Update Gradio_UI.py

compatibility issues fixed

Gradio_UI.py

@@ -1,9 +1,7 @@
 #!/usr/bin/env python
 # coding=utf-8
-import mimetypes
 import os
 import re
-import shutil
 from typing import Optional, List
 from smolagents.agent_types import AgentText, handle_agent_output_types
 from smolagents.agents import ActionStep, MultiStepAgent
@@ -33,7 +31,7 @@ def pull_messages_from_step(step_log: MemoryStep):
             # 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)
+                content = "\n".join(f"• {k}: {v}" for k, v in args.items() if v and k != 'self')
             else:
                 content = str(args).strip()
             
@@ -93,13 +91,11 @@ def stream_to_gradio(
         raise ModuleNotFoundError("Install gradio: `pip install 'smolagents[gradio]'`")
     
     import gradio as gr
-    total_tokens = 0
     
     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"):
-                total_tokens += agent.model.last_input_token_count + 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
             
@@ -110,15 +106,12 @@ def stream_to_gradio(
     final = handle_agent_output_types(step_log)
     if isinstance(final, AgentText):
         content = final.to_string()
-        # Format catalogue nicely
-        if "# 🌍" in content or "Travel Catalogue" in content:
-            yield gr.ChatMessage(
-                role="assistant",
-                content=content,
-                metadata={"react": True}  # Enable Markdown rendering
-            )
-        else:
-            yield gr.ChatMessage(role="assistant", content=f"**Final Answer:**\n{content}")
+        # 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)}")