Update app.py

app.py

@@ -149,6 +149,7 @@ async def run_and_submit_all(profile: gr.OAuthProfile | None):
     Fetches all questions asynchronously, runs the MagAgent on them, submits all answers,
     and displays the results.
     """
+    # --- Determine HF Space Runtime URL and Repo URL ---
     space_id = os.getenv("SPACE_ID")
 
     if profile:
@@ -162,6 +163,7 @@ async def run_and_submit_all(profile: gr.OAuthProfile | None):
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
+    # 1. Instantiate Agent
     try:
         agent = MagAgent(rate_limiter=token_bucket)
     except Exception as e:
@@ -171,6 +173,7 @@ async def run_and_submit_all(profile: gr.OAuthProfile | None):
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
     print(agent_code)
 
+    # 2. Fetch Questions Asynchronously
     async with aiohttp.ClientSession() as session:
         questions_data = await fetch_questions(session, questions_url)
         if questions_data is None:
@@ -178,6 +181,8 @@ async def run_and_submit_all(profile: gr.OAuthProfile | None):
         if not questions_data:
             return "Fetched questions list is empty or invalid format.", None
 
+        # 3. Run Agent on Questions
+        # Process questions sequentially with rate limiting
         results_log = []
         answers_payload = []
         print(f"Running agent on {len(questions_data)} questions...")
@@ -194,13 +199,14 @@ async def run_and_submit_all(profile: gr.OAuthProfile | None):
                 if result:
                     answers_payload.append(result)
             else:
-                print(f"Skipping not related question: {task_id}")
+                print(f"Skipping not related question")
                 results_log.append({
                     "Task ID": task_id,
                     "Question": question_text,
                     "Submitted Answer": "Question skipped - not related"
                 })
-
+#            await asyncio.sleep(30)
+        
         if not answers_payload:
             print("Agent did not produce any answers to submit.")
             return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)