diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml
new file mode 100644
index 0000000..a8719ae
--- /dev/null
+++ b/.github/workflows/publish.yml
@@ -0,0 +1,24 @@
+name: Publish to Comfy registry
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+      - master
+    paths:
+      - "pyproject.toml"
+
+jobs:
+  publish-node:
+    name: Publish Custom Node to registry
+    runs-on: ubuntu-latest
+    # if this is a forked repository. Skipping the workflow.
+    if: github.event.repository.fork == false 
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+      - name: Publish Custom Node
+        uses: Comfy-Org/publish-node-action@main
+        with:
+          ## Add your own personal access token to your Github Repository secrets and reference it here.
+          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..341e31e
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,2 @@
+__pycache__
+.idea
\ No newline at end of file
diff --git a/LivePortrait/config/inference_config.py b/LivePortrait/config/inference_config.py
new file mode 100644
index 0000000..8494c82
--- /dev/null
+++ b/LivePortrait/config/inference_config.py
@@ -0,0 +1,8 @@
+
+import os
+
+current_file_path = os.path.abspath(__file__)
+current_directory = os.path.dirname(current_file_path)
+class InferenceConfig:
+    def __init__(self):
+        self.flag_use_half_precision: bool = False  # whether to use half precision
\ No newline at end of file
diff --git a/config/models.yaml b/LivePortrait/config/models.yaml
similarity index 100%
rename from config/models.yaml
rename to LivePortrait/config/models.yaml
diff --git a/LivePortrait/src/live_portrait_wrapper.py b/LivePortrait/live_portrait_wrapper.py
similarity index 55%
rename from LivePortrait/src/live_portrait_wrapper.py
rename to LivePortrait/live_portrait_wrapper.py
index 935b03e..a71acb2 100644
--- a/LivePortrait/src/live_portrait_wrapper.py
+++ b/LivePortrait/live_portrait_wrapper.py
@@ -1,91 +1,29 @@
-import os.path as osp
 import numpy as np
-import cv2
 import torch
-import yaml
-
-from LivePortrait.src.utils.timer import Timer
-from LivePortrait.src.utils.helper import load_model, concat_feat
-from LivePortrait.src.utils.camera import headpose_pred_to_degree, get_rotation_matrix
-from config.inference_config import InferenceConfig
-from LivePortrait.src.utils.rprint import rlog as log
 
+from .utils.helper import concat_feat
+from .utils.camera import headpose_pred_to_degree, get_rotation_matrix
+from .config.inference_config import InferenceConfig
 
 class LivePortraitWrapper(object):
 
-    def __init__(self, cfg: InferenceConfig):
-
-        model_config = yaml.load(open(cfg.models_config, 'r'), Loader=yaml.SafeLoader)
-
-        # init F
-        self.appearance_feature_extractor = load_model(cfg.checkpoint_F, model_config, cfg.device_id, 'appearance_feature_extractor')
-        log(f'Load appearance_feature_extractor done.')
-        # init M
-        self.motion_extractor = load_model(cfg.checkpoint_M, model_config, cfg.device_id, 'motion_extractor')
-        log(f'Load motion_extractor done.')
-        # init W
-        self.warping_module = load_model(cfg.checkpoint_W, model_config, cfg.device_id, 'warping_module')
-        log(f'Load warping_module done.')
-        # init G
-        self.spade_generator = load_model(cfg.checkpoint_G, model_config, cfg.device_id, 'spade_generator')
-        log(f'Load spade_generator done.')
-        # init S and R
-        if cfg.checkpoint_S is not None and osp.exists(cfg.checkpoint_S):
-            self.stitching_retargeting_module = load_model(cfg.checkpoint_S, model_config, cfg.device_id, 'stitching_retargeting_module')
-            log(f'Load stitching_retargeting_module done.')
-        else:
-            self.stitching_retargeting_module = None
-
-        self.cfg = cfg
-        self.device_id = cfg.device_id
-        self.timer = Timer()
-
-    def prepare_source(self, img: np.ndarray) -> torch.Tensor:
-        """ construct the input as standard
-        img: HxWx3, uint8, 256x256
-        """
-        h, w = img.shape[:2]
-        if h != self.cfg.input_shape[0] or w != self.cfg.input_shape[1]:
-            x = cv2.resize(img, (self.cfg.input_shape[0], self.cfg.input_shape[1]))
-        else:
-            x = img.copy()
-
-        if x.ndim == 3:
-            x = x[np.newaxis].astype(np.float32) / 255.  # HxWx3 -> 1xHxWx3, normalized to 0~1
-        elif x.ndim == 4:
-            x = x.astype(np.float32) / 255.  # BxHxWx3, normalized to 0~1
-        else:
-            raise ValueError(f'img ndim should be 3 or 4: {x.ndim}')
-        x = np.clip(x, 0, 1)  # clip to 0~1
-        x = torch.from_numpy(x).permute(0, 3, 1, 2)  # 1xHxWx3 -> 1x3xHxW
-        x = x.cuda(self.device_id)
-        return x
-
-    def prepare_driving_videos(self, imgs) -> torch.Tensor:
-        """ construct the input as standard
-        imgs: NxBxHxWx3, uint8
-        """
-        if isinstance(imgs, list):
-            _imgs = np.array(imgs)[..., np.newaxis]  # TxHxWx3x1
-        elif isinstance(imgs, np.ndarray):
-            _imgs = imgs
-        else:
-            raise ValueError(f'imgs type error: {type(imgs)}')
+    def __init__(self, cfg: InferenceConfig, appearance_feature_extractor, motion_extractor,
+                                            warping_module, spade_generator, stitching_retargeting_module):
 
-        y = _imgs.astype(np.float32) / 255.
-        y = np.clip(y, 0, 1)  # clip to 0~1
-        y = torch.from_numpy(y).permute(0, 4, 3, 1, 2)  # TxHxWx3x1 -> Tx1x3xHxW
-        y = y.cuda(self.device_id)
+        self.appearance_feature_extractor = appearance_feature_extractor
+        self.motion_extractor = motion_extractor
+        self.warping_module = warping_module
+        self.spade_generator = spade_generator
+        self.stitching_retargeting_module = stitching_retargeting_module
 
-        return y
+        self.cfg = cfg
 
     def extract_feature_3d(self, x: torch.Tensor) -> torch.Tensor:
         """ get the appearance feature of the image by F
         x: Bx3xHxW, normalized to 0~1
         """
         with torch.no_grad():
-            with torch.autocast(device_type='cuda', dtype=torch.float16, enabled=self.cfg.flag_use_half_precision):
-                feature_3d = self.appearance_feature_extractor(x)
+            feature_3d = self.appearance_feature_extractor(x)
 
         return feature_3d.float()
 
@@ -96,8 +34,7 @@ def get_kp_info(self, x: torch.Tensor, **kwargs) -> dict:
         return: A dict contains keys: 'pitch', 'yaw', 'roll', 't', 'exp', 'scale', 'kp'
         """
         with torch.no_grad():
-            with torch.autocast(device_type='cuda', dtype=torch.float16, enabled=self.cfg.flag_use_half_precision):
-                kp_info = self.motion_extractor(x)
+            kp_info = self.motion_extractor(x)
 
             if self.cfg.flag_use_half_precision:
                 # float the dict
@@ -189,11 +126,10 @@ def warp_decode(self, feature_3d: torch.Tensor, kp_source: torch.Tensor, kp_driv
         """
         # The line 18 in Algorithm 1: D(W(f_s; x_s, x′_d,i)）
         with torch.no_grad():
-            with torch.autocast(device_type='cuda', dtype=torch.float16, enabled=self.cfg.flag_use_half_precision):
-                # get decoder input
-                ret_dct = self.warping_module(feature_3d, kp_source=kp_source, kp_driving=kp_driving)
-                # decode
-                ret_dct['out'] = self.spade_generator(feature=ret_dct['out'])
+            # get decoder input
+            ret_dct = self.warping_module(feature_3d, kp_source=kp_source, kp_driving=kp_driving)
+            # decode
+            ret_dct['out'] = self.spade_generator(feature=ret_dct['out'])
 
             # float the dict
             if self.cfg.flag_use_half_precision:
diff --git a/LivePortrait/src/modules/__init__.py b/LivePortrait/modules/__init__.py
similarity index 100%
rename from LivePortrait/src/modules/__init__.py
rename to LivePortrait/modules/__init__.py
diff --git a/LivePortrait/src/modules/appearance_feature_extractor.py b/LivePortrait/modules/appearance_feature_extractor.py
similarity index 100%
rename from LivePortrait/src/modules/appearance_feature_extractor.py
rename to LivePortrait/modules/appearance_feature_extractor.py
diff --git a/LivePortrait/src/modules/convnextv2.py b/LivePortrait/modules/convnextv2.py
similarity index 100%
rename from LivePortrait/src/modules/convnextv2.py
rename to LivePortrait/modules/convnextv2.py
diff --git a/LivePortrait/src/modules/dense_motion.py b/LivePortrait/modules/dense_motion.py
similarity index 98%
rename from LivePortrait/src/modules/dense_motion.py
rename to LivePortrait/modules/dense_motion.py
index 0eec0c4..c1a7f9a 100644
--- a/LivePortrait/src/modules/dense_motion.py
+++ b/LivePortrait/modules/dense_motion.py
@@ -59,7 +59,7 @@ def create_heatmap_representations(self, feature, kp_driving, kp_source):
         heatmap = gaussian_driving - gaussian_source  # (bs, num_kp, d, h, w)
 
         # adding background feature
-        zeros = torch.zeros(heatmap.shape[0], 1, spatial_size[0], spatial_size[1], spatial_size[2]).type(heatmap.type()).to(heatmap.device)
+        zeros = torch.zeros(heatmap.shape[0], 1, spatial_size[0], spatial_size[1], spatial_size[2]).type(heatmap.dtype).to(heatmap.device)
         heatmap = torch.cat([zeros, heatmap], dim=1)
         heatmap = heatmap.unsqueeze(2)         # (bs, 1+num_kp, 1, d, h, w)
         return heatmap
diff --git a/LivePortrait/src/modules/motion_extractor.py b/LivePortrait/modules/motion_extractor.py
similarity index 100%
rename from LivePortrait/src/modules/motion_extractor.py
rename to LivePortrait/modules/motion_extractor.py
diff --git a/LivePortrait/src/modules/spade_generator.py b/LivePortrait/modules/spade_generator.py
similarity index 100%
rename from LivePortrait/src/modules/spade_generator.py
rename to LivePortrait/modules/spade_generator.py
diff --git a/LivePortrait/src/modules/stitching_retargeting_network.py b/LivePortrait/modules/stitching_retargeting_network.py
similarity index 100%
rename from LivePortrait/src/modules/stitching_retargeting_network.py
rename to LivePortrait/modules/stitching_retargeting_network.py
diff --git a/LivePortrait/src/modules/util.py b/LivePortrait/modules/util.py
similarity index 100%
rename from LivePortrait/src/modules/util.py
rename to LivePortrait/modules/util.py
diff --git a/LivePortrait/src/modules/warping_network.py b/LivePortrait/modules/warping_network.py
similarity index 100%
rename from LivePortrait/src/modules/warping_network.py
rename to LivePortrait/modules/warping_network.py
diff --git a/LivePortrait/src/utils/__init__.py b/LivePortrait/utils/__init__.py
similarity index 100%
rename from LivePortrait/src/utils/__init__.py
rename to LivePortrait/utils/__init__.py
diff --git a/LivePortrait/src/utils/camera.py b/LivePortrait/utils/camera.py
similarity index 100%
rename from LivePortrait/src/utils/camera.py
rename to LivePortrait/utils/camera.py
diff --git a/LivePortrait/src/utils/face_analysis_diy.py b/LivePortrait/utils/face_analysis_diy.py
similarity index 100%
rename from LivePortrait/src/utils/face_analysis_diy.py
rename to LivePortrait/utils/face_analysis_diy.py
diff --git a/LivePortrait/src/utils/helper.py b/LivePortrait/utils/helper.py
similarity index 55%
rename from LivePortrait/src/utils/helper.py
rename to LivePortrait/utils/helper.py
index 009c3df..277f63d 100644
--- a/LivePortrait/src/utils/helper.py
+++ b/LivePortrait/utils/helper.py
@@ -11,11 +11,11 @@
 from rich.console import Console
 from collections import OrderedDict
 
-from LivePortrait.src.modules.spade_generator import SPADEDecoder
-from LivePortrait.src.modules.warping_network import WarpingNetwork
-from LivePortrait.src.modules.motion_extractor import MotionExtractor
-from LivePortrait.src.modules.appearance_feature_extractor import AppearanceFeatureExtractor
-from LivePortrait.src.modules.stitching_retargeting_network import StitchingRetargetingNetwork
+from ..modules.spade_generator import SPADEDecoder
+from ..modules.warping_network import WarpingNetwork
+from ..modules.motion_extractor import MotionExtractor
+from ..modules.appearance_feature_extractor import AppearanceFeatureExtractor
+from ..modules.stitching_retargeting_network import StitchingRetargetingNetwork
 from .rprint import rlog as log
 
 
@@ -85,57 +85,6 @@ def concat_feat(kp_source: torch.Tensor, kp_driving: torch.Tensor) -> torch.Tens
     return feat
 
 
-def remove_ddp_dumplicate_key(state_dict):
-    state_dict_new = OrderedDict()
-    for key in state_dict.keys():
-        state_dict_new[key.replace('module.', '')] = state_dict[key]
-    return state_dict_new
-
-
-def load_model(ckpt_path, model_config, device, model_type):
-    model_params = model_config['model_params'][f'{model_type}_params']
-
-    if model_type == 'appearance_feature_extractor':
-        model = AppearanceFeatureExtractor(**model_params).cuda(device)
-    elif model_type == 'motion_extractor':
-        model = MotionExtractor(**model_params).cuda(device)
-    elif model_type == 'warping_module':
-        model = WarpingNetwork(**model_params).cuda(device)
-    elif model_type == 'spade_generator':
-        model = SPADEDecoder(**model_params).cuda(device)
-    elif model_type == 'stitching_retargeting_module':
-        # Special handling for stitching and retargeting module
-        config = model_config['model_params']['stitching_retargeting_module_params']
-        checkpoint = torch.load(ckpt_path, map_location=lambda storage, loc: storage)
-
-        stitcher = StitchingRetargetingNetwork(**config.get('stitching'))
-        stitcher.load_state_dict(remove_ddp_dumplicate_key(checkpoint['retarget_shoulder']))
-        stitcher = stitcher.cuda(device)
-        stitcher.eval()
-
-        retargetor_lip = StitchingRetargetingNetwork(**config.get('lip'))
-        retargetor_lip.load_state_dict(remove_ddp_dumplicate_key(checkpoint['retarget_mouth']))
-        retargetor_lip = retargetor_lip.cuda(device)
-        retargetor_lip.eval()
-
-        retargetor_eye = StitchingRetargetingNetwork(**config.get('eye'))
-        retargetor_eye.load_state_dict(remove_ddp_dumplicate_key(checkpoint['retarget_eye']))
-        retargetor_eye = retargetor_eye.cuda(device)
-        retargetor_eye.eval()
-
-        return {
-            'stitching': stitcher,
-            'lip': retargetor_lip,
-            'eye': retargetor_eye
-        }
-    else:
-        raise ValueError(f"Unknown model type: {model_type}")
-
-    model.load_state_dict(torch.load(ckpt_path, map_location=lambda storage, loc: storage))
-    model.eval()
-    return model
-
-
 # get coefficients of Eqn. 7
 def calculate_transformation(config, s_kp_info, t_0_kp_info, t_i_kp_info, R_s, R_t_0, R_t_i):
     if config.relative:
diff --git a/LivePortrait/src/utils/io.py b/LivePortrait/utils/io.py
similarity index 100%
rename from LivePortrait/src/utils/io.py
rename to LivePortrait/utils/io.py
diff --git a/LivePortrait/src/utils/resources/mask_template.png b/LivePortrait/utils/resources/mask_template.png
similarity index 100%
rename from LivePortrait/src/utils/resources/mask_template.png
rename to LivePortrait/utils/resources/mask_template.png
diff --git a/LivePortrait/src/utils/rprint.py b/LivePortrait/utils/rprint.py
similarity index 100%
rename from LivePortrait/src/utils/rprint.py
rename to LivePortrait/utils/rprint.py
diff --git a/LivePortrait/src/utils/timer.py b/LivePortrait/utils/timer.py
similarity index 100%
rename from LivePortrait/src/utils/timer.py
rename to LivePortrait/utils/timer.py
diff --git a/LivePortrait/src/utils/video.py b/LivePortrait/utils/video.py
similarity index 100%
rename from LivePortrait/src/utils/video.py
rename to LivePortrait/utils/video.py
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..8b8f352
--- /dev/null
+++ b/README.md
@@ -0,0 +1,67 @@
+# ComfyUI-AdvancedLivePortrait
+
+## Update
+11/07/2024
+
+Expressions are feature-reactive (features: audio, MIDI, motion, proximity, and more).
+
+8/21/2024
+
+You can create a video without a video.
+
+Track the face of the source video.
+
+The workflow has been updated.
+
+## Introduction
+
+AdvancedLivePortrait is faster and has real-time preview
+
+https://github.com/user-attachments/assets/90b78639-6477-48af-ba49-7945488df581
+
+Edit facial expressions in photos.
+
+Insert facial expressions into videos.
+
+Create animations using multiple facial expressions.
+
+Extract facial expressions from sample photos.
+
+## Installation
+
+This project has been registered with ComfyUI-Manager. Now you can install it automatically using the manager.
+
+## Usage
+
+The workflows and sample datas placed in '\custom_nodes\ComfyUI-AdvancedLivePortrait\sample\'
+
+-----
+
+You can add expressions to the video. See 'workflow2_advanced.json'.
+
+Describes the 'command' in 'workflow2_advanced.json'
+
+![readme](https://github.com/user-attachments/assets/339568b2-ad52-4aaf-a6ab-fcd877449c56)
+
+
+[Motion index] = [Changing frame length] : [Length of frames waiting for next motion]
+
+Motion index 0 is the original source image.
+
+They are numbered in the order they lead to the motion_link.
+
+Linking the driving video to 'src_images' will add facial expressions to the driving video.
+
+-----
+
+You can save and load expressions with the 'Load Exp Data' 'Save Exp Data' nodes.
+
+\ComfyUI\output\exp_data\  Path to the folder being saved
+
+-----
+
+## Thanks
+
+Original author's link : https://liveportrait.github.io/
+
+This project uses a model converted by kijai. link : https://github.com/kijai/ComfyUI-LivePortraitKJ
diff --git a/__init__.py b/__init__.py
index 476fdb7..4322a4e 100644
--- a/__init__.py
+++ b/__init__.py
@@ -1,48 +1,3 @@
-import requests
-import os, sys
-import subprocess
-from tqdm import tqdm
-from pip._internal import main as pip_main
-from pathlib import Path
-from folder_paths import models_dir
-
-def download_model(file_path, model_url):
-    print('AdvancedLivePortrait: Downloading model...')
-    response = requests.get(model_url, stream=True)
-    try:
-        if response.status_code == 200:
-            total_size = int(response.headers.get('content-length', 0))
-            block_size = 1024  # 1 Kibibyte
-
-            # tqdm will display a progress bar
-            with open(file_path, 'wb') as file, tqdm(
-                desc='Downloading',
-                total=total_size,
-                unit='iB',
-                unit_scale=True,
-                unit_divisor=1024,
-            ) as bar:
-                for data in response.iter_content(block_size):
-                    bar.update(len(data))
-                    file.write(data)
-
-    except requests.exceptions.RequestException as err:
-        print('AdvancedLivePortrait: Model download failed: {err}')
-        print(f'AdvancedLivePortrait: Download it manually from: {model_url}')
-        print(f'AdvancedLivePortrait: And put it in {file_path}')
-    except Exception as e:
-        print(f'AdvancedLivePortrait: An unexpected error occurred: {e}')
-
-save_path = os.path.join(models_dir, "ultralytics")
-if not os.path.exists(save_path):
-    os.makedirs(save_path, exist_ok=True)
-    file_path = os.path.join(save_path, "face_yolov8n.pt")
-    if not Path().is_file():
-        download_model(file_path, "https://huggingface.co/Bingsu/adetailer/resolve/main/face_yolov8n.pt")
-    
-
-    
-
 from .nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
 __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
 
diff --git a/config/inference_config.py b/config/inference_config.py
deleted file mode 100644
index 3a735f6..0000000
--- a/config/inference_config.py
+++ /dev/null
@@ -1,21 +0,0 @@
-
-import os
-from typing import Literal, Tuple
-import folder_paths
-
-current_file_path = os.path.abspath(__file__)
-current_directory = os.path.dirname(current_file_path)
-class InferenceConfig:
-    def __init__(self):
-        self.models_config: str = os.path.join(current_directory, "models.yaml")
-        self.checkpoint_F: str = os.path.join(folder_paths.models_dir, "liveportrait", "base_models", "appearance_feature_extractor.pth")
-        self.checkpoint_M: str = os.path.join(folder_paths.models_dir, "liveportrait", "base_models", "motion_extractor.pth")
-        self.checkpoint_G: str = os.path.join(folder_paths.models_dir, "liveportrait", "base_models", "spade_generator.pth")
-        self.checkpoint_W: str = os.path.join(folder_paths.models_dir, "liveportrait", "base_models", "warping_module.pth")
-        self.checkpoint_S: str = os.path.join(folder_paths.models_dir, "liveportrait", "retargeting_models", "stitching_retargeting_module.pth")
-        self.flag_use_half_precision: bool = True  # whether to use half precision
-
-        self.input_shape: Tuple[int, int] = (256, 256)  # input shape
-
-        self.mask_crop = None
-        self.device_id: int = 0
\ No newline at end of file
diff --git a/nodes.py b/nodes.py
index 6482d4a..3c767fe 100644
--- a/nodes.py
+++ b/nodes.py
@@ -8,21 +8,38 @@
 import comfy.utils
 import time
 import copy
-import math
 import dill
-import torch.nn.functional as torchfn
-from torchvision import transforms
+import yaml
 from ultralytics import YOLO
-from scipy.spatial.transform import Rotation as R
-
 
 current_file_path = os.path.abspath(__file__)
 current_directory = os.path.dirname(current_file_path)
-sys.path.append(current_directory)
-from .LivePortrait.src.live_portrait_wrapper import LivePortraitWrapper
-from .LivePortrait.src.utils.rprint import rlog as log
-from .LivePortrait.src.utils.camera import get_rotation_matrix
-from .config.inference_config import InferenceConfig
+
+from .LivePortrait.live_portrait_wrapper import LivePortraitWrapper
+from .LivePortrait.utils.camera import get_rotation_matrix
+from .LivePortrait.config.inference_config import InferenceConfig
+
+from .LivePortrait.modules.spade_generator import SPADEDecoder
+from .LivePortrait.modules.warping_network import WarpingNetwork
+from .LivePortrait.modules.motion_extractor import MotionExtractor
+from .LivePortrait.modules.appearance_feature_extractor import AppearanceFeatureExtractor
+from .LivePortrait.modules.stitching_retargeting_network import StitchingRetargetingNetwork
+from collections import OrderedDict
+
+cur_device = None
+def get_device():
+    global cur_device
+    if cur_device == None:
+        if torch.cuda.is_available():
+            cur_device = torch.device('cuda')
+            print("Uses CUDA device.")
+        elif torch.backends.mps.is_available():
+            cur_device = torch.device('mps')
+            print("Uses MPS device.")
+        else:
+            cur_device = torch.device('cpu')
+            print("Uses CPU device.")
+    return cur_device
 
 def tensor2pil(image):
     return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
@@ -35,8 +52,8 @@ def rgb_crop_batch(rgbs, region):
     return rgbs[:, region[1]:region[3], region[0]:region[2]]
 def get_rgb_size(rgb):
     return rgb.shape[1], rgb.shape[0]
-def create_transform_matrix(x, y, scale=1):
-    return np.float32([[scale, 0, x], [0, scale, y]])
+def create_transform_matrix(x, y, s_x, s_y):
+    return np.float32([[s_x, 0, x], [0, s_y, y]])
 
 def get_model_dir(m):
     try:
@@ -73,64 +90,236 @@ def __init__(self, src_rgb, crop_trans_m, x_s_info, f_s_user, x_s_user, mask_ori
         self.x_s_user = x_s_user
         self.mask_ori = mask_ori
 
+import requests
+from tqdm import tqdm
+
 class LP_Engine:
     pipeline = None
-    bbox_model = None
+    detect_model = None
     mask_img = None
+    temp_img_idx = 0
+
+    def get_temp_img_name(self):
+        self.temp_img_idx += 1
+        return "expression_edit_preview" + str(self.temp_img_idx) + ".png"
+
+    def download_model(_, file_path, model_url):
+        print('AdvancedLivePortrait: Downloading model...')
+        response = requests.get(model_url, stream=True)
+        try:
+            if response.status_code == 200:
+                total_size = int(response.headers.get('content-length', 0))
+                block_size = 1024  # 1 Kibibyte
+
+                # tqdm will display a progress bar
+                with open(file_path, 'wb') as file, tqdm(
+                        desc='Downloading',
+                        total=total_size,
+                        unit='iB',
+                        unit_scale=True,
+                        unit_divisor=1024,
+                ) as bar:
+                    for data in response.iter_content(block_size):
+                        bar.update(len(data))
+                        file.write(data)
+
+        except requests.exceptions.RequestException as err:
+            print('AdvancedLivePortrait: Model download failed: {err}')
+            print(f'AdvancedLivePortrait: Download it manually from: {model_url}')
+            print(f'AdvancedLivePortrait: And put it in {file_path}')
+        except Exception as e:
+            print(f'AdvancedLivePortrait: An unexpected error occurred: {e}')
+
+    def remove_ddp_dumplicate_key(_, state_dict):
+        state_dict_new = OrderedDict()
+        for key in state_dict.keys():
+            state_dict_new[key.replace('module.', '')] = state_dict[key]
+        return state_dict_new
+
+    def filter_for_model(_, checkpoint, prefix):
+        filtered_checkpoint = {key.replace(prefix + "_module.", ""): value for key, value in checkpoint.items() if
+                               key.startswith(prefix)}
+        return filtered_checkpoint
+
+    def load_model(self, model_config, model_type):
+
+        device = get_device()
+
+        if model_type == 'stitching_retargeting_module':
+            ckpt_path = os.path.join(get_model_dir("liveportrait"), "retargeting_models", model_type + ".pth")
+        else:
+            ckpt_path = os.path.join(get_model_dir("liveportrait"), "base_models", model_type + ".pth")
+
+        is_safetensors = None
+        if os.path.isfile(ckpt_path) == False:
+            is_safetensors = True
+            ckpt_path = os.path.join(get_model_dir("liveportrait"), model_type + ".safetensors")
+            if os.path.isfile(ckpt_path) == False:
+                self.download_model(ckpt_path,
+                "https://huggingface.co/Kijai/LivePortrait_safetensors/resolve/main/" + model_type + ".safetensors")
+        model_params = model_config['model_params'][f'{model_type}_params']
+        if model_type == 'appearance_feature_extractor':
+            model = AppearanceFeatureExtractor(**model_params).to(device)
+        elif model_type == 'motion_extractor':
+            model = MotionExtractor(**model_params).to(device)
+        elif model_type == 'warping_module':
+            model = WarpingNetwork(**model_params).to(device)
+        elif model_type == 'spade_generator':
+            model = SPADEDecoder(**model_params).to(device)
+        elif model_type == 'stitching_retargeting_module':
+            # Special handling for stitching and retargeting module
+            config = model_config['model_params']['stitching_retargeting_module_params']
+            checkpoint = comfy.utils.load_torch_file(ckpt_path)
+
+            stitcher = StitchingRetargetingNetwork(**config.get('stitching'))
+            if is_safetensors:
+                stitcher.load_state_dict(self.filter_for_model(checkpoint, 'retarget_shoulder'))
+            else:
+                stitcher.load_state_dict(self.remove_ddp_dumplicate_key(checkpoint['retarget_shoulder']))
+            stitcher = stitcher.to(device)
+            stitcher.eval()
+
+            return {
+                'stitching': stitcher,
+            }
+        else:
+            raise ValueError(f"Unknown model type: {model_type}")
+
+
+        model.load_state_dict(comfy.utils.load_torch_file(ckpt_path))
+        model.eval()
+        return model
+
+    def load_models(self):
+        model_path = get_model_dir("liveportrait")
+        if not os.path.exists(model_path):
+            os.mkdir(model_path)
+
+        model_config_path = os.path.join(current_directory, 'LivePortrait', 'config', 'models.yaml')
+        model_config = yaml.safe_load(open(model_config_path, 'r'))
 
-    def detect_face(self, image_rgb):
+        appearance_feature_extractor = self.load_model(model_config, 'appearance_feature_extractor')
+        motion_extractor = self.load_model(model_config, 'motion_extractor')
+        warping_module = self.load_model(model_config, 'warping_module')
+        spade_generator = self.load_model(model_config, 'spade_generator')
+        stitching_retargeting_module = self.load_model(model_config, 'stitching_retargeting_module')
 
-        crop_factor = 1.7
-        bbox_drop_size = 10
+        self.pipeline = LivePortraitWrapper(InferenceConfig(), appearance_feature_extractor, motion_extractor, warping_module, spade_generator, stitching_retargeting_module)
 
-        if self.bbox_model == None:
-            bbox_model_path = os.path.join(get_model_dir("ultralytics"), "face_yolov8n.pt")
-            self.bbox_model = YOLO(bbox_model_path)
+    def get_detect_model(self):
+        if self.detect_model == None:
+            model_dir = get_model_dir("ultralytics")
+            if not os.path.exists(model_dir): os.mkdir(model_dir)
+            model_path = os.path.join(model_dir, "face_yolov8n.pt")
+            if not os.path.exists(model_path):
+                self.download_model(model_path, "https://huggingface.co/Bingsu/adetailer/resolve/main/face_yolov8n.pt")
+            self.detect_model = YOLO(model_path)
 
-        pred = self.bbox_model(image_rgb, conf=0.7, device="")
-        bboxes = pred[0].boxes.xyxy.cpu().numpy()
+        return self.detect_model
 
+    def get_face_bboxes(self, image_rgb):
+        detect_model = self.get_detect_model()
+        pred = detect_model(image_rgb, conf=0.7, device="")
+        return pred[0].boxes.xyxy.cpu().numpy()
+
+    def detect_face(self, image_rgb, crop_factor, sort = True):
+        bboxes = self.get_face_bboxes(image_rgb)
         w, h = get_rgb_size(image_rgb)
 
-        # for x, label in zip(segmasks, detected_results[0]):
+        print(f"w, h:{w, h}")
+
+        cx = w / 2
+        min_diff = w
+        best_box = None
         for x1, y1, x2, y2 in bboxes:
             bbox_w = x2 - x1
-            bbox_h = y2 - y1
+            if bbox_w < 30: continue
+            diff = abs(cx - (x1 + bbox_w / 2))
+            if diff < min_diff:
+                best_box = [x1, y1, x2, y2]
+                print(f"diff, min_diff, best_box:{diff, min_diff, best_box}")
+                min_diff = diff
 
-            crop_w = bbox_w * crop_factor
-            crop_h = bbox_h * crop_factor
+        if best_box == None:
+            print("Failed to detect face!!")
+            return [0, 0, w, h]
 
-            crop_w = max(crop_h, crop_w)
-            crop_h = crop_w
+        x1, y1, x2, y2 = best_box
 
-            kernel_x = x1 + bbox_w / 2
-            kernel_y = y1 + bbox_h / 2
+        #for x1, y1, x2, y2 in bboxes:
+        bbox_w = x2 - x1
+        bbox_h = y2 - y1
 
-            new_x1, new_x2, crop_w = calc_crop_limit(kernel_x, w, crop_w)
+        crop_w = bbox_w * crop_factor
+        crop_h = bbox_h * crop_factor
 
-            if crop_w < crop_h:
-                crop_h = crop_w
+        crop_w = max(crop_h, crop_w)
+        crop_h = crop_w
 
-            new_y1, new_y2, crop_h = calc_crop_limit(kernel_y, h, crop_h)
+        kernel_x = int(x1 + bbox_w / 2)
+        kernel_y = int(y1 + bbox_h / 2)
 
-            if crop_h < crop_w:
-                crop_w = crop_h
-                new_x1, new_x2, crop_w = calc_crop_limit(kernel_x, w, crop_w)
+        new_x1 = int(kernel_x - crop_w / 2)
+        new_x2 = int(kernel_x + crop_w / 2)
+        new_y1 = int(kernel_y - crop_h / 2)
+        new_y2 = int(kernel_y + crop_h / 2)
 
+        if not sort:
             return [int(new_x1), int(new_y1), int(new_x2), int(new_y2)]
 
-        print("Failed to detect face!!")
-        return [0, 0, w, h]
-
-    def crop_face(self, rgb_img):
-        region = self.detect_face(rgb_img)
-        face_image = rgb_crop(rgb_img, region)
-        return face_image, region
+        if new_x1 < 0:
+            new_x2 -= new_x1
+            new_x1 = 0
+        elif w < new_x2:
+            new_x1 -= (new_x2 - w)
+            new_x2 = w
+            if new_x1 < 0:
+                new_x2 -= new_x1
+                new_x1 = 0
+
+        if new_y1 < 0:
+            new_y2 -= new_y1
+            new_y1 = 0
+        elif h < new_y2:
+            new_y1 -= (new_y2 - h)
+            new_y2 = h
+            if new_y1 < 0:
+                new_y2 -= new_y1
+                new_y1 = 0
+
+        if w < new_x2 and h < new_y2:
+            over_x = new_x2 - w
+            over_y = new_y2 - h
+            over_min = min(over_x, over_y)
+            new_x2 -= over_min
+            new_y2 -= over_min
+
+        return [int(new_x1), int(new_y1), int(new_x2), int(new_y2)]
+
+
+    def calc_face_region(self, square, dsize):
+        region = copy.deepcopy(square)
+        is_changed = False
+        if dsize[0] < region[2]:
+            region[2] = dsize[0]
+            is_changed = True
+        if dsize[1] < region[3]:
+            region[3] = dsize[1]
+            is_changed = True
+
+        return region, is_changed
+
+    def expand_img(self, rgb_img, square):
+        #new_img = rgb_crop(rgb_img, face_region)
+        crop_trans_m = create_transform_matrix(max(-square[0], 0), max(-square[1], 0), 1, 1)
+        new_img = cv2.warpAffine(rgb_img, crop_trans_m, (square[2] - square[0], square[3] - square[1]),
+                                        cv2.INTER_LINEAR)
+        return new_img
 
     def get_pipeline(self):
         if self.pipeline == None:
             print("Load pipeline...")
-            self.pipeline = LivePortraitWrapper(cfg=InferenceConfig())
+            self.load_models()
 
         return self.pipeline
 
@@ -138,7 +327,9 @@ def prepare_src_image(self, img):
         h, w = img.shape[:2]
         input_shape = [256,256]
         if h != input_shape[0] or w != input_shape[1]:
-            x = cv2.resize(img, (input_shape[0], input_shape[1]), interpolation = cv2.INTER_LINEAR)
+            if 256 < h: interpolation = cv2.INTER_AREA
+            else: interpolation = cv2.INTER_LINEAR
+            x = cv2.resize(img, (input_shape[0], input_shape[1]), interpolation = interpolation)
         else:
             x = img.copy()
 
@@ -150,30 +341,46 @@ def prepare_src_image(self, img):
             raise ValueError(f'img ndim should be 3 or 4: {x.ndim}')
         x = np.clip(x, 0, 1)  # clip to 0~1
         x = torch.from_numpy(x).permute(0, 3, 1, 2)  # 1xHxWx3 -> 1x3xHxW
-        x = x.cuda()
+        x = x.to(get_device())
         return x
 
-    def GetMask(self):
+    def GetMaskImg(self):
         if self.mask_img is None:
-            path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "./LivePortrait/src/utils/resources/mask_template.png")
+            path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "./LivePortrait/utils/resources/mask_template.png")
             self.mask_img = cv2.imread(path, cv2.IMREAD_COLOR)
         return self.mask_img
 
-    def prepare_source(self, source_image, is_video = False):
+    def crop_face(self, img_rgb, crop_factor):
+        crop_region = self.detect_face(img_rgb, crop_factor)
+        face_region, is_changed = self.calc_face_region(crop_region, get_rgb_size(img_rgb))
+        face_img = rgb_crop(img_rgb, face_region)
+        if is_changed: face_img = self.expand_img(face_img, crop_region)
+        return face_img
+
+    def prepare_source(self, source_image, crop_factor, is_video = False, tracking = False):
         print("Prepare source...")
         engine = self.get_pipeline()
         source_image_np = (source_image * 255).byte().numpy()
         img_rgb = source_image_np[0]
-        face_img, crop_region = self.crop_face(img_rgb)
-
-        scale = face_img.shape[0] / 512.
-        crop_trans_m = create_transform_matrix(crop_region[0], crop_region[1], scale)
-        mask_ori = cv2.warpAffine(self.GetMask(), crop_trans_m, get_rgb_size(img_rgb), cv2.INTER_LINEAR)
-        mask_ori = mask_ori.astype(np.float32) / 255.
 
         psi_list = []
         for img_rgb in source_image_np:
-            face_img = rgb_crop(img_rgb, crop_region)
+            if tracking or len(psi_list) == 0:
+                crop_region = self.detect_face(img_rgb, crop_factor)
+                face_region, is_changed = self.calc_face_region(crop_region, get_rgb_size(img_rgb))
+
+                s_x = (face_region[2] - face_region[0]) / 512.
+                s_y = (face_region[3] - face_region[1]) / 512.
+                crop_trans_m = create_transform_matrix(crop_region[0], crop_region[1], s_x, s_y)
+                mask_ori = cv2.warpAffine(self.GetMaskImg(), crop_trans_m, get_rgb_size(img_rgb), cv2.INTER_LINEAR)
+                mask_ori = mask_ori.astype(np.float32) / 255.
+
+                if is_changed:
+                    s = (crop_region[2] - crop_region[0]) / 512.
+                    crop_trans_m = create_transform_matrix(crop_region[0], crop_region[1], s, s)
+
+            face_img = rgb_crop(img_rgb, face_region)
+            if is_changed: face_img = self.expand_img(face_img, crop_region)
             i_s = self.prepare_src_image(face_img)
             x_s_info = engine.get_kp_info(i_s)
             f_s_user = engine.extract_feature_3d(i_s)
@@ -192,9 +399,8 @@ def prepare_driving_video(self, face_images):
 
         out_list = []
         for f_img in f_img_np:
-            i_d = pipeline.prepare_source(f_img)
+            i_d = self.prepare_src_image(f_img)
             d_info = pipeline.get_kp_info(i_d)
-            #out_list.append((d_info, get_rotation_matrix(d_info['pitch'], d_info['yaw'], d_info['roll'])))
             out_list.append(d_info)
 
         return out_list
@@ -249,6 +455,8 @@ def calc_fe(_, x_d_new, eyes, eyebrow, wink, pupil_x, pupil_y, mouth, eee, woo,
         x_d_new[0, 13, 1] += eyes * 0.0003
         x_d_new[0, 15, 1] += eyes * -0.001
         x_d_new[0, 16, 1] += eyes * 0.0003
+        x_d_new[0, 1, 1] += eyes * -0.00025
+        x_d_new[0, 2, 1] += eyes * 0.00025
 
 
         if 0 < eyebrow:
@@ -277,7 +485,7 @@ def __init__(self, erst = None, es = None):
             self.s = erst[2]
             self.t = erst[3]
         else:
-            self.e = torch.from_numpy(np.zeros((1, 21, 3))).float().to(device='cuda')
+            self.e = torch.from_numpy(np.zeros((1, 21, 3))).float().to(get_device())
             self.r = torch.Tensor([0, 0, 0])
             self.s = 0
             self.t = 0
@@ -315,7 +523,10 @@ def wrapper_fn(*args, **kwargs):
     return wrapper_fn
 
 
-exp_data_dir = os.path.join(current_directory, "exp_data")
+#exp_data_dir = os.path.join(current_directory, "exp_data")
+exp_data_dir = os.path.join(folder_paths.output_directory, "exp_data")
+if os.path.isdir(exp_data_dir) == False:
+    os.mkdir(exp_data_dir)
 class SaveExpData:
     @classmethod
     def INPUT_TYPES(s):
@@ -328,7 +539,7 @@ def INPUT_TYPES(s):
     RETURN_TYPES = ("STRING",)
     RETURN_NAMES = ("file_name",)
     FUNCTION = "run"
-    CATEGORY = "파워집돌이"
+    CATEGORY = "AdvancedLivePortrait"
     OUTPUT_NODE = True
 
     def run(self, file_name, save_exp:ExpressionSet=None):
@@ -353,7 +564,7 @@ def INPUT_TYPES(s):
     RETURN_TYPES = ("EXP_DATA",)
     RETURN_NAMES = ("exp",)
     FUNCTION = "run"
-    CATEGORY = "파워집돌이"
+    CATEGORY = "AdvancedLivePortrait"
 
     def run(self, file_name, ratio):
         # es = ExpressionSet()
@@ -384,25 +595,20 @@ def INPUT_TYPES(s):
     RETURN_TYPES = ("EXP_DATA",)
     RETURN_NAMES = ("exp",)
     FUNCTION = "run"
-    CATEGORY = "파워집돌이"
+    CATEGORY = "AdvancedLivePortrait"
 
     def run(self, code1, value1, code2, value2, code3, value3, code4, value4, code5, value5, add_exp=None):
-        #print(f"type(None):{type(None)}")
-        #if type(add_exp) == type(None):
         if add_exp == None:
             es = ExpressionSet()
-            log(f"exp11:{es.exp[0,1,1]}")
         else:
             es = ExpressionSet(es = add_exp)
-            if id(es.exp) == id(add_exp.exp):
-                log("id(es.exp) == id(add_exp.exp) is True")
 
         codes = [code1, code2, code3, code4, code5]
         values = [value1, value2, value3, value4, value5]
         for i in range(5):
             idx = int(codes[i] / 10)
             r = codes[i] % 10
-            es.exp[0, idx, r] += values[i] * 0.001
+            es.e[0, idx, r] += values[i] * 0.001
 
         return (es,)
 
@@ -418,7 +624,7 @@ def INPUT_TYPES(s):
     RETURN_TYPES = ("EXP_DATA",)
     RETURN_NAMES = ("exp",)
     FUNCTION = "run"
-    CATEGORY = "파워집돌이"
+    CATEGORY = "AdvancedLivePortrait"
     OUTPUT_NODE = True
 
     def run(self, cut_noise, exp = None):
@@ -440,11 +646,17 @@ def __init__(self, es, change, keep):
         self.es:ExpressionSet = es
         self.change = change
         self.keep = keep
+
+crop_factor_default = 1.7
+crop_factor_min = 1.5
+crop_factor_max = 2.5
+
 class AdvancedLivePortrait:
-    def __init__(s):
-        s.src_images = None
-        s.driving_images = None
-        s.pbar = comfy.utils.ProgressBar(1)
+    def __init__(self):
+        self.src_images = None
+        self.driving_images = None
+        self.pbar = comfy.utils.ProgressBar(1)
+        self.crop_factor = None
 
     @classmethod
     def INPUT_TYPES(s):
@@ -453,7 +665,11 @@ def INPUT_TYPES(s):
             "required": {
                 "retargeting_eyes": ("FLOAT", {"default": 0, "min": 0, "max": 1, "step": 0.01}),
                 "retargeting_mouth": ("FLOAT", {"default": 0, "min": 0, "max": 1, "step": 0.01}),
+                "crop_factor": ("FLOAT", {"default": crop_factor_default,
+                                          "min": crop_factor_min, "max": crop_factor_max, "step": 0.1}),
                 "turn_on": ("BOOLEAN", {"default": True}),
+                "tracking_src_vid": ("BOOLEAN", {"default": False}),
+                "animate_without_vid": ("BOOLEAN", {"default": False}),
                 "command": ("STRING", {"multiline": True, "default": ""}),
             },
             "optional": {
@@ -467,7 +683,7 @@ def INPUT_TYPES(s):
     RETURN_NAMES = ("images",)
     FUNCTION = "run"
     OUTPUT_NODE = True
-    CATEGORY = "파워집돌이"
+    CATEGORY = "AdvancedLivePortrait"
 
     # INPUT_IS_LIST = False
     # OUTPUT_IS_LIST = (False,)
@@ -488,7 +704,6 @@ def parsing_command(self, command, motoin_link):
             if line == '': continue
             try:
                 cmds = line.split('=')
-                #assert len(cmds) == 2, f"(파워집돌이) 명령어오류 {i}번줄: {line}: '=' 기호가 1개 들어가야 합니다"
                 idx = int(cmds[0])
                 if idx == 0: es = ExpressionSet()
                 else: es = ExpressionSet(es = motoin_link[idx])
@@ -496,8 +711,7 @@ def parsing_command(self, command, motoin_link):
                 change = int(cmds[0])
                 keep = int(cmds[1])
             except:
-                #log(f"(파워집돌이) 명령어오류 {i}번줄: {line}")
-                assert False, f"(파워집돌이) 명령어오류 {i}번줄: {line}"
+                assert False, f"(AdvancedLivePortrait) Command Err Line {i}: {line}"
 
 
                 return None, None
@@ -509,7 +723,7 @@ def parsing_command(self, command, motoin_link):
         return cmd_list, total_length
 
 
-    def run(self, retargeting_eyes, retargeting_mouth, turn_on, command,
+    def run(self, retargeting_eyes, retargeting_mouth, turn_on, tracking_src_vid, animate_without_vid, command, crop_factor,
             src_images=None, driving_images=None, motion_link=None):
         if turn_on == False: return (None,None)
         src_length = 1
@@ -521,12 +735,13 @@ def run(self, retargeting_eyes, retargeting_mouth, turn_on, command,
 
         if src_images != None:
             src_length = len(src_images)
-            if id(src_images) != id(self.src_images):
+            if id(src_images) != id(self.src_images) or self.crop_factor != crop_factor:
+                self.crop_factor = crop_factor
                 self.src_images = src_images
                 if 1 < src_length:
-                    self.psi_list = g_engine.prepare_source(src_images, True)
+                    self.psi_list = g_engine.prepare_source(src_images, crop_factor, True, tracking_src_vid)
                 else:
-                    self.psi_list = [g_engine.prepare_source(src_images)]
+                    self.psi_list = [g_engine.prepare_source(src_images, crop_factor)]
 
 
         cmd_list, cmd_length = self.parsing_command(command, motion_link)
@@ -540,9 +755,11 @@ def run(self, retargeting_eyes, retargeting_mouth, turn_on, command,
                 self.driving_values = g_engine.prepare_driving_video(driving_images)
             driving_length = len(self.driving_values)
 
-        #total_length = max(driving_length, cmd_length, src_length)
         total_length = max(driving_length, src_length)
 
+        if animate_without_vid:
+            total_length = max(total_length, cmd_length)
+
         c_i_es = ExpressionSet()
         c_o_es = ExpressionSet()
         d_0_es = None
@@ -561,7 +778,6 @@ def run(self, retargeting_eyes, retargeting_mouth, turn_on, command,
 
             if i < cmd_length:
                 cmd = cmd_list[cmd_idx]
-                #cmd = Command()#지울거
                 if 0 < cmd.change:
                     cmd.change -= 1
                     c_i_es.add(cmd.es)
@@ -586,11 +802,10 @@ def run(self, retargeting_eyes, retargeting_mouth, turn_on, command,
 
                 if d_0_es is None:
                     d_0_es = ExpressionSet(erst = (d_i_info['exp'], d_i_r, d_i_info['scale'], d_i_info['t']))
-                    #d_i_es = d_0_es
+
                     retargeting(s_es.e, d_0_es.e, retargeting_eyes, (11, 13, 15, 16))
                     retargeting(s_es.e, d_0_es.e, retargeting_mouth, (14, 17, 19, 20))
 
-                #r_new = (r_d_i @ d_0_es.r.permute(0, 2, 1)) @ r_new
                 new_es.e += d_i_info['exp'] - d_0_es.e
                 new_es.r += d_i_r - d_0_es.r
                 new_es.t += d_i_info['t'] - d_0_es.t
@@ -619,6 +834,7 @@ class ExpressionEditor:
     def __init__(self):
         self.sample_image = None
         self.src_image = None
+        self.crop_factor = None
 
     @classmethod
     def INPUT_TYPES(s):
@@ -642,7 +858,10 @@ def INPUT_TYPES(s):
                 "smile": ("FLOAT", {"default": 0, "min": -0.3, "max": 1.3, "step": 0.01, "display": display}),
 
                 "src_ratio": ("FLOAT", {"default": 1, "min": 0, "max": 1, "step": 0.01, "display": display}),
-                "sample_ratio": ("FLOAT", {"default": 1, "min": 0, "max": 1, "step": 0.01, "display": display}),
+                "sample_ratio": ("FLOAT", {"default": 1, "min": -0.2, "max": 1.2, "step": 0.01, "display": display}),
+                "sample_parts": (["OnlyExpression", "OnlyRotation", "OnlyMouth", "OnlyEyes", "All"],),
+                "crop_factor": ("FLOAT", {"default": crop_factor_default,
+                                          "min": crop_factor_min, "max": crop_factor_max, "step": 0.1}),
             },
 
             "optional": {"src_image": ("IMAGE",), "motion_link": ("EDITOR_LINK",),
@@ -657,13 +876,13 @@ def INPUT_TYPES(s):
 
     OUTPUT_NODE = True
 
-    CATEGORY = "파워집돌이"
+    CATEGORY = "AdvancedLivePortrait"
 
     # INPUT_IS_LIST = False
     # OUTPUT_IS_LIST = (False,)
 
     def run(self, rotate_pitch, rotate_yaw, rotate_roll, blink, eyebrow, wink, pupil_x, pupil_y, aaa, eee, woo, smile,
-            src_ratio, sample_ratio, src_image=None, sample_image=None, motion_link=None, add_exp=None):
+            src_ratio, sample_ratio, sample_parts, crop_factor, src_image=None, sample_image=None, motion_link=None, add_exp=None):
         rotate_yaw = -rotate_yaw
 
         new_editor_link = None
@@ -671,8 +890,9 @@ def run(self, rotate_pitch, rotate_yaw, rotate_roll, blink, eyebrow, wink, pupil
             self.psi = motion_link[0]
             new_editor_link = motion_link.copy()
         elif src_image != None:
-            if id(src_image) != id(self.src_image):
-                self.psi = g_engine.prepare_source(src_image)
+            if id(src_image) != id(self.src_image) or self.crop_factor != crop_factor:
+                self.crop_factor = crop_factor
+                self.psi = g_engine.prepare_source(src_image, crop_factor)
                 self.src_image = src_image
             new_editor_link = []
             new_editor_link.append(self.psi)
@@ -694,14 +914,23 @@ def run(self, rotate_pitch, rotate_yaw, rotate_roll, blink, eyebrow, wink, pupil
             if id(self.sample_image) != id(sample_image):
                 self.sample_image = sample_image
                 d_image_np = (sample_image * 255).byte().numpy()
-                d_face, _ = g_engine.crop_face(d_image_np[0])
-                i_d = pipeline.prepare_source(d_face)
+                d_face = g_engine.crop_face(d_image_np[0], 1.7)
+                i_d = g_engine.prepare_src_image(d_face)
                 self.d_info = pipeline.get_kp_info(i_d)
                 self.d_info['exp'][0, 5, 0] = 0
                 self.d_info['exp'][0, 5, 1] = 0
 
-            # delta_new += s_exp * (1 - sample_ratio) + self.d_info['exp'] * sample_ratio
-            es.e += self.d_info['exp'] * sample_ratio
+            # "OnlyExpression", "OnlyRotation", "OnlyMouth", "OnlyEyes", "All"
+            if sample_parts == "OnlyExpression" or sample_parts == "All":
+                es.e += self.d_info['exp'] * sample_ratio
+            if sample_parts == "OnlyRotation" or sample_parts == "All":
+                rotate_pitch += self.d_info['pitch'] * sample_ratio
+                rotate_yaw += self.d_info['yaw'] * sample_ratio
+                rotate_roll += self.d_info['roll'] * sample_ratio
+            elif sample_parts == "OnlyMouth":
+                retargeting(es.e, self.d_info['exp'], sample_ratio, (14, 17, 19, 20))
+            elif sample_parts == "OnlyEyes":
+                retargeting(es.e, self.d_info['exp'], sample_ratio, (1, 2, 11, 13, 15, 16))
 
         es.r = g_engine.calc_fe(es.e, blink, eyebrow, wink, pupil_x, pupil_y, aaa, eee, woo, smile,
                                   rotate_pitch, rotate_yaw, rotate_roll)
@@ -723,7 +952,7 @@ def run(self, rotate_pitch, rotate_yaw, rotate_roll, blink, eyebrow, wink, pupil
 
         out_img = pil2tensor(out)
 
-        filename = "fe_edit_preview.png"
+        filename = g_engine.get_temp_img_name() #"fe_edit_preview.png"
         folder_paths.get_save_image_path(filename, folder_paths.get_temp_directory())
         img = Image.fromarray(crop_out)
         img.save(os.path.join(folder_paths.get_temp_directory(), filename), compress_level=1)
@@ -734,41 +963,307 @@ def run(self, rotate_pitch, rotate_yaw, rotate_roll, blink, eyebrow, wink, pupil
 
         return {"ui": {"images": results}, "result": (out_img, new_editor_link, es)}
 
-class TestNode:
 
-    def __init__(s):
-        s.pbar = comfy.utils.ProgressBar(1)
+class FlexExpressionEditor(ExpressionEditor):
+    """
+    Enhanced version of ExpressionEditor that adds support for feature-based parameter modulation.
+    Allows for dynamic modification of facial expressions based on input features (e.g. audio, motion, etc.).
+    
+    TODO: Consider refactoring these methods into the base ExpressionEditor class:
+    - generate_preview_image
+    - process_sample_image
+    - create_expression_set
+    
+    These methods have been implemented here to avoid modifying the original ExpressionEditor
+    until the author can review the changes.
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        base_inputs = super().INPUT_TYPES()
+        base_inputs["required"].update({
+            "constrain_min_max": ("BOOLEAN", {"default": True})
+        })
+        # Rename motion_link to flex_motion_link in optional inputs
+        base_inputs["optional"]["flex_motion_link"] = base_inputs["optional"].pop("motion_link")
+        base_inputs["optional"].update({
+            "feature": ("FEATURE",),
+            "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 2.0, "step": 0.01}),
+            "feature_threshold": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01}),
+            "feature_param": (cls.get_modifiable_params(), {"default": cls.get_modifiable_params()[0]}),
+            "feature_mode": (["relative", "absolute"], {"default": "absolute"}),
+             
+        })
+        
+        return base_inputs
+
+    RETURN_TYPES = ("IMAGE", "EDITOR_LINK", "EXP_DATA", "STRING")
+    RETURN_NAMES = ("image", "flex_motion_link", "save_exp", "command")
+    FUNCTION = "run"
+    OUTPUT_NODE = True
+    CATEGORY = "AdvancedLivePortrait"
 
     @classmethod
-    def INPUT_TYPES(s):
-        return {"required": {
-            #"images": ("IMAGE",),
-            #"test_value": ("INT", {"default": 1, "min": 1}),
-            "command": ("STRING", {"multiline": True, "default": ""}),
-        },
+    def get_modifiable_params(cls):
+        return ["rotate_pitch", "rotate_yaw", "rotate_roll", "blink", "eyebrow", "wink", "pupil_x", "pupil_y",
+                "aaa", "eee", "woo", "smile", "None"]
+
+    def modulate_param(self, base_value, feature_value, strength, mode="relative", param_name=None, constrain_min_max=True):
+        """
+        Helper method to modulate a parameter based on feature value.
+        
+        Args:
+            base_value: Original parameter value
+            feature_value: Feature value to modulate with
+            strength: Modulation strength
+            mode: Either "relative" or "absolute"
+            param_name: Name of the parameter being modulated (for min/max constraints)
+            constrain_min_max: Whether to constrain the output to the parameter's min/max values
+            
+        Returns:
+            Modulated parameter value
+        """
+        if mode == "relative":
+            modulated_value = base_value * (1 + feature_value * strength)
+        else:  # absolute
+            modulated_value = base_value * feature_value * strength
+
+        if constrain_min_max and param_name:
+            # Get parameter constraints from INPUT_TYPES
+            param_info = self.INPUT_TYPES()["required"].get(param_name)
+            if param_info and isinstance(param_info[1], dict):
+                param_min = param_info[1].get("min")
+                param_max = param_info[1].get("max")
+                if param_min is not None:
+                    modulated_value = max(param_min, modulated_value)
+                if param_max is not None:
+                    modulated_value = min(param_max, modulated_value)
+
+        return modulated_value
+
+    #TODO: base class
+    def generate_preview_image(self, psi, preview_es):
+        """
+        Generate preview image from the expression set and PSI data.
+        
+        Args:
+            psi: PSI data containing source image information
+            preview_es: Expression set to apply for preview
+            
+        Returns:
+            tuple: (output_image_tensor, results_dict)
+        """
+        s_info = psi.x_s_info
+        pipeline = g_engine.get_pipeline()
+        
+        new_rotate = get_rotation_matrix(s_info['pitch'] + preview_es.r[0], 
+                                       s_info['yaw'] + preview_es.r[1], 
+                                       s_info['roll'] + preview_es.r[2])
+        x_d_new = (s_info['scale'] * (1 + preview_es.s)) * ((s_info['kp'] + preview_es.e) @ new_rotate) + s_info['t']
+
+        x_d_new = pipeline.stitching(psi.x_s_user, x_d_new)
+        crop_out = pipeline.warp_decode(psi.f_s_user, psi.x_s_user, x_d_new)
+        crop_out = pipeline.parse_output(crop_out['out'])[0]
+        crop_with_fullsize = cv2.warpAffine(crop_out, psi.crop_trans_m, get_rgb_size(psi.src_rgb), cv2.INTER_LINEAR)
+        out = np.clip(psi.mask_ori * crop_with_fullsize + (1 - psi.mask_ori) * psi.src_rgb, 0, 255).astype(np.uint8)
+        out_img = pil2tensor(out)
+
+        filename = g_engine.get_temp_img_name()
+        folder_paths.get_save_image_path(filename, folder_paths.get_temp_directory())
+        img = Image.fromarray(crop_out)
+        img.save(os.path.join(folder_paths.get_temp_directory(), filename), compress_level=1)
+        results = [{"filename": filename, "type": "temp"}]
+        
+        return out_img, results
+
+    #TODO: base class
+    def initialize_psi(self, src_image, motion_link, crop_factor):
+        """Initialize PSI data from source image or motion link"""
+        new_editor_link = []
+        
+        if motion_link is not None:
+            self.psi = motion_link[0]
+            new_editor_link.append(self.psi)
+        elif src_image is not None:
+            if id(src_image) != id(self.src_image) or self.crop_factor != crop_factor:
+                self.crop_factor = crop_factor
+                self.psi = g_engine.prepare_source(src_image, crop_factor)
+                self.src_image = src_image
+            new_editor_link.append(self.psi)
+        else:
+            return None
+            
+        return new_editor_link
+
+    #TODO: base class   
+    def process_sample_image(self, sample_image, sample_parts, sample_ratio, es, rotate_pitch, rotate_yaw, rotate_roll):
+        """Process sample image and apply transformations"""
+        pipeline = g_engine.get_pipeline()
+        
+        if id(self.sample_image) != id(sample_image):
+            self.sample_image = sample_image
+            d_image_np = (sample_image * 255).byte().numpy()
+            d_face = g_engine.crop_face(d_image_np[0], 1.7)
+            i_d = g_engine.prepare_src_image(d_face)
+            self.d_info = pipeline.get_kp_info(i_d)
+            self.d_info['exp'][0, 5, 0] = 0
+            self.d_info['exp'][0, 5, 1] = 0
+
+        if sample_parts == "OnlyExpression" or sample_parts == "All":
+            es.e += self.d_info['exp'] * sample_ratio
+        if sample_parts == "OnlyRotation" or sample_parts == "All":
+            rotate_pitch += self.d_info['pitch'] * sample_ratio
+            rotate_yaw += self.d_info['yaw'] * sample_ratio
+            rotate_roll += self.d_info['roll'] * sample_ratio
+        elif sample_parts == "OnlyMouth":
+            retargeting(es.e, self.d_info['exp'], sample_ratio, (14, 17, 19, 20))
+        elif sample_parts == "OnlyEyes":
+            retargeting(es.e, self.d_info['exp'], sample_ratio, (1, 2, 11, 13, 15, 16))
+            
+        return rotate_pitch, rotate_yaw, rotate_roll
+
+    def run(self, rotate_pitch, rotate_yaw, rotate_roll, blink, eyebrow, wink, pupil_x, pupil_y, aaa, eee, woo, smile,
+            src_ratio, sample_ratio, sample_parts, crop_factor, constrain_min_max, src_image=None, sample_image=None, 
+            flex_motion_link=None, add_exp=None, feature=None, strength=1.0, feature_threshold=0.0, 
+            feature_param="None", feature_mode="relative"):
+        rotate_yaw = -rotate_yaw
+
+        # Initialize PSI data
+        new_editor_link = self.initialize_psi(src_image, flex_motion_link, crop_factor)
+        if new_editor_link is None:
+            return (None, None, None, None)
+
+        pipeline = g_engine.get_pipeline()
+        psi = self.psi
+        s_info = psi.x_s_info
+
+        es = ExpressionSet()
+
+        # Process sample image if provided
+        if sample_image is not None:
+            rotate_pitch, rotate_yaw, rotate_roll = self.process_sample_image(
+                sample_image, sample_parts, sample_ratio, es, rotate_pitch, rotate_yaw, rotate_roll
+            )
+
+        # Add any additional expression data
+        if add_exp is not None:
+            es.add(add_exp)
+
+        # Prepare parameters dictionary
+        params = {
+            'blink': blink,
+            'eyebrow': eyebrow,
+            'wink': wink,
+            'pupil_x': pupil_x,
+            'pupil_y': pupil_y,
+            'aaa': aaa,
+            'eee': eee,
+            'woo': woo,
+            'smile': smile,
+            'rotate_pitch': rotate_pitch,
+            'rotate_yaw': rotate_yaw,
+            'rotate_roll': rotate_roll,
         }
 
-    RETURN_TYPES = ("IMAGE",)
-    RETURN_NAMES = ("images",)
-    FUNCTION = "run"
-    OUTPUT_NODE = True
+        # When calling calc_fe, unpack the parameters in the correct order
+        def apply_params(es, params):
+            return g_engine.calc_fe(
+                es,
+                params['blink'],
+                params['eyebrow'],
+                params['wink'],
+                params['pupil_x'],
+                params['pupil_y'],
+                params['aaa'],
+                params['eee'],
+                params['woo'],
+                params['smile'],
+                params['rotate_pitch'],
+                params['rotate_yaw'],
+                params['rotate_roll']
+            )
+
+        # Check if feature is provided for modulation
+        if (feature is not None) and feature_param != "None" and feature_param in params:
+            total_frames = feature.frame_count
+            feature_values = [feature.get_value_at_frame(i) for i in range(total_frames)]
+        else:
+            # No modulation
+            total_frames = 1
+            if flex_motion_link is not None and len(flex_motion_link) > 1:
+                total_frames = len(flex_motion_link) - 1  # Subtract 1 because first element is psi
+            feature_values = [1.0] * total_frames
+
+        # Generate 'command' string expected by AdvancedLivePortrait node
+        command_lines = []
+        for idx in range(total_frames):
+            # Start with base expression set or previous modifications
+            if flex_motion_link is not None and idx + 1 < len(flex_motion_link):
+                es_frame = ExpressionSet(es=flex_motion_link[idx + 1])
+                if add_exp is not None:
+                    es_frame.add(add_exp)
+            else:
+                es_frame = ExpressionSet(es=es)
+
+            # Apply feature modulation if available
+            frame_params = params.copy()
+            if (feature is not None) and feature_param != "None" and feature_param in params:
+                feature_value = feature_values[idx]
+                if abs(feature_value) >= feature_threshold:
+                    frame_params[feature_param] = self.modulate_param(
+                        params[feature_param], 
+                        feature_value, 
+                        strength, 
+                        feature_mode,
+                        feature_param,
+                        constrain_min_max
+                    )
+
+            # Calculate the new rotations and add them to existing ones
+            new_rotations = apply_params(es_frame.e, frame_params)
+            if flex_motion_link is not None and idx + 1 < len(flex_motion_link):
+                es_frame.r += new_rotations  # Add to existing rotations
+            else:
+                es_frame.r = new_rotations  # Set new rotations
+                
+            new_editor_link.append(es_frame)
+
+            # Create command line
+            command_lines.append(f"{idx}=1:0")
+
+        command = '\n'.join(command_lines)
+
+        # Apply the expressions for preview image (using first frame)
+        preview_es = new_editor_link[1] if len(new_editor_link) > 1 else es
+        out_img, results = self.generate_preview_image(psi, preview_es)
+
+        # Find the frame with maximum feature value and use its expression
+        if feature is not None and feature_param != "None" and len(new_editor_link) > 1:
+            max_idx = feature_values.index(max(feature_values))
+            save_exp = new_editor_link[max_idx + 1]  # +1 because first element is psi
+        else:
+            save_exp = es
+
+        return {"ui": {"images": results}, "result": (out_img, new_editor_link, save_exp, command)}
+
+
 
-    def run(self, command):
-        self.parsing_command(command)
 
-        return (None,)
 
 NODE_CLASS_MAPPINGS = {
     "AdvancedLivePortrait": AdvancedLivePortrait,
     "ExpressionEditor": ExpressionEditor,
-    "ExpData": ExpData,
     "LoadExpData": LoadExpData,
     "SaveExpData": SaveExpData,
+    "ExpData": ExpData,
     "PrintExpData:": PrintExpData,
-    #"TestNode": TestNode,
+    "FlexExpressionEditor": FlexExpressionEditor,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
-    "AdvancedLivePortrait": "Advanced Live Portrait (파워집돌이)",
-    "ExpressionEditor": "Expression Editor (파워집돌이)",
+    "AdvancedLivePortrait": "Advanced Live Portrait (PHM)",
+    "ExpressionEditor": "Expression Editor (PHM)",
+    "LoadExpData": "Load Exp Data (PHM)",
+    "SaveExpData": "Save Exp Data (PHM)",
+    "FlexExpressionEditor": "Flex Expression Editor (RyanOnTheInside)",
 }
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..5b3c401
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,15 @@
+[project]
+name = "comfyui-advancedliveportrait"
+description = "AdvancedLivePortrait with Facial expression editor"
+version = "1.0.0"
+license = {file = "LICENSE"}
+dependencies = ["numpy>=1.26.4", "opencv-python-headless", "imageio-ffmpeg>=0.5.1", "lmdb>=1.4.1", "timm>=1.0.7", "rich>=13.7.1", "albumentations>=1.4.10", "ultralytics", "tyro==0.8.5", "dill"]
+
+[project.urls]
+Repository = "https://github.com/PowerHouseMan/ComfyUI-AdvancedLivePortrait"
+#  Used by Comfy Registry https://comfyregistry.org
+
+[tool.comfy]
+PublisherId = "starmapking"
+DisplayName = "ComfyUI-AdvancedLivePortrait"
+Icon = ""
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new file mode 100644
index 0000000..966aa37
Binary files /dev/null and b/sample/original_sample_asset/driving/d9.mp4 differ
diff --git a/sample/original_sample_asset/source/s0.jpg b/sample/original_sample_asset/source/s0.jpg
new file mode 100644
index 0000000..ef44c59
Binary files /dev/null and b/sample/original_sample_asset/source/s0.jpg differ
diff --git a/sample/original_sample_asset/source/s1.jpg b/sample/original_sample_asset/source/s1.jpg
new file mode 100644
index 0000000..ebacda3
Binary files /dev/null and b/sample/original_sample_asset/source/s1.jpg differ
diff --git a/sample/original_sample_asset/source/s10.jpg b/sample/original_sample_asset/source/s10.jpg
new file mode 100644
index 0000000..ee9616b
Binary files /dev/null and b/sample/original_sample_asset/source/s10.jpg differ
diff --git a/sample/original_sample_asset/source/s2.jpg b/sample/original_sample_asset/source/s2.jpg
new file mode 100644
index 0000000..e851bd2
Binary files /dev/null and b/sample/original_sample_asset/source/s2.jpg differ
diff --git a/sample/original_sample_asset/source/s3.jpg b/sample/original_sample_asset/source/s3.jpg
new file mode 100644
index 0000000..9f3ba2a
Binary files /dev/null and b/sample/original_sample_asset/source/s3.jpg differ
diff --git a/sample/original_sample_asset/source/s4.jpg b/sample/original_sample_asset/source/s4.jpg
new file mode 100644
index 0000000..17f611b
Binary files /dev/null and b/sample/original_sample_asset/source/s4.jpg differ
diff --git a/sample/original_sample_asset/source/s5.jpg b/sample/original_sample_asset/source/s5.jpg
new file mode 100644
index 0000000..9abad7e
Binary files /dev/null and b/sample/original_sample_asset/source/s5.jpg differ
diff --git a/sample/original_sample_asset/source/s6.jpg b/sample/original_sample_asset/source/s6.jpg
new file mode 100644
index 0000000..91c13d5
Binary files /dev/null and b/sample/original_sample_asset/source/s6.jpg differ
diff --git a/sample/original_sample_asset/source/s7.jpg b/sample/original_sample_asset/source/s7.jpg
new file mode 100644
index 0000000..cf96f2d
Binary files /dev/null and b/sample/original_sample_asset/source/s7.jpg differ
diff --git a/sample/original_sample_asset/source/s8.jpg b/sample/original_sample_asset/source/s8.jpg
new file mode 100644
index 0000000..b415ed1
Binary files /dev/null and b/sample/original_sample_asset/source/s8.jpg differ
diff --git a/sample/original_sample_asset/source/s9.jpg b/sample/original_sample_asset/source/s9.jpg
new file mode 100644
index 0000000..3ef7251
Binary files /dev/null and b/sample/original_sample_asset/source/s9.jpg differ
diff --git a/sample/royalty_free.mp3 b/sample/royalty_free.mp3
new file mode 100644
index 0000000..8ae727f
Binary files /dev/null and b/sample/royalty_free.mp3 differ
diff --git "a/exp_data/\354\236\205\354\210\240\353\202\264\353\260\200\352\270\260.exp" b/sample/sample_exp_data.exp
similarity index 100%
rename from "exp_data/\354\236\205\354\210\240\353\202\264\353\260\200\352\270\260.exp"
rename to sample/sample_exp_data.exp
diff --git a/sample/workflow_advanced_screenshot.png b/sample/workflow_advanced_screenshot.png
new file mode 100644
index 0000000..755b0cb
Binary files /dev/null and b/sample/workflow_advanced_screenshot.png differ
diff --git a/sample/workflow_basic_screenshot.png b/sample/workflow_basic_screenshot.png
new file mode 100644
index 0000000..6894fa2
Binary files /dev/null and b/sample/workflow_basic_screenshot.png differ
diff --git a/sample/workflows/Advanced_Animate_without_vid.json b/sample/workflows/Advanced_Animate_without_vid.json
new file mode 100644
index 0000000..e0ff6cb
--- /dev/null
+++ b/sample/workflows/Advanced_Animate_without_vid.json
@@ -0,0 +1,359 @@
+{
+  "last_node_id": 18,
+  "last_link_id": 11,
+  "nodes": [
+    {
+      "id": 3,
+      "type": "LoadImage",
+      "pos": [
+        1385,
+        278
+      ],
+      "size": [
+        223.20395091844193,
+        308.6326788490376
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            11
+          ],
+          "slot_index": 0,
+          "shape": 3
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "slot_index": 1,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "source_image.png",
+        "image"
+      ]
+    },
+    {
+      "id": 7,
+      "type": "AdvancedLivePortrait",
+      "pos": [
+        1889,
+        270
+      ],
+      "size": {
+        "0": 235.1999969482422,
+        "1": 523.0364379882812
+      },
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "src_images",
+          "type": "IMAGE",
+          "link": null
+        },
+        {
+          "name": "motion_link",
+          "type": "EDITOR_LINK",
+          "link": 10
+        },
+        {
+          "name": "driving_images",
+          "type": "IMAGE",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "links": [
+            8
+          ],
+          "slot_index": 0,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "AdvancedLivePortrait"
+      },
+      "widgets_values": [
+        0,
+        0,
+        1.7000000000000002,
+        true,
+        false,
+        true,
+        "1 = 5:5\n0 = 3:5"
+      ]
+    },
+    {
+      "id": 10,
+      "type": "VHS_VideoCombine",
+      "pos": [
+        2163,
+        203
+      ],
+      "size": [
+        261.79998779296875,
+        565.7999877929688
+      ],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 8
+        },
+        {
+          "name": "audio",
+          "type": "AUDIO",
+          "link": null
+        },
+        {
+          "name": "meta_batch",
+          "type": "VHS_BatchManager",
+          "link": null
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "Filenames",
+          "type": "VHS_FILENAMES",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "VHS_VideoCombine"
+      },
+      "widgets_values": {
+        "frame_rate": 15,
+        "loop_count": 0,
+        "filename_prefix": "AdvancedLivePortrait",
+        "format": "video/h264-mp4",
+        "pix_fmt": "yuv420p",
+        "crf": 19,
+        "save_metadata": true,
+        "pingpong": false,
+        "save_output": true,
+        "videopreview": {
+          "hidden": false,
+          "paused": false,
+          "params": {
+            "filename": "AdvancedLivePortrait_00021.mp4",
+            "subfolder": "",
+            "type": "output",
+            "format": "video/h264-mp4",
+            "frame_rate": 15
+          }
+        }
+      }
+    },
+    {
+      "id": 15,
+      "type": "ExpressionEditor",
+      "pos": [
+        1643,
+        271
+      ],
+      "size": {
+        "0": 210,
+        "1": 690
+      },
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "src_image",
+          "type": "IMAGE",
+          "link": 11
+        },
+        {
+          "name": "motion_link",
+          "type": "EDITOR_LINK",
+          "link": null
+        },
+        {
+          "name": "sample_image",
+          "type": "IMAGE",
+          "link": null
+        },
+        {
+          "name": "add_exp",
+          "type": "EXP_DATA",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "motion_link",
+          "type": "EDITOR_LINK",
+          "links": [
+            10
+          ],
+          "slot_index": 1,
+          "shape": 3
+        },
+        {
+          "name": "save_exp",
+          "type": "EXP_DATA",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ExpressionEditor"
+      },
+      "widgets_values": [
+        0,
+        0,
+        0,
+        0,
+        0,
+        25,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        1,
+        1,
+        "OnlyExpression",
+        1.7
+      ]
+    },
+    {
+      "id": 16,
+      "type": "Note",
+      "pos": [
+        1892,
+        831
+      ],
+      "size": [
+        483.8180073265835,
+        161.2032413725933
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "properties": {
+        "text": ""
+      },
+      "widgets_values": [
+        "Command Description\n1 = 5:5\n0 = 3:5\n\n[Motion index] = [Changing frame length] : [Length of frames waiting for next motion]\n\nfor example, first line -> 1 = 5:5\nChange over 5 frames with motion 1, and wait for the next motion for 5 frames"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 17,
+      "type": "Note",
+      "pos": [
+        1629,
+        996
+      ],
+      "size": [
+        227.12395091844178,
+        58
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "properties": {
+        "text": ""
+      },
+      "widgets_values": [
+        "motion 1"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 18,
+      "type": "Note",
+      "pos": [
+        1373,
+        625
+      ],
+      "size": {
+        "0": 210,
+        "1": 58
+      },
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "properties": {
+        "text": ""
+      },
+      "widgets_values": [
+        "orginal src : motion 0\n"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    }
+  ],
+  "links": [
+    [
+      8,
+      7,
+      0,
+      10,
+      0,
+      "IMAGE"
+    ],
+    [
+      10,
+      15,
+      1,
+      7,
+      1,
+      "EDITOR_LINK"
+    ],
+    [
+      11,
+      3,
+      0,
+      15,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 1.1000000000000005,
+      "offset": [
+        -841.7371241966999,
+        104.19308875020204
+      ]
+    }
+  },
+  "version": 0.4
+}
\ No newline at end of file
diff --git a/sample/sample2.json b/sample/workflows/Advanced_Inserting_expressions_into_vid.json
similarity index 71%
rename from sample/sample2.json
rename to sample/workflows/Advanced_Inserting_expressions_into_vid.json
index 6c1c152..7810b6f 100644
--- a/sample/sample2.json
+++ b/sample/workflows/Advanced_Inserting_expressions_into_vid.json
@@ -1,12 +1,12 @@
 {
-  "last_node_id": 10,
+  "last_node_id": 14,
   "last_link_id": 8,
   "nodes": [
     {
       "id": 3,
       "type": "LoadImage",
       "pos": [
-        465,
+        736,
         299
       ],
       "size": {
@@ -23,15 +23,15 @@
           "links": [
             3
           ],
-          "shape": 3,
-          "slot_index": 0
+          "slot_index": 0,
+          "shape": 3
         },
         {
           "name": "MASK",
           "type": "MASK",
           "links": null,
-          "shape": 3,
-          "slot_index": 1
+          "slot_index": 1,
+          "shape": 3
         }
       ],
       "properties": {
@@ -46,15 +46,15 @@
       "id": 6,
       "type": "ExpressionEditor",
       "pos": [
-        844,
-        301
+        1085,
+        294
       ],
       "size": {
-        "0": 315,
-        "1": 642
+        "0": 210,
+        "1": 690
       },
       "flags": {},
-      "order": 2,
+      "order": 6,
       "mode": 0,
       "inputs": [
         {
@@ -91,8 +91,8 @@
           "links": [
             5
           ],
-          "shape": 3,
-          "slot_index": 1
+          "slot_index": 1,
+          "shape": 3
         },
         {
           "name": "save_exp",
@@ -118,22 +118,79 @@
         0,
         0,
         1,
-        1
+        1,
+        "OnlyExpression",
+        1.7000000000000002
+      ]
+    },
+    {
+      "id": 7,
+      "type": "AdvancedLivePortrait",
+      "pos": [
+        1845,
+        304
+      ],
+      "size": {
+        "0": 235.1999969482422,
+        "1": 523.0364379882812
+      },
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "src_images",
+          "type": "IMAGE",
+          "link": null
+        },
+        {
+          "name": "motion_link",
+          "type": "EDITOR_LINK",
+          "link": 6
+        },
+        {
+          "name": "driving_images",
+          "type": "IMAGE",
+          "link": 7
+        }
+      ],
+      "outputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "links": [
+            8
+          ],
+          "slot_index": 0,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "AdvancedLivePortrait"
+      },
+      "widgets_values": [
+        0,
+        0,
+        1.7000000000000002,
+        "1 = 1:10\n2 = 5:10\n0 = 2:50\n1 = 2:0",
+        "1 = 1:10\n2 = 5:10\n0 = 2:50\n1 = 2:0",
+        false,
+        "1 = 1:10\n2 = 5:10\n0 = 2:50\n1 = 2:0"
       ]
     },
     {
       "id": 8,
       "type": "ExpressionEditor",
       "pos": [
-        1205,
-        299
+        1342,
+        304
       ],
       "size": {
-        "0": 315,
-        "1": 642
+        "0": 210,
+        "1": 690
       },
       "flags": {},
-      "order": 3,
+      "order": 7,
       "mode": 0,
       "inputs": [
         {
@@ -170,8 +227,8 @@
           "links": [
             6
           ],
-          "shape": 3,
-          "slot_index": 1
+          "slot_index": 1,
+          "shape": 3
         },
         {
           "name": "save_exp",
@@ -197,14 +254,16 @@
         0,
         0,
         1,
-        1
+        1,
+        "OnlyExpression",
+        1.7
       ]
     },
     {
       "id": 9,
       "type": "VHS_LoadVideo",
       "pos": [
-        1551,
+        1570,
         399
       ],
       "size": [
@@ -233,8 +292,8 @@
           "links": [
             7
           ],
-          "shape": 3,
-          "slot_index": 0
+          "slot_index": 0,
+          "shape": 3
         },
         {
           "name": "frame_count",
@@ -283,71 +342,19 @@
         }
       }
     },
-    {
-      "id": 7,
-      "type": "AdvancedLivePortrait",
-      "pos": [
-        1823,
-        301
-      ],
-      "size": [
-        289.7234384275689,
-        513.2487798331999
-      ],
-      "flags": {},
-      "order": 4,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "src_images",
-          "type": "IMAGE",
-          "link": null
-        },
-        {
-          "name": "motion_link",
-          "type": "EDITOR_LINK",
-          "link": 6
-        },
-        {
-          "name": "driving_images",
-          "type": "IMAGE",
-          "link": 7
-        }
-      ],
-      "outputs": [
-        {
-          "name": "images",
-          "type": "IMAGE",
-          "links": [
-            8
-          ],
-          "shape": 3,
-          "slot_index": 0
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "AdvancedLivePortrait"
-      },
-      "widgets_values": [
-        0,
-        0,
-        true,
-        "1 = 1:10\n2 = 5:10\n0 = 2:50\n1 = 2:0"
-      ]
-    },
     {
       "id": 10,
       "type": "VHS_VideoCombine",
       "pos": [
-        2150,
-        307
+        2117,
+        305
       ],
       "size": [
-        261.8000000000002,
-        565.8000000000002
+        261.79998779296875,
+        565.7999877929688
       ],
       "flags": {},
-      "order": 5,
+      "order": 9,
       "mode": 0,
       "inputs": [
         {
@@ -385,25 +392,119 @@
       "widgets_values": {
         "frame_rate": 15,
         "loop_count": 0,
-        "filename_prefix": "AnimateDiff",
+        "filename_prefix": "AdvancedLivePortrait",
         "format": "video/h264-mp4",
         "pix_fmt": "yuv420p",
         "crf": 19,
         "save_metadata": true,
         "pingpong": false,
-        "save_output": false,
+        "save_output": true,
         "videopreview": {
           "hidden": false,
           "paused": false,
           "params": {
-            "filename": "AnimateDiff_00003.mp4",
+            "filename": "AdvancedLivePortrait_00023.mp4",
             "subfolder": "",
-            "type": "temp",
+            "type": "output",
             "format": "video/h264-mp4",
             "frame_rate": 15
           }
         }
       }
+    },
+    {
+      "id": 11,
+      "type": "Note",
+      "pos": [
+        1834,
+        935
+      ],
+      "size": {
+        "0": 539.0599975585938,
+        "1": 184.96444702148438
+      },
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "properties": {
+        "text": ""
+      },
+      "widgets_values": [
+        "Command Description\n1 = 1:10\n2 = 5:10\n0 = 2:50\n1 = 2:0\n\n[Motion index] = [Changing frame length] : [Length of frames waiting for next motion]\n\nfor example, second line -> 2 = 5:10\nChange over 5 frames with motion 2, and wait for the next motion for 10 frames\n\n"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 12,
+      "type": "Note",
+      "pos": [
+        1089,
+        1038
+      ],
+      "size": {
+        "0": 210,
+        "1": 58
+      },
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "properties": {
+        "text": ""
+      },
+      "widgets_values": [
+        "motion1\n"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 13,
+      "type": "Note",
+      "pos": [
+        1341,
+        1041
+      ],
+      "size": {
+        "0": 210,
+        "1": 58
+      },
+      "flags": {
+        "collapsed": false
+      },
+      "order": 3,
+      "mode": 0,
+      "properties": {
+        "text": ""
+      },
+      "widgets_values": [
+        "motion2\n"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 14,
+      "type": "Note",
+      "pos": [
+        776,
+        684
+      ],
+      "size": {
+        "0": 210,
+        "1": 58
+      },
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "properties": {
+        "text": ""
+      },
+      "widgets_values": [
+        "orginal src : motion0\n"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
     }
   ],
   "links": [
@@ -452,10 +553,10 @@
   "config": {},
   "extra": {
     "ds": {
-      "scale": 0.620921323059155,
+      "scale": 1.1000000000000005,
       "offset": [
-        501.16957927340843,
-        325.0434083711576
+        -678.8740830330757,
+        -35.741089089667945
       ]
     }
   },
diff --git a/sample/workflows/Bacis_Extracting_expression_from_photo.json b/sample/workflows/Bacis_Extracting_expression_from_photo.json
new file mode 100644
index 0000000..e22f5c4
--- /dev/null
+++ b/sample/workflows/Bacis_Extracting_expression_from_photo.json
@@ -0,0 +1,241 @@
+{
+  "last_node_id": 33,
+  "last_link_id": 39,
+  "nodes": [
+    {
+      "id": 19,
+      "type": "LoadImage",
+      "pos": [
+        1022,
+        702
+      ],
+      "size": {
+        "0": 220.3717041015625,
+        "1": 314
+      },
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            25
+          ],
+          "slot_index": 0,
+          "shape": 3
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
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+      "widgets_values": [
+        "exp_image.png",
+        "image"
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+      "type": "LoadImage",
+      "pos": [
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+        "0": 210.9286651611328,
+        "1": 314
+      },
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            26
+          ],
+          "slot_index": 0,
+          "shape": 3
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3
+        }
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+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "source_image.png",
+        "image"
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+    },
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+      "type": "ExpressionEditor",
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+      "inputs": [
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+          "type": "IMAGE",
+          "link": 26
+        },
+        {
+          "name": "motion_link",
+          "type": "EDITOR_LINK",
+          "link": null
+        },
+        {
+          "name": "sample_image",
+          "type": "IMAGE",
+          "link": 25
+        },
+        {
+          "name": "add_exp",
+          "type": "EXP_DATA",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [
+            39
+          ],
+          "slot_index": 0,
+          "shape": 3
+        },
+        {
+          "name": "motion_link",
+          "type": "EDITOR_LINK",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "save_exp",
+          "type": "EXP_DATA",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ExpressionEditor"
+      },
+      "widgets_values": [
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+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
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+        1,
+        "OnlyExpression",
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+      ]
+    },
+    {
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+      "type": "SaveImage",
+      "pos": [
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+      "size": [
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+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 39
+        }
+      ],
+      "properties": {},
+      "widgets_values": [
+        "ExpressionEditing"
+      ]
+    }
+  ],
+  "links": [
+    [
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+      0,
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+      2,
+      "IMAGE"
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+    [
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+      20,
+      0,
+      21,
+      0,
+      "IMAGE"
+    ],
+    [
+      39,
+      21,
+      0,
+      33,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [
+    {
+      "title": "Extracting facial expressions from photos",
+      "bounding": [
+        970,
+        233,
+        939,
+        823
+      ],
+      "color": "#a1309b",
+      "font_size": 30
+    }
+  ],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 1,
+      "offset": [
+        -256.9678555487616,
+        -36.006961063159906
+      ]
+    }
+  },
+  "version": 0.4
+}
\ No newline at end of file
diff --git a/sample/sample.json b/sample/workflows/Bacis_Liveportrait_with_expression_editing.json
similarity index 80%
rename from sample/sample.json
rename to sample/workflows/Bacis_Liveportrait_with_expression_editing.json
index 8085518..f3eaebf 100644
--- a/sample/sample.json
+++ b/sample/workflows/Bacis_Liveportrait_with_expression_editing.json
@@ -1,18 +1,140 @@
 {
-  "last_node_id": 9,
-  "last_link_id": 8,
+  "last_node_id": 32,
+  "last_link_id": 38,
   "nodes": [
     {
-      "id": 5,
-      "type": "AdvancedLivePortrait",
+      "id": 26,
+      "type": "LoadImage",
       "pos": [
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       "size": {
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+        "0": 210,
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+      },
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
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+          "type": "IMAGE",
+          "links": [
+            30
+          ],
+          "slot_index": 0,
+          "shape": 3
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+        {
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+          "type": "MASK",
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+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "source_image.png",
+        "image"
+      ]
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+    {
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+      "type": "VHS_LoadVideo",
+      "pos": [
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+        443
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+        491.1999969482422
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+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
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+          "name": "meta_batch",
+          "type": "VHS_BatchManager",
+          "link": null
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            31
+          ],
+          "slot_index": 0,
+          "shape": 3
+        },
+        {
+          "name": "frame_count",
+          "type": "INT",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "audio",
+          "type": "AUDIO",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "video_info",
+          "type": "VHS_VIDEOINFO",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "VHS_LoadVideo"
       },
+      "widgets_values": {
+        "video": "driving_video.mp4",
+        "force_rate": 0,
+        "force_size": "Disabled",
+        "custom_width": 512,
+        "custom_height": 512,
+        "frame_load_cap": 0,
+        "skip_first_frames": 0,
+        "select_every_nth": 2,
+        "choose video to upload": "image",
+        "videopreview": {
+          "hidden": false,
+          "paused": false,
+          "params": {
+            "frame_load_cap": 0,
+            "skip_first_frames": 0,
+            "force_rate": 0,
+            "filename": "driving_video.mp4",
+            "type": "input",
+            "format": "video/mp4",
+            "select_every_nth": 2
+          }
+        }
+      }
+    },
+    {
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+      "type": "AdvancedLivePortrait",
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+        674.0390319824219
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       "order": 3,
       "mode": 0,
@@ -20,7 +142,7 @@
         {
           "name": "src_images",
           "type": "IMAGE",
-          "link": 8
+          "link": 38
         },
         {
           "name": "motion_link",
@@ -30,8 +152,7 @@
         {
           "name": "driving_images",
           "type": "IMAGE",
-          "link": 3,
-          "slot_index": 2
+          "link": 31
         }
       ],
       "outputs": [
@@ -39,10 +160,10 @@
           "name": "images",
           "type": "IMAGE",
           "links": [
-            5
+            35
           ],
-          "shape": 3,
-          "slot_index": 0
+          "slot_index": 0,
+          "shape": 3
         }
       ],
       "properties": {
@@ -51,20 +172,23 @@
       "widgets_values": [
         0,
         0,
+        1.5,
         true,
+        "",
+        false,
         ""
       ]
     },
     {
-      "id": 8,
+      "id": 29,
       "type": "VHS_VideoCombine",
       "pos": [
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       "size": [
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+        272.9300842285156,
+        576.9300842285156
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       "order": 4,
@@ -73,7 +197,7 @@
         {
           "name": "images",
           "type": "IMAGE",
-          "link": 5
+          "link": 35
         },
         {
           "name": "audio",
@@ -105,7 +229,7 @@
       "widgets_values": {
         "frame_rate": 15,
         "loop_count": 0,
-        "filename_prefix": "AnimateDiff",
+        "filename_prefix": "AdvancedLivePortrait",
         "format": "video/h264-mp4",
         "pix_fmt": "yuv420p",
         "crf": 19,
@@ -116,9 +240,9 @@
           "hidden": false,
           "paused": false,
           "params": {
-            "filename": "AnimateDiff_00027.mp4",
+            "filename": "AdvancedLivePortrait_00001.mp4",
             "subfolder": "",
-            "type": "output",
+            "type": "temp",
             "format": "video/h264-mp4",
             "frame_rate": 15
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@@ -126,15 +250,15 @@
       }
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       "type": "ExpressionEditor",
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@@ -143,7 +267,7 @@
         {
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+          "link": 30
         },
         {
           "name": "motion_link",
@@ -166,10 +290,10 @@
           "name": "image",
           "type": "IMAGE",
           "links": [
-            8
+            38
           ],
-          "shape": 3,
-          "slot_index": 0
+          "slot_index": 0,
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@@ -201,174 +325,66 @@
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-      "properties": {
-        "Node name for S&R": "LoadImage"
-      },
-      "widgets_values": [
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   ],
-  "groups": [],
+  "groups": [
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+      "title": "Live Portrait with facial expression editing",
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   "config": {},
   "extra": {
     "ds": {
       "scale": 0.8264462809917354,
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+        185.1062862025528,
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   },
diff --git a/sample/workflows/Bacis_Simple_expression_editing.json b/sample/workflows/Bacis_Simple_expression_editing.json
new file mode 100644
index 0000000..408833d
--- /dev/null
+++ b/sample/workflows/Bacis_Simple_expression_editing.json
@@ -0,0 +1,194 @@
+{
+  "last_node_id": 33,
+  "last_link_id": 40,
+  "nodes": [
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+          "type": "IMAGE",
+          "link": 19
+        },
+        {
+          "name": "motion_link",
+          "type": "EDITOR_LINK",
+          "link": null
+        },
+        {
+          "name": "sample_image",
+          "type": "IMAGE",
+          "link": null
+        },
+        {
+          "name": "add_exp",
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+      ],
+      "properties": {
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+      "outputs": [
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+            19
+          ],
+          "slot_index": 0,
+          "shape": 3
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+          "shape": 3
+        }
+      ],
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+      "widgets_values": [
+        "source_image.png",
+        "image"
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+    },
+    {
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+      "type": "SaveImage",
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+        }
+      ],
+      "properties": {},
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+        "ExpressionEditing"
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+    }
+  ],
+  "links": [
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+    [
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+      0,
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+  ],
+  "groups": [
+    {
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+      "bounding": [
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+      "color": "#88A",
+      "font_size": 30
+    }
+  ],
+  "config": {},
+  "extra": {
+    "ds": {
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+  },
+  "version": 0.4
+}
\ No newline at end of file
diff --git a/sample/workflows/flex/FLEX_Advanced_Audio_Reactive_expression.json b/sample/workflows/flex/FLEX_Advanced_Audio_Reactive_expression.json
new file mode 100644
index 0000000..861cabb
--- /dev/null
+++ b/sample/workflows/flex/FLEX_Advanced_Audio_Reactive_expression.json
@@ -0,0 +1,2330 @@
+{
+  "last_node_id": 88,
+  "last_link_id": 76,
+  "nodes": [
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+      "inputs": [
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+          "type": "IMAGE",
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+      "outputs": [
+        {
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+          "type": "FEATURE",
+          "links": null,
+          "shape": 3
+        },
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+          "name": "FEATURE_PIPE",
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+      "inputs": [
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+          "type": "IMAGE",
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+        }
+      ],
+      "outputs": [
+        {
+          "name": "FEATURE",
+          "type": "FEATURE",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "FEATURE_PIPE",
+          "type": "FEATURE_PIPE",
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diff --git a/sample/workflows/flex/FLEX_Advanced_Inserting_expressions_into_vid.json b/sample/workflows/flex/FLEX_Advanced_Inserting_expressions_into_vid.json
new file mode 100644
index 0000000..1bababb
--- /dev/null
+++ b/sample/workflows/flex/FLEX_Advanced_Inserting_expressions_into_vid.json
@@ -0,0 +1,1954 @@
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+}
\ No newline at end of file