Update app.py

Adding story too?

app.py

@@ -22,6 +22,11 @@ disney = disney.to(device)
 disney.enable_xformers_memory_efficient_attention()
 torch.cuda.empty_cache()
 
+story = DiffusionPipeline.from_pretrained("circulus/canvers-story-v3.8.1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-story-v3.8.1")
+story = story.to(device)
+story.enable_xformers_memory_efficient_attention()
+torch.cuda.empty_cache()
+
 refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16") if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0")
 refiner.enable_xformers_memory_efficient_attention()
 refiner = refiner.to(device)
@@ -50,7 +55,8 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, up
             image = anime(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
             torch.cuda.empty_cache()
             return image
-    else:
+            
+    if Model == "Disney":
         if upscale == "Yes":
             int_image = disney(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]
@@ -59,9 +65,21 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, up
         else:
             image = disney(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 == "Story":
+        if upscale == "Yes":
+            int_image = story(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 = story(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(['Real', 'Anime', 'Disney'], value='Real', label='Choose Canvers Model'),
+gr.Interface(fn=genie, inputs=[gr.Radio(['Real', 'Anime', 'Disney', 'Story'], value='Real', 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'),