Update app.py

app.py

@@ -14,6 +14,9 @@ from bs4 import BeautifulSoup
 from pydantic import BaseModel, Field
 import nest_asyncio
 import requests
+import asyncio
+from tavily import TavilyClient
+
 
 #from agents.extensions.models.litellm_model import LitellmModel
 
@@ -135,7 +138,7 @@ class BasicAgent:
         print("BasicAgent initialized.")
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-
+    
         instructions = """
 You are a ReAct (Reason-Act-Observe) agent that searches the internet to find accurate answers to questions.
 ## Available Tools
@@ -174,25 +177,17 @@ When you've found the answer, stop reasoning and return ONLY the answer.
 - Just the answer text — for example: `California`
 
 """
-
+    
         my_agent = Agent(
             name="Expert Question Answering Agent",
             instructions=instructions,
-            tools = [
-                web_search,
-                visit_website
-            ],
+            tools = [tavily_search, visit_website],
             model="gpt-4o-mini"
         )
-
-        import nest_asyncio
-        import asyncio
-        
-        nest_asyncio.apply()
-        
+    
         async def run_agent_streamed():
             async for update in Runner.run_streamed(my_agent, input=question, max_turns=25):
-                if update.new_items:
+                if hasattr(update, "new_items") and update.new_items:
                     for step in update.new_items:
                         print("🧠 Thought:", step.thought)
                         print("⚙️ Action:", step.tool_call)
@@ -200,23 +195,12 @@ When you've found the answer, stop reasoning and return ONLY the answer.
                         print("-" * 50)
             print(f"Agent gave answer (first 50 chars): {update.final_output[:50]}...")
             return update.final_output
+    
+        result = asyncio.run(run_agent_streamed())
+        return result
+
         
-        result = await run_agent_streamed()  # If already inside an async context
-
-#        result = Runner.run_sync(
-#                my_agent,
-#                input=question,
-#               max_turns=25
-#           )
-#        print("\n--- Intermediate Reasoning ---")
-#        for step in result.steps:
-#            print("🧠 Thought:", step.thought)
-#           print("⚙️ Action:", step.tool_call)
-#            print("🔍 Observation:", step.observation)
-#           print("-" * 50)
-
-#        print(f"Agent returning fixed answer(first 50 chars): {result.final_output[:50]}...")
-#       return result.final_output
+
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """