Update app.py

app.py

@@ -129,18 +129,43 @@ with playground:
                                         outputs=[summary_textbox, translated_textbox])
             
         with gr.TabItem("Name Entity"):
-            gr.Markdown("""
-                        > Name Entity Recognition
-                        """)
-
-            iface = gr.Interface(fn=ner,
-                    inputs=[gr.Textbox(label="Text to find entities", lines=2)],
-                    outputs=[gr.HighlightedText(label="Text with entities")],
-                    title="NER with dslim/bert-base-NER",
-                    description="Find entities using the `dslim/bert-base-NER` model!",
-                    allow_flagging="never",
-                    examples=["My name is Ray, I'm learning through Hugging Face and DeepLearning.AI and I live in Caversham, Reading", "My name is Raymond, I work at A&O IT Group"])
+            # gr.Markdown("""
+            #             > Name Entity Recognition
+            #             """)
+
+            # iface = gr.Interface(fn=ner,
+            #         inputs=[gr.Textbox(label="Text to find entities", lines=2)],
+            #         outputs=[gr.HighlightedText(label="Text with entities")],
+            #         title="NER with dslim/bert-base-NER",
+            #         description="Find entities using the `dslim/bert-base-NER` model!",
+            #         allow_flagging="never",
+            #         examples=["My name is Ray, I'm learning through Hugging Face and DeepLearning.AI and I live in Caversham, Reading", "My name is Raymond, I work at A&O IT Group"])
+            
+            gr.Markdown("# NER with dslim/bert-base-NER")
+            gr.Markdown("Find entities using the `dslim/bert-base-NER` model!")
+            with gr.Row():
+                with gr.Column(scale=4):
+                    gr.Markdown("""
+                                ## Find entities
+                                ### Entities involved Name, Organization, and Location.
+                                > pipeline: ner, model: [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER)
+                                """)
+                    
+                with gr.Column(scale=1):
+                    ner_pipeline_button = gr.Button(value="Process")
+                    
+            with gr.Row():
+                with gr.Column():
+                    ner_text_input = gr.Textbox(label="Text to find entities", lines=2)
+                    examples = gr.Examples(examples=[
+                        "My name is Ray, I'm learning through Hugging Face and DeepLearning.AI and I live in Caversham, Reading", 
+                        "My name is Raymond, I work at A&O IT Group"
+                    ], inputs=ner_text_input)
+                
+                with gr.Column():
+                    ner_text_output = gr.HighlightedText(label="Text with entities")
 
+            ner_pipeline_button.click(ner, inputs=ner_text_input, outputs=ner_text_output)
             
     create_playground_footer()