Update app.py

app.py

@@ -14,6 +14,8 @@ DESCRIPTION = "# InstructBLIP"
 
 MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1024"))
 
+SECRET_TOKEN = os.getenv('SECRET_TOKEN', 'default_secret')
+
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 model_id = "Salesforce/instructblip-vicuna-7b"
@@ -23,6 +25,7 @@ model = InstructBlipForConditionalGeneration.from_pretrained(model_id, torch_dty
 
 @spaces.GPU
 def run(
+    secret_token: str,
     image: PIL.Image.Image,
     prompt: str,
     text_decoding_method: str = "Nucleus sampling",
@@ -34,6 +37,10 @@ def run(
     length_penalty: float = 1.0,
     temperature: float = 1.0,
 ) -> str:
+    if secret_token != SECRET_TOKEN:
+        raise gr.Error(
+            f'Invalid secret token. Please fork the original space if you want to use it for yourself.')
+
     h, w = image.size
     scale = MAX_IMAGE_SIZE / max(h, w)
     if scale < 1:
@@ -62,6 +69,7 @@ with gr.Blocks(css="style.css") as demo:
 
     with gr.Row():
         with gr.Column():
+            secret_token = gr.Textbox(label="Secret token")
             input_image = gr.Image(type="pil")
             prompt = gr.Textbox(label="Prompt")
             run_button = gr.Button()
@@ -131,6 +139,7 @@ with gr.Blocks(css="style.css") as demo:
         triggers=[prompt.submit, run_button.click],
         fn=run,
         inputs=[
+            secret_token,
             input_image,
             prompt,
             text_decoding_method,