Update app.py

app.py

@@ -1,15 +1,16 @@
 import torch
-from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
+from diffusers import StableDiffusionPipeline
+import gradio as gr
 
-# Load the model with torch.float32 for CPU
+# Load model (use float32 for CPU)
 pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32)
-pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)  # Faster scheduler
-pipe = pipe.to("cpu")
+pipe.to("cpu")
 
-# Optimized function for faster image generation
+# Image generation function
 def generate_image(prompt):
-    image = pipe(prompt, num_inference_steps=15, guidance_scale=7.0).images[0]  # Reduced steps
-    image.save("output.png")
-    print("Image saved!")
+    image = pipe(prompt).images[0]
+    return image
 
-generate_image("a photo of an astronaut riding a horse on Mars")
+# Gradio Interface
+demo = gr.Interface(fn=generate_image, inputs="text", outputs="image")
+demo.launch()