Update app.py

app.py

@@ -3,7 +3,7 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-from smolagents import CodeAgent, DuckDuckGoSearchTool, FinalAnswerTool, PythonInterpreterTool, VisitWebpageTool, LiteLLMModel, ToolCallingAgent
+from smolagents import CodeAgent, DuckDuckGoSearchTool, FinalAnswerTool, PythonInterpreterTool, VisitWebpageTool, LiteLLMModel, ToolCallingAgent, WebSearchTool
 from groq import Groq
 import time
 
@@ -17,7 +17,7 @@ GROQ_KEY = os.environ['GROQ_KEY']
 
 class LLaMaAgent:
     def __init__(self):
-        self.model = model = LiteLLMModel(
+        self.model = LiteLLMModel(
                 "meta-llama/llama-4-scout-17b-16e-instruct",
                 api_base="https://api.groq.com/openai/v1",
                 api_key=GROQ_KEY,
@@ -25,8 +25,9 @@ class LLaMaAgent:
         self.model.flatten_messages_as_text = True
 
         self.agent = CodeAgent(
-            tools=[DuckDuckGoSearchTool(), FinalAnswerTool(), VisitWebpageTool(), PythonInterpreterTool()],
-            model=model,
+            tools=[DuckDuckGoSearchTool(), FinalAnswerTool(), VisitWebpageTool(), PythonInterpreterTool(), WebSearchTool()],
+            add_base_tools=True,
+            model=self.model,
         )
         
     def __call__(self, question: str) -> str:
@@ -37,28 +38,6 @@ class LLaMaAgent:
             print("First LLaMa Error!!!")
             raise 
 
-class LLaMaAgent2:
-    def __init__(self):
-        self.model = model = LiteLLMModel(
-                "meta-llama/llama-4-scout-17b-16e-instruct",
-                api_base="https://api.groq.com/openai/v1",
-                api_key=GROQ_KEY,
-            )
-        self.model.flatten_messages_as_text = True
-
-        self.agent = ToolCallingAgent(
-            tools=[DuckDuckGoSearchTool(), FinalAnswerTool(), VisitWebpageTool(), PythonInterpreterTool()],
-            model=model,
-        )
-        
-    def __call__(self, question: str) -> str:
-        try:
-            response = self.agent.run(question)
-            return response
-        except Exception as e:
-            print("Third LLaMa Error!!!")
-            raise 
-
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
@@ -81,7 +60,6 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
         llama = LLaMaAgent()
-        llama2 = LLaMaAgent2()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
@@ -121,12 +99,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            try:
-                submitted_answer = llama(question_text)
-            except Exception as ke:
-                print("Second LLaMa Error!")
-                time.sleep(60)
-                submitted_answer = llama2(question_text)
+            submitted_answer = llama(question_text)
             print(f"\n\n### Answer{submitted_answer} ###\n\n")
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})