Update app.py

app.py

@@ -2,6 +2,7 @@ import os
 os.environ['HF_HOME'] = os.path.abspath(
     os.path.realpath(os.path.join(os.path.dirname(__file__), './hf_download'))
 )
+
 import gradio as gr
 import torch
 import traceback
@@ -11,26 +12,41 @@ import numpy as np
 import math
 import spaces
 from PIL import Image
+
+# Diffusers models
 from diffusers import AutoencoderKLHunyuanVideo
+
+# Transformers models
 from transformers import (
     LlamaModel, CLIPTextModel,
-    LlamaTokenizerFast, CLIPTokenizer, AutoImageProcessor, CLIPImageProcessor, CLIPVisionModel
+    LlamaTokenizerFast, CLIPTokenizer,
+    AutoImageProcessor, CLIPImageProcessor, CLIPVisionModel
 )
+
+# Local helper modules
 from diffusers_helper.hunyuan import (
     encode_prompt_conds, vae_decode,
     vae_encode, vae_decode_fake
 )
+
 from diffusers_helper.utils import (
     save_bcthw_as_mp4, crop_or_pad_yield_mask,
     soft_append_bcthw, resize_and_center_crop,
     state_dict_weighted_merge, state_dict_offset_merge,
     generate_timestamp
 )
+
 from diffusers_helper.models.hunyuan_video_packed import HunyuanVideoTransformer3DModelPacked
 from diffusers_helper.pipelines.k_diffusion_hunyuan import sample_hunyuan
 from diffusers_helper.clip_vision import hf_clip_vision_encode
 from diffusers_helper.bucket_tools import find_nearest_bucket
 
+# Thread utilities
+from diffusers_helper.thread_utils import AsyncStream, async_run
+
+# Gradio progress bar utils
+from diffusers_helper.gradio.progress_bar import make_progress_bar_css, make_progress_bar_html
+
 # Set device to CPU
 device = torch.device("cpu")