Update app.py

app.py

@@ -2,10 +2,10 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
+import time
 
 # --- Constants ---
-DEFAULT_API_URL = "https://agents-course-unit4-scoring-api.hf.space"
-
+DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # 👉 You can customize this class with your own logic or tools
@@ -21,6 +21,23 @@ class BasicAgent:
         return fixed_answer
 
 
+def check_api_status(api_url: str) -> tuple[bool, str]:
+    """Check if the API is accessible"""
+    try:
+        # Try to access the base URL or a health check endpoint
+        response = requests.get(api_url, timeout=10)
+        if response.status_code == 200:
+            return True, "API is accessible"
+        else:
+            return False, f"API returned status code: {response.status_code}"
+    except requests.exceptions.Timeout:
+        return False, "API request timed out"
+    except requests.exceptions.ConnectionError:
+        return False, "Cannot connect to API (connection error)"
+    except Exception as e:
+        return False, f"API check failed: {str(e)}"
+
+
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
     Fetch all questions, run the agent, submit answers, and show results.
@@ -32,17 +49,33 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         print(f"👤 User logged in: {username}")
     else:
         print("❌ User not logged in.")
-        return "Please login to Hugging Face first.", None
+        return "❌ Please login to Hugging Face first.", None
 
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
+    # Check API status first
+    print("🔍 Checking API status...")
+    api_ok, api_msg = check_api_status(api_url)
+    if not api_ok:
+        error_msg = (
+            f"⚠️ API Status Check Failed\n\n"
+            f"Issue: {api_msg}\n\n"
+            f"Possible solutions:\n"
+            f"1. The scoring API at {api_url} may be down or moved\n"
+            f"2. Check if the API URL is correct\n"
+            f"3. The Hugging Face Space might need to be restarted\n"
+            f"4. Try again in a few minutes\n\n"
+            f"You can verify the API status by visiting: {api_url}"
+        )
+        return error_msg, None
+
     # 1️⃣ Create Agent
     try:
         agent = BasicAgent()
     except Exception as e:
-        return f"Agent initialization failed: {e}", None
+        return f"❌ Agent initialization failed: {e}", None
 
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else "Local_Run"
     print(f"📁 Agent code link: {agent_code}")
@@ -51,39 +84,72 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     try:
         print("📡 Fetching questions...")
         response = requests.get(questions_url, timeout=15)
+        
+        if response.status_code == 404:
+            error_msg = (
+                f"⚠️ Questions endpoint not found (404)\n\n"
+                f"The endpoint {questions_url} is not available.\n\n"
+                f"Possible issues:\n"
+                f"1. The API structure may have changed\n"
+                f"2. The scoring service might be under maintenance\n"
+                f"3. You may need to update the API URL\n\n"
+                f"Please check the course materials or contact the instructor for the correct API endpoint."
+            )
+            return error_msg, None
+        
         response.raise_for_status()
         questions_data = response.json()
+        
         if not questions_data:
-            return "Fetched question list is empty or invalid.", None
+            return "⚠️ Fetched question list is empty or invalid.", None
+        
         print(f"✅ Retrieved {len(questions_data)} questions.")
+        
+    except requests.exceptions.Timeout:
+        return f"⏱️ Request timed out while fetching questions from {questions_url}", None
+    except requests.exceptions.ConnectionError:
+        return f"🔌 Connection error: Cannot reach {questions_url}", None
+    except requests.exceptions.HTTPError as e:
+        return f"❌ HTTP Error fetching questions: {e}", None
+    except ValueError as e:
+        return f"❌ Invalid JSON response from questions endpoint: {e}", None
     except Exception as e:
-        return f"Error fetching questions: {e}", None
+        return f"❌ Error fetching questions: {e}", None
 
     # 3️⃣ Run Agent
     results_log = []
     answers_payload = []
-    for item in questions_data:
+    
+    print(f"🤖 Running agent on {len(questions_data)} questions...")
+    
+    for i, item in enumerate(questions_data):
         task_id = item.get("task_id")
         question_text = item.get("question")
+        
         if not task_id or question_text is None:
+            print(f"⚠️ Skipping invalid question item: {item}")
             continue
+        
         try:
+            print(f"Processing question {i+1}/{len(questions_data)}: {task_id}")
             submitted_answer = agent(question_text)
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({
                 "Task ID": task_id,
-                "Question": question_text,
-                "Submitted Answer": submitted_answer
+                "Question": question_text[:100] + "..." if len(question_text) > 100 else question_text,
+                "Submitted Answer": submitted_answer[:100] + "..." if len(str(submitted_answer)) > 100 else submitted_answer
             })
         except Exception as e:
+            error_msg = f"AGENT ERROR: {e}"
+            print(f"❌ {error_msg} for task {task_id}")
             results_log.append({
                 "Task ID": task_id,
-                "Question": question_text,
-                "Submitted Answer": f"AGENT ERROR: {e}"
+                "Question": question_text[:100] + "..." if len(question_text) > 100 else question_text,
+                "Submitted Answer": error_msg
             })
 
     if not answers_payload:
-        return "No answers generated by the agent.", pd.DataFrame(results_log)
+        return "⚠️ No answers generated by the agent.", pd.DataFrame(results_log)
 
     # 4️⃣ Submit Answers
     submission_data = {
@@ -95,8 +161,19 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     try:
         print("📤 Submitting answers...")
         response = requests.post(submit_url, json=submission_data, timeout=60)
+        
+        if response.status_code == 404:
+            error_msg = (
+                f"⚠️ Submit endpoint not found (404)\n\n"
+                f"Generated {len(answers_payload)} answers but cannot submit them.\n"
+                f"The endpoint {submit_url} is not available.\n\n"
+                f"Your answers are shown in the table below for reference."
+            )
+            return error_msg, pd.DataFrame(results_log)
+        
         response.raise_for_status()
         result_data = response.json()
+        
         final_status = (
             f"✅ Submission Successful!\n"
             f"👤 User: {result_data.get('username')}\n"
@@ -106,12 +183,17 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         )
         results_df = pd.DataFrame(results_log)
         return final_status, results_df
+        
+    except requests.exceptions.Timeout:
+        return f"⏱️ Submission timed out. Your answers:\n{len(answers_payload)} answers generated but not submitted.", pd.DataFrame(results_log)
+    except requests.exceptions.HTTPError as e:
+        return f"❌ HTTP Error during submission: {e}\nYour answers are shown below.", pd.DataFrame(results_log)
     except Exception as e:
-        return f"Submission failed: {e}", pd.DataFrame(results_log)
+        return f"❌ Submission failed: {e}\nYour answers are shown below.", pd.DataFrame(results_log)
 
 
 # --- Gradio Interface ---
-with gr.Blocks() as demo:
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 🤖 Basic Agent Evaluation Runner")
     gr.Markdown(
         """
@@ -122,13 +204,16 @@ with gr.Blocks() as demo:
         ---
         The process may take time (the agent answers all questions).  
         You can customize the agent with reasoning, search tools, or memory.
+        
+        ⚠️ **Note**: If you see a 404 error, the scoring API may be temporarily unavailable.
+        Check with your instructor for the correct API endpoint.
         """
     )
 
     gr.LoginButton()
-    run_button = gr.Button("🚀 Run Evaluation & Submit All Answers")
+    run_button = gr.Button("🚀 Run Evaluation & Submit All Answers", variant="primary")
 
-    status_output = gr.Textbox(label="Run Status / Submission Result", lines=6, interactive=False)
+    status_output = gr.Textbox(label="Run Status / Submission Result", lines=8, interactive=False)
     results_table = gr.DataFrame(label="Questions and Agent Answers")
 
     run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
@@ -136,4 +221,4 @@ with gr.Blocks() as demo:
 
 if __name__ == "__main__":
     print("🚀 Launching Gradio Interface...")
-    demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)