10))
+    ax.set_xticklabels([f'{i}%' for i in range(0, 101, 10)])
 
     # Add title and labels
     ax.set_title('Emotion Analysis', fontsize=16, fontweight='bold')
-    ax.set_xlabel('Emotions', fontsize=12)
-    ax.set_ylabel('Score (%)', fontsize=12)
+    ax.set_ylabel('Emotions', fontsize=12)
+    ax.set_xlabel('Score (%)', fontsize=12)
 
-    # Add verdict as text annotation
+    # Add verdict as text annotation below the chart
     verdict = result['emotional_verdict']['label']
     description = result['emotional_verdict']['description']
-    ax.text(0.5, -0.25, f"Verdict: {verdict}", ha='center', transform=ax.transAxes, fontsize=14, fontweight='bold')
-    ax.text(0.5, -0.32, f"{description}", ha='center', transform=ax.transAxes, fontsize=12)
-
-    # Rotate x-axis labels for readability
-    plt.xticks(rotation=45, ha='right')
+    ax.text(0.5, -0.2, f"Verdict: {verdict}", ha='center', transform=ax.transAxes, fontsize=14, fontweight='bold')
+    ax.text(0.5, -0.27, f"{description}", ha='center', transform=ax.transAxes, fontsize=12)
 
     # Add value labels on top of bars
     for bar in bars:
-        height = bar.get_height()
-        ax.text(bar.get_x() + bar.get_width()/2., height + 0.5,
-                f'{height:.1f}%', ha='center', va='bottom', fontsize=10)
+        width = bar.get_width()
+        ax.text(width + 0.5, bar.get_y() + bar.get_height() / 2,
+                f'{width:.1f}%', ha='left', va='center', fontsize=10)
 
     # Adjust layout
     plt.tight_layout()
-    plt.subplots_adjust(bottom=0.35)  # Make room for the verdict text
+    plt.subplots_adjust(bottom=0.3)  # Make room for the verdict text
 
     # Return figure
     return fig
 
+
 def analyze_text(text):
     """Analyze text and return visualization and detailed results"""
     fig, result = analyze_emotions(text)