Update app.py

app.py

@@ -6,54 +6,52 @@ from diffusers import FluxPipeline
 from huggingface_hub import login
 
 # --- AUTHENTICATION ---
+# Ensure your secret is named HF_TOKEN in Space Settings
 token = os.getenv("HF_TOKEN")
 if token:
     login(token=token)
 
-# --- MODEL LOADING ---
+# --- MODEL LOADING WITH GATED CHECK ---
 model_id = "black-forest-labs/FLUX.1-schnell"
 
-# Load the pipe ONCE. 
-# Do NOT move it to cuda here; ZeroGPU handles the transfer.
 pipe = FluxPipeline.from_pretrained(
     model_id, 
     torch_dtype=torch.bfloat16,
-    token=token
+    token=token,           # Explicitly passing token for gated access
+    use_auth_token=token   # Backup parameter for older diffusers versions
 )
 
 @spaces.GPU(duration=60)
-def generate_image(prompt, seed, width, height, steps):
-    # ZeroGPU automatically moves 'pipe' to CUDA when this function starts
-    # and moves it back to CPU when it finishes.
-    
-    generator = torch.Generator("cuda").manual_seed(int(seed))
+def generate_image(prompt):
+    # Hidden settings for a clean UI
+    generator = torch.Generator("cuda").manual_seed(42)
         
     image = pipe(
         prompt=prompt,
-        width=width,
-        height=height,
-        num_inference_steps=steps, 
+        width=1024,
+        height=1024,
+        num_inference_steps=4, 
         generator=generator,
         guidance_scale=0.0
     ).images[0]
         
     return image
 
-# --- GRADIO INTERFACE ---
-with gr.Blocks() as demo:
-    gr.Markdown("# 🚀 FLUX.1 Schnell - Direct Access")
-    with gr.Row():
-        with gr.Column():
-            prompt = gr.Textbox(label="Prompt", placeholder="A glass sculpture of a bird...")
-            btn = gr.Button("Generate", variant="primary")
-            with gr.Accordion("Advanced", open=False):
-                seed = gr.Number(label="Seed", value=42)
-                width = gr.Slider(512, 1024, value=1024, step=64)
-                height = gr.Slider(512, 1024, value=1024, step=64)
-                steps = gr.Slider(1, 4, value=4, step=1)
-        output_img = gr.Image(label="Result")
+# --- MINIMALIST UI ---
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# FLUX.1 Minimal")
+    
+    with gr.Group():
+        prompt = gr.Textbox(
+            placeholder="Describe your image...",
+            show_label=False,
+            container=False
+        )
+        btn = gr.Button("Generate", variant="primary")
+    
+    output_img = gr.Image(show_label=False, interactive=False)
     
-    btn.click(fn=generate_image, inputs=[prompt, seed, width, height, steps], outputs=output_img)
+    btn.click(fn=generate_image, inputs=[prompt], outputs=output_img)
 
 if __name__ == "__main__":
-    demo.launch(share=True)
+    demo.launch()