Update app.py

app.py

@@ -3,35 +3,48 @@ __all__ = ['block', 'make_clickable_model', 'make_clickable_user', 'get_submissi
 
 import gradio as gr
 import pandas as pd
-from huggingface_hub import list_models
+from huggingface_hub import HfApi, repocard
+
+def is_duplicated(space_id:str)->None:
+    card = repocard.RepoCard.load(space_id, repo_type="space")
+    return getattr(card.data, "duplicated_from", None) is not None
+
+
 
 def make_clickable_model(model_name, link=None):
     if link is None:
-        link = "https://huggingface.co/" + model_name
-    # Remove user from model name
+        link = "https://huggingface.co/" + "spaces/" + model_name
     return f'<a target="_blank" href="{link}">{model_name.split("/")[-1]}</a>'
 
+def get_space_ids(category):
+    api = HfApi()
+    spaces = api.list_spaces(filter=["keras-dreambooth", category])
+    print(spaces)
+    space_ids = [x for x in spaces]
+    return space_ids
+
 
 def make_clickable_user(user_id):
     link = "https://huggingface.co/" + user_id
     return f'<a  target="_blank" href="{link}">{user_id}</a>'
 
-def get_submissions(category):
-    submissions = list_models(filter=["keras-dreambooth", category], full=True)
+def get_submissions():
+    submissions = get_space_ids(category)
     leaderboard_models = []
 
     for submission in submissions:
         # user, model, likes
-        user_id = submission.id.split("/")[0]
-        leaderboard_models.append(
-            (
-                make_clickable_user(user_id),
-                make_clickable_model(submission.id),
-                submission.likes,
+        if not is_duplicated(submission.id):
+            user_id = submission.id.split("/")[0]
+            leaderboard_models.append(
+                (
+                    make_clickable_user(user_id),
+                    make_clickable_model(submission.id),
+                    submission.likes,
+                )
             )
-        )
 
-    df = pd.DataFrame(data=leaderboard_models, columns=["User", "Model", "Likes"])
+    df = pd.DataFrame(data=leaderboard_models, columns=["User", "Space", "Likes"])
     df.sort_values(by=["Likes"], ascending=False, inplace=True)
     df.insert(0, "Rank", list(range(1, len(df) + 1)))
     return df