Update app.py

app.py

@@ -41,16 +41,19 @@ footer {
 
 repo_nsfw_classifier = pipeline("image-classification", model="Falconsai/nsfw_image_detection")
 
-repo_default = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, use_safetensors=True, add_watermarker=False)
+repo_default = DiffusionPipeline.from_pretrained("fluently/Fluently-XL-Final", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False)
 repo_default.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="default_base")
 repo_default.load_lora_weights("artificialguybr/PixelArtRedmond", adapter_name="pixel_base")
 repo_default.load_lora_weights("nerijs/pixel-art-xl", adapter_name="pixel_base_2")
 
+repo_pro = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, use_safetensors=True, add_watermarker=False)
+
 repo_customs = {
     "Default": repo_default,
     "Realistic": DiffusionPipeline.from_pretrained("ehristoforu/Visionix-alpha", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
     "Anime": DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.1", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
     "Pixel": repo_default,
+    "Pro": repo_pro,
 }
 
 # Functions
@@ -85,12 +88,15 @@ def generate(input=DEFAULT_INPUT, filter_input="", negative_input=DEFAULT_NEGATI
         steps_set = 25
         guidance_set = 7
     elif model == "Pixel":   
-        steps_set = 5
-        guidance_set = 3.5
+        steps_set = 10
+        guidance_set = 1.5
         repo.set_adapters(["pixel_base", "pixel_base_2"], adapter_weights=[1, 1])
-    else:
-        steps_set = 15
+    elif model == "Pro":   
+        steps_set = 10
         guidance_set = 3.5
+    else:
+        steps_set = 25
+        guidance_set = 7
         repo.set_adapters(["default_base"], adapter_weights=[0.7])
 
     if not steps: