remove useless stuff

app.py

@@ -38,31 +38,23 @@ def encode_image(image_path):
 @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
     prompt,
-    negative_prompt,
-    seed,
-    randomize_seed,
-    width,
-    height,
-    guidance_scale,
-    num_inference_steps,
     progress=gr.Progress(track_tqdm=True),
 ):
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
+    # seed = random.randint(0, MAX_SEED)
 
-    generator = torch.Generator().manual_seed(seed)
+    # generator = torch.Generator().manual_seed(seed)
 
     image = pipe(
         prompt=prompt,
-        negative_prompt=negative_prompt,
         guidance_scale=0.,
         num_inference_steps=4,
         width=1420,
         height=1080,
         max_sequence_length=256,
+        
     ).images[0]
 
-    return image, seed
+    return image
 
 @spaces.GPU #[uncomment to use ZeroGPU]
 def generate_description_fn(
@@ -96,12 +88,6 @@ def generate_description_fn(
     return chat_completion.choices[0].message.content
 
 
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
-
 css = """
 #col-container {
     margin: 0 auto;
@@ -134,73 +120,13 @@ with gr.Blocks(css=css) as demo:
 
             result = gr.Image(label="Result", show_label=False)
 
-            with gr.Accordion("Advanced Settings", open=False):
-                negative_prompt = gr.Text(
-                    label="Negative prompt",
-                    max_lines=1,
-                    placeholder="Enter a negative prompt",
-                    visible=False,
-                )
-
-                seed = gr.Slider(
-                    label="Seed",
-                    minimum=0,
-                    maximum=MAX_SEED,
-                    step=1,
-                    value=0,
-                )
-
-                randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-
-                with gr.Row():
-                    width = gr.Slider(
-                        label="Width",
-                        minimum=256,
-                        maximum=MAX_IMAGE_SIZE,
-                        step=32,
-                        value=1024,  # Replace with defaults that work for your model
-                    )
-
-                    height = gr.Slider(
-                        label="Height",
-                        minimum=256,
-                        maximum=MAX_IMAGE_SIZE,
-                        step=32,
-                        value=1024,  # Replace with defaults that work for your model
-                    )
-
-                with gr.Row():
-                    guidance_scale = gr.Slider(
-                        label="Guidance scale",
-                        minimum=0.0,
-                        maximum=10.0,
-                        step=0.1,
-                        value=0.0,  # Replace with defaults that work for your model
-                    )
-
-                    num_inference_steps = gr.Slider(
-                        label="Number of inference steps",
-                        minimum=1,
-                        maximum=50,
-                        step=1,
-                        value=2,  # Replace with defaults that work for your model
-                    )
-
-            gr.Examples(examples=examples, inputs=[prompt])
         gr.on(
             triggers=[run_button.click, prompt.submit],
             fn=infer,
             inputs=[
                 prompt,
-                negative_prompt,
-                seed,
-                randomize_seed,
-                width,
-                height,
-                guidance_scale,
-                num_inference_steps,
             ],
-            outputs=[result, seed],
+            outputs=[result],
         )
 
         gr.on(