Update app.py

app.py

@@ -26,6 +26,21 @@ ENABLE_USE_LORA = os.getenv("ENABLE_USE_LORA", "1") == "1"
 ENABLE_USE_VAE = os.getenv("ENABLE_USE_VAE", "1") == "1"
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+models = ["runwayml/stable-diffusion-v1-5",
+"stabilityai/stable-diffusion-xl-base-1.0",
+"stablediffusionapi/juggernaut-xl-v8",
+"emilianJR/epiCRealism",
+"SG161222/Realistic_Vision_V5.1_noVAE",
+"cagliostrolab/animagine-xl-3.0",
+"misri/cyberrealistic_v41BackToBasics",
+"malcolmrey/serenity",
+"SG161222/RealVisXL_V3.0",
+"stablediffusionapi/realistic-stock-photo-v2",
+"stablediffusionapi/pixel-art-diffusion-xl",
+"playgroundai/playground-v2-1024px-aesthetic",
+"dataautogpt3/ProteusV0.3",
+"stablediffusionapi/disney-pixar-cartoon",
+"RunDiffusion/Juggernaut-XL-Lightning"]  
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     if randomize_seed:
@@ -52,7 +67,7 @@ def generate(
     use_vae: bool = False,
     use_lora: bool = False,
     apply_refiner: bool = False,
-    model = 'SG161222/Realistic_Vision_V6.0_B1_noVAE',
+    dropdown_model = 'cagliostrolab/animagine-xl-3.0',
     vaecall = 'stabilityai/sd-vae-ft-mse',
     lora = 'amazonaws-la/juliette',
     lora_scale: float = 0.7,
@@ -60,11 +75,11 @@ def generate(
     if torch.cuda.is_available():
 
         if not use_vae:  
-            pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch.float16)
+            pipe = DiffusionPipeline.from_pretrained(dropdown_model, torch_dtype=torch.float16)
             
         if use_vae:
             vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
-            pipe = DiffusionPipeline.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
+            pipe = DiffusionPipeline.from_pretrained(dropdown_model, vae=vae, torch_dtype=torch.float16)
             
         if use_lora:
             pipe.load_lora_weights(lora)
@@ -140,7 +155,7 @@ with gr.Blocks(css="style.css") as demo:
         visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
     )
     with gr.Group():
-        model = gr.Text(label='Modelo')
+        dropdown_model = gr.Dropdown(label='Model', value='cagliostrolab/animagine-xl-3.0', choices=models)
         vaecall = gr.Text(label='VAE')
         lora = gr.Text(label='LoRA')
         lora_scale = gr.Slider(
@@ -325,7 +340,7 @@ with gr.Blocks(css="style.css") as demo:
             use_vae,
             use_lora,
             apply_refiner,
-            model,
+            dropdown_model,
             vaecall,
             lora,
             lora_scale,