Update app.py

app.py

@@ -1,13 +1,10 @@
 import os
-from datetime import datetime
 import random
 
-import pandas as pd
-from huggingface_hub import HfApi, hf_hub_download, Repository, whoami
-from huggingface_hub.repocard import metadata_load
+from huggingface_hub import HfApi, whoami
 
 import gradio as gr
-from datasets import load_dataset, Dataset
+from datasets import load_dataset
 
 from data_to_parquet import to_parquet
 
@@ -17,12 +14,6 @@ EXAM_PASSING_SCORE = os.getenv("EXAM_PASSING_SCORE") or 0.7
 
 ds = load_dataset(EXAM_DATASET_ID, split="train")
 
-DATASET_REPO_URL = "https://huggingface.co/datasets/agents-course/certificates"
-CERTIFIED_USERS_FILENAME = "certified_students.csv"
-CERTIFIED_USERS_DIR = "certificates"
-repo = Repository(
-    local_dir=CERTIFIED_USERS_DIR, clone_from=DATASET_REPO_URL, use_auth_token=os.getenv("HF_TOKEN")
-)
 upload_api = HfApi(token=os.getenv("HF_TOKEN"))
 # Convert dataset to a list of dicts and randomly sort
 quiz_data = ds.to_pandas().to_dict("records")
@@ -86,20 +77,28 @@ def push_results_to_hub(user_answers, token: gr.OAuthToken | None):
         gr.Warning(
             f"Score {grade:.1%} below passing threshold of {float(EXAM_PASSING_SCORE):.1%}"
         )
-        return
+        return  # do not continue
 
     gr.Info("Submitting answers to the Hub. Please wait...", duration=2)
 
     user_info = whoami(token=token.token)
-    repo_id = f"{EXAM_DATASET_ID}_student_scores"
-    # TODO: 
+    # TODO:
     # check if username already has "username.parquet" in the dataset and download that (or read values directly from dataset viewer if possible)
     # instead of replacing the values check if the new score is better than the old one
-    to_parquet(upload_api,"not-lain/testing-my-upload",user_info["name"],grade,0,0,0)
-    
-    gr.Success(f"Your responses have been submitted to the Hub! Final grade: {grade:.1%}")
-
+    to_parquet(
+        upload_api,  # api
+        "agents-course/students-data",  # repo_id
+        user_info["name"],  # username
+        grade,  # unit1 score
+        0.0,  # unit2 score
+        0.0,  # unit3 score
+        0.0,  # unit4 score
+        0,  # already certified or not
+    )
 
+    gr.Success(
+        f"Your responses have been submitted to the Hub! Final grade: {grade:.1%}"
+    )
 
 
 def handle_quiz(question_idx, user_answers, selected_answer, is_start):