Update app.py

Code complete.

app.py

@@ -6,246 +6,141 @@ import gradio as gr
 from datasets import load_dataset, Dataset
 from huggingface_hub import whoami
 
-EXAM_DATASET_ID = (
-    os.getenv("EXAM_DATASET_ID") or "nlp-course/supervised-finetuning_quiz"
-)
-EXAM_MAX_QUESTIONS = os.getenv("EXAM_MAX_QUESTIONS") or 10
-EXAM_PASSING_SCORE = os.getenv("EXAM_PASSING_SCORE") or 0.7
+# Dataset corretto
+EXAM_DATASET_ID = "huggingface-course/chapter_1_exam"
+EXAM_MAX_QUESTIONS = 10
+EXAM_PASSING_SCORE = 0.7
 
+# Caricamento e mescolamento delle domande
 ds = load_dataset(EXAM_DATASET_ID, split="train")
-
-# Convert dataset to a list of dicts and randomly sort
 quiz_data = ds.to_pandas().to_dict("records")
 random.shuffle(quiz_data)
+quiz_data = quiz_data[:EXAM_MAX_QUESTIONS]
 
-# Limit to max questions if specified
-if EXAM_MAX_QUESTIONS:
-    quiz_data = quiz_data[: int(EXAM_MAX_QUESTIONS)]
-
-
-def on_user_logged_in(token: gr.OAuthToken | None):
-    """
-    If the user has a valid token, show Start button.
-    Otherwise, keep the login button visible.
-    """
+def on_user_logged_in(token):
     if token is not None:
         return [
-            gr.update(visible=False),  # login button visibility
-            gr.update(visible=True),  # start button visibility
-            gr.update(visible=False),  # next button visibility
-            gr.update(visible=False),  # submit button visibility
-            "",  # question text
-            [],  # radio choices (empty list = no choices)
-            "Click 'Start' to begin the quiz",  # status message
-            0,  # question_idx
-            [],  # user_answers
-            "",  # final_markdown content
-            token,  # user token
+            gr.update(visible=False), gr.update(visible=True), gr.update(visible=False),
+            gr.update(visible=False), "", [],
+            "Click 'Start' to begin the quiz", 0, [], "", token
         ]
     else:
         return [
-            gr.update(visible=True),  # login button visibility
-            gr.update(visible=False),  # start button visibility
-            gr.update(visible=False),  # next button visibility
-            gr.update(visible=False),  # submit button visibility
-            "",  # question text
-            [],  # radio choices
-            "",  # status message
-            0,  # question_idx
-            [],  # user_answers
-            "",  # final_markdown content
-            None,  # no token
+            gr.update(visible=True), gr.update(visible=False), gr.update(visible=False),
+            gr.update(visible=False), "", [], "", 0, [], "", None
         ]
 
-
-def push_results_to_hub(user_answers, token: gr.OAuthToken | None):
-    """
-    Create a new dataset from user_answers and push it to the Hub.
-    Calculates grade and checks against passing threshold.
-    """
+def push_results_to_hub(user_answers, token):
     if token is None:
         gr.Warning("Please log in to Hugging Face before pushing!")
         return
 
-    # Calculate grade
-    correct_count = sum(1 for answer in user_answers if answer["is_correct"])
+    correct_count = sum(1 for a in user_answers if a["is_correct"])
     total_questions = len(user_answers)
     grade = correct_count / total_questions if total_questions > 0 else 0
 
-    if grade < float(EXAM_PASSING_SCORE):
-        gr.Warning(
-            f"Score {grade:.1%} below passing threshold of {float(EXAM_PASSING_SCORE):.1%}"
-        )
-        return f"You scored {grade:.1%}. Please try again to achieve at least {float(EXAM_PASSING_SCORE):.1%}"
+    if grade < EXAM_PASSING_SCORE:
+        gr.Warning(f"Score {grade:.1%} below passing threshold of {EXAM_PASSING_SCORE:.1%}")
+        return f"You scored {grade:.1%}. Please try again to achieve at least {EXAM_PASSING_SCORE:.1%}"
 
     gr.Info("Submitting answers to the Hub. Please wait...", duration=2)
-
     user_info = whoami(token=token.token)
     repo_id = f"{EXAM_DATASET_ID}_student_responses"
     submission_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
     new_ds = Dataset.from_list(user_answers)
-    new_ds = new_ds.map(
-        lambda x: {
-            "username": user_info["name"],
-            "datetime": submission_time,
-            "grade": grade,
-        }
-    )
+    new_ds = new_ds.map(lambda x: {
+        "username": user_info["name"],
+        "datetime": submission_time,
+        "grade": grade
+    })
     new_ds.push_to_hub(repo_id)
     return f"Your responses have been submitted to the Hub! Final grade: {grade:.1%}"
 
-
 def handle_quiz(question_idx, user_answers, selected_answer, is_start):
-    """
-    Handle quiz state transitions and store answers
-    """
     if not is_start and question_idx < len(quiz_data):
         current_q = quiz_data[question_idx]
-        correct_reference = current_q["correct_answer"]
-        correct_reference = f"answer_{correct_reference}".lower()
-        is_correct = selected_answer == current_q[correct_reference]
-        user_answers.append(
-            {
-                "question": current_q["question"],
-                "selected_answer": selected_answer,
-                "correct_answer": current_q[correct_reference],
-                "is_correct": is_correct,
-                "correct_reference": correct_reference,
-            }
-        )
+        correct_key = f"answer_{current_q['correct_answer']}".lower()
+        is_correct = selected_answer == current_q[correct_key]
+        user_answers.append({
+            "question": current_q["question"],
+            "selected_answer": selected_answer,
+            "correct_answer": current_q[correct_key],
+            "is_correct": is_correct,
+            "correct_reference": correct_key
+        })
         question_idx += 1
 
     if question_idx >= len(quiz_data):
-        correct_count = sum(1 for answer in user_answers if answer["is_correct"])
+        correct_count = sum(1 for a in user_answers if a["is_correct"])
         grade = correct_count / len(user_answers)
-        results_text = (
-            f"**Quiz Complete!**\n\n"
-            f"Your score: {grade:.1%}\n"
-            f"Passing score: {float(EXAM_PASSING_SCORE):.1%}\n\n"
-        )
+        results_text = f"**Quiz Complete!**\n\nYour score: {grade:.1%}\nPassing score: {EXAM_PASSING_SCORE:.1%}\n"
         return [
-            "",  # question_text
-            gr.update(choices=[], visible=False),  # hide radio choices
-            f"{'✅ Passed!' if grade >= float(EXAM_PASSING_SCORE) else '❌ Did not pass'}",
-            question_idx,
-            user_answers,
-            gr.update(visible=False),  # start button visibility
-            gr.update(visible=False),  # next button visibility
-            gr.update(visible=True),  # submit button visibility
-            results_text,  # final results text
+            "", gr.update(choices=[], visible=False),
+            f"{'✅ Passed!' if grade >= EXAM_PASSING_SCORE else '❌ Did not pass'}",
+            question_idx, user_answers,
+            gr.update(visible=False), gr.update(visible=False), gr.update(visible=True),
+            results_text
         ]
 
-    # Show next question
     q = quiz_data[question_idx]
     return [
-        f"## Question {question_idx + 1} \n### {q['question']}",  # question text
-        gr.update(  # properly update radio choices
-            choices=[q["answer_a"], q["answer_b"], q["answer_c"], q["answer_d"]],
-            value=None,
-            visible=True,
-        ),
+        f"## Question {question_idx + 1}\n### {q['question']}",
+        gr.update(choices=[q["answer_a"], q["answer_b"], q["answer_c"], q["answer_d"]], value=None, visible=True),
         "Select an answer and click 'Next' to continue.",
-        question_idx,
-        user_answers,
-        gr.update(visible=False),  # start button visibility
-        gr.update(visible=True),  # next button visibility
-        gr.update(visible=False),  # submit button visibility
-        "",  # clear final markdown
+        question_idx, user_answers,
+        gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), ""
     ]
 
-
 def success_message(response):
-    # response is whatever push_results_to_hub returned
     return f"{response}\n\n**Success!**"
 
-
 with gr.Blocks() as demo:
     demo.title = f"Dataset Quiz for {EXAM_DATASET_ID}"
 
-    # State variables
     question_idx = gr.State(value=0)
     user_answers = gr.State(value=[])
     user_token = gr.State(value=None)
 
-    with gr.Row(variant="compact"):
-        gr.Markdown(f"## Welcome to the {EXAM_DATASET_ID} Quiz")
+    gr.Markdown(f"## Welcome to the {EXAM_DATASET_ID} Quiz")
+    gr.Markdown("Log in first, then click 'Start' to begin. Answer each question, click 'Next', and finally click 'Submit'.")
 
-    with gr.Row(variant="compact"):
-        gr.Markdown(
-            "Log in first, then click 'Start' to begin. Answer each question, click 'Next', and finally click 'Submit' to publish your results to the Hugging Face Hub."
-        )
+    question_text = gr.Markdown("")
+    radio_choices = gr.Radio(choices=[], label="Your Answer", scale=1.5, visible=False)
+    status_text = gr.Markdown("")
+    final_markdown = gr.Markdown("")
 
-    with gr.Row(variant="panel"):
-        question_text = gr.Markdown("")
-        radio_choices = gr.Radio(
-            choices=[], label="Your Answer", scale=1.5, visible=False
-        )
+    login_btn = gr.LoginButton(visible=True)
+    start_btn = gr.Button("Start ⏭️", visible=True)
+    next_btn = gr.Button("Next ⏭️", visible=False)
+    submit_btn = gr.Button("Submit ✅", visible=False)
 
-    with gr.Row(variant="compact"):
-        status_text = gr.Markdown("")
-        final_markdown = gr.Markdown("")
-
-    with gr.Row(variant="compact"):
-        login_btn = gr.LoginButton(visible=True)
-        start_btn = gr.Button("Start ⏭️", visible=True)
-        next_btn = gr.Button("Next ⏭️", visible=False)
-        submit_btn = gr.Button("Submit ✅", visible=False)
-
-    # Wire up the event handlers
     login_btn.click(
         fn=on_user_logged_in,
         inputs=None,
-        outputs=[
-            login_btn,
-            start_btn,
-            next_btn,
-            submit_btn,
-            question_text,
-            radio_choices,
-            status_text,
-            question_idx,
-            user_answers,
-            final_markdown,
-            user_token,
-        ],
+        outputs=[login_btn, start_btn, next_btn, submit_btn, question_text, radio_choices,
+                 status_text, question_idx, user_answers, final_markdown, user_token]
     )
 
     start_btn.click(
         fn=handle_quiz,
         inputs=[question_idx, user_answers, gr.State(""), gr.State(True)],
-        outputs=[
-            question_text,
-            radio_choices,
-            status_text,
-            question_idx,
-            user_answers,
-            start_btn,
-            next_btn,
-            submit_btn,
-            final_markdown,
-        ],
+        outputs=[question_text, radio_choices, status_text, question_idx, user_answers,
+                 start_btn, next_btn, submit_btn, final_markdown]
     )
 
     next_btn.click(
         fn=handle_quiz,
         inputs=[question_idx, user_answers, radio_choices, gr.State(False)],
-        outputs=[
-            question_text,
-            radio_choices,
-            status_text,
-            question_idx,
-            user_answers,
-            start_btn,
-            next_btn,
-            submit_btn,
-            final_markdown,
-        ],
+        outputs=[question_text, radio_choices, status_text, question_idx, user_answers,
+                 start_btn, next_btn, submit_btn, final_markdown]
     )
 
-    submit_btn.click(fn=push_results_to_hub, inputs=[user_answers])
+    submit_btn.click(
+        fn=push_results_to_hub,
+        inputs=[user_answers, user_token],
+        outputs=[final_markdown]
+    )
 
 if __name__ == "__main__":
-    # Note: If testing locally, you'll need to run `huggingface-cli login` or set HF_TOKEN
-    # environment variable for the login to work locally.
     demo.launch()