Update app.py

app.py

@@ -3,20 +3,24 @@ from optimum.intel import OVStableDiffusionXLPipeline
 import gradio as gr
 
 
+
 model_id = "stabilityai/stable-diffusion-xl-base-1.0"
 pipe = DiffusionPipeline.from_pretrained(model_id)
-pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
+pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)  
 pipe.load_lora_weights("latent-consistency/lcm-lora-sdxl")
-
 pipeline = OVStableDiffusionXLPipeline.from_pretrained(
-    pipe,
+    pipe,  
     export=True 
 )
 
-def generate_images(prompt, batch_size):
+def generate_images(prompt, batch_size, num_inference_steps, guidance_scale):
     images = []
     for _ in range(batch_size):
-        results = pipeline(prompt)
+        results = pipeline(
+            prompt=prompt, 
+            num_inference_steps=num_inference_steps,
+            guidance_scale=guidance_scale
+        )
         images.append(results.images[0])
     return images
 
@@ -24,10 +28,12 @@ iface = gr.Interface(
     fn=generate_images,
     inputs=[
         gr.Textbox(label="Prompt"),
-        gr.Slider(label="Number of Images", minimum=1, maximum=12, step=1, value=1)
+        gr.Slider(label="Batch Size", minimum=1, maximum=12, step=1, value=1),
+        gr.Slider(label="Num Inference Steps", minimum=1, maximum=6, step=1, value=4),
+        gr.Slider(label="Guidance Scale", minimum=0.0, maximum=3, step=0.1, value=1.4)
     ],
     outputs=gr.Gallery(label="Generated Images"),
-    title="SuperFast SDXL Generation on CPU"
+    title="Fast SDXL Generation on CPU"
 )
 
-iface.launch(debug=True)
+iface.launch()