diff --git a/main.py b/main.py
index fc4efcd..dc1d257 100644
--- a/main.py
+++ b/main.py
@@ -87,7 +87,7 @@ class UAVAgentGUI:
 
         self.provider_var = tk.StringVar(value="Ollama")
         self.model_var = tk.StringVar()
-        self.uav_base_url_var = tk.StringVar(value="http://localhost:8000")
+        self.uav_base_url_var = tk.StringVar(value="http://127.0.0.1:8000")
         self.uav_api_key_var = tk.StringVar(value="agent_secret_key_change_in_production")  # UAV API key for authentication
         self.temperature_var = tk.DoubleVar(value=0.1)
         self.verbose_var = tk.BooleanVar(value=True)
diff --git a/uav_agent.py b/uav_agent.py
index 20d4532..5492fc1 100644
--- a/uav_agent.py
+++ b/uav_agent.py
@@ -8,16 +8,40 @@ from langchain_classic.agents import AgentExecutor
 from langchain_classic.prompts import PromptTemplate
 from langchain_ollama import ChatOllama
 from langchain_openai import ChatOpenAI
+from langchain_core.outputs import ChatResult
+from langchain_core.messages import AIMessage
 from uav_api_client import UAVAPIClient
 from uav_langchain_tools import create_uav_tools
 from template.agent_prompt import AGENT_PROMPT
 from template.parsing_error import PARSING_ERROR_TEMPLATE
-from typing import Optional, Dict, Any
+from typing import Optional, Dict, Any, List
 import json
 import os
 from pathlib import Path
 
 
+class EnhancedChatOpenAI(ChatOpenAI):
+    """ChatOpenAI subclass that captures reasoning_content if provided by the API"""
+    
+    def _create_chat_result(self, response: Any) -> ChatResult:
+        result = super()._create_chat_result(response)
+        
+        if hasattr(response, "choices") and response.choices:
+            for i, choice in enumerate(response.choices):
+                # Handle MiniMax reasoning_details
+                if hasattr(choice.message, "reasoning_details") and choice.message.reasoning_details:
+                    reasoning = choice.message.reasoning_details[0].get('text', '')
+                    if reasoning and i < len(result.generations):
+                        gen = result.generations[i]
+                        if isinstance(gen.message, AIMessage):
+                            # Store in additional_kwargs
+                            gen.message.additional_kwargs["reasoning_content"] = reasoning
+                            # Prepend to content for ReAct agent visibility
+                            if "Thought:" not in gen.message.content:
+                                gen.message.content = f"Thought: {reasoning}\n" + gen.message.content
+        return result
+
+
 def load_llm_settings(settings_path: str = "llm_settings.json") -> Optional[Dict[str, Any]]:
     """Load LLM settings from JSON file"""
     try: