small refactor

app.py

@@ -4,13 +4,27 @@ from cachetools import TTLCache, cached
 from huggingface_hub import list_models
 from toolz import groupby
 from tqdm.auto import tqdm
+from dotenv import load_dotenv
+import os
+from huggingface_hub import HfApi, hf_hub_url, login, snapshot_download
+
+load_dotenv(override=True)
+
+HF_TOKEN = os.getenv("HF_TOKEN")
+USER_AGENT = os.getenv("USER_AGENT")
+login(token=HF_TOKEN)
+hf_api = HfApi(token=HF_TOKEN, user_agent=USER_AGENT)
 
 
 @cached(TTLCache(maxsize=10, ttl=60 * 60 * 3))
 def get_all_models():
     models = list(
         tqdm(
-            iter(list_models(cardData=True, limit=None, sort="downloads", direction=-1))
+            iter(
+                hf_api.list_models(
+                    cardData=True, limit=None, sort="downloads", direction=-1
+                )
+            )
         )
     )
     models = [model for model in models if model is not None]
@@ -87,6 +101,8 @@ def get_grandchildren(base_model):
 
 def return_models_for_base_model(base_model):
     models = grouped_by_base_model.get(base_model)
+    if models is None:
+        return f"No models found for base model: {base_model}"
     # sort models by downloads
     models = sorted(models, key=lambda x: x.downloads, reverse=True)
     results = ""
@@ -139,9 +155,6 @@ def return_base_model_popularity(pipeline=None):
 
 
 def return_base_model_popularity_by_org(pipeline=None):
-    referenced_base_models = [
-        f"[`{model}`](https://huggingface.co/{model})" for model in base_models
-    ]
     df_with_pipeline_info = pd.DataFrame(
         {"base_model": base_models, "pipeline": pipeline_tags}
     )