Update app.py

app.py

@@ -1,3 +1,37 @@
 import gradio as gr
+from diffusers import StableDiffusionPipeline
+import torch
 
-gr.load("models/stable-diffusion-v1-5/stable-diffusion-v1-5").launch()
+# Load the Stable Diffusion model
+model_id = "runwayml/stable-diffusion-v1-5"
+pipeline = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipeline = pipeline.to("cuda")
+
+def generate_image(prompt, num_inference_steps=50, guidance_scale=7.5):
+    """Generate an image from a text prompt using Stable Diffusion."""
+    image = pipeline(prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale).images[0]
+    return image
+
+# Define the Gradio app layout
+with gr.Blocks() as app:
+    gr.Markdown("# Stable Diffusion v1.5 Gradio App\nGenerate stunning images from text prompts!")
+
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here", lines=2)
+            num_inference_steps = gr.Slider(label="Inference Steps", minimum=10, maximum=100, value=50, step=5)
+            guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=20.0, value=7.5, step=0.5)
+            generate_btn = gr.Button("Generate Image")
+
+        with gr.Column():
+            output_image = gr.Image(label="Generated Image", type="pil")
+
+    generate_btn.click(
+        generate_image, 
+        inputs=[prompt, num_inference_steps, guidance_scale], 
+        outputs=output_image
+    )
+
+# Run the app
+if __name__ == "__main__":
+    app.launch()