Update app.py

app.py

@@ -13,7 +13,7 @@ import torch
 from diffusers import DiffusionPipeline
 from typing import Tuple
 
-#Check for the Model Base..//
+# Check for the Model Base..//
 bad_words = json.loads(os.getenv('BAD_WORDS', "[]"))
 bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]"))
 default_negative = os.getenv("default_negative","")
@@ -26,11 +26,9 @@ def check_text(prompt, negative=""):
         if i in negative:
             return True
     return False
-#End of the - Prompt Con
-
+# End of the - Prompt Con
 
 style_list = [
-
     {
         "name": "3840 x 2160",
         "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
@@ -58,18 +56,9 @@ def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str
         negative = ""
     return p.replace("{prompt}", positive), n + negative
 
-
-
-    
-
 DESCRIPTION = """## MidJourney 3D
-
 """
 
-
-
-
-
 if not torch.cuda.is_available():
     DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
 
@@ -85,13 +74,6 @@ NUM_IMAGES_PER_PROMPT = 1
 
 if torch.cuda.is_available():
     pipe = DiffusionPipeline.from_pretrained(
-        "yodayo-ai/kivotos-xl-2.0",
-        torch_dtype=torch.float16,
-        use_safetensors=True,
-        add_watermarker=False,
-        variant="fp16"
-    )
-    pipe2 = DiffusionPipeline.from_pretrained(
         "Yntec/3Danimation",
         torch_dtype=torch.float16,
         use_safetensors=True,
@@ -100,15 +82,12 @@ if torch.cuda.is_available():
     )
     if ENABLE_CPU_OFFLOAD:
         pipe.enable_model_cpu_offload()
-        pipe2.enable_model_cpu_offload()
     else:
         pipe.to(device)    
-        pipe2.to(device)    
         print("Loaded on Device!")
     
     if USE_TORCH_COMPILE:
         pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
-        pipe2.unet = torch.compile(pipe2.unet, mode="reduce-overhead", fullgraph=True)
         print("Model Compiled!")
 
 def save_image(img):
@@ -159,7 +138,7 @@ def generate(
         "output_type": "pil",
     }
     
-    images = pipe(**options).images + pipe2(**options).images
+    images = pipe(**options).images
 
     image_paths = [save_image(img) for img in images]
     return image_paths, seed
@@ -297,4 +276,4 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
     )
 
 if __name__ == "__main__":
-    demo.queue(max_size=20).launch()
+    demo.queue(max_size=50).launch()