update

app.py

@@ -6,8 +6,6 @@ import random
 import numpy as np
 import os
 import gc
-import tempfile
-import imageio
 from diffusers import AutoencoderKLWan
 from wan_pipeline import WanPipeline
 from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepScheduler
@@ -18,7 +16,6 @@ from huggingface_hub import login
 # Authenticate with HF
 login(token=os.getenv('HF_TOKEN'))
 
-# Set seed
 def set_seed(seed):
     random.seed(seed)
     os.environ['PYTHONHASHSEED'] = str(seed)
@@ -26,7 +23,6 @@ def set_seed(seed):
     torch.manual_seed(seed)
     torch.cuda.manual_seed(seed)
 
-# Model paths
 model_paths = {
     "sd3": "stabilityai/stable-diffusion-3-medium-diffusers",
     "sd3.5": "stabilityai/stable-diffusion-3.5-large",
@@ -55,7 +51,10 @@ def load_model(model_name):
     return current_model.to("cuda")
 
 @spaces.GPU(duration=500)
-def generate_content(prompt, model_name, guidance_scale=7.5, num_inference_steps=50, use_cfg_zero_star=True, use_zero_init=True, zero_steps=0, seed=None, compare_mode=False):
+def generate_content(prompt, model_name, guidance_scale=7.5, num_inference_steps=50,
+                     use_cfg_zero_star=True, use_zero_init=True, zero_steps=0,
+                     seed=None, compare_mode=False):
+    
     model = load_model(model_name)
     if seed is None:
         seed = random.randint(0, 2**32 - 1)
@@ -82,8 +81,6 @@ def generate_content(prompt, model_name, guidance_scale=7.5, num_inference_steps
 
         return None, None, video1_path, seed
 
-    print("prompt:", prompt)
-
     if compare_mode:
         set_seed(seed)
         image1 = model(
@@ -121,7 +118,7 @@ def generate_content(prompt, model_name, guidance_scale=7.5, num_inference_steps
         else:
             return None, image, None, seed
 
-# Gradio UI
+# Gradio UI with left-right layout
 with gr.Blocks() as demo:
     gr.HTML("""
         <div style="text-align: center; font-size: 32px; font-weight: bold; margin-bottom: 20px;">
@@ -134,31 +131,24 @@ with gr.Blocks() as demo:
     """)
 
     with gr.Row():
-        prompt = gr.Textbox(value="A spooky haunted mansion on a hill silhouetted by a full moon.", label="Enter your prompt")
-        model_choice = gr.Dropdown(choices=list(model_paths.keys()), label="Choose Model")
-
-    with gr.Row():
-        guidance_scale = gr.Slider(1, 20, value=4.0, step=0.5, label="Guidance Scale")
-        inference_steps = gr.Slider(10, 100, value=28, step=5, label="Inference Steps")
-
-    with gr.Row():
-        use_opt_scale = gr.Checkbox(value=True, label="Use Optimized-Scale")
-        use_zero_init = gr.Checkbox(value=True, label="Use Zero Init")
-        zero_steps = gr.Slider(0, 20, value=0, step=1, label="Zero out steps")
-
-    with gr.Row():
-        seed = gr.Number(value=42, label="Seed (Leave blank for random)")
-        compare_mode = gr.Checkbox(value=True, label="Compare Mode")
-
-    with gr.Row():
-        out1 = gr.Image(type="pil", label="CFG-Zero* Image")
-        out2 = gr.Image(type="pil", label="CFG Image")
-        video = gr.Video(label="Video")
-        used_seed = gr.Textbox(label="Used Seed")
-
-    generate_btn = gr.Button("Generate")
+        with gr.Column(scale=1):
+            prompt = gr.Textbox(value="A spooky haunted mansion on a hill silhouetted by a full moon.", label="Enter your prompt")
+            model_choice = gr.Dropdown(choices=list(model_paths.keys()), label="Choose Model")
+            guidance_scale = gr.Slider(1, 20, value=4.0, step=0.5, label="Guidance Scale")
+            inference_steps = gr.Slider(10, 100, value=28, step=5, label="Inference Steps")
+            use_opt_scale = gr.Checkbox(value=True, label="Use Optimized-Scale")
+            use_zero_init = gr.Checkbox(value=True, label="Use Zero Init")
+            zero_steps = gr.Slider(0, 20, value=0, step=1, label="Zero out steps")
+            seed = gr.Number(value=42, label="Seed (Leave blank for random)")
+            compare_mode = gr.Checkbox(value=True, label="Compare Mode")
+            generate_btn = gr.Button("Generate")
+
+        with gr.Column(scale=2):
+            out1 = gr.Image(type="pil", label="CFG-Zero* Image")
+            out2 = gr.Image(type="pil", label="CFG Image")
+            video = gr.Video(label="Video")
+            used_seed = gr.Textbox(label="Used Seed")
 
-    # Change logic for when "wan-t2v" is selected
     def update_params(model_name):
         if model_name == "wan-t2v":
             return (