Update app.py

app.py

@@ -2,25 +2,29 @@ import gradio as gr
 import torch
 from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
 
+# ---- Configuration ---- #
 MODEL_ID = "runwayml/stable-diffusion-v1-5"
 USE_CUDA = torch.cuda.is_available()
 DEVICE = "cuda" if USE_CUDA else "cpu"
 DTYPE = torch.float16 if USE_CUDA else torch.float32
 
+# ---- Load Pipeline ---- #
 pipe = StableDiffusionPipeline.from_pretrained(
     MODEL_ID,
     torch_dtype=DTYPE
 ).to(DEVICE)
 
 pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
-pipe.enable_attention_slicing()  # Helps with memory optimization
+pipe.enable_attention_slicing()
 
+# ---- Image Generation Function ---- #
 def generate_image(prompt):
     enhanced_prompt = f"{prompt}, ultra realistic, high detail, 8k resolution, DSLR photography, natural lighting"
     with torch.inference_mode():
         result = pipe(enhanced_prompt, num_inference_steps=25)
     return result.images[0]
 
+# ---- Gradio UI ---- #
 demo = gr.Interface(
     fn=generate_image,
     inputs=gr.Textbox(
@@ -32,5 +36,6 @@ demo = gr.Interface(
     description="Generate high-quality, photorealistic images using Stable Diffusion v1.5 + DPM Scheduler"
 )
 
+# ---- Launch ---- #
 if __name__ == "__main__":
-    demo.queue().launch(max_concurrent=1)
+    demo.queue().launch()