Update app.py

app.py

@@ -8,39 +8,19 @@ from PIL import Image
 import spaces
 import torch
 from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
+from typing import Tuple  # Added this import
 
 DESCRIPTIONx = """## STABLE HAMSTER
-
-Drop your best results in the community: [rb.gy/klkbs7](http://rb.gy/klkbs7)
 """
 
-
-style_list = [
-    {
-        "name": "3840 x 2160",
-        "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
-    },
-    {
-        "name": "2560 x 1440",
-        "prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
-    },
-    {
-        "name": "3D Model",
-        "prompt": "professional 3d model {prompt}. octane render, highly detailed, volumetric, dramatic lighting",
-        "negative_prompt": "ugly, deformed, noisy, low poly, blurry, painting",
-    },
-]
-
-#User -- Env -- .os -- Mode_Repo
-
+# Use environment variables for flexibility
 MODEL_ID = os.getenv("MODEL_REPO")
 MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "4096"))
 USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
 ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
-BATCH_SIZE = int(os.getenv("BATCH_SIZE", "1"))  
+BATCH_SIZE = int(os.getenv("BATCH_SIZE", "1"))  # Allow generating multiple images at once
 
+# Determine device and load model outside of function for efficiency
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 pipe = StableDiffusionXLPipeline.from_pretrained(
     MODEL_ID,
@@ -50,16 +30,34 @@ pipe = StableDiffusionXLPipeline.from_pretrained(
 ).to(device)
 pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
 
-# potential speedup
+# Torch compile for potential speedup (experimental)
 if USE_TORCH_COMPILE:
     pipe.compile()
 
-# CPU offloading for Bigger RAM
+# CPU offloading for larger RAM capacity (experimental)
 if ENABLE_CPU_OFFLOAD:
     pipe.enable_model_cpu_offload()
 
 MAX_SEED = np.iinfo(np.int32).max
 
+style_list = [
+    {
+        "name": "3840 x 2160",
+        "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
+        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
+    },
+    {
+        "name": "2560 x 1440",
+        "prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
+        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
+    },
+    {
+        "name": "3D Model",
+        "prompt": "professional 3d model {prompt}. octane render, highly detailed, volumetric, dramatic lighting",
+        "negative_prompt": "ugly, deformed, noisy, low poly, blurry, painting",
+    },
+]
+
 styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
 STYLE_NAMES = list(styles.keys())
 DEFAULT_STYLE_NAME = "3840 x 2160"