Update Gradio_UI.py

Fixed UnboundLocalError

Gradio_UI.py

@@ -9,7 +9,7 @@ from smolagents.memory import MemoryStep
 from smolagents.utils import _is_package_available
 
 def pull_messages_from_step(step_log: MemoryStep):
-    """Extract ChatMessage objects from agent steps with proper nesting"""
+    """Extract ChatMessage objects from agent steps with proper nesting and error resilience"""
     import gradio as gr
     
     if isinstance(step_log, ActionStep):
@@ -21,8 +21,14 @@ def pull_messages_from_step(step_log: MemoryStep):
             model_output = re.sub(r"```\s*<end_code>.*", "```", step_log.model_output.strip())
             model_output = re.sub(r"<end_code>\s*```", "```", model_output)
             if model_output.strip():
+                # Prevent code generation display - show as plain text
+                if model_output.startswith("```"):
+                    model_output = model_output.replace("```python", "```\n💭 Reasoning:").replace("```", "")
                 yield gr.ChatMessage(role="assistant", content=model_output)
         
+        # Initialize parent_id to None for safe referencing
+        parent_id = None
+        
         # Handle tool calls
         if hasattr(step_log, "tool_calls") and step_log.tool_calls:
             tool_call = step_log.tool_calls[0]
@@ -52,15 +58,15 @@ def pull_messages_from_step(step_log: MemoryStep):
                 yield gr.ChatMessage(
                     role="assistant",
                     content=obs,
-                    metadata={"title": "✅ Result", "parent_id": parent_id if hasattr(step_log, 'tool_calls') else None},
+                    metadata={"title": "✅ Result", "parent_id": parent_id},
                 )
         
-        # Show errors if any
+        # Show errors if any (safe parent_id reference)
         if hasattr(step_log, "error") and step_log.error:
             yield gr.ChatMessage(
                 role="assistant",
                 content=str(step_log.error),
-                metadata={"title": "⚠️ Warning", "parent_id": parent_id if hasattr(step_log, 'tool_calls') else None},
+                metadata={"title": "⚠️ Warning", "parent_id": parent_id},
             )
         
         # Step footer with metrics
@@ -82,33 +88,42 @@ def stream_to_gradio(
     reset_agent_memory: bool = False,
     additional_args: Optional[dict] = None,
 ):
-    """Runs agent and streams messages as gradio ChatMessages"""
+    """Runs agent and streams messages as gradio ChatMessages with error resilience"""
     if not _is_package_available("gradio"):
         raise ModuleNotFoundError("Install gradio: `pip install 'smolagents[gradio]'`")
     
     import gradio as gr
     
-    for step_log in agent.run(task, stream=True, reset=reset_agent_memory, additional_args=additional_args):
-        if isinstance(step_log, ActionStep):
-            # Track tokens if available
-            if hasattr(agent.model, "last_input_token_count") and hasattr(agent.model, "last_output_token_count"):
-                step_log.input_token_count = agent.model.last_input_token_count
-                step_log.output_token_count = agent.model.last_output_token_count
-            
-            for message in pull_messages_from_step(step_log):
-                yield message
+    try:
+        for step_log in agent.run(task, stream=True, reset=reset_agent_memory, additional_args=additional_args):
+            if isinstance(step_log, ActionStep):
+                # Track tokens if available
+                if hasattr(agent.model, "last_input_token_count") and hasattr(agent.model, "last_output_token_count"):
+                    step_log.input_token_count = agent.model.last_input_token_count
+                    step_log.output_token_count = agent.model.last_output_token_count
+                
+                for message in pull_messages_from_step(step_log):
+                    yield message
+        
+        # Final answer handling
+        final = handle_agent_output_types(step_log)
+        if isinstance(final, AgentText):
+            content = final.to_string()
+            # Format catalogue nicely with Markdown rendering
+            yield gr.ChatMessage(
+                role="assistant",
+                content=content,
+                metadata={"react": True}
+            )
+        else:
+            yield gr.ChatMessage(role="assistant", content=f"**Final Answer:** {str(final)}")
     
-    # Final answer handling
-    final = handle_agent_output_types(step_log)
-    if isinstance(final, AgentText):
-        content = final.to_string()
+    except Exception as e:
         yield gr.ChatMessage(
             role="assistant",
-            content=content,
-            metadata={"react": True}
+            content=f"⚠️ **Error during planning:** {str(e)}\n\nPlease try again with a clearer trip description (include destination, dates, origin city, and budget).",
+            metadata={"title": "❌ Planning Failed"}
         )
-    else:
-        yield gr.ChatMessage(role="assistant", content=f"**Final Answer:** {str(final)}")
 
 class GradioUI:
     """Production-ready Gradio interface for travel agent"""
@@ -153,7 +168,7 @@ class GradioUI:
             with gr.Row():
                 text_input = gr.Textbox(
                     label="Describe your trip",
-                    placeholder="e.g., '5-day trip to Barcelona from New York, Oct 15-19, budget $1500 USD'",
+                    placeholder="e.g., '3-day trip to Lisbon from London, Sep 20-22, budget £600 GBP'",
                     lines=2,
                 )
                 submit_btn = gr.Button("Plan My Trip", variant="primary")
@@ -161,7 +176,7 @@ class GradioUI:
             gr.Markdown("""
             ### 💡 Tips for best results:
             • Include: destination, dates, origin city, budget amount + currency  
-            • Example: *"4-day Tokyo trip from London, Nov 5-8, budget 2000 GBP"*  
+            • Example: *"5-day Barcelona trip from NYC, Oct 15-19, budget $1500 USD"*  
             • Agent will research attractions, check weather, convert currency, and generate images
             """)