Update app.py

app.py

@@ -13,44 +13,13 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 import os
 from typing import List, Dict, Any, Optional
 from smolagents import CodeAgent, Tool, tool, LiteLLMModel
-from linkup import LinkupClient
+from agents import create_agent
 
 import json
 import re
 from datetime import datetime
 
 
-class LinkupSearchTool(Tool):
-    name = "linkup_web_search"
-    description = "Performs a search for your text query using Linkup sdk then returns a string of the top search results."
-    inputs = {
-        "query": {"type": "string", "description": "The search query to perform."},
-    }
-    output_type = "string"
-
-    def __init__(self, answer_output_type: str = "sourcedAnswer",
-                 **kwargs):
-        super().__init__(self)
-        import os
-
-        self.api_key = os.getenv("LINKUP_API_KEY")
-        if self.api_key is None:
-            raise ValueError("Missing Linkup API key. Make sure you have 'LINKUP_API_KEY' in your env variables.")
-
-        self.client = LinkupClient(api_key=self.api_key)
-        self.answer_output_type = answer_output_type
-
-    def forward(self, query: str) -> str:
-        response = self.client.search(
-            query=query,
-            depth="deep",
-            output_type=self.answer_output_type
-        )
-
-        answer_text = getattr(response, "answer", "No answer provided.")
-
-        return f'Answer:{answer_text}'
-
 
 custom_role_conversions = {"tool-call": "assistant", "tool-response": "user"}
 
@@ -66,23 +35,8 @@ class BasicAgent:
         """
         print("BasicAgent initialized.")
         
-        # Initialize tools
-        self.web_search_tool = LinkupSearchTool()
-
-        model_params = {
-        "model_id": "gpt-4o-mini",
-        "custom_role_conversions": custom_role_conversions,
-        "max_completion_tokens": 8192,
-        }
-        self.model = LiteLLMModel(**model_params)
-        
         # Initialize the agent
-        self.agent = CodeAgent(
-            model=self.model,
-            tools=[
-                self.web_search_tool, 
-            ],
-        )
+        self.agent = create_agent()
     
     def __call__(self, question: str) -> str:
         """