Create app.py

app.py

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+import gradio as gr
+from diffusers import DiffusionPipeline
+import torch
+import random
+
+# Use lightweight model (faster & less resources)
+model_id = "OFA-Sys/small-stable-diffusion-v0"  # 35x smaller than SDXL
+
+# Load model with optimizations
+pipe = DiffusionPipeline.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16
+).to("cuda")
+
+def generate(prompt):
+    # Random seed for unique generations
+    random_seed = random.randint(0, 2147483647)
+    generator = torch.Generator("cuda").manual_seed(random_seed)
+    
+    # Generate image with variations
+    image = pipe(
+        prompt,
+        num_inference_steps=20,  # Faster generation
+        generator=generator
+    ).images[0]
+    
+    return image
+
+# Simple interface
+gr.Interface(
+    fn=generate,
+    inputs=gr.Textbox(label="Enter text prompt"),
+    outputs=gr.Image(label="Generated Image"),
+    title="Simple AI Image Generator",
+    description="Type anything - get random images every time!",
+    allow_flagging="never"  # Remove feedback buttons
+).launch()