Update app.py

app.py

@@ -12,40 +12,43 @@ from langchain_core.messages import AnyMessage, HumanMessage, AIMessage
 from typing import TypedDict, Annotated
 from langgraph.graph.message import add_messages
 
+from smolagents import ToolCallingAgent, LiteLLMModel, tool, DuckDuckGoSearchTool
+from langchain_community.utilities import WikipediaAPIWrapper
+
+
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
+
+
+wikipedia = WikipediaAPIWrapper()
+@tool
+def wikipedia_search(query: str) -> str:
+    '''
+    Search Wikipedia and return a summary for a given query.
+    Args:
+        query: The search term or question to look up in Wikipedia.
+    '''
+    return wikipedia.run(query)
+
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
-        self.search_tool = DuckDuckGoSearchRun()
-        self.tools = [self.search_tool]
-
-        class AgentState(TypedDict):
-            messages: Annotated[list[AnyMessage], add_messages]
-
-        def assistant(state: AgentState):
-            user_message = state['messages'][-1]
-            if isinstance(user_message, HumanMessage):
-                result = self.search_tool.invoke(user_message.content)
-                return {'messages': [AIMessage(content=result)]}
-            return {'messages': [AIMessage(content='I can only answer human questions.')]}
-            
-        builder = StateGraph(AgentState)
-        builder.add_node("assistant", assistant)
-        builder.add_edge(START, "assistant")
-        self.alfred = builder.compile()
-        
+        print('BasicAgent initialized.')
+
     def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        messages = [HumanMessage(content=question)]
-        response = self.alfred.invoke({'messages': messages})
-        answer = response['messages'][-1].content
-        print(f"Agent returning fixed answer: {answer}")
+        print(f"Agent received question: {question[:50]}...")
+
+        agent = ToolCallingAgent(
+            tools=[DuckDuckGoSearchTool(), wikipedia_search],
+            model = LiteLLMModel(model_id="ollama/qwen2:7b", api_base='http://192.168.1.77:11434')
+            max_steps=15,
+            verbosity_level=2,
+        )
+
+        return agent.run(question)
         return answer
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):