Update app.py

app.py

@@ -8,7 +8,7 @@ HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
 def get_available_free(use_cache = False):
     if use_cache:
         if os.path.exists(str(os.getcwd())+"/data.csv"):
-            print("Loading data from file...")
+            # print("Loading data from file...")
             return pd.read_csv("data.csv").to_dict(orient='list')
     models_dict = InferenceClient(token=HUGGINGFACE_TOKEN).list_deployed_models("text-generation-inference")
     models = models_dict['text-generation'] + models_dict['text2text-generation']
@@ -22,37 +22,41 @@ def get_available_free(use_cache = False):
         "Chat Completion": [],
         "Vision": []
     }
-    for m in list(set(models + models_vision + models_others)):
+
+    all_models = list(set(models + models_vision + models_others))
+    print(all_models)
+    for m in all_models:
         text_available = False
         chat_available = False
         vision_available = False
         if m in models_vision:
             vision_available = True
         pro_sub = False
+        print(m)
         try:
             InferenceClient(m, timeout=10, token=HUGGINGFACE_TOKEN).text_generation("Hi.", max_new_tokens=1)
             text_available = True
         except Exception as e:
-            print(e)
+            # print(e)
             if e and "Model requires a Pro subscription" in str(e):
                 pro_sub = True
             if e and "Rate limit reached" in str(e):
-                print("Rate Limited!!")
+                # print("Rate Limited!!")
                 if os.path.exists(str(os.getcwd())+"/data.csv"):
-                    print("Loading data from file...")
+                    # print("Loading data from file...")
                     return pd.read_csv(str(os.getcwd())+"/data.csv").to_dict(orient='list')
                 return []
         try:
             InferenceClient(m, timeout=10).chat_completion(messages=[{'role': 'user', 'content': 'Hi.'}], max_tokens=1)
             chat_available = True
         except Exception as e:
-            print(e)
+            # print(e)
             if e and "Model requires a Pro subscription" in str(e):
                 pro_sub = True
             if e and "Rate limit reached" in str(e):
-                print("Rate Limited!!")
+                # print("Rate Limited!!")
                 if os.path.exists("data.csv"):
-                    print("Loading data from file...")
+                    # print("Loading data from file...")
                     return pd.read_csv(str(os.getcwd())+"/data.csv").to_dict(orient='list')
                 return []
         models_conclusion["Model"].append(m)