Update app.py

app.py

@@ -1,23 +1,41 @@
-import spaces, torch
+import torch
 from diffusers import DiffusionPipeline
 import gradio as gr
 
+# Load the pre-trained diffusion model
 pipe = DiffusionPipeline.from_pretrained('ptx0/terminus-xl-velocity-v2', torch_dtype=torch.bfloat16)
-#pipe.unet = torch.compile(pipe.unet)
 pipe.to('cuda')
 
-@spaces.GPU
-def generate(prompt):
-    return pipe(
-        prompt,
-        negative_prompt="underexposed, blurry, ugly, washed-out",
-        guidance_rescale=0.7,
-        guidance_scale=9.5,
-        num_inference_steps=30,
-    ).images
+# Define the image generation function with adjustable parameters and a progress bar
+def generate(prompt, guidance_scale, num_inference_steps, negative_prompt):
+    with gr.Progress(steps=num_inference_steps) as progress:
+        for i in range(num_inference_steps):
+            progress.update(progress=i)
+        return pipe(
+            prompt,
+            negative_prompt=negative_prompt,
+            guidance_scale=guidance_scale,
+            num_inference_steps=num_inference_steps
+        ).images
 
-gr.Interface(
+# Example prompts to demonstrate the model's capabilities
+example_prompts = [
+    ["A futuristic cityscape at night under a starry sky", 7.5, 25, "blurry, overexposed"],
+    ["A serene landscape with a flowing river and autumn trees", 8.0, 20, "crowded, noisy"],
+    ["An abstract painting of joy and energy in bright colors", 9.0, 30, "dark, dull"]
+]
+
+# Create a Gradio interface
+iface = gr.Interface(
     fn=generate,
-    inputs=gr.Text(),
-    outputs=gr.Gallery(),
+    inputs=[
+        gr.Text(label="Enter your prompt"),
+        gr.Slider(5, 10, step=0.1, label="Guidance Scale", default=7.5),
+        gr.Slider(10, 50, step=5, label="Number of Inference Steps", default=25),
+        gr.Text(value="underexposed, blurry, ugly, washed-out", label="Negative Prompt")
+    ],
+    outputs=gr.Gallery(height=512, width=512, columns=2),
+    examples=example_prompts,
+    title="Image Generation with Diffusion Model",
+    description="Generate images based on textual prompts. Adjust the parameters to see how they affect the outcome."
 ).launch()