Create functional AI image generation app with Stable Diffusion

app.py

@@ -1,4 +1,68 @@
-from gradio.sketch.run import create
+import gradio as gr
+import torch
+from diffusers import StableDiffusionPipeline
+from PIL import Image
 
-demo = create("test.py", "test.py.json")
-demo.launch()
+# Load the model
+model_id = "runwayml/stable-diffusion-v1-5"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")
+
+def generate_image(prompt, negative_prompt="", num_inference_steps=50, guidance_scale=7.5, height=512, width=512):
+    """
+    Generate an image from text prompt using Stable Diffusion
+    """
+    try:
+        with torch.no_grad():
+            image = pipe(
+                prompt=prompt,
+                negative_prompt=negative_prompt,
+                num_inference_steps=num_inference_steps,
+                guidance_scale=guidance_scale,
+                height=height,
+                width=width
+            ).images[0]
+        return image
+    except Exception as e:
+        return f"Error generating image: {str(e)}"
+
+# Create Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# AI Image Generator")
+    gr.Markdown("Generate images from text descriptions using Stable Diffusion")
+    
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(
+                label="Prompt",
+                placeholder="Enter a detailed description of the image you want to generate",
+                lines=3
+            )
+            negative_prompt = gr.Textbox(
+                label="Negative Prompt",
+                placeholder="(Optional) Things to avoid in the image",
+                lines=2
+            )
+            
+            with gr.Row():
+                steps = gr.Slider(20, 100, value=50, step=1, label="Inference Steps")
+                guidance = gr.Slider(1.0, 20.0, value=7.5, step=0.5, label="Guidance Scale")
+            
+            with gr.Row():
+                height = gr.Slider(256, 768, value=512, step=64, label="Height")
+                width = gr.Slider(256, 768, value=512, step=64, label="Width")
+            
+            generate_btn = gr.Button("Generate Image", variant="primary")
+        
+        with gr.Column():
+            output_image = gr.Image(label="Generated Image", type="pil")
+    
+    # Connect the generate button to the function
+    generate_btn.click(
+        fn=generate_image,
+        inputs=[prompt, negative_prompt, steps, guidance, height, width],
+        outputs=output_image
+    )
+
+if __name__ == "__main__":
+    demo.launch()