Update app.py

app.py

@@ -5,7 +5,7 @@ import pandas as pd
 
 # Import smol-agent and tool components
 from smolagents import CodeAgent, LiteLLMModel, tool
-from smolagents.tools import WebSearchTool
+from smolagents.tools import DuckDuckGoSearchTool
 from unstructured.partition.auto import partition
 
 
@@ -39,31 +39,32 @@ def file_reader(file_path: str) -> str:
 class GaiaSmolAgent:
     def __init__(self):
         print("Initializing GaiaSmolAgent with OpenAI...")
-        # --- MODIFICATION 1: Use OPENAI_API_KEY ---
         # Ensure you have set your OPENAI_API_KEY as a secret in your HF Space
-        api_key = os.getenv("OPENAI_API_KEY") 
+        api_key = os.getenv("OPENAI_API_KEY")
         if not api_key:
             raise ValueError("API key 'OPENAI_API_KEY' not found in environment secrets.")
 
-        # --- MODIFICATION 2: Use an OpenAI Model ID ---
         # The "Planner" model - for high-level reasoning
         self.planner_model = LiteLLMModel(
             model_id="gpt-4o", # Using OpenAI's gpt-4o model
             api_key=api_key,
             temperature=0.0,
         )
+        
+        from smolagents.tools import DuckDuckGoSearchTool 
 
         # The "Executor" agent - for executing tasks with tools
         self.executor_agent = CodeAgent(
             model=self.planner_model, # Can use the same model
-            tools=[file_reader, WebSearchTool()],
-            # add_base_tools=True will add a Python interpreter
+            # --- MODIFICATION 2: Use the correct tool name in the list ---
+            tools=[file_reader, DuckDuckGoSearchTool()], # Corrected class name
             add_base_tools=True,
         )
         print("GaiaSmolAgent initialized successfully with OpenAI.")
 
     def _generate_plan(self, question: str) -> list[str]:
         """Generates a step-by-step plan to answer the question."""
+        # ... (This method remains unchanged)
         print(f"Generating plan for question: {question[:100]}...")
         prompt = f"""
         You are an expert planner. Your job is to create a clear, step-by-step plan to answer the given question.
@@ -91,14 +92,10 @@ class GaiaSmolAgent:
 
     def __call__(self, question: str) -> str:
         """Runs the planner and executor to answer the question."""
+        # ... (This method remains unchanged)
         print(f"Agent received question: {question[:100]}...")
-
-        # Step 1: Generate the plan
         plan = self._generate_plan(question)
-
-        # Step 2: Execute the plan
         final_answer = self.executor_agent.run(plan)
-
         print(f"Agent returning final answer: {final_answer}")
         return str(final_answer)