Update app.py

app.py

@@ -7,7 +7,7 @@ from threading import Timer
 HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
 def get_available_free(use_cache = False):
     if use_cache:
-        if os.path.exists("./data.csv"):
+        if os.path.exists(str(os.getcwd())+"/data.csv"):
             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")
@@ -38,9 +38,9 @@ def get_available_free(use_cache = False):
                 pro_sub = True
             if e and "Rate limit reached" in str(e):
                 print("Rate Limited!!")
-                if os.path.exists("data.csv"):
+                if os.path.exists(str(os.getcwd())+"/data.csv"):
                     print("Loading data from file...")
-                    return pd.read_csv("./data.csv").to_dict(orient='list')
+                    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)
@@ -53,14 +53,14 @@ def get_available_free(use_cache = False):
                 print("Rate Limited!!")
                 if os.path.exists("data.csv"):
                     print("Loading data from file...")
-                    return pd.read_csv("data.csv").to_dict(orient='list')
+                    return pd.read_csv(str(os.getcwd())+"/data.csv").to_dict(orient='list')
                 return []
         models_conclusion["Model"].append(m)
         models_conclusion["API"].append("Free" if chat_available or text_available else ("Pro Subscription" if pro_sub else "Not Responding"))
         models_conclusion["Chat Completion"].append("---" if (pro_sub or (not chat_available and not text_available)) else ("✓" if chat_available else "⌀"))
         models_conclusion["Text Completion"].append("---" if (pro_sub or (not chat_available and not text_available)) else ("✓" if text_available else "⌀"))
         models_conclusion["Vision"].append("✓" if vision_available else "⌀")
-    pd.DataFrame(models_conclusion).to_csv("./data.csv", index=False)
+    pd.DataFrame(models_conclusion).to_csv(str(os.getcwd())+"/data.csv", index=False)
     return models_conclusion
 
 def update_data(use_cache = False):