Update app.py

Try smolagents code agent with Serper google search

app.py

@@ -4,9 +4,8 @@ import requests
 import inspect
 import pandas as pd
 import os
-from smolagents import LiteLLMModel, CodeAgent, tool
+from smolagents import LiteLLMModel, CodeAgent, tool, GoogleSearchTool
 from google import genai
-# from google.genai.types import Tool, GoogleSearch
 from google.genai import types
 import asyncio
 import requests
@@ -15,6 +14,7 @@ import requests
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 GEMINI_API_KEY = os.getenv("Gemini_API_key")
+SERPER_API_KEY = os.getenv("Serper_API_key")
 
 # --- Basic Agent Definition ---
 # Agent capabilities required: Search the web, listen to audio recordings, watch YouTube videos (process the footage, not the transcript), work with Excel spreadsheets
@@ -22,16 +22,16 @@ GEMINI_API_KEY = os.getenv("Gemini_API_key")
 
 class BasicAgent:
     def __init__(self):
-        # self.llm_model = LiteLLMModel(
-        #     model_id="gemini/gemini-2.0-flash", # you can see other model names here: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models. It is important to prefix the name with "gemini/"
-        #     api_key=GEMINI_API_KEY,
-        #     max_tokens=8192
-        #     )
-        # # self.google_search_tool = Tool(google_search = GoogleSearch())
-        # self.google_search_tool = GoogleSearchTool()
-        # self.agent = CodeAgent(model = self.llm_model, tools = [self.google_search_tool])
-        # Define Google API client with GoogleSearch tool
-        self.client = genai.Client(api_key=GEMINI_API_KEY)
+        self.llm_model = LiteLLMModel(
+            model_id="gemini/gemini-2.0-flash", # you can see other model names here: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models. It is important to prefix the name with "gemini/"
+            api_key=GEMINI_API_KEY,
+            max_tokens=8192
+            )
+        # self.google_search_tool = Tool(google_search = GoogleSearch())
+        self.google_search_tool = GoogleSearchTool()
+        self.agent = CodeAgent(model = self.llm_model, tools = [self.google_search_tool, self.get_file])
+        # # Define Google API client with GoogleSearch tool
+        # self.client = genai.Client(api_key=GEMINI_API_KEY)
         
         print("BasicAgent initialized.")
     
@@ -40,20 +40,22 @@ class BasicAgent:
         fixed_answer = "This is a default answer."
         # print(f"Agent returning fixed answer: {fixed_answer}")
         # return fixed_answer
-        # return self.agent.run(question)
-        # Use the Google GenAI client to run the question
+        
         await asyncio.sleep(10)
-        answer = self.client.models.generate_content(
-            model='gemini-2.0-flash',
-            contents=f'''Answer the following question in the format as requested. If the format not specified, then provide a single word/number/name. 
-            In your response, do not include anything other than your answer. {question}''',
-            config=types.GenerateContentConfig(
-                tools=[types.Tool(google_search=types.GoogleSearch()),
-                    types.Tool(code_execution=self.get_file)]
-            )
-        )
-        return answer.text
+        return self.agent.run(question, task_id)
+        # # Use the Google GenAI client to run the question
+        # answer = self.client.models.generate_content(
+        #     model='gemini-2.0-flash',
+        #     contents=f'''Answer the following question in the format as requested. If the format not specified, then provide a single word/number/name. 
+        #     In your response, do not include anything other than your answer. {question}''',
+        #     config=types.GenerateContentConfig(
+        #         tools=[types.Tool(google_search=types.GoogleSearch()),
+        #             types.Tool(code_execution=self.get_file)]
+        #     )
+        # )
+        # return answer.text
 
+    @tool
     def get_file(self, task_id):
         '''
         Downloads the file associated with the given task_id, if one exists and is mapped.