Update app.py

app.py

@@ -10,7 +10,8 @@ import numpy as np
 import PIL.Image
 import spaces
 import torch
-from diffusers import AutoencoderKL, DiffusionPipeline, DPMSolverMultistepScheduler
+import diffusers
+from diffusers import AutoencoderKL, DiffusionPipeline, DDIMScheduler
 
 DESCRIPTION = "# SDXL"
 if not torch.cuda.is_available():
@@ -26,6 +27,15 @@ 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")
+schedulers = [
+    ("LMSDiscreteScheduler", diffusers.schedulers.scheduling_lms_discrete.LMSDiscreteScheduler),
+    ("DDIMScheduler", diffusers.schedulers.scheduling_ddim.DDIMScheduler),
+    ("DPMSolverMultistepScheduler", diffusers.schedulers.scheduling_dpmsolver_multistep.DPMSolverMultistepScheduler),
+    ("EulerDiscreteScheduler", diffusers.schedulers.scheduling_euler_discrete.EulerDiscreteScheduler),
+    ("PNDMScheduler", diffusers.schedulers.scheduling_pndm.PNDMScheduler),
+    ("DDPMScheduler", diffusers.schedulers.scheduling_ddpm.DDPMScheduler),
+    ("EulerAncestralDiscreteScheduler", diffusers.schedulers.scheduling_euler_ancestral_discrete.EulerAncestralDiscreteScheduler)
+]
 models = ["cagliostrolab/animagine-xl-3.0"]  # Substitua isso pelo valor real do modelo selecionado
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int: