Update Gradio_UI.py

fixed Pydantic validations

Gradio_UI.py

@@ -2,7 +2,7 @@
 # coding=utf-8
 import os
 import re
-from typing import Optional, List
+from typing import Optional, List, Dict
 from smolagents.agent_types import AgentText, handle_agent_output_types
 from smolagents.agents import ActionStep, MultiStepAgent
 from smolagents.memory import MemoryStep
@@ -21,12 +21,8 @@ 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
@@ -34,42 +30,36 @@ def pull_messages_from_step(step_log: MemoryStep):
             tool_call = step_log.tool_calls[0]
             parent_id = f"tool_{step_log.step_number}"
             
-            # Format tool arguments cleanly
             args = tool_call.arguments
             if isinstance(args, dict):
                 content = "\n".join(f"• {k}: {v}" for k, v in args.items() if v and k != 'self')
             else:
                 content = str(args).strip()
             
-            yield gr.ChatMessage(
-                role="assistant",
-                content=content,
-                metadata={
-                    "title": f"🛠️ Using: {tool_call.name}",
-                    "id": parent_id,
-                    "status": "running",
-                },
-            )
+            metadata: Dict = {
+                "title": f"🛠️ Using: {tool_call.name}",
+                "id": parent_id,
+                "status": "running",
+            }
+            yield gr.ChatMessage(role="assistant", content=content, metadata=metadata)
         
-        # Show observations/results
+        # Show observations/results (only include parent_id if defined)
         if hasattr(step_log, "observations") and step_log.observations:
             obs = step_log.observations.strip()
             if obs and not obs.startswith("Execution logs:"):
-                yield gr.ChatMessage(
-                    role="assistant",
-                    content=obs,
-                    metadata={"title": "✅ Result", "parent_id": parent_id},
-                )
+                metadata = {"title": "✅ Result"}
+                if parent_id is not None:
+                    metadata["parent_id"] = parent_id
+                yield gr.ChatMessage(role="assistant", content=obs, metadata=metadata)
         
-        # Show errors if any (safe parent_id reference)
+        # Show errors (only include parent_id if defined)
         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},
-            )
+            metadata = {"title": "⚠️ Warning"}
+            if parent_id is not None:
+                metadata["parent_id"] = parent_id
+            yield gr.ChatMessage(role="assistant", content=str(step_log.error), metadata=metadata)
         
-        # Step footer with metrics
+        # Step footer
         footer_parts = [step_number]
         if hasattr(step_log, "duration") and step_log.duration:
             footer_parts.append(f"⏱️ {float(step_log.duration):.1f}s")
@@ -97,7 +87,6 @@ def stream_to_gradio(
     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
@@ -105,16 +94,10 @@ def stream_to_gradio(
                 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}
-            )
+            yield gr.ChatMessage(role="assistant", content=content, metadata={"react": True})
         else:
             yield gr.ChatMessage(role="assistant", content=f"**Final Answer:** {str(final)}")
     
@@ -122,7 +105,6 @@ def stream_to_gradio(
         yield gr.ChatMessage(
             role="assistant",
             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"}
         )
 
 class GradioUI:
@@ -176,11 +158,9 @@ class GradioUI:
             gr.Markdown("""
             ### 💡 Tips for best results:
             • Include: destination, dates, origin city, budget amount + currency  
-            • Example: *"5-day Barcelona trip from NYC, Oct 15-19, budget $1500 USD"*  
-            • Agent will research attractions, check weather, convert currency, and generate images
+            • Example: *"5-day Barcelona trip from NYC, Oct 15-19, budget $1500 USD"*
             """)
             
-            # Submit on button click or Enter
             submit_btn.click(
                 self.interact_with_agent,
                 inputs=[text_input, chatbot],