Create app.py

app.py

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+import gradio as gr
+import torch
+from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
+from PIL import Image
+import spaces
+
+# Initialize the model
+MODEL_ID = "runwayml/stable-diffusion-v1-5"
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Load the pipeline
+@spaces.GPU
+def load_pipeline():
+    pipe = StableDiffusionPipeline.from_pretrained(
+        MODEL_ID,
+        torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
+        safety_checker=None,
+        requires_safety_checker=False
+    )
+    pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+    pipe = pipe.to(DEVICE)
+    
+    if torch.cuda.is_available():
+        pipe.enable_memory_efficient_attention()
+        pipe.enable_xformers_memory_efficient_attention()
+    
+    return pipe
+
+# Load pipeline at startup
+pipe = load_pipeline()
+
+@spaces.GPU
+def generate_image(prompt, negative_prompt="", num_inference_steps=25, guidance_scale=7.5, width=512, height=512, seed=-1):
+    """
+    Generate image from text prompt using Stable Diffusion
+    """
+    try:
+        # Set seed for reproducibility
+        if seed != -1:
+            generator = torch.Generator(device=DEVICE).manual_seed(seed)
+        else:
+            generator = None
+        
+        # Generate image
+        with torch.autocast(DEVICE):
+            image = pipe(
+                prompt=prompt,
+                negative_prompt=negative_prompt,
+                num_inference_steps=num_inference_steps,
+                guidance_scale=guidance_scale,
+                width=width,
+                height=height,
+                generator=generator
+            ).images[0]
+        
+        return image
+    
+    except Exception as e:
+        print(f"Error generating image: {e}")
+        return None
+
+# Create Gradio interface
+def create_interface():
+    with gr.Blocks(title="Text-to-Image Generator", theme=gr.themes.Soft()) as demo:
+        gr.HTML("""
+        <div style="text-align: center; margin-bottom: 20px;">
+            <h1>🎨 Text-to-Image Generator</h1>
+            <p>Generate beautiful images from text descriptions using Stable Diffusion</p>
+        </div>
+        """)
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                # Input controls
+                prompt_input = gr.Textbox(
+                    label="Prompt",
+                    placeholder="Enter your image description here...",
+                    lines=3,
+                    value="A beautiful sunset over mountains, highly detailed, 8k resolution"
+                )
+                
+                negative_prompt_input = gr.Textbox(
+                    label="Negative Prompt (Optional)",
+                    placeholder="What you don't want in the image...",
+                    lines=2,
+                    value="blurry, low quality, distorted"
+                )
+                
+                with gr.Row():
+                    steps_slider = gr.Slider(
+                        minimum=10,
+                        maximum=50,
+                        value=25,
+                        step=1,
+                        label="Inference Steps"
+                    )
+                    
+                    guidance_slider = gr.Slider(
+                        minimum=1.0,
+                        maximum=20.0,
+                        value=7.5,
+                        step=0.5,
+                        label="Guidance Scale"
+                    )
+                
+                with gr.Row():
+                    width_slider = gr.Slider(
+                        minimum=256,
+                        maximum=1024,
+                        value=512,
+                        step=64,
+                        label="Width"
+                    )
+                    
+                    height_slider = gr.Slider(
+                        minimum=256,
+                        maximum=1024,
+                        value=512,
+                        step=64,
+                        label="Height"
+                    )
+                
+                seed_input = gr.Number(
+                    label="Seed (-1 for random)",
+                    value=-1,
+                    precision=0
+                )
+                
+                generate_btn = gr.Button(
+                    "🎨 Generate Image",
+                    variant="primary",
+                    size="lg"
+                )
+            
+            with gr.Column(scale=1):
+                # Output
+                output_image = gr.Image(
+                    label="Generated Image",
+                    type="pil",
+                    height=500
+                )
+        
+        # Example prompts
+        gr.HTML("<h3>💡 Example Prompts</h3>")
+        examples = gr.Examples(
+            examples=[
+                ["A majestic lion in a savanna at golden hour, photorealistic, 8k"],
+                ["Cyberpunk city at night with neon lights, futuristic, detailed"],
+                ["A cozy cottage in a magical forest, fairy tale style, warm lighting"],
+                ["Abstract art with vibrant colors, geometric shapes, modern"],
+                ["A space explorer on an alien planet, sci-fi, dramatic lighting"],
+            ],
+            inputs=prompt_input,
+            label="Click on an example to try it out!"
+        )
+        
+        # Event handlers
+        generate_btn.click(
+            fn=generate_image,
+            inputs=[
+                prompt_input,
+                negative_prompt_input,
+                steps_slider,
+                guidance_slider,
+                width_slider,
+                height_slider,
+                seed_input
+            ],
+            outputs=output_image,
+            show_progress=True
+        )
+        
+        # Allow Enter key to generate
+        prompt_input.submit(
+            fn=generate_image,
+            inputs=[
+                prompt_input,
+                negative_prompt_input,
+                steps_slider,
+                guidance_slider,
+                width_slider,
+                height_slider,
+                seed_input
+            ],
+            outputs=output_image,
+            show_progress=True
+        )
+    
+    return demo
+
+# Launch the app
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.queue(max_size=20)
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False
+    )