Update app.py

app.py

@@ -1,10 +1,32 @@
 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.")
-        button = gr.LoginButton("Sign in")
-    gr.load("models/black-forest-labs/FLUX.1-dev", accept_token=button, provider="nebius")
-    
-demo.launch()
+        
+        # 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()