Update app.py

app.py

@@ -11,7 +11,7 @@ import PIL.Image
 import torch
 from diffusers import DiffusionPipeline
 
-DESCRIPTION = '# SD-XL'
+DESCRIPTION = 'This space is an API service meant to be used by VideoChain and VideoQuest.\nWant to use this space for yourself? Please use the original code: [https://huggingface.co/spaces/hysts/SD-XL](https://huggingface.co/spaces/hysts/SD-XL)'
 if not torch.cuda.is_available():
     DESCRIPTION += '\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>'
 
@@ -21,6 +21,7 @@ CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv(
 MAX_IMAGE_SIZE = int(os.getenv('MAX_IMAGE_SIZE', '1024'))
 USE_TORCH_COMPILE = os.getenv('USE_TORCH_COMPILE') == '1'
 ENABLE_CPU_OFFLOAD = os.getenv('ENABLE_CPU_OFFLOAD') == '1'
+SECRET_TOKEN = os.getenv('SECRET_TOKEN', 'default_secret')
 
 device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
 if torch.cuda.is_available():
@@ -54,6 +55,11 @@ else:
     pipe = None
     refiner = None
 
+def check_secret_token(token: str) -> str:
+    """Raises an error if the token does not match the secret token."""
+    if token != SECRET_TOKEN:
+        raise ValueError("Invalid secret token!")
+    return token
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     if randomize_seed:
@@ -125,11 +131,13 @@ examples = [
 
 with gr.Blocks(css='style.css') as demo:
     gr.Markdown(DESCRIPTION)
-    gr.DuplicateButton(value='Duplicate Space for private use',
-                       elem_id='duplicate-button',
-                       visible=os.getenv('SHOW_DUPLICATE_BUTTON') == '1')
     with gr.Box():
         with gr.Row():
+            secret_token = gr.Text(
+                label='Secret Token',
+                max_lines=1,
+                placeholder='Enter your secret token',
+            )
             prompt = gr.Text(
                 label='Prompt',
                 show_label=False,
@@ -265,8 +273,15 @@ with gr.Blocks(css='style.css') as demo:
         num_inference_steps_base,
         num_inference_steps_refiner,
         apply_refiner,
+        secret_token,
     ]
     prompt.submit(
+        fn=check_secret_token,
+        inputs=[secret_token],
+        outputs=gr.outputs.Void(),
+        queue=False,
+        api_name=False,
+    ).then(
         fn=randomize_seed_fn,
         inputs=[seed, randomize_seed],
         outputs=seed,