Update app.py

app.py

@@ -4,18 +4,64 @@ import requests
 import inspect
 import pandas as pd
 
+Copied
+from typing import TypedDict, Annotated
+from langgraph.graph.message import add_messages
+from langchain_core.messages import AnyMessage, HumanMessage, AIMessage
+from langgraph.graph import StateGraph, START, END
+from langchain_community.tools import DuckDuckGoSearchRun
+from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
+
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+class AgentState(TypedDict):
+    messages: Annotated[list[AnyMessage], add_messages]
+
 class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
+        
+        llm = HuggingFaceEndpoint(
+        repo_id="Qwen/Qwen2.5-Coder-32B-Instruct",
+        huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
+        )
+        
+        search_tool = DuckDuckGoSearchRun()
+        tools = [search_tool]
+        chat_with_tools = chat.bind_tools(tools)
+        
+        def assistant(state: AgentState):
+            return {
+                "messages": [chat_with_tools.invoke(state["messages"])],
+            }
+        
+        ## The graph
+        builder = StateGraph(AgentState)
+        
+        # Define nodes: these do the work
+        builder.add_node("assistant", assistant)
+        builder.add_node("tools", ToolNode(tools))
+        
+        # Define edges: these determine how the control flow moves
+        builder.add_edge(START, "assistant")
+        builder.add_conditional_edges(
+            "assistant",
+            # If the latest message requires a tool, route to tools
+            # Otherwise, provide a direct response
+            tools_condition,
+        )
+        builder.add_edge("tools", "assistant")
+        self.agent = builder.compile()
+        
     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)]
+        answer = self.agent.invoke({"messages": messages})
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer