cyber security

app.py

@@ -76,16 +76,7 @@ https://www.kaggle.com/datasets/trainingdatapro/20000-customers-reviews-on-banks
 
 [![Hits](https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fkevinhug%2FclientX&count_bg=%2379C83D&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=hits&edge_flat=false)](https://hits.seeyoufarm.com)
   """)
-  gr.Examples(
-    [
-      ["having credit card problem", "having credit card problem"],
-
-     ["low interest credit card", "low interest credit card"],
-      ["upset customer", "upset customer"],
-      ["what is the password", "what is the password"],
-    ],
-    [in_similar, in_like]
-  )
+
   with gr.Tab("Semantic Similarity Document Search (SSDS)"):
     in_similar = gr.Textbox(placeholder="having credit card problem",
                             label="Issue",
@@ -96,6 +87,16 @@ https://www.kaggle.com/datasets/trainingdatapro/20000-customers-reviews-on-banks
     btn_similar = gr.Button("Find Similar Verbatim")
     btn_similar.click(fn=similar, inputs=in_similar, outputs=out_similar)
 
+    gr.Examples(
+      [
+        ["having credit card problem"],
+
+        ["low interest credit card"],
+        ["upset customer"],
+        ["what is the password"],
+      ],
+      [in_similar]
+    )
     gr.Markdown("""
 Description:
 =======
@@ -151,6 +152,16 @@ Customer-Centric Approach: Gain insights into customer concerns, allowing us to
 
     btn_like = gr.Button("Classify Like Score")
     btn_like.click(fn=like, inputs=in_like, outputs=out_like)
+
+    gr.Examples(
+      [
+        ["having credit card problem"],
+        ["low interest credit card"],
+        ["upset customer"],
+        ["what is the password"],
+      ],
+      [in_like]
+    )
     gr.Markdown("""
 Smart Insights: Elevating Customer Engagement Through Sentiment Analysis
 =========