Update app.py

app.py

@@ -146,7 +146,9 @@ def generate_furniture_mask(image, furniture_type):
     return Image.fromarray(mask)
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
-    return random.randint(0, MAX_SEED) if randomize_seed else seed
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    return seed
 
 def get_additional_prompt():
     prompt = "hyperrealistic photography,extremely detailed,(intricate details),unity 8k wallpaper,ultra detailed"
@@ -385,13 +387,12 @@ with gr.Blocks(theme="bethecloud/storj_theme", css=css) as demo:
     with gr.Row():
         helper_text = gr.Markdown("## Tap and hold (on mobile) to save the image.", visible=True)
     
-    @gr.on(triggers=[image.upload, prompt.submit, run_button.click], inputs=[image, style_selection, prompt, a_prompt, n_prompt, num_images, image_resolution, preprocess_resolution, num_steps, guidance_scale, seed, randomize_seed], outputs=result, show_progress="minimal")
-    def auto_process_image(image, style_selection, prompt, a_prompt, n_prompt, num_images, image_resolution, preprocess_resolution, num_steps, guidance_scale, seed, randomize_seed, progress=gr.Progress(track_tqdm=True)):
-        # Тепер ми отримуємо randomize_seed як окремий параметр
-        seed = randomize_seed_fn(seed, randomize_seed) # Використовуємо функцію для оновлення seed
+    # image processing
+    @gr.on(triggers=[image.upload, prompt.submit, run_button.click], inputs=config, outputs=result, show_progress="minimal")
+    def auto_process_image(image, style_selection, prompt, a_prompt, n_prompt, num_images, image_resolution, preprocess_resolution, num_steps, guidance_scale, seed, progress=gr.Progress(track_tqdm=True)):
         return process_image(image, style_selection, prompt, a_prompt, n_prompt, num_images, image_resolution, preprocess_resolution, num_steps, guidance_scale, seed)
     
-        # AI image processing
+    # AI image processing
     @gr.on(triggers=[use_ai_button.click], inputs=[result] + config, outputs=[image, result], show_progress="minimal")
     def submit(previous_result, image, style_selection, prompt, a_prompt, n_prompt, num_images, image_resolution, preprocess_resolution, num_steps, guidance_scale, seed, progress=gr.Progress(track_tqdm=True)):
         # First, yield the previous result to update the input image immediately
@@ -424,7 +425,7 @@ def process_image(
     preprocess_resolution,
     num_steps,
     guidance_scale,
-    seed: int,
+    seed,
 ):
     seed = random.randint(0, MAX_SEED)
     generator = torch.cuda.manual_seed(seed)
@@ -498,4 +499,7 @@ def process_image(
     )
     return initial_result
 
-demo.queue(api_open=True).launch(share=True)
+if prod:
+    demo.queue(max_size=20).launch(server_name="localhost", server_port=port)
+else:
+    demo.queue(api_open=False).launch(show_api=False)