Update app.py

app.py

@@ -4,20 +4,61 @@ import requests
 import inspect
 import pandas as pd
 
+
+from langgraph.graph import StateGraph, END
+from langchain_core.runnables import Runnable
+from langchain_core.agents import AgentFinish
+from langchain.agents import create_react_agent
+from langchain.agents.agent import RunnableAgent
+from langchain.agents.tools import Tool
+from langchain_core.messages import HumanMessage
+from langchain_openai import ChatOpenAI
+
+
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+
+
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
+        print("LangGraph ReAct Agent initialized.")
+        if not OPENAI_API_KEY:
+            raise ValueError("OPENAI_API_KEY environment variable not found.")
+
+        self.llm = ChatOpenAI(model="gpt-4o", api_key=OPENAI_API_KEY)
+
+        # Example tools
+        self.tools = [
+            Tool(
+                name="DuckDuckGo Search",
+                func=lambda q: f"Pretend search result for: {q}",
+                description="Search the web using DuckDuckGo. Useful for recent events."
+            )
+        ]
+
+        react_agent = create_react_agent(self.llm, self.tools)
+
+        workflow = StateGraph({"agent_outcome": Runnable})
+        workflow.add_node("agent", react_agent)
+        workflow.set_entry_point("agent")
+        workflow.add_edge("agent", END)
+
+        app = workflow.compile()
+        self.agent = RunnableAgent(app)
+
     def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+        result = self.agent.invoke({"input": HumanMessage(content=question)})
+        if isinstance(result, AgentFinish):
+            return result.return_values["output"]
+        elif isinstance(result, dict) and "output" in result:
+            return result["output"]
+        else:
+            return "No valid output returned."
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """