Update app.py

app.py

@@ -8,11 +8,6 @@ from optimum_neuron_export import convert
 from gradio_huggingfacehub_search import HuggingfaceHubSearch
 from apscheduler.schedulers.background import BackgroundScheduler
 
-import torch 
-from diffusers import FluxPipeline
-from optimum.neuron import NeuronFluxPipeline
-from huggingface_hub.utils import HfHubHTTPError, RepositoryNotFoundError
-
 # Define transformer tasks and their categories for coloring
 TRANSFORMER_TASKS = {
     "auto": {"color": "#6b7280", "category": "Auto"},
@@ -132,39 +127,6 @@ def toggle_custom_repo_box(pr_destinations: List[str]):
 
 def neuron_export(model_id: str, model_type: str, task_or_pipeline: str, 
                   pr_destinations: List[str], custom_repo_id: str, custom_cache_repo: str, oauth_token: gr.OAuthToken):
-
-    try:
-        # 3. The core test: try to load the model's config using the user's token.
-        # This will fail if the user doesn't have access to the gated repo's files.
-        # pipe = FluxPipeline.from_pretrained(pretrained_model_name_or_path="black-forest-labs/FLUX.1-Krea-dev", torch_dtype=torch.bfloat16, token=oauth_token.token)
-
-        model = NeuronFluxPipeline.from_pretrained(
-            "black-forest-labs/FLUX.1-Krea-dev",
-            export=True,
-            tensor_parallel_size=4,
-            token=oauth_token.token,
-            batch_size=1,
-            sequence_length=128,
-        )
-    
-    except RepositoryNotFoundError:
-        # 5. Handle the case where the repository does not exist
-        return f"### <span style='color: red;'>Not Found 🔴</span>\nThe repository **{model_id}** does not exist."
-        
-    except HfHubHTTPError as e:
-        # 6. Handle HTTP errors, which typically indicate permission issues for gated models
-        if e.response.status_code in [401, 403]:
-            return f"""
-            ### <span style='color: red;'>Access Denied 🔴</span>
-            You do not have permission to download files from **{model_id}**.
-            
-            - Please ensure you have accepted the terms and conditions on the model's page.
-            - This might be a private model you don't have access to.
-            - **Status Code:** {e.response.status_code}
-            """
-        else:
-            return f"### <span style='color: red;'>An Error Occurred 🔴</span>\n**Details:** {str(e)}"
-            
     
     log_buffer = ""
     def log(msg):
@@ -183,7 +145,6 @@ def neuron_export(model_id: str, model_type: str, task_or_pipeline: str,
         yield log("🚫 Invalid input. Please specify a model name from the hub.")
         return
         
-    yield log(f"token in app is {oauth_token.token}")
     try:
         api = HfApi(token=oauth_token.token)
         # Set custom cache repo as environment variable