replying all qs

app.py

@@ -226,40 +226,27 @@ class GaiaAgent:
             return f"Error during agent invocation: {e}"
 
 
-# In app.py
-
-# ... (keep all the code above this function)
-
-
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     if not profile:
-        return "Please Login to Hugging Face with the button.", None
+        return "Please Login to Hugging Face.", None
     username = profile.username
     logging.info(f"User logged in: {username}")
 
     space_id = os.getenv("SPACE_ID")
     if not space_id:
-        space_id = "leofltt/HF_Agents_Final_Assignment"
-        logging.warning(f"SPACE_ID not found, using fallback for local run: {space_id}")
-
-    if not space_id:
-        return "CRITICAL ERROR: SPACE_ID environment variable is not set.", None
+        space_id = "leofltt/HF_Agents_Final_Assignment"  # Your fallback
+        logging.warning(f"SPACE_ID not found, using fallback: {space_id}")
 
-    api_url = DEFAULT_API_URL
-    questions_url = f"{api_url}/questions"
-    submit_url = f"{api_url}/submit"
+    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
 
     try:
         agent = GaiaAgent()
     except Exception as e:
-        logging.critical(f"Fatal error instantiating agent: {e}", exc_info=True)
         return f"Fatal error initializing agent: {e}", None
 
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-
-    logging.info(f"Fetching questions from: {questions_url}")
+    logging.info("Fetching questions...")
     try:
-        response = requests.get(questions_url, timeout=20)
+        response = requests.get(f"{DEFAULT_API_URL}/questions", timeout=20)
         response.raise_for_status()
         questions_data = response.json()
         if not questions_data:
@@ -268,81 +255,65 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     except Exception as e:
         return f"Error fetching questions: {e}", None
 
-    # --- MODIFICATION FOR DEBUGGING ---
-    # We will only process the first question from the list.
-    questions_to_process = [questions_data[0]]
+    # The loop will now process the full 'questions_data' list
     logging.info(
-        f"DEBUG MODE: Processing only the first question out of {len(questions_data)}."
+        f"FULL EVALUATION MODE: Processing all {len(questions_data)} questions..."
     )
-    # --- END OF MODIFICATION ---
 
     results_log = []
     answers_payload = []
-
-    # The loop now runs only once.
-    for i, item in enumerate(questions_to_process):
+    for i, item in enumerate(questions_data):
         task_id = item.get("task_id")
         question_text = item.get("question")
-        logging.info(f"--- Processing question (Task ID: {task_id}) ---")
-        if not task_id or question_text is None:
-            continue
+        logging.info(
+            f"--- Processing question {i+1}/{len(questions_data)} (Task ID: {task_id}) ---"
+        )
         try:
-            submitted_answer = agent(question_text)
-            answers_payload.append(
-                {"task_id": task_id, "submitted_answer": submitted_answer}
-            )
+            answer = agent(question_text)
+            answers_payload.append({"task_id": task_id, "submitted_answer": answer})
             results_log.append(
                 {
                     "Task ID": task_id,
                     "Question": question_text,
-                    "Submitted Answer": submitted_answer,
+                    "Submitted Answer": answer,
                 }
             )
         except Exception as e:
-            logging.error(f"Error running agent on task {task_id}: {e}", exc_info=True)
+            error_message = f"AGENT ERROR on task {task_id}: {e}"
+            logging.error(error_message, exc_info=True)
             results_log.append(
                 {
                     "Task ID": task_id,
                     "Question": question_text,
-                    "Submitted Answer": f"AGENT ERROR: {e}",
+                    "Submitted Answer": error_message,
                 }
             )
-            # Also return the error in the status for immediate feedback
-            return f"Agent failed on the first question with error: {e}", pd.DataFrame(
-                results_log
-            )
 
     if not answers_payload:
-        return "Agent did not produce an answer for the first question.", pd.DataFrame(
-            results_log
-        )
-
-    submission_data = {
-        "username": username.strip(),
-        "agent_code": agent_code,
-        "answers": answers_payload,
-    }
-    logging.info(f"Submitting {len(answers_payload)} answer for user '{username}'...")
+        return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
+    logging.info(f"Submitting {len(answers_payload)} answers...")
     try:
-        response = requests.post(submit_url, json=submission_data, timeout=60)
+        submission_data = {
+            "username": username,
+            "agent_code": agent_code,
+            "answers": answers_payload,
+        }
+        response = requests.post(
+            f"{DEFAULT_API_URL}/submit", json=submission_data, timeout=60
+        )
         response.raise_for_status()
         result_data = response.json()
-        final_status = (
-            f"Submission Successful (for one question)!\n"
+        status = (
+            f"Submission Successful!\n"
             f"User: {result_data.get('username')}\n"
             f"Overall Score: {result_data.get('score', 'N/A')}% "
             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)
-    except requests.exceptions.HTTPError as e:
-        error_detail = f"Server responded with status {e.response.status_code}. Detail: {e.response.text}"
-        return f"Submission Failed: {error_detail}", pd.DataFrame(results_log)
+        return status, pd.DataFrame(results_log)
     except Exception as e:
-        return f"An unexpected error occurred during submission: {e}", pd.DataFrame(
-            results_log
-        )
+        return f"Submission Failed: {e}", pd.DataFrame(results_log)
 
 
 with gr.Blocks() as demo: