Update ContentGradio.py

ContentGradio.py

@@ -31,22 +31,27 @@ def get_example():
 def create_header():
 
     agent_header =   """
-                # Content Agent
- 
-                Use content agent to determine whether language is polite by passing it text strings. 
-            
-                Content Agent checks text and classifies it as polite, somewhat polite, neutral, and impolite.  
-                Uses Intel's Polite Guard NLP library 
-                
-                 
+                # Content Agent                
                 """
     with gr.Row():
         gr.Markdown("<div id='header'>" + agent_header" </div>")
 
 # Create the user guidance section
 def create_user_guidance():
+
+    guidance = """
+                Please enter  text below to get started. The AI Agent will try to determine whether language is polite and uses the following classification:
+                - polite
+                - somewhat polite
+                - neutral
+                - impolite.  
+                
+                App is running <pre>deepseek-ai/DeepSeek-R1-Distill-Qwen-32B</pre> text generation model.
+                Uses Intel's Polite Guard NLP library.
+                Compute is GCP · Nvidia L4 · 4x GPUs · 96 GB 
+                """
     with gr.Row():
-        gr.Markdown("<div id='user-guidance'>Please enter  text below to get started. Select one of the examples to see the classfication results.</div>")
+        gr.Markdown("<div id='user-guidance'>" + guidance+ "</div>")
 
 # Create the main content section
 def create_main():
@@ -63,10 +68,7 @@ def create_main():
 def create_examples(user_input):
     # Fetch examples by calling get_example() here
     examples = get_example()
-
-    gr.Markdown("<div id='examples'>Try one of these examples:</div>")
-    # Create a Radio component with the list of examples
-    example_radio = gr.Radio(choices=examples, label="Select an Example")
+    example_radio = gr.Radio(choices=examples, label="Try one of these examples:")
         
     # When an example is selected, populate the input field
     example_radio.change(fn=lambda example: example, inputs=example_radio, outputs=user_input)