Update app.py

app.py

@@ -87,10 +87,25 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, up
         else:
             image = semi(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
             torch.cuda.empty_cache()
+            return image
+
+    if Model == "Animagine XL 3.0":
+        animagine = DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.0", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.0")
+        animagine = animagine.to(device)
+        animagine.enable_xformers_memory_efficient_attention()
+        torch.cuda.empty_cache()
+        if upscale == "Yes":
+            int_image = animagine(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images
+            image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
+            torch.cuda.empty_cache()
+            return image
+        else:
+            image = animagine(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
+            torch.cuda.empty_cache()
             
     return image
     
-gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Anime', 'Disney', 'StoryBook', 'SemiReal'], value='PhotoReal', label='Choose Canvers Model'),
+gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Anime', 'Disney', 'StoryBook', 'SemiReal', 'Animagine XL 3.0'], value='PhotoReal', label='Choose Canvers Model'),
                                gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), 
                                gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'),
                                gr.Slider(512, 1024, 768, step=128, label='Height'),