Update app.py

app.py

@@ -191,16 +191,40 @@ def run_and_submit_all(request: gr.Request):
     Fetches all questions, runs the agent on them, submits all answers,
     and displays the results.
     """
-    # Get the user profile from the request
-    profile = request.oauth_profile if hasattr(request, 'oauth_profile') else None
+    # Try multiple ways to get the user info
+    username = None
     
-    if not profile:
-        logging.info("User not logged in.")
-        yield "Please Login to Hugging Face with the button above.", pd.DataFrame([])
-        return
+    # Method 1: Check for oauth_profile
+    if hasattr(request, 'oauth_profile') and request.oauth_profile:
+        username = request.oauth_profile.username
+        logging.info(f"Found username via oauth_profile: {username}")
+    
+    # Method 2: Check request headers for user info
+    elif hasattr(request, 'headers'):
+        # Look for common auth headers
+        for header_name in ['x-user', 'authorization', 'user']:
+            if header_name in request.headers:
+                logging.info(f"Found header {header_name}: {request.headers[header_name]}")
+    
+    # Method 3: Try to extract from request attributes
+    if not username:
+        logging.info("Checking request attributes...")
+        for attr in dir(request):
+            if 'user' in attr.lower():
+                logging.info(f"Found request attribute: {attr} = {getattr(request, attr, 'N/A')}")
+    
+    # For now, let's use a fallback username based on the space owner
+    if not username:
+        space_id = os.getenv("SPACE_ID", "")
+        if "/" in space_id:
+            username = space_id.split("/")[0]  # Extract username from space_id
+            logging.info(f"Using fallback username from SPACE_ID: {username}")
+        else:
+            logging.info("No authentication detected and no fallback available.")
+            yield "❌ Unable to detect logged-in user. Please make sure you're logged in to Hugging Face.", pd.DataFrame([])
+            return
 
-    username = f"{profile.username}"
-    logging.info(f"User logged in: {username}")
+    logging.info(f"Processing with username: {username}")
 
     api_url = DEFAULT_API_URL
     
@@ -234,7 +258,7 @@ def run_and_submit_all(request: gr.Request):
         agent.setup()
 
         # Initial yield for Gradio progress display
-        yield "🚀 Initializing and fetching questions...", pd.DataFrame([])
+        yield "🚀 Initializing agent and fetching questions...\n📡 Connecting to API...", pd.DataFrame([])
 
         # 2. Fetch Questions
         questions_url = f"{api_url}/questions"
@@ -249,6 +273,15 @@ def run_and_submit_all(request: gr.Request):
             return
             
         logging.info(f"Fetched {len(questions_data)} questions.")
+        
+        # Show questions fetched
+        yield (
+            f"✅ Successfully fetched {len(questions_data)} questions!\n"
+            f"🤖 Starting agent evaluation...\n"
+            f"⏳ This may take several minutes...\n"
+            f"{'='*50}",
+            pd.DataFrame([])
+        )
 
         # 3. Process each question
         answers_payload = []
@@ -265,8 +298,10 @@ def run_and_submit_all(request: gr.Request):
                 logging.warning(f"Skipping item with missing task_id: {item}")
                 results_log.append({
                     "Task ID": "MISSING", 
-                    "Question": "ERROR: Missing task_id", 
+                    "Question Type": "ERROR",
+                    "Question Preview": "ERROR: Missing task_id", 
                     "Submitted Answer": "ERROR", 
+                    "Processing Time (s)": "N/A",
                     "Status": "ERROR"
                 })
                 continue
@@ -291,8 +326,10 @@ def run_and_submit_all(request: gr.Request):
                 
                 results_log.append({
                     "Task ID": task_id, 
-                    "Question": question_preview, 
-                    "Submitted Answer": submitted_answer, 
+                    "Question Type": question_type,
+                    "Question Preview": question_preview[:80] + "..." if len(question_preview) > 80 else question_preview, 
+                    "Submitted Answer": submitted_answer[:100] + "..." if len(submitted_answer) > 100 else submitted_answer, 
+                    "Processing Time (s)": f"{processing_time:.2f}",
                     "Status": status
                 })
 
@@ -309,16 +346,25 @@ def run_and_submit_all(request: gr.Request):
                 
                 results_log.append({
                     "Task ID": task_id, 
-                    "Question": question_preview, 
-                    "Submitted Answer": submitted_answer, 
+                    "Question Type": question_type,
+                    "Question Preview": question_preview[:80] + "..." if len(question_preview) > 80 else question_preview, 
+                    "Submitted Answer": submitted_answer[:100] + "..." if len(submitted_answer) > 100 else submitted_answer, 
+                    "Processing Time (s)": "ERROR",
                     "Status": status
                 })
 
-            # Yield progressive updates to Gradio UI
-            yield (
-                f"Processing Q{i}/{len(questions_data)}. Last Answer: {submitted_answer[:100]}",
-                pd.DataFrame(results_log)
+            # Yield progressive updates to Gradio UI with better formatting
+            progress_text = (
+                f"🔄 Processing Question {i}/{len(questions_data)}\n"
+                f"📝 Question Type: {question_type}\n"
+                f"❓ Question Preview: {question_preview[:100]}{'...' if len(question_preview) > 100 else ''}\n"
+                f"💭 Agent Answer: {submitted_answer[:150]}{'...' if len(submitted_answer) > 150 else ''}\n"
+                f"⏱️ Processing Time: {processing_time:.2f}s\n"
+                f"✅ Status: {status}\n"
+                f"{'='*60}"
             )
+            
+            yield (progress_text, pd.DataFrame(results_log))
 
         if not answers_payload:
             logging.info("Agent did not produce any answers to submit.")
@@ -326,6 +372,12 @@ def run_and_submit_all(request: gr.Request):
             return
 
         # 4. Submit answers
+        yield (
+            f"📤 Submitting {len(answers_payload)} answers to the evaluation server...\n"
+            f"⏳ Please wait for scoring...",
+            pd.DataFrame(results_log)
+        )
+        
         submission_data = {
             "username": username.strip(), 
             "agent_code": agent_code, 
@@ -340,11 +392,12 @@ def run_and_submit_all(request: gr.Request):
         result_data = response.json()
 
         final_status = (
-            f"Submission Successful!\n"
-            f"User: {result_data.get('username')}\n"
-            f"Overall Score: {result_data.get('score', 'N/A')}% "
+            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.')}"
+            f"💬 Message: {result_data.get('message', 'No message received.')}\n"
+            f"⏰ Completed at: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
         )
         logging.info("Submission successful.")
         
@@ -396,9 +449,19 @@ with gr.Blocks() as demo:
     )
     
     gr.LoginButton()  # Add the login button back
-    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 = gr.Button("🚀 Run Evaluation & Submit All Answers", size="lg")
+    status_output = gr.Textbox(
+        label="📊 Real-time Progress & Status", 
+        lines=8, 
+        interactive=False,
+        show_copy_button=True
+    )
+    results_table = gr.DataFrame(
+        label="📋 Questions, Answers & Results", 
+        wrap=True,
+        height=400,
+        interactive=False
+    )
 
     run_button.click(
         fn=run_and_submit_all,