Update app.py

app.py

@@ -178,4 +178,179 @@ class SmartAgent:
             return "Date not specified"
         
         # Grocery/cooking questions
-        elif "grocery" in question_lower or "pie" in question_lowe
+        elif "grocery" in question_lower or "pie" in question_lower:
+            return "Check recipe for ingredients"
+        
+        else:
+            return "Need more information to answer accurately"
+
+    def cleanup(self):
+        """Clean up resources"""
+        logging.info("Cleaning up agent resources...")
+        logging.info("SmartAgent resources cleaned up.")
+
+# --- Main Function (Fixed) ---
+def run_and_submit_all(request: gr.Request):
+    """Run agent evaluation and submit results"""
+    # Get username from request or fallback
+    username = None
+    
+    if hasattr(request, 'oauth_profile') and request.oauth_profile:
+        username = request.oauth_profile.username
+        logging.info(f"Found username via oauth_profile: {username}")
+    
+    if not username:
+        space_id = os.getenv("SPACE_ID", "")
+        if "/" in space_id:
+            username = space_id.split("/")[0]
+            logging.info(f"Using fallback username from SPACE_ID: {username}")
+        else:
+            logging.info("No authentication detected.")
+            yield "❌ Unable to detect logged-in user.", pd.DataFrame([])
+            return
+
+    logging.info(f"Processing with username: {username}")
+
+    api_url = DEFAULT_API_URL
+    space_id = os.getenv("SPACE_ID") 
+    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else "N/A_LOCAL_RUN"
+
+    # Setup HTTP session
+    from requests.adapters import HTTPAdapter
+    from urllib3.util.retry import Retry
+    
+    retry_strategy = Retry(
+        total=5,
+        backoff_factor=1,
+        status_forcelist=[429, 500, 502, 503, 504],
+        allowed_methods=["HEAD", "GET", "POST", "PUT", "DELETE", "OPTIONS", "TRACE"]
+    )
+    adapter = HTTPAdapter(max_retries=retry_strategy) 
+    
+    http_session = requests.Session()
+    http_session.mount("https://", adapter)
+    http_session.mount("http://", adapter)
+    
+    agent = None
+    results_log = []
+
+    try:
+        # Initialize agent
+        agent = SmartAgent(username=username, http_session=http_session)
+        agent.setup()
+
+        yield "🚀 Initializing and fetching questions...", pd.DataFrame([])
+
+        # Fetch questions
+        questions_url = f"{api_url}/questions"
+        logging.info(f"Fetching questions from: {questions_url}")
+        response = requests.get(questions_url, timeout=15)
+        response.raise_for_status()
+        questions_data = response.json()
+        
+        if not questions_data:
+            yield "No questions available.", pd.DataFrame([])
+            return
+            
+        logging.info(f"Fetched {len(questions_data)} questions.")
+
+        # Process questions
+        answers_payload = []
+        
+        for i, item in enumerate(questions_data, 1):
+            task_id = item.get("task_id")
+            question_text = item.get("question")
+            question_type = item.get("question_type", "")
+            question_preview = item.get("question_preview", question_text[:50] + "...")
+
+            if not task_id or question_text is None:
+                continue
+            
+            start_time = time.time()
+            try:
+                # Process question with file attachment if present
+                file_name = item.get("file_name")
+                if file_name:
+                    file_url = f"{api_url}/files/{task_id}"
+                    question_with_file = f"{question_text}\n\nAttached file: {file_url}"
+                else:
+                    question_with_file = question_text
+
+                submitted_answer = agent(question_with_file, question_type)
+                processing_time = time.time() - start_time
+                status = "OK"
+                
+                answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
+                results_log.append({
+                    "Task ID": task_id,
+                    "Question": question_preview,
+                    "Submitted Answer": submitted_answer,
+                    "Status": status
+                })
+                
+                logging.info(f"Q{i} Answer: {submitted_answer}")
+
+            except Exception as e:
+                processing_time = time.time() - start_time
+                logging.error(f"Error on task {task_id}: {e}")
+                answers_payload.append({"task_id": task_id, "submitted_answer": "ERROR"})
+                results_log.append({
+                    "Task ID": task_id,
+                    "Question": question_preview,
+                    "Submitted Answer": "ERROR",
+                    "Status": "ERROR"
+                })
+
+            yield f"Processing Q{i}/{len(questions_data)}", pd.DataFrame(results_log)
+
+        # Submit answers
+        submission_data = {
+            "username": username.strip(), 
+            "agent_code": agent_code, 
+            "answers": answers_payload
+        }
+        
+        submit_url = f"{api_url}/submit"
+        response = requests.post(submit_url, json=submission_data, timeout=120)
+        response.raise_for_status()
+        result_data = response.json()
+
+        final_status = (
+            f"🎉 Submission Successful!\n"
+            f"User: {result_data.get('username')}\n"
+            f"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')}"
+        )
+        
+        yield final_status, pd.DataFrame(results_log)
+
+    except Exception as e:
+        yield f"Error: {str(e)}", pd.DataFrame(results_log)
+    finally:
+        if agent:
+            agent.cleanup()
+
+# --- Gradio Interface ---
+with gr.Blocks() as demo:
+    gr.Markdown("# Hugging Face Agent Certification Runner")
+    gr.Markdown("""
+    **Instructions:**
+    1. Log in to your Hugging Face account using the button below.
+    2. Click 'Run Evaluation & Submit All Answers' to start the evaluation.
+    3. The process may take several minutes.
+    """)
+    
+    gr.LoginButton()
+    run_button = gr.Button("🚀 Run Evaluation & Submit All Answers")
+    status_output = gr.Textbox(label="Status", lines=5, interactive=False)
+    results_table = gr.DataFrame(label="Results", wrap=True)
+
+    run_button.click(
+        fn=run_and_submit_all,
+        outputs=[status_output, results_table],
+        show_progress=True,
+    )
+
+if __name__ == "__main__":
+    demo.launch(debug=True, share=False)