Update app.py

app.py

@@ -1,56 +1,38 @@
+
 import torch
 from diffusers import StableDiffusionPipeline
 import gradio as gr
 
-# Load Stable Diffusion model (CPU)
+# Use a smaller Stable Diffusion model for CPU
+model_id = "stabilityai/stable-diffusion-2-1-base"
+
 pipe = StableDiffusionPipeline.from_pretrained(
-    "stabilityai/stable-diffusion-2-1-base",
+    model_id,
     torch_dtype=torch.float32
 ).to("cpu")
+
+# Optimize for CPU
 pipe.enable_attention_slicing()
+pipe.enable_sequential_cpu_offload()
 
-# Generate function
-def generate(prompt, steps, guidance, width, height):
+def generate(prompt):
+    # Keep steps and resolution low for faster generation
     image = pipe(
         prompt,
-        num_inference_steps=steps,
-        guidance_scale=guidance,
-        width=width,
-        height=height
+        num_inference_steps=12,  # lower steps = faster
+        guidance_scale=7,        # balanced CFG
+        width=384,               # lower res (CPU safe)
+        height=384
     ).images[0]
     return image
 
-# Responsive Layout
-with gr.Blocks(css="""
-    .gradio-container {max-width: 900px; margin: auto;}
-    @media (max-width: 768px) {
-        .gradio-container {padding: 10px;}
-    }
-""") as demo:
-    gr.Markdown(
-        """
-        # 🎨 AI Image Generator  
-        Enter your prompt below and generate images with Stable Diffusion (CPU).  
-        Works on desktop & mobile 📱
-        """
-    )
-    
-    with gr.Row():
-        with gr.Column(scale=2):
-            prompt = gr.Textbox(
-                label="Prompt",
-                placeholder="Describe your image here...",
-                lines=2
-            )
-            steps = gr.Slider(5, 30, value=15, step=1, label="Steps")
-            guidance = gr.Slider(1, 15, value=7.5, step=0.5, label="Guidance Scale")
-            width = gr.Slider(256, 512, value=384, step=64, label="Width (px)")
-            height = gr.Slider(256, 512, value=384, step=64, label="Height (px)")
-            btn = gr.Button("🚀 Generate", elem_classes="generate-btn")
-        
-        with gr.Column(scale=3):
-            output = gr.Image(type="pil", label="Generated Image")
-
-    btn.click(fn=generate, inputs=[prompt, steps, guidance, width, height], outputs=output)
+with gr.Blocks(css=".gradio-container {max-width: 800px; margin: auto;}") as demo:
+    gr.Markdown("## 🎨 AI Image Generator (CPU Friendly)\nType your prompt and get results in ~20s (CPU).")
+
+    prompt = gr.Textbox(label="Prompt", placeholder="A castle on a hill at sunset")
+    output = gr.Image(type="pil", label="Generated Image")
+    btn = gr.Button("🚀 Generate")
+
+    btn.click(fn=generate, inputs=prompt, outputs=output)
 
 demo.launch()