Upload 2 files

frontend/app.py

@@ -48,20 +48,20 @@ with gr.Blocks() as demo:
         generate_button = gr.Button("Generate")
         output = gr.Image(type='pil')
 
-        example_list = gr.Examples(
-        examples=[['./example/img_1.jpg', './example/img_2.jpg', './example/img_3.jpg', './example/img_4.jpg', 100, 768]],
-            inputs=[
-                input_image_1, 
-                input_image_2, 
-                input_image_3, 
-                input_image_4,
-                alpha_gradient_width, 
-                init_image_height
-                ],
-            outputs=[output],
-            fn=call_inpainting_api,
-            cache_examples=True,
-        )
+        # example_list = gr.Examples(
+        # examples=[['./example/img_1.jpg', './example/img_2.jpg', './example/img_3.jpg', './example/img_4.jpg', 100, 768]],
+        #     inputs=[
+        #         input_image_1, 
+        #         input_image_2, 
+        #         input_image_3, 
+        #         input_image_4,
+        #         alpha_gradient_width, 
+        #         init_image_height
+        #         ],
+        #     outputs=[output],
+        #     fn=call_inpainting_api,
+        #     cache_examples=True,
+        # )
 
         generate_button.click(
             fn=call_inpainting_api, 

frontend/utils.py

@@ -9,7 +9,8 @@ import os
 
 load_dotenv()
 endpoint = 'https://serving.hopter.staging.picc.co/api/v1/services/gen-ai-image-expansion/predictions'
-token = os.getenv('API_TOKEN')
+# token = os.getenv('API_TOKEN')
+token = os.environ["API_TOKEN"]
 
 def pil_to_b64(image:Image.Image) -> str:
     buffered = BytesIO()