change done

app.py

@@ -3,6 +3,7 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from agent import run_agent 
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -10,14 +11,25 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
-class BasicAgent:
-    def __init__(self):
-        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."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+class GAIAAgentWrapper:
+    """Wrap run_agent to match agent(question) signature."""
+    def __call__(self, question_data) -> str:
+        """
+        question_data: str or dict with keys:
+            - 'question': text
+            - 'file_path': optional path to attached file
+        """
+        if isinstance(question_data, str):
+            question_text = question_data
+            file_path = None
+        elif isinstance(question_data, dict):
+            question_text = question_data.get("question", "")
+            file_path = question_data.get("file_path")
+        else:
+            raise ValueError("Invalid input type for agent.")
+        return run_agent(question_text, file_path=file_path)
+    
+
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
@@ -40,7 +52,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
-        agent = BasicAgent()
+        agent = GAIAAgentWrapper()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
@@ -76,11 +88,14 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     for item in questions_data:
         task_id = item.get("task_id")
         question_text = item.get("question")
+        file_path = item.get("file_name")
+        print(f"Question (Task {task_id}): {question_text}")
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            submitted_answer = agent(question_text)
+            submitted_answer = agent({"question": question_text, "file_path": file_path})
+            print(f"Submitted Answer: {submitted_answer}\n{'-'*50}")
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e:

requirements.txt

@@ -1,2 +1,11 @@
+agent
 gradio
-requests
+langchain
+langchain_community
+langchain_core
+langchain_openai
+langgraph
+openai
+pandas
+requests
+tavily