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import gradio as gr
from diffusers import StableDiffusionPipeline
import torch
# ✅ Choose device (GPU if available, else CPU)
device = "cuda" if torch.cuda.is_available() else "cpu"
# ✅ Load the model with correct settings
pipe = StableDiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-2-1",
torch_dtype=torch.float16 if device == "cuda" else torch.float32,
revision="fp16" if device == "cuda" else "main"
).to(device)
# ✅ Generate image or placeholder for 3D
def generate_muse(prompt, output_type):
if output_type == "Image":
image = pipe(prompt).images[0]
return image
else:
return "⚠️ 3D Model generation coming soon. Please select 'Image'."
# ✅ Gradio UI layout
with gr.Blocks() as demo:
gr.Markdown("## 🎨 Welcome to **MUSE**")
gr.Markdown("Turn your architectural, artistic, or design ideas into stunning visual concepts.\n\n🧠 Just describe your **muse**, pick a format, and let the AI do the rest.")
with gr.Row():
with gr.Column():
prompt = gr.Textbox(
label="🖋️ Describe your muse idea",
placeholder="e.g. a floating bamboo pavilion shaped like a jellyfish with fabric sails",
lines=3
)
output_type = gr.Radio(["Image", "3D Model"], label="📌 Choose output type", value="Image")
generate_button = gr.Button("✨ Generate Muse")
with gr.Column():
image_output = gr.Image(label="🎨 Your Muse Output")
generate_button.click(fn=generate_muse, inputs=[prompt, output_type], outputs=image_output)
demo.launch()
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