Update app.py

app.py

@@ -2,12 +2,11 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
+import re
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-import re
-
 # ----- Robust Hardcoded Agent Definition -----
 class RobustHardcodedAgent:
     def __init__(self):
@@ -28,7 +27,7 @@ class RobustHardcodedAgent:
         # Supprime retours à la ligne, espaces multiples, ponctuation et met en minuscules
         text = text.lower()
         text = re.sub(r'\s+', ' ', text)
-        text = re.sub(r'[^\w\s]', '', text)  # retire ponctuation
+        text = re.sub(r'[^\w\s]', '', text)
         return text.strip()
 
     def __call__(self, question: str) -> str:
@@ -38,11 +37,10 @@ class RobustHardcodedAgent:
         print(f"Agent returning answer: {answer}")
         return answer
 
-
-# ----- Run & Submit Function -----
+# ----- Run and Submit All -----
 def run_and_submit_all(profile: gr.OAuthProfile | None):
-    """ Fetches all questions, runs the HardcodedAgent on them, submits all answers, and displays the results. """
-    space_id = os.getenv("SPACE_ID")
+    """ Fetches all questions, runs the RobustHardcodedAgent on them, submits answers, and returns results. """
+    
     if profile:
         username = profile.username
         print(f"User logged in: {username}")
@@ -54,25 +52,26 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
-    # Instantiate agent
+    # 1. Instantiate Agent
     try:
-        agent = HardcodedAgent()
+        agent = RobustHardcodedAgent()
     except Exception as e:
+        print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
 
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-
-    # Fetch questions
+    # 2. Fetch Questions
     try:
         response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
         questions_data = response.json()
         if not questions_data:
             return "Fetched questions list is empty or invalid format.", None
+        print(f"Fetched {len(questions_data)} questions.")
     except Exception as e:
+        print(f"Error fetching questions: {e}")
         return f"Error fetching questions: {e}", None
 
-    # Run agent on questions
+    # 3. Run Agent
     results_log = []
     answers_payload = []
     for item in questions_data:
@@ -90,8 +89,12 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     if not answers_payload:
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # Submit answers
+    # 4. Prepare Submission
+    space_id = os.getenv("SPACE_ID")
+    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
     submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
+
+    # 5. Submit
     try:
         response = requests.post(submit_url, json=submission_data, timeout=60)
         response.raise_for_status()
@@ -103,37 +106,29 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
             f"Message: {result_data.get('message', 'No message received.')}"
         )
-        return final_status, pd.DataFrame(results_log)
+        results_df = pd.DataFrame(results_log)
+        return final_status, results_df
     except Exception as e:
-        status_message = f"Submission Failed: {e}"
-        return status_message, pd.DataFrame(results_log)
+        results_df = pd.DataFrame(results_log)
+        return f"Submission Failed: {e}", results_df
 
-# ----- Build Gradio Interface -----
+# ----- Gradio Interface -----
 with gr.Blocks() as demo:
-    gr.Markdown("# Hardcoded Agent Evaluation Runner")
-    gr.Markdown("""
-**Instructions:**  
-1. Clone this space, then modify the code to define your agent's logic if needed.  
-2. Log in to your Hugging Face account using the button below.  
-3. Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
-""")
+    gr.Markdown("# Robust Hardcoded Agent Evaluation Runner")
+    gr.Markdown(
+        """
+        **Instructions:**  
+        1. Log in to your Hugging Face account.  
+        2. Click 'Run Evaluation & Submit All Answers' to fetch questions, run the agent, submit answers, and see the score.
+        """
+    )
     gr.LoginButton()
     run_button = gr.Button("Run Evaluation & Submit All Answers")
     status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
-
     run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
+# ----- Main -----
 if __name__ == "__main__":
-    print("\n" + "-"*30 + " App Starting " + "-"*30)
-    space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID")
-    if space_host_startup:
-        print(f"✅ SPACE_HOST found: {space_host_startup}")
-        print(f" Runtime URL should be: https://{space_host_startup}.hf.space")
-    if space_id_startup:
-        print(f"✅ SPACE_ID found: {space_id_startup}")
-        print(f" Repo URL: https://huggingface.co/spaces/{space_id_startup}")
-    print("-"*(60 + len(" App Starting ")) + "\n")
-    print("Launching Gradio Interface for Hardcoded Agent Evaluation...")
+    print("\nLaunching Gradio Interface for Robust Hardcoded Agent...")
     demo.launch(debug=True, share=False)