Update app.py

app.py

@@ -3,15 +3,15 @@ import gradio as gr
 import requests
 import pandas as pd
 
-from smolagents import CodeAgent, OpenAIServerModel
 from tools import FinalAnswerTool
+from smolagents import CodeAgent, OpenAIServerModel
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 class BasicAgent:
     def __init__(self):
-    
+        # Use GPT-3.5-turbo for quota-friendly operation
         model = OpenAIServerModel(model_id="gpt-3.5-turbo")
         final_tool = FinalAnswerTool()
         self.agent = CodeAgent(
@@ -22,18 +22,31 @@ class BasicAgent:
         )
 
     def __call__(self, question: str) -> str:
-  
         return self.agent.run(question)
 
-def run_and_submit_all(profile):
-    space_id = os.getenv("SPACE_ID")
+
+def extract_username(profile):
+    """
+    Extract username from the Hugging Face OAuthProfile or dict.
+    """
     if not profile:
-        return "Please login to Hugging Face with the login button.", None
-    username = getattr(profile, "username", None) or getattr(profile, "name", None)
+        return None
+    # If profile is a dict (Gradio may return dict), extract keys
+    if isinstance(profile, dict):
+        return profile.get('username') or profile.get('name') or profile.get('login') or profile.get('id')
+    # Otherwise, assume object with attributes
+    return getattr(profile, 'username', None) or getattr(profile, 'name', None) or getattr(profile, 'login', None)
+
+
+def run_and_submit_all(profile):
+    """
+    Fetch all questions, run the BasicAgent, submit answers, and return status and DataFrame.
+    """
+    username = extract_username(profile)
     if not username:
-        return "Login error: username not found.", None
+        return "Please login to Hugging Face with the login button.", None
 
-    # 1) Fetch questions
+    # Fetch questions
     try:
         resp = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
         resp.raise_for_status()
@@ -41,26 +54,30 @@ def run_and_submit_all(profile):
     except Exception as e:
         return f"Error fetching questions: {e}", None
 
-    # 2) Run agent
+    # Run agent on each question
     agent = BasicAgent()
-    results, payload = [], []
+    results = []
+    payload = []
     for q in questions:
-        tid, text = q["task_id"], q["question"]
+        tid = q.get('task_id')
+        text = q.get('question')
+        if not tid or not text:
+            continue
         try:
             ans = agent(text)
         except Exception as e:
             ans = f"ERROR: {e}"
-        results.append({"Task ID": tid, "Question": text, "Answer": ans})
-        payload.append({"task_id": tid, "submitted_answer": ans})
+        results.append({'Task ID': tid, 'Question': text, 'Answer': ans})
+        payload.append({'task_id': tid, 'submitted_answer': ans})
 
     if not payload:
         return "Agent returned no answers.", pd.DataFrame(results)
 
-    # 3) Submit
+    # Prepare and submit
     submission = {
-        "username": username,
-        "agent_code": f"https://huggingface.co/spaces/{space_id}/tree/main",
-        "answers": payload
+        'username': username,
+        'agent_code': f"https://huggingface.co/spaces/{os.getenv('SPACE_ID')}/tree/main",
+        'answers': payload
     }
     try:
         sub_resp = requests.post(f"{DEFAULT_API_URL}/submit", json=submission, timeout=60)
@@ -68,47 +85,51 @@ def run_and_submit_all(profile):
         data = sub_resp.json()
         status = (
             f"Submission Successful!\n"
-            f"User: {data['username']}\n"
-            f"Score: {data['score']}% "
-            f"({data['correct_count']}/{data['total_attempted']})\n"
-            f"Message: {data['message']}"
+            f"User: {data.get('username')}\n"
+            f"Score: {data.get('score')}% ({data.get('correct_count')}/{data.get('total_attempted')})\n"
+            f"Message: {data.get('message')}"
         )
     except Exception as e:
         status = f"Submission Failed: {e}"
 
     return status, pd.DataFrame(results)
 
+
 def test_random_question(profile):
-    if not profile:
+    """
+    Fetch a random question and return question and agent answer.
+    """
+    username = extract_username(profile)
+    if not username:
         return "Please login to Hugging Face with the login button.", ""
     try:
         q = requests.get(f"{DEFAULT_API_URL}/random-question", timeout=15).json()
-        ans = BasicAgent()(q["question"])
-        return q["question"], ans
+        ans = BasicAgent()(q.get('question', ''))
+        return q.get('question', ''), ans
     except Exception as e:
         return f"Error during test: {e}", ""
 
 # --- Gradio UI ---
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
-    gr.Markdown("""
-**Instructions:**
-1. Clone this space and define your agent in `tools.py`.
-2. Log in with your HF account.
-3. Use **Run Evaluation & Submit All Answers** or **Test Random Question**.
-""")
-
+    gr.Markdown(
+        """
+        **Instructions:**
+        1. Clone this space and define your agent in `tools.py`.
+        2. Log in with your Hugging Face account.
+        3. Use **Run Evaluation & Submit All Answers** or **Test Random Question**.
+        """
+    )
     login = gr.LoginButton()
     run_btn = gr.Button("Run Evaluation & Submit All Answers")
     test_btn = gr.Button("Test Random Question")
-
     status_out = gr.Textbox(label="Status / Result", lines=5, interactive=False)
     table_out = gr.DataFrame(label="Full Results Table", wrap=True)
     question_out = gr.Textbox(label="Random Question", lines=3, interactive=False)
     answer_out = gr.Textbox(label="Agent Answer", lines=3, interactive=False)
 
-    run_btn.click(run_and_submit_all, inputs=[login], outputs=[status_out, table_out])
-    test_btn.click(test_random_question, inputs=[login], outputs=[question_out, answer_out])
+    run_btn.click(fn=run_and_submit_all, inputs=[login], outputs=[status_out, table_out])
+    test_btn.click(fn=test_random_question, inputs=[login], outputs=[question_out, answer_out])
 
 if __name__ == "__main__":
     demo.launch(debug=True, share=False)