Update app.py

app.py

@@ -1,31 +1,19 @@
-import gradio as gr
 import torch
+import gradio as gr
 from diffusers import StableDiffusionPipeline
 
-# Load model (you can replace this with your own if needed)
-pipe = StableDiffusionPipeline.from_pretrained(
-    "runwayml/stable-diffusion-v1-5",
-    torch_dtype=torch.float16
-).to("cuda")
+model_id = "runwayml/stable-diffusion-v1-5"  # You can change to your own model
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
 
-def generate_image(prompt, width, height, guidance_scale):
-    image = pipe(prompt, width=width, height=height, guidance_scale=guidance_scale).images[0]
+def generate(prompt):
+    image = pipe(prompt).images[0]
     return image
 
-with gr.Blocks() as demo:
-    gr.Markdown("## 🎨 AI Image Generator - Powered by Stable Diffusion")
-    
-    with gr.Row():
-        prompt = gr.Textbox(label="Enter your prompt", placeholder="e.g. A futuristic city at sunset")
-    
-    with gr.Row():
-        width = gr.Slider(256, 1024, value=512, step=64, label="Width")
-        height = gr.Slider(256, 1024, value=512, step=64, label="Height")
-        guidance_scale = gr.Slider(1, 20, value=7.5, step=0.5, label="Guidance Scale")
-    
-    generate_btn = gr.Button("Generate Image")
-    output = gr.Image(label="Generated Image")
-
-    generate_btn.click(fn=generate_image, inputs=[prompt, width, height, guidance_scale], outputs=output)
-
-demo.launch()
+gr.Interface(
+    fn=generate,
+    inputs=gr.Textbox(label="Enter your prompt"),
+    outputs=gr.Image(type="pil"),
+    title="🎨 AI Image Generator",
+    description="Enter a prompt to generate images using Stable Diffusion",
+).launch()