added security

app.py

@@ -1,27 +1,26 @@
 import gradio as gr
 from datasets import load_dataset, Dataset, concatenate_datasets
 from datetime import datetime
-import requests
 import os
+from huggingface_hub import hf_hub_download, whoami
+from huggingface_hub import HfApi, ModelCard, whoami
 
 # Load your private Hugging Face dataset
 DATASET_NAME = "andito/technical_interview_internship_2025"
 TOKEN = os.environ.get("HF_TOKEN")
 EXERCISE_URL = os.environ.get("EXERCISE")
 dataset = load_dataset(DATASET_NAME, split="train")
-LOCAL_FILE_PATH = "exercise.pdf"
 
 # Function to fetch the exercise file if not already downloaded
 def fetch_exercise_file():
-    if not os.path.exists(LOCAL_FILE_PATH):
-        response = requests.get(EXERCISE_URL)
-        with open(LOCAL_FILE_PATH, "wb") as f:
-            f.write(response.content)
+    return hf_hub_download(repo_id=DATASET_NAME, filename=EXERCISE_URL, repo_type="dataset", local_dir=".")
 
 # Function to log download data to the HF Dataset
-def log_to_hf_dataset(username):
-    if not username:
-        return "Please enter your username to proceed.", None
+def log_to_hf_dataset(oauth_token: gr.OAuthToken | None):
+    if oauth_token is None:
+        return "You have to be logged in.", "README.md"
+
+    username = whoami(token=oauth_token.token)["name"]
 
     # Get current timestamp
     timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
@@ -34,19 +33,20 @@ def log_to_hf_dataset(username):
     })
     updated_dataset = concatenate_datasets([dataset, new_entry])
     updated_dataset.push_to_hub(DATASET_NAME, token=TOKEN)
+    local_file_path = fetch_exercise_file()
 
     # Provide file for download
-    return "Thank you! Your download is ready.", LOCAL_FILE_PATH  # Replace with your file path
+    return "Thank you! Your download is ready.", local_file_path  # Replace with your file path
 
 # Gradio interface
 with gr.Blocks() as demo:
-    username = gr.Textbox(label="Enter your username", placeholder="Your Hugging Face username")
+    gr.Markdown("You must be logged in to use download the exercise.")
+    gr.LoginButton(min_width=250)
     download_button = gr.Button("Download Exercise")
     output = gr.Text()
     file = gr.File(label="Download your exercise file")
     
-    download_button.click(log_to_hf_dataset, inputs=[username], outputs=[output, file])
+    download_button.click(log_to_hf_dataset, inputs=[], outputs=[output, file])
 
 # Launch the app
-demo.launch()
-
+demo.launch()