Update app.py

app.py

@@ -511,7 +511,7 @@ def calculate_nps_image_from_excel(file_path):
     fig, ax = plt.subplots(figsize=(3.3, 3.3))
     wedges, _ = ax.pie(values, colors=colors, startangle=90, wedgeprops=dict(width=0.35))
 
-    ax.text(0, 0, f"{nps_score}", ha='center', va='center', fontsize=10, fontweight='bold')
+    ax.text(0, 0, f"{nps_score}", ha='center', va='center', fontsize=19, fontweight='bold')
 
     radius = 1.3
     for i, (label, pct) in enumerate(zip(labels, values)):
@@ -585,7 +585,7 @@ def calculate_r2_image_from_excel(file_path):
     ax.text(
         0, 0, f"{int(round(r2_percent))}%",
         ha='center', va='center',
-        fontsize=14, fontweight='bold'
+        fontsize=19, fontweight='bold'
     )
 
     ax.set_title("R²", fontsize=11, pad=10)
@@ -652,7 +652,7 @@ def vwcalculate_r2_image_from_excel(file_path):
     ax.text(
         0, 0, f"{int(round(r2_percent))}%",
         ha='center', va='center',
-        fontsize=14, fontweight='bold'
+        fontsize=19, fontweight='bold'
     )
 
     ax.set_title("R²", fontsize=11, pad=10)
@@ -2348,7 +2348,7 @@ def generate_trust_score_image(score):
     )
 
     # Center Score
-    ax.text(0, 0, f"{score}", ha='center', va='center', fontsize=14, fontweight='bold')
+    ax.text(0, 0, f"{score}", ha='center', va='center', fontsize=19, fontweight='bold')
 
     # Radial labels (adjusted for perfect alignment)
     labels = ["0–4: Low Trust", "5–6: Neutral", "7–8: Trust", "9–10: High Trust"]