diff --git a/README.en.md b/README.en.md
index 07855dc..247451e 100644
--- a/README.en.md
+++ b/README.en.md
@@ -37,6 +37,8 @@ PS: Please update [ComfyUI_IPAdapter_plus](https://github.com/cubiq/ComfyUI_IPAd
 <br>
 - Added `easy ipadapterApply`
 - Added `easy ipadapterApplyADV`
+- Added `easy ipadapterApplyEncoder`
+- Added `easy ipadapterApplyEmbeds`
 - Added `easy preMaskDetailerFix`
 - Fixed `easy stylesSelector` is change the prompt when not select the style
 
diff --git a/README.md b/README.md
index 852b59e..79f3be3 100644
--- a/README.md
+++ b/README.md
@@ -41,6 +41,8 @@ PS: 请更新至最新版v2的 [ComfyUI_IPAdapter_plus](https://github.com/cubiq
 <br>
 - 增加 `easy ipadapterApply`
 - 增加 `easy ipadapterApplyADV`
+- 增加 `easy ipadapterApplyEncoder`
+- 增加 `easy ipadapterApplyEmbeds`
 - 增加 `easy preMaskDetailerFix`
 - 修复 `easy stylesSelector` 当未选择样式时，原有提示词发生了变化
 
diff --git a/py/easyNodes.py b/py/easyNodes.py
index a060964..0685ce5 100644
--- a/py/easyNodes.py
+++ b/py/easyNodes.py
@@ -1598,7 +1598,7 @@ def insightface_loader(provider):
 class ipadapter:
 
     def __init__(self):
-        self.normol_presets = [
+        self.normal_presets = [
             'LIGHT - SD1.5 only (low strength)',
             'STANDARD (medium strength)',
             'VIT-G (medium strength)',
@@ -1612,7 +1612,9 @@ class ipadapter:
             'FACEID PLUS V2',
             'FACEID PORTRAIT (style transfer)'
         ]
-        self.presets = self.normol_presets + self.faceid_presets
+        self.weight_types = ["linear", "ease in", "ease out", 'ease in-out', 'reverse in-out', 'weak input', 'weak output',
+                        'weak middle', 'strong middle', 'style transfer (SDXL)']
+        self.presets = self.normal_presets + self.faceid_presets
 
 
     def error(self):
@@ -1831,7 +1833,7 @@ class ipadapterApply(ipadapter):
     FUNCTION = "apply"
 
     def apply(self, model, image, preset, lora_strength, provider, weight, weight_faceidv2, start_at, end_at, cache_mode, use_tiled, attn_mask=None, optional_ipadapter=None):
-        tiles, masks = [None], [None]
+        tiles, masks = image, [None]
         model, ipadapter = self.load_model(model, preset, lora_strength, provider, clip_vision=None, optional_ipadapter=optional_ipadapter, cache_mode=cache_mode)
         if use_tiled and preset not in self.faceid_presets:
             if "IPAdapterTiled" not in ALL_NODE_CLASS_MAPPINGS:
@@ -1859,9 +1861,9 @@ class ipadapterApplyAdvanced(ipadapter):
 
     @classmethod
     def INPUT_TYPES(cls):
-        presets = cls().presets
-        WEIGHT_TYPES = ["linear", "ease in", "ease out", 'ease in-out', 'reverse in-out', 'weak input', 'weak output',
-                        'weak middle', 'strong middle', 'style transfer (SDXL)']
+        ipa_cls = cls()
+        presets = ipa_cls.presets
+        weight_types = ipa_cls.weight_types
         return {
             "required": {
                 "model": ("MODEL",),
@@ -1871,7 +1873,7 @@ class ipadapterApplyAdvanced(ipadapter):
                 "provider": (["CPU", "CUDA", "ROCM", "DirectML", "OpenVINO", "CoreML"],),
                 "weight": ("FLOAT", {"default": 1.0, "min": -1, "max": 3, "step": 0.05}),
                 "weight_faceidv2": ("FLOAT", {"default": 1.0, "min": -1, "max": 5.0, "step": 0.05 }),
-                "weight_type": (WEIGHT_TYPES,),
+                "weight_type": (weight_types,),
                 "combine_embeds": (["concat", "add", "subtract", "average", "norm average"],),
                 "start_at": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
                 "end_at": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
@@ -1896,7 +1898,7 @@ class ipadapterApplyAdvanced(ipadapter):
     FUNCTION = "apply"
 
     def apply(self, model, image, preset, lora_strength, provider, weight, weight_faceidv2, weight_type, combine_embeds, start_at, end_at, embeds_scaling, cache_mode, use_tiled, use_batch, sharpening, image_negative=None, clip_vision=None, attn_mask=None, optional_ipadapter=None):
-        tiles, masks = [None], [None]
+        tiles, masks = image, [None]
         model, ipadapter = self.load_model(model, preset, lora_strength, provider, clip_vision=clip_vision, optional_ipadapter=optional_ipadapter, cache_mode=cache_mode)
         if use_tiled:
             if use_batch:
@@ -1920,6 +1922,135 @@ class ipadapterApplyAdvanced(ipadapter):
             model, = cls().apply_ipadapter(model, ipadapter, image, weight, weight_type, start_at, end_at, combine_embeds=combine_embeds, weight_faceidv2=weight_faceidv2, image_negative=image_negative, clip_vision=clip_vision, attn_mask=attn_mask, insightface=None, embeds_scaling=embeds_scaling)
 
         return (model, tiles, masks, ipadapter)
+class ipadapterApplyEncoder(ipadapter):
+    def __init__(self):
+        super().__init__()
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        ipa_cls = cls()
+        normal_presets = ipa_cls.normal_presets
+        max_embeds_num = 3
+        inputs = {
+            "required": {
+                "model": ("MODEL",),
+                "image1": ("IMAGE",),
+                "preset": (normal_presets,),
+                "num_embeds":  ("INT", {"default": 2, "min": 1, "max": max_embeds_num}),
+            },
+            "optional": {}
+        }
+
+        for i in range(1, max_embeds_num + 1):
+            if i > 1:
+                inputs["optional"][f"image{i}"] = ("IMAGE",)
+        for i in range(1, max_embeds_num + 1):
+            inputs["optional"][f"mask{i}"] = ("MASK",)
+            inputs["optional"][f"weight{i}"] = ("FLOAT", {"default": 1.0, "min": -1, "max": 3, "step": 0.05})
+        inputs["optional"]["combine_method"] = (["concat", "add", "subtract", "average", "norm average", "max", "min"],)
+        inputs["optional"]["optional_ipadapter"] = ("IPADAPTER",)
+        inputs["optional"]["pos_embeds"] = ("EMBEDS",)
+        inputs["optional"]["neg_embeds"] = ("EMBEDS",)
+        return inputs
+
+    RETURN_TYPES = ("MODEL", "IPADAPTER", "EMBEDS", "EMBEDS", )
+    RETURN_NAMES = ("model", "ipadapter", "pos_embed", "neg_embed", )
+    CATEGORY = "EasyUse/Adapter"
+    FUNCTION = "apply"
+
+    def batch(self, embeds, method):
+        if method == 'concat' and len(embeds) == 1:
+            return (embeds[0],)
+
+        embeds = [embed for embed in embeds if embed is not None]
+        embeds = torch.cat(embeds, dim=0)
+
+        if method == "add":
+            embeds = torch.sum(embeds, dim=0).unsqueeze(0)
+        elif method == "subtract":
+            embeds = embeds[0] - torch.mean(embeds[1:], dim=0)
+            embeds = embeds.unsqueeze(0)
+        elif method == "average":
+            embeds = torch.mean(embeds, dim=0).unsqueeze(0)
+        elif method == "norm average":
+            embeds = torch.mean(embeds / torch.norm(embeds, dim=0, keepdim=True), dim=0).unsqueeze(0)
+        elif method == "max":
+            embeds = torch.max(embeds, dim=0).values.unsqueeze(0)
+        elif method == "min":
+            embeds = torch.min(embeds, dim=0).values.unsqueeze(0)
+
+        return embeds
+
+    def apply(self, **kwargs):
+        model = kwargs['model']
+        preset = kwargs['preset']
+        if 'optional_ipadapter' in kwargs:
+            ipadapter = kwargs['optional_ipadapter']
+        else:
+            model, ipadapter = self.load_model(model, preset, 0, 'CPU', clip_vision=None, optional_ipadapter=None, cache_mode='none')
+
+        if "IPAdapterEncoder" not in ALL_NODE_CLASS_MAPPINGS:
+            self.error()
+        encoder_cls = ALL_NODE_CLASS_MAPPINGS["IPAdapterEncoder"]
+
+        pos_embeds = kwargs["pos_embeds"] if "pos_embeds" in kwargs else []
+        neg_embeds = kwargs["neg_embeds"] if "neg_embeds" in kwargs else []
+        for i in range(1, kwargs['num_embeds'] + 1):
+            if f"image{i}" not in kwargs:
+                raise Exception(f"image{i} is required")
+            kwargs[f"mask{i}"] = kwargs[f"mask{i}"] if f"mask{i}" in kwargs else None
+            kwargs[f"weight{i}"] = kwargs[f"weight{i}"] if f"weight{i}" in kwargs else 1.0
+
+            pos, neg = encoder_cls().encode(ipadapter, kwargs[f"image{i}"], kwargs[f"weight{i}"], kwargs[f"mask{i}"], clip_vision=None)
+            pos_embeds.append(pos)
+            neg_embeds.append(neg)
+
+        pos_embeds = self.batch(pos_embeds, kwargs['combine_method'])
+        neg_embeds = self.batch(neg_embeds, kwargs['combine_method'])
+
+        return (model, ipadapter, pos_embeds, neg_embeds)
+
+class ipadapterApplyEmbeds(ipadapter):
+    def __init__(self):
+        super().__init__()
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        ipa_cls = cls()
+        weight_types = ipa_cls.weight_types
+        return {
+            "required": {
+                "model": ("MODEL",),
+                "ipadapter": ("IPADAPTER",),
+                "pos_embed": ("EMBEDS",),
+                "weight": ("FLOAT", {"default": 1.0, "min": -1, "max": 3, "step": 0.05}),
+                "weight_type": (weight_types,),
+                "start_at": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
+                "end_at": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
+                "embeds_scaling": (['V only', 'K+V', 'K+V w/ C penalty', 'K+mean(V) w/ C penalty'],),
+            },
+
+            "optional": {
+                "neg_embed": ("EMBEDS",),
+                "attn_mask": ("MASK",),
+            }
+        }
+
+    RETURN_TYPES = ("MODEL", "IPADAPTER",)
+    RETURN_NAMES = ("model", "ipadapter", )
+    CATEGORY = "EasyUse/Adapter"
+    FUNCTION = "apply"
+
+    def apply(self, model, ipadapter, pos_embed, weight, weight_type, start_at, end_at, embeds_scaling, attn_mask=None, neg_embed=None,):
+        if "IPAdapterEmbeds" not in ALL_NODE_CLASS_MAPPINGS:
+            self.error()
+        cls = ALL_NODE_CLASS_MAPPINGS["IPAdapterEmbeds"]
+        model, = cls().apply_ipadapter(model, ipadapter, pos_embed, weight, weight_type, start_at, end_at, neg_embed=neg_embed, attn_mask=attn_mask, clip_vision=None, embeds_scaling=embeds_scaling)
+
+        return (model, ipadapter)
+
 
 #Apply InstantID
 class instantID:
@@ -5872,6 +6003,8 @@ NODE_CLASS_MAPPINGS = {
     # Adapter 适配器
     "easy ipadapterApply": ipadapterApply,
     "easy ipadapterApplyADV": ipadapterApplyAdvanced,
+    "easy ipadapterApplyEncoder": ipadapterApplyEncoder,
+    "easy ipadapterApplyEmbeds": ipadapterApplyEmbeds,
     "easy instantIDApply": instantIDApply,
     "easy instantIDApplyADV": instantIDApplyAdvanced,
     # Inpaint 内补
@@ -5961,6 +6094,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     # Adapter 适配器
     "easy ipadapterApply": "Easy Apply IPAdapter",
     "easy ipadapterApplyADV": "Easy Apply IPAdapter (Advanced)",
+    "easy ipadapterApplyEncoder": "Easy Apply IPAdapter (Encoder)",
+    "easy ipadapterApplyEmbeds": "Easy Apply IPAdapter (Embeds)",
     "easy instantIDApply": "Easy Apply InstantID",
     "easy instantIDApplyADV": "Easy Apply InstantID (Advanced)",
     # Inpaint 内补
diff --git a/web/js/easy/easyDynamicWidgets.js b/web/js/easy/easyDynamicWidgets.js
index ea5683e..58cbe2e 100644
--- a/web/js/easy/easyDynamicWidgets.js
+++ b/web/js/easy/easyDynamicWidgets.js
@@ -28,6 +28,11 @@ function toggleWidget(node, widget, show = false, suffix = "") {
 	node.setSize([node.size[0], height]);
 }
 
+function toggleInput(node, name, show = false) {
+	if(!show){
+	}
+}
+
 function widgetLogic(node, widget) {
 	if (widget.name === 'lora_name') {
 		if (widget.value === "None") {
@@ -227,8 +232,8 @@ function widgetLogic(node, widget) {
 			toggleWidget(node, findWidgetByName(node, 'provider'))
 			toggleWidget(node, findWidgetByName(node, 'weight_faceidv2'))
 			toggleWidget(node, findWidgetByName(node, 'use_tiled'), true)
-			let use_tiled = findWidgetByName(node, 'use_tiled').value
-			if(use_tiled){
+			let use_tiled = findWidgetByName(node, 'use_tiled')
+			if(use_tiled && use_tiled.value){
 				toggleWidget(node, findWidgetByName(node, 'sharpening'), true)
 			}else {
 				toggleWidget(node, findWidgetByName(node, 'sharpening'))
@@ -261,6 +266,21 @@ function widgetLogic(node, widget) {
 			toggleWidget(node, findWidgetByName(node, 'sharpening'))
 		updateNodeHeight(node)
 	}
+
+	if (widget.name === 'num_embeds') {
+		let number_to_show = widget.value + 1
+		for (let i = 0; i < number_to_show; i++) {
+			toggleInput(node, 'image'+i, true)
+			toggleInput(node, 'mask'+i, true)
+			toggleWidget(node, findWidgetByName(node, 'weight'+i), true)
+		}
+		for (let i = number_to_show; i < 6; i++) {
+			toggleInput(node, 'image'+i)
+			toggleInput(node, 'mask'+i)
+			toggleWidget(node, findWidgetByName(node, 'weight'+i))
+		}
+		updateNodeHeight(node)
+	}
 }
 
 function widgetLogic2(node, widget) {
@@ -541,6 +561,7 @@ app.registerExtension({
 			case 'easy pipeEdit':
 			case 'easy ipadapterApply':
 			case 'easy ipadapterApplyADV':
+			case 'easy ipadapterApplyEncoder':
 				getSetters(node)
 				break
 			case "easy wildcards":
@@ -977,7 +998,7 @@ const getSetWidgets = ['rescale_after_model', 'rescale',
 						'refiner_lora1_name', 'refiner_lora2_name', 'upscale_method', 
 						'image_output', 'add_noise', 'info', 'sampler_name',
 						'ckpt_B_name', 'ckpt_C_name', 'save_model', 'refiner_ckpt_name',
-						'num_loras', 'mode', 'toggle', 'resolution', 'target_parameter', 'input_count', 'replace_count', 'downscale_mode', 'range_mode','text_combine_mode', 'input_mode','lora_count','ckpt_count', 'conditioning_mode', 'preset', 'use_tiled', 'use_batch']
+						'num_loras', 'mode', 'toggle', 'resolution', 'target_parameter', 'input_count', 'replace_count', 'downscale_mode', 'range_mode','text_combine_mode', 'input_mode','lora_count','ckpt_count', 'conditioning_mode', 'preset', 'use_tiled', 'use_batch', 'num_embeds']
 
 function getSetters(node) {
 	if (node.widgets)