Update app.py

Step 2: Add Real Image Generation with Stable Diffusion

app.py

@@ -1,18 +1,31 @@
 import gradio as gr
+from diffusers import StableDiffusionPipeline
+import torch
 
-def dummy_muse_generator(prompt, output_type):
-    return f"📌 You asked for a '{output_type}' based on: {prompt}"
+# Load model
+pipe = StableDiffusionPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-2-1",
+    torch_dtype=torch.float16,
+    revision="fp16"
+).to("cuda")
+
+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'."
 
 with gr.Blocks() as demo:
     gr.Markdown("## 🎨 Welcome to MUSE – Your Visual Muse Generator")
 
     with gr.Row():
-        prompt = gr.Textbox(label="Describe your idea", placeholder="e.g. organic wood structure, open-air, inspired by coral")
+        prompt = gr.Textbox(label="Describe your idea", placeholder="e.g. bamboo dome with fabric sails, inspired by jellyfish")
         output_type = gr.Radio(["Image", "3D Model"], label="Choose output type", value="Image")
 
-    generate_button = gr.Button("Generate")
-    output_display = gr.Textbox(label="Output Preview")
+    generate_button = gr.Button("Generate Muse")
+    image_output = gr.Image(label="Your Muse Output")
 
-    generate_button.click(fn=dummy_muse_generator, inputs=[prompt, output_type], outputs=output_display)
+    generate_button.click(fn=generate_muse, inputs=[prompt, output_type], outputs=image_output)
 
 demo.launch()