Update app.py

app.py

@@ -1,32 +1,10 @@
 import gradio as gr
-from huggingface_hub import login
 
-# A function to handle Hugging Face login (authentication)
-def authenticate_user(token):
-    login(token)  # This will authenticate using the provided Hugging Face token
-
-# Create the Gradio Blocks interface
 with gr.Blocks(fill_height=True) as demo:
     with gr.Sidebar():
         gr.Markdown("# Inference Provider")
         gr.Markdown("This Space showcases the black-forest-labs/FLUX.1-dev model, served by the nebius API. Sign in with your Hugging Face account to use this API.")
-        
-        # Textbox for user to input Hugging Face token
-        token_input = gr.Textbox(label="Hugging Face Token", type="password")
-        button = gr.Button("Sign in")
-
-    # The button action triggers authentication
-    button.click(authenticate_user, inputs=token_input, outputs=None)
-
-    # Assuming you want to load the model into the Gradio interface after authentication
-    def inference_function(input_text):
-        # Add your model inference logic here
-        # Example: interact with Hugging Face model API using authenticated token
-        from transformers import pipeline
-        model = pipeline("text-generation", model="black-forest-labs/FLUX.1-dev")
-        return model(input_text)
-
-    # Create the main interface
-    gr.Interface(fn=inference_function, inputs="text", outputs="text").launch()
-
-demo.launch()
+        button = gr.LoginButton("Sign in")
+    gr.load("models/black-forest-labs/FLUX.1-dev", accept_token=button, provider="nebius")
+    
+demo.launch()