:bug: remove useless arg

app.py

@@ -7,7 +7,7 @@ import pipeline_openvino_stable_diffusion
 
 model_id = 'OFA-Sys/small-stable-diffusion-v0'
 prefix = ''
-     
+
 scheduler = DPMSolverMultistepScheduler.from_pretrained(model_id, subfolder="scheduler")
 
 
@@ -22,10 +22,9 @@ def error_str(error, title="Error"):
     return f"""#### {title}
             {error}"""  if error else ""
 
-def inference(prompt, guidance, steps, width=512, height=512, seed=0, neg_prompt="", auto_prefix=False):
+def inference(prompt, guidance, steps, width=512, height=512, seed=0, neg_prompt=""):
 
   generator = torch.Generator('cuda').manual_seed(seed) if seed != 0 else None
-  prompt = f"{prefix} {prompt}" if auto_prefix else prompt
 
   try:
     return txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator), None
@@ -42,7 +41,7 @@ def txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator):
       width = width,
       height = height,
       generator = generator)
-    
+
     return result.images[0]
 
 
@@ -60,12 +59,12 @@ with gr.Blocks(css=css) as demo:
 
               </p>
               Running on CPUs with <a href="https://github.com/OFA-Sys/diffusion-deploy">diffusion-deploy</a> to speedup the inference.
-             
+
             </div>
         """
     )
     with gr.Row():
-        
+
         with gr.Column(scale=55):
           with gr.Group():
               with gr.Row():
@@ -79,7 +78,7 @@ with gr.Blocks(css=css) as demo:
           with gr.Tab("Options"):
             with gr.Group():
               neg_prompt = gr.Textbox(label="Negative prompt", placeholder="What to exclude from the image")
-              
+
 
               with gr.Row():
                 guidance = gr.Slider(label="Guidance scale", value=7.5, maximum=15)
@@ -92,9 +91,9 @@ with gr.Blocks(css=css) as demo:
               seed = gr.Slider(0, 2147483647, label='Seed (0 = random)', value=0, step=1)
 
 
-    
 
-    inputs = [prompt, guidance, steps, width, height, seed, neg_prompt, auto_prefix]
+
+    inputs = [prompt, guidance, steps, width, height, seed, neg_prompt]
     outputs = [image_out, error_output]
     prompt.submit(inference, inputs=inputs, outputs=outputs)
     generate.click(inference, inputs=inputs, outputs=outputs)