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app.py

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+import gradio as gr
+from diffusers import AutoPipelineForText2Image
+import torch
+import gc
+
+# --------------------------------------------------------
+# 1. Loading the Turbo Model for CPU Inference
+# --------------------------------------------------------
+print("🔄 Loading the Text-to-Image AI Model (SD Turbo - Fast Inference)...")
+
+# We use the AutoPipelineForText2Image from diffusers.
+# 'stabilityai/sd-turbo' allows acceptable quality in just 1 to 4 steps!
+# This makes it viable for CPU-only execution in HuggingFace free spaces.
+try:
+    pipe = AutoPipelineForText2Image.from_pretrained(
+        "stabilityai/sd-turbo",
+        torch_dtype=torch.float32, 
+        variant="fp16" # use fp16 weights where possible to save memory
+    )
+    pipe = pipe.to("cpu")
+    
+    # Optional performance tweaks for CPU:
+    pipe.set_progress_bar_config(disable=True)
+    
+    print("✅ Model loaded successfully!")
+    print(f"Pipeline components: {list(pipe.components.keys())}")
+except Exception as e:
+    print(f"❌ Error loading model: {e}")
+    # Fallback in case fp16 variant fails to download on CPU
+    pipe = AutoPipelineForText2Image.from_pretrained(
+        "stabilityai/sd-turbo",
+        torch_dtype=torch.float32
+    )
+    pipe = pipe.to("cpu")
+    print("✅ Model loaded via fallback!")
+
+# --------------------------------------------------------
+# 2. Generation Logic
+# --------------------------------------------------------
+def generate_image(prompt, num_steps, guidance_scale, seed):
+    if not prompt or not prompt.strip():
+        raise gr.Error("⚠️ Please enter a text prompt.")
+        
+    print(f"Generating: '{prompt}' (Steps: {num_steps}, Seed: {seed})")
+    
+    # Manage seed reproducibility
+    generator = torch.Generator("cpu").manual_seed(int(seed))
+    
+    try:
+        # Generate the image 
+        # SD-Turbo performs best around 1-4 steps
+        result = pipe(
+            prompt=prompt,
+            num_inference_steps=int(num_steps),
+            guidance_scale=float(guidance_scale), # Usually 0.0 for SD-Turbo
+            generator=generator
+        )
+        
+        # Free up memory
+        gc.collect()
+        
+        return result.images[0]
+        
+    except Exception as e:
+        import traceback
+        traceback.print_exc()
+        raise gr.Error(f"❌ Error during generation: {str(e)}")
+
+# --------------------------------------------------------
+# 3. Custom UI Styling
+# --------------------------------------------------------
+custom_css = """
+@import url('https://fonts.googleapis.com/css2?family=Outfit:wght@300;400;600;800&display=swap');
+
+* {
+    font-family: 'Outfit', sans-serif !important;
+}
+
+.gradio-container {
+    max-width: 1000px !important;
+    margin: auto !important;
+    background: radial-gradient(circle at 50% 0%, #1e293b 0%, #0f172a 100%) !important;
+    min-height: 100vh;
+}
+
+.header-container {
+    text-align: center;
+    padding: 30px;
+    margin-bottom: 20px;
+    border-radius: 20px;
+    background: rgba(255, 255, 255, 0.03);
+    border: 1px solid rgba(255, 255, 255, 0.1);
+    box-shadow: 0 10px 30px rgba(0,0,0,0.5);
+    backdrop-filter: blur(10px);
+}
+
+.title-text {
+    font-size: 3rem !important;
+    font-weight: 800 !important;
+    background: linear-gradient(135deg, #00f2fe 0%, #4facfe 100%) !important;
+    -webkit-background-clip: text !important;
+    -webkit-text-fill-color: transparent !important;
+    margin-bottom: 15px !important;
+    letter-spacing: -1px;
+}
+
+.subtitle-text {
+    color: #94a3b8 !important;
+    font-size: 1.2rem !important;
+    font-weight: 300 !important;
+}
+
+.generate-btn {
+    background: linear-gradient(135deg, #00f2fe 0%, #4facfe 100%) !important;
+    border: none !important;
+    box-shadow: 0 4px 15px rgba(79, 172, 254, 0.4) !important;
+    color: white !important;
+    font-weight: 800 !important;
+    font-size: 1.2rem !important;
+    border-radius: 12px !important;
+    transition: all 0.3s ease !important;
+    padding: 15px !important;
+}
+
+.generate-btn:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 8px 25px rgba(79, 172, 254, 0.6) !important;
+}
+
+/* Make image display beautiful */
+.image-output img {
+    border-radius: 12px !important;
+    box-shadow: 0 10px 25px rgba(0,0,0,0.5) !important;
+}
+"""
+
+# --------------------------------------------------------
+# 4. Gradio Application Construction
+# --------------------------------------------------------
+with gr.Blocks(css=custom_css, title="🎨 Fast Text-to-Image AI", theme=gr.themes.Monochrome()) as demo:
+    
+    # Header Section
+    gr.HTML("""
+    <div class="header-container">
+        <h1 class="title-text">⚡ Fast Text-to-Image AI</h1>
+        <p class="subtitle-text">Powered by SD-Turbo. Generates beautiful images on CPU in seconds.</p>
+    </div>
+    """)
+    
+    with gr.Row():
+        # Left Column - Controls
+        with gr.Column(scale=1):
+            prompt = gr.Textbox(
+                label="🔮 Your Prompt",
+                placeholder="A futuristic city at sunset, highly detailed, cyberpunk style...",
+                lines=3
+            )
+            
+            with gr.Accordion("⚙️ Advanced Settings", open=False):
+                num_steps = gr.Slider(
+                    label="Steps (Quality vs Speed)",
+                    minimum=1, 
+                    maximum=10, 
+                    value=2, 
+                    step=1,
+                    info="SD-Turbo is designed for 1-4 steps!"
+                )
+                guidance_scale = gr.Slider(
+                    label="Guidance Scale",
+                    minimum=0.0, 
+                    maximum=5.0, 
+                    value=0.0, 
+                    step=0.1,
+                    info="Must be 0.0 for SD-Turbo!"
+                )
+                seed = gr.Slider(
+                    label="Random Seed",
+                    minimum=1, 
+                    maximum=999999, 
+                    value=1337, 
+                    step=1,
+                    info="Change to get different images"
+                )
+                
+            generate_btn = gr.Button("🚀 Generate Image", elem_classes=["generate-btn"])
+            
+            gr.Examples(
+                examples=[
+                    ["A cute corgi dog in a spacesuit on Mars", 2, 0.0, 42],
+                    ["A hyper-realistic photograph of a juicy hamburger with melted cheese", 3, 0.0, 100],
+                    ["Cinematic shot of an ancient mechanical dragon sleeping in a cave", 4, 0.0, 999]
+                ],
+                inputs=[prompt, num_steps, guidance_scale, seed],
+                label="💡 Try examples"
+            )
+            
+        # Right Column - Output
+        with gr.Column(scale=1):
+            output_image = gr.Image(
+                label="✨ Generated Result", 
+                type="pil", 
+                elem_classes=["image-output"]
+            )
+            
+    # Connect UI to logic
+    generate_btn.click(
+        fn=generate_image,
+        inputs=[prompt, num_steps, guidance_scale, seed],
+        outputs=output_image
+    )
+
+# Launch app
+demo.launch()