Wajahat698 commited on
Commit
e0bb23c
·
verified ·
1 Parent(s): 83c5260

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +23 -22
app.py CHANGED
@@ -1318,8 +1318,6 @@ def bold_high_impact_row(row):
1318
  return [''] * len(row)
1319
 
1320
 
1321
-
1322
-
1323
  def variable_outputs(file_inputs):
1324
 
1325
  file_inputs_single = file_inputs
@@ -1381,38 +1379,47 @@ def variable_outputs(file_inputs):
1381
  """,
1382
  visible=True,
1383
  ),
1384
-
1385
- # ✅ Side-by-side Trust & NPS drivers
1386
  gr.Image(
1387
  value=combine_two_images_horizontally(img_trust, "Trust Drivers", img_nps, "NPS Drivers"),
1388
  type="pil",
1389
  label="Trust + NPS Drivers",
1390
  visible=True,
1391
  ),
 
1392
  gr.Image(
1393
- value=None,
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  type="pil",
1395
- visible=False,
 
1396
  ),
1397
-
1398
-
1399
  gr.Image(
1400
- value=None,
1401
  type="pil",
1402
- visible=False,
 
1403
  ),
1404
  gr.Image(
1405
- value=None,
1406
  type="pil",
1407
- visible=False,
 
1408
  ),
1409
  gr.Image(
1410
- value=None,
1411
  type="pil",
1412
- visible=False,
 
 
 
 
 
 
 
1413
  ),
1414
  gr.Textbox(
1415
  value=output_text,
 
1416
  visible=False,
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  ),
1418
  ]
@@ -1430,14 +1437,11 @@ def variable_outputs(file_inputs):
1430
 
1431
  markdown_6 = gr.Markdown(
1432
  "<span style='font-size:17px; font-weight:bold;'>The features and messages that improve your NPS and trust most effectively. They key ones are marked in bold.</span>",
1433
- #+ "<br>In the table, use the little arrow in each column to toggle the most to least effective TrustBuilders® to fill each Trust Bucket®. Your focus is only on the Trust Bucket® with the highest driver impact. "
1434
- # + "<br> Note: Even if Trust Buckets® for Customers and Prospects overlap, the most effective statements are very different. This provides clear guidance for acquisition versus loyalty activities.",
1435
  visible=True,
1436
  )
1437
 
1438
  styled_df = df_builder_pivot.style.apply(bold_high_impact_row, axis=1)
1439
 
1440
-
1441
  table_builder_2 = gr.Dataframe(
1442
  value=styled_df,
1443
  headers=list(df_builder_pivot.columns),
@@ -1448,8 +1452,6 @@ def variable_outputs(file_inputs):
1448
  wrap=True,
1449
  )
1450
 
1451
-
1452
-
1453
  plots_visible.append(markdown_5)
1454
  plots_visible.append(markdown_6)
1455
  plots_visible.append(table_builder_2)
@@ -1458,12 +1460,11 @@ def variable_outputs(file_inputs):
1458
  plots_visible.append(gr.Markdown("", visible=False))
1459
  plots_visible.append(gr.Dataframe(value=None, label="", visible=False))
1460
 
 
1461
  plots_invisible = [
1462
  gr.Markdown("", visible=False),
1463
  gr.Markdown("", visible=False),
1464
- gr.Image(label="Trust Buckets", visible=False),
1465
- gr.Markdown("", visible=False),
1466
- gr.Markdown("", visible=False),
1467
  gr.Image(label="Trust Drivers", visible=False),
1468
  gr.Image(label="NPS Drivers", visible=False),
1469
  gr.Image(label="Loyalty Drivers", visible=False),
 
1318
  return [''] * len(row)
1319
 
1320
 
 
 
1321
  def variable_outputs(file_inputs):
1322
 
1323
  file_inputs_single = file_inputs
 
1379
  """,
1380
  visible=True,
1381
  ),
1382
+ # Keep the combined image
 
1383
  gr.Image(
1384
  value=combine_two_images_horizontally(img_trust, "Trust Drivers", img_nps, "NPS Drivers"),
1385
  type="pil",
1386
  label="Trust + NPS Drivers",
1387
  visible=True,
1388
  ),
1389
+ # But also provide the individual images
1390
  gr.Image(
1391
+ value=img_trust,
1392
  type="pil",
1393
+ label="Trust Drivers",
1394
+ visible=False, # Hidden but available
1395
  ),
 
 
1396
  gr.Image(
1397
+ value=img_nps,
1398
  type="pil",
1399
+ label="NPS Drivers",
1400
+ visible=False, # Hidden but available
1401
  ),
1402
  gr.Image(
1403
+ value=img_loyalty,
1404
  type="pil",
1405
+ label="Loyalty Drivers",
1406
+ visible=False, # Hidden but available
1407
  ),
1408
  gr.Image(
1409
+ value=img_consideration,
1410
  type="pil",
1411
+ label="Consideration Drivers",
1412
+ visible=False, # Hidden but available
1413
+ ),
1414
+ gr.Image(
1415
+ value=img_satisfaction,
1416
+ type="pil",
1417
+ label="Satisfaction Drivers",
1418
+ visible=False, # Hidden but available
1419
  ),
1420
  gr.Textbox(
1421
  value=output_text,
1422
+ label="Analysis Summary",
1423
  visible=False,
1424
  ),
1425
  ]
 
1437
 
1438
  markdown_6 = gr.Markdown(
1439
  "<span style='font-size:17px; font-weight:bold;'>The features and messages that improve your NPS and trust most effectively. They key ones are marked in bold.</span>",
 
 
1440
  visible=True,
1441
  )
1442
 
1443
  styled_df = df_builder_pivot.style.apply(bold_high_impact_row, axis=1)
1444
 
 
1445
  table_builder_2 = gr.Dataframe(
1446
  value=styled_df,
1447
  headers=list(df_builder_pivot.columns),
 
1452
  wrap=True,
1453
  )
1454
 
 
 
1455
  plots_visible.append(markdown_5)
1456
  plots_visible.append(markdown_6)
1457
  plots_visible.append(table_builder_2)
 
1460
  plots_visible.append(gr.Markdown("", visible=False))
1461
  plots_visible.append(gr.Dataframe(value=None, label="", visible=False))
1462
 
1463
+ # Adjusted to include all expected outputs
1464
  plots_invisible = [
1465
  gr.Markdown("", visible=False),
1466
  gr.Markdown("", visible=False),
1467
+ gr.Image(label="Trust + NPS Drivers", visible=False),
 
 
1468
  gr.Image(label="Trust Drivers", visible=False),
1469
  gr.Image(label="NPS Drivers", visible=False),
1470
  gr.Image(label="Loyalty Drivers", visible=False),