add parse answer

agent.py

@@ -10,10 +10,10 @@ from tools import tools
 from retriever import vector_store
 from langchain_openai import ChatOpenAI
 
-
 load_dotenv()
 
 
+
 # System message
 sys_msg = SystemMessage(content=SYS_PROMPT)
 
@@ -62,5 +62,6 @@ if __name__ == "__main__":
     # Run the graph
     messages = [HumanMessage(content=question)]
     messages = graph.invoke({"messages": messages})
+    answer = messages['messages'][-1].content
     for m in messages["messages"]:
         m.pretty_print()

app.py

@@ -1,8 +1,13 @@
+""" Basic Agent Evaluation Runner"""
 import os
+import inspect
 import gradio as gr
+import re
 import requests
-import inspect
 import pandas as pd
+from langchain_core.messages import HumanMessage
+from agent import build_graph
+
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -10,14 +15,32 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+
+
 class BasicAgent:
+    """A langgraph agent."""
     def __init__(self):
         print("BasicAgent initialized.")
+        self.graph = build_graph()
+
     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
+        # Wrap the question in a HumanMessage from langchain_core
+        messages = [HumanMessage(content=question)]
+        messages = self.graph.invoke({"messages": messages})
+        answer = messages['messages'][-1].content
+        return parse_final_answer(answer)
+
+def parse_final_answer(answer: str) -> str:
+    """
+    Parses the final answer from the agent's response.
+    This function is a placeholder and should be modified based on the actual output format of your agent.
+    """
+    match = re.search(r'FINAL ANSWER:\s*(.*)', answer)
+    if match:
+        final_answer = match.group(1)
+        return final_answer.strip()
+    return answer.strip()
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """