Update app.py

app.py

@@ -1136,70 +1136,70 @@ def variable_outputs(file_inputs):
         dataset_name = file_inputs_single[row].split("/")[-1]
 
         plots = [
-        gr.Markdown(
-            "<span style='font-size:20px; font-weight:bold;'>2) Trust Profile</span>",
-            visible=True,
-        ),
-        gr.Markdown(
-            "<div style='font-size:16px;'>This analysis shows you how strongly you are trusted in each of the Six Buckets of Trust®. You can also see this for any competitor.</div>",
-            visible=True,
-        ),
-        gr.Image(
-            value=img_bucketfull,
-            type="pil",
-            label="Trust Profile",
-            visible=True,
-        ),
-        gr.Markdown(
-            "<span style='font-size:20px; font-weight:bold;'>3) Trust and KPI Drivers</span>",
-            visible=True,
-        ),
-        gr.Markdown(
-            """
-            <div style='font-size:16px;'>
-            This analysis highlights which Trust Buckets® are most effective in improving NPS and building trust.
-            <br><br>
-            The baseline impact for each driver is <b>16.7%</b> (100% divided across 6 Trust Buckets®). Any percentage above this average indicates higher significance,
-            meaning these Trust Buckets® require more attention. To maximise their potential, focus on “filling” them with the right attributes and tailored messaging.
-            </div>
-            """,
-            visible=True,
-        ),
-    
-        
-        gr.Image(
-            value=img_trust,
-            type="pil",
-            label="Trust Drivers",
-            visible=True,
-        ),
-        gr.Image(
-            value=img_nps,
-            type="pil",
-            label="NPS Drivers",
-            visible=True,
-        ),
+            gr.Markdown(
+                "<span style='font-size:20px; font-weight:bold;'>2) Trust Profile</span>",
+                visible=True,
+            ),
+            gr.Markdown(
+                "<div style='font-size:16px;'>This analysis shows you how strongly you are trusted in each of the Six Buckets of Trust®. You can also see this for any competitor.</div>",
+                visible=True,
+            ),
+            gr.Image(
+                value=img_bucketfull,
+                type="pil",
+                label="Trust Profile",
+                visible=True,
+            ),
+            gr.Markdown(
+                "<span style='font-size:20px; font-weight:bold;'>3) Trust and KPI Drivers</span>",
+                visible=True,
+            ),
+            gr.Markdown(
+                """
+                <div style='font-size:16px;'>
+                This analysis highlights which Trust Buckets® are most effective in improving NPS and building trust.
+                <br><br>
+                The baseline impact for each driver is <b>16.7%</b> (100% divided across 6 Trust Buckets®). Any percentage above this average indicates higher significance,
+                meaning these Trust Buckets® require more attention. To maximise their potential, focus on “filling” them with the right attributes and tailored messaging.
+                </div>
+                """,
+                visible=True,
+            ),
         
-        gr.Image(
-            value=img_loyalty,
-            type="pil",
-            visible=True,
-        ),
-        gr.Image(
-            value=img_consideration,
-            type="pil",
-            visible=True,
-        ),
-        gr.Image(
-            value=img_satisfaction,
-            type="pil",
-            visible=True,
-        ),
-        gr.Textbox(
-            value=output_text,
-            visible=False,
-        ),
-    ]
+            
+            gr.Image(
+                value=img_trust,
+                type="pil",
+                label="Trust Drivers",
+                visible=True,
+            ),
+            gr.Image(
+                value=img_nps,
+                type="pil",
+                label="NPS Drivers",
+                visible=True,
+            ),
+            
+            gr.Image(
+                value=img_loyalty,
+                type="pil",
+                visible=True,
+            ),
+            gr.Image(
+                value=img_consideration,
+                type="pil",
+                visible=True,
+            ),
+            gr.Image(
+                value=img_satisfaction,
+                type="pil",
+                visible=True,
+            ),
+            gr.Textbox(
+                value=output_text,
+                visible=False,
+            ),
+        ]
 
 
         if isinstance(df_builder_pivot, pd.DataFrame):