♻️ refactor(app): improve pipeline loading mechanism

- move pipeline loading into a separate function `load_pipeline` for lazy loading
- use a global `pipe` variable and update it dynamically based on the selected model
- remove redundant pipeline loading code and use the `load_pipeline` function instead
- improve code organization and readability by separating concerns into different functions

app.py

@@ -39,25 +39,17 @@ vae = AutoencoderKL.from_pretrained(
     "madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16
 ).to("cuda")
 
-pipe = StableDiffusionXLFillPipeline.from_pretrained(
-    "SG161222/RealVisXL_V5.0_Lightning",
-    torch_dtype=torch.float16,
-    vae=vae,
-    controlnet=model,
-    variant="fp16",
-)
-
-pipe = StableDiffusionXLFillPipeline.from_pretrained(
-    "GraydientPlatformAPI/lustify-lightning",
-    torch_dtype=torch.float16,
-    vae=vae,
-    controlnet=model,
-)
-
-pipe.to("cuda")
-
-pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)
-
+# Move pipeline loading into a function to enable lazy loading
+def load_pipeline(model_name):
+    pipe = StableDiffusionXLFillPipeline.from_pretrained(
+        MODELS[model_name],
+        torch_dtype=torch.float16,
+        vae=vae,
+        controlnet=model,
+    )
+    pipe.to("cuda")
+    pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)
+    return pipe
 
 def can_expand(source_width, source_height, target_width, target_height, alignment):
     """Checks if the image can be expanded based on the alignment."""
@@ -187,12 +179,8 @@ def preview_image_and_mask(image, width, height, overlap_percentage, resize_opti
 def inpaint(prompt, image, model_name, paste_back):
     global pipe
     if pipe.config.model_name != MODELS[model_name]:
-        pipe = StableDiffusionXLFillPipeline.from_pretrained(
-            MODELS[model_name],
-            torch_dtype=torch.float16,
-            vae=vae,
-            controlnet=model,
-        ).to("cuda")
+        # Lazily load the pipeline for the selected model
+        pipe = load_pipeline(model_name)
     
     mask = Image.fromarray(image["mask"]).convert("L")
     image = Image.fromarray(image["image"])
@@ -206,6 +194,7 @@ def inpaint(prompt, image, model_name, paste_back):
 
 @spaces.GPU(duration=24)
 def outpaint(image, width, height, overlap_percentage, num_inference_steps, resize_option, custom_resize_percentage, prompt_input, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom):
+    # Use the currently loaded pipeline
     background, mask = prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom)
     
     if not can_expand(background.width, background.height, width, height, alignment):