Update app.py

app.py

@@ -1,49 +1,24 @@
 # 17/08/2025 -AO
+
 import os
 import gradio as gr
 import requests
 import inspect
 import pandas as pd
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer
-from transformers.agents import HfAgent 
-from transformers.tools import DuckDuckGoSearchTool 
-from huggingface_hub import InferenceClient
+from agent import BasicAgent
+
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Advanced Agent Definition ---
-# ----- THIS IS WHERE YOU BUILD YOUR AGENT ------
-class MyAgent:
-    def __init__(self):
-        # Initialize the model and tokenizer for tool use
-        print("Initializing MyAgent with Qwen2.5-72B-Instruct...")
-      
-        # Muista asettaa -> HF_TOKEN secret in your space settings.
-        self.agent = HfAgent(
-            llm="Qwen/Qwen2.5-72B-Instruct",
-            additional_tools=[DuckDuckGoSearchTool()],
-        )
-        print("Agent initialized with InferenceClient.")
-
-    def __call__(self, question: str) -> str:
-        print(f"Agent received question: {question[:50]}...")
-        try:
-            result = self.agent.run(question)
-            
-            # The GAIA scoring is an "EXACT MATCH".
-            final_answer = str(result)
-            print(f"Agent returning answer: {final_answer}")
-            return final_answer
-        except Exception as e:
-            print(f"An error occurred during agent execution: {e}")
-            return f"Error: {e}"
 
-# The rest of the `run_and_submit_all` and Gradio code remains the same as in the template.
-def run_and_submit_all(profile: gr.OAuthProfile | None):
+def run_and_submit_all( profile: gr.OAuthProfile | None):
+    """
+    Fetches all questions, runs the BasicAgent on them, submits all answers,
+    and displays the results.
+    """
     # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = os.getenv("SPACE_ID")
+    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
 
     if profile:
         username= f"{profile.username}"
@@ -58,7 +33,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
-        agent = MyAgent()
+        agent = BasicAgent()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
@@ -94,11 +69,12 @@ 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_name_text = item.get("file_name")
         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_text, file_name_text)
             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:
@@ -109,7 +85,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # 4. Prepare Submission
+    # 4. Prepare Submission 
     submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
@@ -157,16 +133,20 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
 
+
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
     gr.Markdown(
         """
         **Instructions:**
-
         1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
         2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
         3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
+        ---
+        **Disclaimers:**
+        Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
+        This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
         """
     )
 
@@ -175,6 +155,7 @@ with gr.Blocks() as demo:
     run_button = gr.Button("Run Evaluation & Submit All Answers")
 
     status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
+    # Removed max_rows=10 from DataFrame constructor
     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
     run_button.click(