Update app.py

app.py

@@ -8,12 +8,15 @@ import requests
 import pandas as pd
 import json
 import re
+import time
 from typing import List, Dict, Any, Optional, Callable, Union
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 DEFAULT_MODEL = "google/flan-t5-small"  # Smaller model for faster loading
+MAX_RETRIES = 3  # Maximum number of submission retries
+RETRY_DELAY = 5  # Seconds to wait between retries
 
 class LLMGAIAAgent:
     """
@@ -280,8 +283,8 @@ class EvaluationRunner:
         if not answers_payload:
             return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
         
-        # Submit answers
-        submission_result = self._submit_answers(username, agent_code_url, answers_payload)
+        # Submit answers with retry logic
+        submission_result = self._submit_answers_with_retry(username, agent_code_url, answers_payload)
         
         # Return results
         return submission_result, pd.DataFrame(results_log)
@@ -355,11 +358,11 @@ class EvaluationRunner:
         
         return results_log, answers_payload
     
-    def _submit_answers(self, 
-                       username: str, 
-                       agent_code_url: str, 
-                       answers_payload: List[Dict[str, Any]]) -> str:
-        """Submit answers to the evaluation server."""
+    def _submit_answers_with_retry(self, 
+                                  username: str, 
+                                  agent_code_url: str, 
+                                  answers_payload: List[Dict[str, Any]]) -> str:
+        """Submit answers to the evaluation server with retry logic."""
         submission_data = {
             "username": username.strip(),
             "agent_code": agent_code_url,
@@ -369,30 +372,75 @@ class EvaluationRunner:
         status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
         print(status_update)
         
-        try:
-            response = requests.post(self.submit_url, json=submission_data, timeout=60)
-            response.raise_for_status()
-            result_data = response.json()
-            
-            final_status = (
-                f"Submission Successful!\n"
-                f"User: {result_data.get('username')}\n"
-                f"Overall Score: {result_data.get('overall_score', 'N/A')}\n"
-                f"Correct Answers: {result_data.get('correct_answers', 'N/A')}\n"
-                f"Total Questions: {result_data.get('total_questions', 'N/A')}\n"
-            )
-            print(final_status)
-            return final_status
-            
-        except requests.exceptions.RequestException as e:
-            error_msg = f"Error submitting answers: {e}"
-            print(error_msg)
-            return error_msg
+        # Try submission with retries
+        for attempt in range(1, MAX_RETRIES + 1):
+            try:
+                print(f"Submission attempt {attempt} of {MAX_RETRIES}...")
+                response = requests.post(self.submit_url, json=submission_data, timeout=60)
+                response.raise_for_status()
+                result_data = response.json()
+                
+                # Check if all evaluation results are N/A
+                if all(result_data.get(key, "N/A") == "N/A" for key in ["overall_score", "correct_answers", "total_questions"]):
+                    # If all values are N/A and we have retries left
+                    if attempt < MAX_RETRIES:
+                        print(f"Received N/A results. Waiting {RETRY_DELAY} seconds before retry...")
+                        time.sleep(RETRY_DELAY)
+                        continue
+                    
+                    # If this was our last attempt, provide detailed information
+                    final_status = (
+                        f"Submission Successful, but results are pending!\n"
+                        f"User: {result_data.get('username')}\n"
+                        f"Overall Score: {result_data.get('overall_score', 'N/A')}\n"
+                        f"Correct Answers: {result_data.get('correct_answers', 'N/A')}\n"
+                        f"Total Questions: {result_data.get('total_questions', 'N/A')}\n\n"
+                        f"Note: Results show N/A. This might be due to:\n"
+                        f"1. Account activity restrictions (Hugging Face limits submissions from new accounts)\n"
+                        f"2. Temporary delay in processing (try checking the results page directly)\n"
+                        f"3. API evaluation service issue\n\n"
+                        f"Recommendations:\n"
+                        f"- Check your submission status at: {DEFAULT_API_URL}/results?username={username}\n"
+                        f"- Try again in a few minutes\n"
+                        f"- Check the course forum for any known service issues\n"
+                        f"- Ensure your Hugging Face account has been active for at least 24 hours"
+                    )
+                else:
+                    # We got actual results
+                    final_status = (
+                        f"Submission Successful!\n"
+                        f"User: {result_data.get('username')}\n"
+                        f"Overall Score: {result_data.get('overall_score', 'N/A')}\n"
+                        f"Correct Answers: {result_data.get('correct_answers', 'N/A')}\n"
+                        f"Total Questions: {result_data.get('total_questions', 'N/A')}\n"
+                    )
+                
+                print(final_status)
+                return final_status
+                
+            except requests.exceptions.RequestException as e:
+                error_msg = f"Error submitting answers (attempt {attempt}): {e}"
+                print(error_msg)
+                
+                if attempt < MAX_RETRIES:
+                    print(f"Waiting {RETRY_DELAY} seconds before retry...")
+                    time.sleep(RETRY_DELAY)
+                else:
+                    return f"{error_msg}\n\nRecommendation: Please try again later or check your internet connection."
             
-        except Exception as e:
-            error_msg = f"An unexpected error occurred during submission: {e}"
-            print(error_msg)
-            return error_msg
+            except Exception as e:
+                error_msg = f"An unexpected error occurred during submission (attempt {attempt}): {e}"
+                print(error_msg)
+                
+                if attempt < MAX_RETRIES:
+                    print(f"Waiting {RETRY_DELAY} seconds before retry...")
+                    time.sleep(RETRY_DELAY)
+                else:
+                    return f"{error_msg}\n\nRecommendation: Please try again later."
+        
+        # This should not be reached due to the return statements in the loop,
+        # but added as a fallback
+        return "Submission failed after multiple attempts. Please try again later."
 
 
 def run_and_submit_all(profile: gr.OAuthProfile | None, *args):
@@ -437,7 +485,16 @@ with gr.Blocks() as demo:
     
     gr.Markdown("---")
     
-    gr.Markdown("**Note:** This version uses a language model to generate responses. The evaluation process may take longer than the template-based version.")
+    gr.Markdown("""
+    **Note:** This version uses a language model to generate responses. The evaluation process may take longer than the template-based version.
+    
+    **Important:** If you receive 'N/A' results, this is usually due to:
+    - Account activity restrictions (Hugging Face limits submissions from new accounts)
+    - Temporary processing delays
+    - API evaluation service issues
+    
+    The system will automatically retry submissions if needed.
+    """)
     
     with gr.Row():
         login_button = gr.LoginButton(value="Sign in with Hugging Face")
@@ -447,7 +504,7 @@ with gr.Blocks() as demo:
     
     with gr.Row():
         with gr.Column():
-            output_status = gr.Textbox(label="Submission Result")
+            output_status = gr.Textbox(label="Submission Result", lines=10)
             output_results = gr.Dataframe(label="Questions and Agent Answers")
     
     submit_button.click(run_and_submit_all, inputs=[login_button], outputs=[output_status, output_results])