Update ui/contentagentui.py

ui/contentagentui.py

@@ -14,11 +14,13 @@ class ContentAgentUI:
       - reveals the main chat panel (with header, guidance, examples, footer) after init.
     """
 
-    def __init__(self, endpoint_uri: str, is_healthy: bool, health_message: str, agent_initializer):
+    def __init__(self, endpoint_uri: str, is_healthy: bool, health_message: str, agent_initializer, agent_type:str, compute:str ):
         self.endpoint_uri = endpoint_uri
         self.is_healthy = bool(is_healthy)
         self.health_message = health_message or ""
         self.agent_initializer = agent_initializer  # callable: (uri) -> CodeAgent
+        self.agenttype = agenttype or ""
+        self.compute = compute or ""
 
         # set in build()
         self.app: gr.Blocks | None = None
@@ -29,24 +31,36 @@ class ContentAgentUI:
         self.reply = None
         self.agent_state = None
         self.examples_radio = None
+       
+        
 
     # ---------- helpers ----------
 
 
+    
     def _create_user_guidance(self):
+
+
        gr.Markdown("""
                 Please enter text below to get started. Content Agent will try to determine whether the language is polite and uses the following classification:
                 - `polite`
                 - `somewhat polite`
                 - `neutral`
                 - `impolite`
-                Technology:
-                - App is running `deepseek-ai/DeepSeek-R1-Distill-Qwen-32B` text generation model.
-                - Agent uses Intel's Polite Guard NLP library tool
-                - Compute on GCP · Nvidia L4 · 4x GPUs · 96 GB
-                - By design, the inference endpoint is designed to fall asleep to save electricity and $$. If you were to run Content Agent for your business, you would configure it to run 24 hr/day, 7 days/week
-                
-        """)
+
+                Classificiation Scores
+                - Scoring runs from O to 1 
+
+                """)
+
+  #      gr.Markdown ("""
+  #              Technology:
+  #              - App is running `deepseek-ai/DeepSeek-R1-Distill-Qwen-32B` text generation model.
+  #              - Agent uses Intel's Polite Guard NLP library tool
+  #              - Compute:  GCP · Nvidia L4 · 4x GPUs · 96 GB
+  #              - Content Agents's LLM runs on-demand rather than using resources for 24 hrs/day, 7 days a week
+  #              
+  #      """)
 
 
     def _get_css(self) -> str | None:
@@ -90,7 +104,7 @@ class ContentAgentUI:
     def _call_agent(text: str, agent) -> str:
         try:
             if agent is None:
-                return "The LLM is not initialized and will need to be started.  Click 'Start Agent'."
+                return "Content Agent's LLM is sleeping and will need to be started.  Click 'Start Agent'."
             return str(agent.run(text))  # smolagents.CodeAgent API
         except Exception as e:
             return f"Error: {e}"
@@ -117,7 +131,8 @@ class ContentAgentUI:
                     lines=8,
                     interactive=False,
                 )
-                start_btn = gr.Button("Start Agent (it can take up to 5 minute to start up)")
+                start_btn = gr.Button("Start Agent")
+                gr.Markdown("It may take up to 5 minutes to wake up the agent"
 
             
             # Main panel (hidden until agent is initialized)