Update app.py

app.py

@@ -3,6 +3,7 @@ import subprocess
 from typing import Union
 from huggingface_hub import whoami
 from huggingface_hub import HfApi
+from huggingface_hub import HfHubHTTPError
 from huggingface_hub import upload_folder
 is_spaces = True if os.environ.get("SPACE_ID") else False
 
@@ -178,6 +179,8 @@ def start_training(
     profile: Union[gr.OAuthProfile, None],
     oauth_token: Union[gr.OAuthToken, None],
 ):
+
+    api = HfApi(token=hf_token)
     
     if not lora_name:
         raise gr.Error("You forgot to insert your LoRA name! This name has to be unique.")
@@ -201,6 +204,15 @@ def start_training(
         print(f"Created model repo {model_repo_id}")
     except Exception as e:
         print(f"Model repo might already exist: {e}")
+#    try:
+#        api.create_repo(repo_id=model_repo_id, repo_type="model", private=True)
+#        print(f"Created model repo {model_repo_id}")
+#    except HfHubHTTPError as e:
+#        if e.response is not None and e.response.status_code == 409:
+#            print(f"Model repo {model_repo_id} already exists, continuing.")
+#        else:
+#            raise e
+
     
     # Load the default config
     with open("train_lora_flux_24gb.yaml" if is_spaces else "ai-toolkit/config/examples/train_lora_flux_24gb.yaml", "r") as f:
@@ -273,7 +285,7 @@ def start_training(
         # command to run autotrain spacerunner
         # --- Pre-create subspace and inject token ---
         hf_token = oauth_token.token
-        api = HfApi(token=hf_token)
+#        api = HfApi(token=hf_token)
         new_space_id = f"{profile.username}/autotrain-{slugged_lora_name}"
 
         try: