update

app.py

@@ -18,7 +18,7 @@ from huggingface_hub import (
     InferenceClient,
     login,
     snapshot_download,
-    hf_hub_download
+    hf_hub_download,
 )
 from PIL import Image
 from utils import string_to_image
@@ -37,20 +37,18 @@ np.random.seed(int(time.time()))
 session_token = os.environ.get("SessionToken")
 login(token=session_token, add_to_git_credential=True)
 
-# Using snapshot_download to handle the download and extraction
-# snapshot_download(
-#     repo_id='XAI/PEEB-Data',
-#     repo_type='dataset',
-#     local_dir='./',
-#     cache_dir='./hf_cache'
-# )
-zip_file_path = hf_hub_download(repo_id='XAI/PEEB-Data', repo_type='dataset', cache_dir='./hf_cache', filename="data.zip")
+zip_file_path = hf_hub_download(
+    repo_id="XAI/PEEB-Data",
+    repo_type="dataset",
+    cache_dir="./hf_cache",
+    filename="data.zip",
+)
 
+print(f"zip_file_path: {zip_file_path}")
 
-with zipfile.ZipFile('./data.zip', 'r') as zip_ref:
+with zipfile.ZipFile("./data.zip", "r") as zip_ref:
     zip_ref.extractall("./")
 
-
 NUMBER_OF_IMAGES = 30
 intro_screen = Image.open("./images/intro.jpg")
 
@@ -70,7 +68,6 @@ for k in all_data["topK"].keys():
     all_data["topK"][k]["type"] = "topK"
 
 
-
 REPO_URL = "taesiri/AdvisingNetworksReviewDataExtension"
 JSON_DATASET_DIR = Path("responses")
 
@@ -239,7 +236,7 @@ def update_app(decision, data, current_index, history, username):
         # TODO, Call the accuracy and show it to the user
         # calcualte the mean of is_user_correct
         all_is_user_correct = [d["is_user_correct"] for d in history]
-        accuracy = np.mean(all_is_user_correct) * 100   
+        accuracy = np.mean(all_is_user_correct) * 100
         accuracy = round(accuracy, 2)
 
         return (