diff --git a/README.md b/README.md
index 60be329..9c21b40 100644
--- a/README.md
+++ b/README.md
@@ -47,7 +47,9 @@ Make sure your system meets these requirements:
 You have two options to install this integration:
 
 #### Option 1: Using ComfyUI Manager (Recommended)
-You can easily install ComfyUI-Runware via the ComfyUI Manager. Just search for "ComfyUI-Runware" and install with a single click! ✨
+First, ensure you have the `ComfyUI-Manager` custom node installed. If you don't have it or are using the beta ComfyUI desktop version, follow the instructions on this [GitHub Repo](https://github.com/ltdrdata/ComfyUI-Manager?tab=readme-ov-file#installation).
+
+After installing ComfyUI-Manager, open it and click on "Custom Nodes Manager". Search for "Runware" or "Runware.ai" and then click on install or update. Finally, restart your ComfyUI. ✨
 
 #### Option 2: Manual Installation
 
@@ -61,7 +63,12 @@ You can easily install ComfyUI-Runware via the ComfyUI Manager. Just search for
    git clone https://github.com/Runware/ComfyUI-Runware.git
    ```
 
-3. Install dependencies:
+3. Navigate to the repository folder:
+   ```bash
+   cd ComfyUI-Runware
+   ```
+
+4. Install dependencies:
    ```bash
    pip install -r requirements.txt
    ```
@@ -80,7 +87,7 @@ python main.py --cpu --front-end-version Comfy-Org/ComfyUI_frontend@latest
 ```
 
 ### Step 4: Explore Workflows
-Inside the `comfyui-runware` custom node folder, you’ll find a `workflows` folder with pre-made workflows to get you started! 🚀
+Inside the `ComfyUI-Runware` custom node folder, you’ll find a `workflows` folder with pre-made workflows to get you started! 🚀
 
 ---
 
@@ -88,7 +95,7 @@ Inside the `comfyui-runware` custom node folder, you’ll find a `workflows` fol
 
 Here’s a breakdown of the amazing nodes included in this integration:
 
-- **Runware API Manager**: Set your API keys directly in ComfyUI—no need to edit config files manually! 🔑
+- **Runware API Manager**: Set or change your API keys and adjust the max connection timeout directly in ComfyUI—no need to edit config files manually! 🔑
 - **Runware Image Inference**: Perform advanced tasks like inpainting, outpainting, and more. 🎨
 - **Runware PhotoMakerV2**: Create consistent identities with our photomaker pipeline. 🖼️
 - **Runware Image Upscale**: Upscale your images up to 4x. 🔍
@@ -101,6 +108,9 @@ Here’s a breakdown of the amazing nodes included in this integration:
 - **Runware ControlNet Combine**: Combine multiple ControlNets for complex workflows. 🧩
 - **Runware Image Masking**: Automatically mask elements like faces, hands, and more. 🖌️
 - **Runware ControlNet Preprocessor**: Preprocess images before using them as guide images in ControlNet. 🔄
+- **Runware VAE**: Search and connect a VAE to Image inference. 🖼️
+- **Runware Embedding**: Search and connect Embedding to image inference. 🧩
+- **Runware Embedding Combine**: Combine multiple embeddings together. 🔗
 
 ---
 
diff --git a/__init__.py b/__init__.py
index 8faa6a0..efd05cc 100644
--- a/__init__.py
+++ b/__init__.py
@@ -13,8 +13,11 @@ from .modules.controlNetPreprocessor import controlNetPreprocessor
 from .modules.apiManager import apiManager
 from .modules.imageCaptioning import imageCaptioning
 from .modules.controlNetCombine import controlNetCombine
+from .modules.embeddingSearch import embeddingSearch
+from .modules.embeddingsCombine import embeddingsCombine
+from .modules.vaeSearch import vaeSearch
 
-RUNWARE_COMFYUI_VERSION = "0.9.1 Beta"
+RUNWARE_COMFYUI_VERSION = "0.9.2 Beta"
 
 RESET_COLOR = "\033[0m"
 BLUE_COLOR = "\033[94m"
@@ -32,6 +35,9 @@ NODE_CLASS_MAPPINGS = {
     "Runware Image Upscaler": upscaler,
     "Runware Model Search": modelSearch,
     "Runware Lora Search": loraSearch,
+    "Runware Embedding Search": embeddingSearch,
+    "Runware VAE Search": vaeSearch,
+    "Runware Embeddings Combine": embeddingsCombine,
     "Runware ControlNet": controlNet,
     "Runware Lora Combine": loraCombine,
     "Runware Refiner": refiner,
@@ -45,6 +51,8 @@ NODE_CLASS_MAPPINGS = {
 NODE_DISPLAY_NAME_MAPPINGS = {
     "Runware Model Search": "Runware Model",
     "Runware Lora Search": "Runware Lora",
+    "Runware Embedding Search": "Runware Embedding",
+    "Runware VAE Search": "Runware VAE",
 }
 
 WEB_DIRECTORY = "./clientlibs"
diff --git a/clientlibs/types.js b/clientlibs/types.js
index cb89431..16f452c 100644
--- a/clientlibs/types.js
+++ b/clientlibs/types.js
@@ -42,9 +42,9 @@ const DEFAULT_CONTROLNET_CONDITIONING_LIST = {
     "Soft Edge": "softedge",
 };
 
-const SEARCH_TERMS = ["Model Search", "Lora Search", "ControlNet Search"];
+const SEARCH_TERMS = ["Model Search", "Lora Search", "ControlNet Search", "Embedding Search", "VAE Search"];
 const MODEL_TYPES_TERMS = ["ModelType", "LoraType", "ControlNetType"];
-const MODEL_LIST_TERMS = ["ModelList", "LoraList", "ControlNetList"];
+const MODEL_LIST_TERMS = ["ModelList", "LoraList", "ControlNetList", "EmbeddingList", "VAEList"];
 
 const RUNWARE_NODE_TYPES = {
     IMAGEINFERENCE: "Runware Image Inference",
@@ -61,6 +61,9 @@ const RUNWARE_NODE_TYPES = {
     CONTROLNETPREPROCESSING: "Runware ControlNet PreProcessor",
     APIMANAGER: "Runware API Manager",
     IMAGECAPTION: "Runware Image Caption",
+    EMBEDDING: "Runware Embedding Search",
+    EMBEDDINGCOMBINE: "Runware Embedding Combine",
+    VAE: "Runware VAE Search",
 };
 
 const RUNWARE_NODE_PROPS = {
@@ -82,10 +85,22 @@ const RUNWARE_NODE_PROPS = {
         bgColor: DEFAULT_BGCOLOR,
         liveSearch: true,
     },
+    [RUNWARE_NODE_TYPES.EMBEDDING]: {
+        bgColor: DEFAULT_BGCOLOR,
+        liveSearch: true,
+    },
     [RUNWARE_NODE_TYPES.CONTROLNET]: {
         bgColor: DEFAULT_BGCOLOR,
         liveSearch: true,
     },
+    [RUNWARE_NODE_TYPES.VAE]: {
+        bgColor: DEFAULT_BGCOLOR,
+        liveSearch: true,
+    },
+    [RUNWARE_NODE_TYPES.EMBEDDINGCOMBINE]: {
+        bgColor: DEFAULT_BGCOLOR,
+        colorModeOnly: true,
+    },
     [RUNWARE_NODE_TYPES.CONTROLNETCONDITIONING]: {
         bgColor: DEFAULT_BGCOLOR,
         liveSearch: true,
diff --git a/clientlibs/utils.js b/clientlibs/utils.js
index f165e94..0dc9d9c 100644
--- a/clientlibs/utils.js
+++ b/clientlibs/utils.js
@@ -148,6 +148,23 @@ async function APIKeyHandler(apiManagerNode) {
     }
 }
 
+function addTriggerWords(prompt, triggerWords) {
+    if (!triggerWords?.trim()) return prompt;
+    const cleanedTriggerWords = triggerWords
+        .trim()
+        .replace(/,\s*$/, '')
+        .split(',')
+        .map(word => word.trim())
+        .filter(word => word.length);
+    if (!prompt?.trim()) return cleanedTriggerWords.join(', ');
+    const wordsToAdd = cleanedTriggerWords.filter(word => 
+        !new RegExp(`\\b${word}\\b`, 'i').test(prompt)
+    );
+    return wordsToAdd.length 
+        ? `${prompt}${prompt.endsWith(',') ? ' ' : ', '}${wordsToAdd.join(', ')}`
+        : prompt;
+}
+
 function handleCustomErrors(errObj) {
     const errData = errObj.detail;
     const errCode = errData.errorCode;
@@ -265,12 +282,25 @@ async function syncDimensionsNodeHandler(node, dimensionsWidget) {
     }
 }
 
+const shortenAirCode = input => !input || !input.startsWith('urn:air:') ? input : input.match(/urn:air:.*?:.*?(civitai:\d+@\d+)$/)?.[1] || input;
+
 async function searchNodeHandler(searchNode, searchInputWidget) {
     const searchNodeWidgets = searchNode.widgets;
-    let modelArchWidget = false, modelTypeWidget = false, modelListWidget = false, defaultWidgetValues = {};
-    let isLora = false, isControlNet = false, modelTypeValue;
+    let modelArchWidget = false, modelTypeWidget = false, modelListWidget = false,
+    defaultWidgetValues = {}, triggerWordsList = {
+        "civitai:58390@62833": "", "civitai:82098@87153": "", "civitai:122359@135867": "",
+        "civitai:14171@16677": "mix4", "civitai:13941@16576": "", "civitai:25995@32988": "full body, chibi"
+    }, embeddingTriggerWordsList = {
+        "civitai:7808@9208": "easynegative", "civitai:4629@5637": "ng_deepnegative_v1_75t",
+        "civitai:56519@60938": "negative_hand", "civitai:72437@77169": "BadDream",
+        "civitai:11772@25820": "verybadimagenegative_v1.3", "civitai:71961@94057": "FastNegativeV2",
+    };
+    let isLora = false, isControlNet = false, isEmbedding = false, isVAE = false, modelTypeValue = false;
     if(searchNode.comfyClass === RUNWARE_NODE_TYPES.LORASEARCH) isLora = true;
     if(searchNode.comfyClass === RUNWARE_NODE_TYPES.CONTROLNET) isControlNet = true;
+    if(searchNode.comfyClass === RUNWARE_NODE_TYPES.EMBEDDING) isEmbedding = true;
+    if(searchNode.comfyClass === RUNWARE_NODE_TYPES.VAE) isVAE = true;
+
     for(const searchWidget of searchNodeWidgets) {
         const widgetName = searchWidget.name;
         const widgetType = searchWidget.type;
@@ -304,18 +334,25 @@ async function searchNodeHandler(searchNode, searchInputWidget) {
     }
 
     async function searchModels() {
-        const searchQuery = searchInputWidget.value.trim();
+        let searchQuery = searchInputWidget.value.trim();
+        searchQuery = shortenAirCode(searchQuery);
         const modelArchValue = DEFAULT_MODELS_ARCH_LIST[modelArchWidget.value];
         if(isControlNet) {
             modelTypeValue = DEFAULT_CONTROLNET_CONDITIONING_LIST[modelTypeWidget.value];
         } else {
-            modelTypeValue = modelTypeWidget.value.toLowerCase().replace("model", "").trim();
+            if(isEmbedding) {
+                modelTypeValue = "embedding";
+            } else if(isVAE) {
+                modelTypeValue = "vae";
+            } else {
+                modelTypeValue = modelTypeWidget.value.toLowerCase().replace("model", "").trim();
+            }
         }
 
         let modelSearchResults = null;
         if(isControlNet) {
             modelSearchResults = await modelSearch(searchQuery, modelArchValue, "", "controlnet", modelTypeValue);
-        } else if(isLora) {
+        } else if(isLora || isEmbedding || isVAE) {
             modelSearchResults = await modelSearch(searchQuery, modelArchValue, "", modelTypeValue);
         } else {
             modelSearchResults = await modelSearch(searchQuery, modelArchValue, modelTypeValue);
@@ -324,6 +361,8 @@ async function searchNodeHandler(searchNode, searchInputWidget) {
         if(modelSearchResults.success) {
             const modelListArray = [];
             modelSearchResults.modelList.forEach(modelObj => {
+                if(isLora) triggerWordsList[modelObj.air] = modelObj.positiveTriggerWords.trim();
+                if(isEmbedding) embeddingTriggerWordsList[modelObj.air] = modelObj.positiveTriggerWords.trim();
                 modelListArray.push(`${modelObj.air} (${modelObj.name} ${modelObj.version})`);
             });
             modelListWidget.options.values = modelListArray;
@@ -333,8 +372,95 @@ async function searchNodeHandler(searchNode, searchInputWidget) {
         }
     }
 
+    function findTargetWidget(currentNode, targetWidgetName, depth = 1) {
+        if(depth < 0) return false;
+        const nodeOutputs = currentNode.outputs;
+        if(nodeOutputs.length === 0) return false;
+        const outputLinks = nodeOutputs[0].links;
+        if(outputLinks.length === 0) return false;
+        for(const linkID of outputLinks) {
+            const linkInfo = app.graph.links[linkID];
+            const linkNodeID = linkInfo.target_id;
+            if(!linkNodeID) continue;
+            const targetNode = app.graph.getNodeById(linkNodeID);
+            let widgetFound = false;
+            if(targetNode.widgets !== undefined && targetNode.widgets.length > 0){
+                widgetFound = targetNode.widgets.find(widget => widget.name === targetWidgetName) || false;
+            }
+            if(widgetFound) {
+                return widgetFound;
+            } else {
+                return findTargetWidget(targetNode, targetWidgetName, depth - 1);
+            }
+        }
+        return false;
+    }
+
+    if(isLora) {
+        const runwareButton = document.createElement("button");
+        runwareButton.textContent = "Add Lora To Prompt";
+        runwareButton.style = "max-height: 50px; background-color: #333; color: #ccc;";
+        searchNode.addDOMWidget("addLora", "custom", runwareButton, {
+            selectOn: ['focus', 'click'],
+        });
+
+        runwareButton.addEventListener("click", async () => {
+            const chosenLora = modelListWidget.value.split(" ")[0];
+            const triggerWords = triggerWordsList[chosenLora];
+            if(triggerWords.length > 0) {
+                const positivePromptWidget = findTargetWidget(searchNode, "positivePrompt");
+                if(!positivePromptWidget) {
+                    notifyUser("Lora Node Is Not Linked To Any Runware Inference Node!", "error", "Runware Lora Connector");
+                    return;
+                }
+                const positivePromptWithTrigger = addTriggerWords(positivePromptWidget.value, triggerWords);
+                if(positivePromptWidget.value === positivePromptWithTrigger) {
+                    notifyUser("Trigger Words Already Exists", "info", "Runware Lora Connector");
+                    return;
+                }
+                positivePromptWidget.value = positivePromptWithTrigger;
+                notifyUser("Trigger Words Added Successfully!", "success", "Runware Lora Connector");
+            } else {
+                notifyUser("No Trigger Words Found For This Lora!", "warn", "Runware Lora Connector");
+            }
+        });
+    } else if(isEmbedding) {
+        const runwareButton = document.createElement("button");
+        runwareButton.textContent = "Add Embedding To Negative Prompt";
+        runwareButton.style = "max-height: 50px; background-color: #333; color: #ccc;";
+        searchNode.addDOMWidget("addEmbedding", "custom", runwareButton, {
+            selectOn: ['focus', 'click'],
+        });
+
+        runwareButton.addEventListener("click", async () => {
+            const chosenEmbedding = modelListWidget.value.split(" ")[0];
+            const triggerWords = embeddingTriggerWordsList[chosenEmbedding];
+            if(triggerWords.length > 0) {
+                const negativePromptWidget = findTargetWidget(searchNode, "negativePrompt");
+                if(!negativePromptWidget) {
+                    notifyUser("Embedding Node Is Not Linked To Any Runware Inference Node!", "error", "Runware Embedding Connector");
+                    return;
+                }
+                const negativePromptWithTrigger = addTriggerWords(negativePromptWidget.value, triggerWords);
+                if(negativePromptWidget.value === negativePromptWithTrigger) {
+                    notifyUser("Trigger Words Already Exists", "info", "Runware Embedding Connector");
+                    return;
+                }
+                negativePromptWidget.value = negativePromptWithTrigger;
+                notifyUser("Trigger Words Added Successfully!", "success", "Runware Embedding Connector");
+            } else {
+                notifyUser("No Trigger Words Found For This Embedding!", "warn", "Runware Embedding Connector");
+            }
+        });
+    }
+
     appendWidgetCB(searchInputWidget, async function(...args) {
-        const searchQuery = args[0].trim();
+        let searchQuery = args[0].trim();
+        const shortenSearchQuery = shortenAirCode(searchQuery);
+        if(searchQuery !== shortenSearchQuery) {
+            searchQuery = shortenSearchQuery;
+            searchInputWidget.value = searchQuery;
+        }
         if(searchQuery.length === 0) {
             resetValues();
         } else if(searchQuery.length < 2 || searchQuery.length > 32) {
@@ -349,8 +475,8 @@ async function searchNodeHandler(searchNode, searchInputWidget) {
         await searchModels();
     });
 
-    if(!isLora){
-        appendWidgetCB(modelTypeWidget, async function(...args) {     
+    if(!isVAE && !isEmbedding) {
+        appendWidgetCB(modelTypeWidget, async function(...args) {
             await searchModels();
         });
     }
diff --git a/modules/bridges/mainRoute.py b/modules/bridges/mainRoute.py
index d72d003..c69a0d6 100644
--- a/modules/bridges/mainRoute.py
+++ b/modules/bridges/mainRoute.py
@@ -70,11 +70,12 @@ async def modelSearch(reqPayload):
         "sort": "-downloadCount",
     }]
 
-    if(modelCategory != "controlnet" and modelCategory != "lora"):
+    aclTypes = ["controlnet", "lora", "lycoris", "embedding", "vae"]
+
+    if(modelCategory not in aclTypes):
         utilityConfig[0]["type"] = modelType
     elif(modelCategory == "controlnet" and controlNetConditioning != "all"):
         utilityConfig[0]["conditioning"] = controlNetConditioning
-
     if(modelArch != "all"):
         utilityConfig[0]["architecture"] = modelArch
     if(modelQuery != ""):
diff --git a/modules/embeddingSearch.py b/modules/embeddingSearch.py
new file mode 100644
index 0000000..fb5d1fb
--- /dev/null
+++ b/modules/embeddingSearch.py
@@ -0,0 +1,66 @@
+class embeddingSearch:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "Embedding Search": ("STRING", {
+                    "tooltip": "Searchg For A Specific Embedding By Name Or Civit AIR Code (eg: EasyNegative).",
+                }),
+                "Model Architecture": ([
+                        "All",
+                        "FLUX.1-Schnell",
+                        "FLUX.1-Dev",
+                        "Pony",
+                        "SD 1.5",
+                        "SD 1.5 Hyper",
+                        "SD 1.5 LCM",
+                        "SD 3",
+                        "SDXL 1.0",
+                        "SDXL 1.0 LCM",
+                        "SDXL Distilled",
+                        "SDXL Hyper",
+                        "SDXL Lightning",
+                        "SDXL Turbo",
+                    ], {
+                    "tooltip": "Choose Embedding Model Architecture To Filter Out The Results.",
+                    "default": "SD 1.5",
+                }),
+                "EmbeddingList": ([
+                        "civitai:7808@9208 (EasyNegative)",
+                        "civitai:4629@5637 (Deep Negative V1.x)",
+                        "civitai:56519@60938 (negative_hand Negative Embedding)",
+                        "civitai:72437@77169 (BadDream + UnrealisticDream (Negative Embeddings))",
+                        "civitai:11772@25820 (veryBadImageNegative)",
+                        "civitai:71961@94057 (Fast Negative Embedding (+ FastNegativeV2))",
+                    ], {
+                    "tooltip": "Embedding Results Will Show UP Here So You Could Choose From.",
+                    "default": "civitai:7808@9208 (EasyNegative)",
+                }),
+                "weight": ("FLOAT", {
+                    "tooltip": "Defines the strength or influence of the Embedding on the generation process.",
+                    "default": 1.0,
+                    "min": 0,
+                    "max": 1,
+                    "step": 0.1,
+                }),
+            },
+        }
+
+    DESCRIPTION = "Directly Search and Connect Embeddings to Runware Inference Nodes In ComfyUI."
+    FUNCTION = "embeddingSearch"
+    RETURN_TYPES = ("RUNWAREEMBEDDING",)
+    RETURN_NAMES = ("Runware Embedding",)
+    CATEGORY = "Runware"
+
+    @classmethod
+    def VALIDATE_INPUTS(cls, EmbeddingList):
+        return True
+
+    def embeddingSearch(self, **kwargs):
+        currentModel = kwargs.get("EmbeddingList")
+        embeddingWeight = kwargs.get("weight")
+        embeddingAIRCode = currentModel.split(" ")[0]
+        return ({
+            "model": embeddingAIRCode,
+            "weight": round(embeddingWeight, 2),
+        },)
\ No newline at end of file
diff --git a/modules/embeddingsCombine.py b/modules/embeddingsCombine.py
new file mode 100644
index 0000000..1834c79
--- /dev/null
+++ b/modules/embeddingsCombine.py
@@ -0,0 +1,37 @@
+class embeddingsCombine:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "Embedding 1": ("RUNWAREEMBEDDING", {
+                    "tooltip": "Connect a Runware Embedding From an Embedding Node.",
+                }),
+            },
+            "optional": {
+                "Embedding 2": ("RUNWAREEMBEDDING", {
+                    "tooltip": "Connect a Runware Embedding From an Embedding Node.",
+                }),
+                "Embedding 3": ("RUNWAREEMBEDDING", {
+                    "tooltip": "Connect a Runware Embedding From an Embedding Node.",
+                }),
+            },
+        }
+
+    DESCRIPTION = "Combine One or More Embeddings To Connect It With Runware Image Inference."
+    FUNCTION = "embeddingsCombine"
+    RETURN_TYPES = ("RUNWAREEMBEDDING",)
+    RETURN_NAMES = ("Runware Embeddings",)
+    CATEGORY = "Runware"
+
+    def embeddingsCombine(self, **kwargs):
+        embeddingV1 = kwargs.get("Embedding 1")
+        embeddingV2 = kwargs.get("Embedding 2", None)
+        embeddingV3 = kwargs.get("Embedding 3", None)
+
+        embeddingsObjArray = []
+        embeddingsObjArray.append(embeddingV1)
+        if(embeddingV2):
+            embeddingsObjArray.append(embeddingV2)
+        if(embeddingV3):
+            embeddingsObjArray.append(embeddingV3)
+        return (embeddingsObjArray,)
\ No newline at end of file
diff --git a/modules/imageInference.py b/modules/imageInference.py
index f700e6c..bd68804 100644
--- a/modules/imageInference.py
+++ b/modules/imageInference.py
@@ -118,6 +118,12 @@ class txt2img:
                 "maskImage": ("MASK", {
                     "tooltip": "Specifies the mask image to be used for the inpainting process, when doing Inpainting, this parameter is required.",
                 }),
+                "Embeddings": ("RUNWAREEMBEDDING", {
+                    "tooltip": "Connect a Runware Embedding Node to help the model generate images that align with the desired structure.",
+                }),
+                "VAE": ("RUNWAREVAE", {
+                    "tooltip": "Connect a Runware VAE Node to help the model generate images that align with the desired structure.",
+                }),
             }
         }
 
@@ -142,6 +148,8 @@ class txt2img:
         runwareControlNet = kwargs.get("ControlNet", None)
         runwareLora = kwargs.get("Lora", None)
         runwareRefiner = kwargs.get("Refiner", None)
+        runwareEmbedding = kwargs.get("Embeddings", None)
+        runwareVAE = kwargs.get("VAE", None)
         seedImage = kwargs.get("seedImage", None)
         seedImageStrength = kwargs.get("strength", 0.8)
         maskImage = kwargs.get("maskImage", None)
@@ -193,6 +201,13 @@ class txt2img:
                 genConfig[0]["lora"] = runwareLora
             elif(isinstance(runwareLora, dict)):
                 genConfig[0]["lora"] = [runwareLora]
+        if(runwareEmbedding is not None):
+            if(isinstance(runwareEmbedding, list)):
+                genConfig[0]["embeddings"] = runwareEmbedding
+            elif(isinstance(runwareEmbedding, dict)):
+                genConfig[0]["embeddings"] = [runwareEmbedding]
+        if(runwareVAE is not None):
+            genConfig[0]["vae"] = runwareVAE
         if(runwareControlNet is not None):
             genConfig[0]["controlNet"] = runwareControlNet
         if(runwareRefiner is not None):
diff --git a/modules/loraSearch.py b/modules/loraSearch.py
index d47581c..53069d7 100644
--- a/modules/loraSearch.py
+++ b/modules/loraSearch.py
@@ -27,8 +27,9 @@ class loraSearch:
                 }),
                 "LoraType": ([
                         "Lora",
+                        "LyCORIS"
                     ], {
-                    "tooltip": "Choose Lora Type To Filter Results.",
+                    "tooltip": "Choose Lora Type To Filter Out The Results.",
                     "default": "Lora",
                 }),
                 "LoraList": ([
diff --git a/modules/vaeSearch.py b/modules/vaeSearch.py
new file mode 100644
index 0000000..6641473
--- /dev/null
+++ b/modules/vaeSearch.py
@@ -0,0 +1,55 @@
+class vaeSearch:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "VAE Search": ("STRING", {
+                    "tooltip": "Searchg For A Specific VAE By Name Or Civit AIR Code (eg: ClearVAE).",
+                }),
+                "Model Architecture": ([
+                        "All",
+                        "FLUX.1-Schnell",
+                        "FLUX.1-Dev",
+                        "Pony",
+                        "SD 1.5",
+                        "SD 1.5 Hyper",
+                        "SD 1.5 LCM",
+                        "SD 3",
+                        "SDXL 1.0",
+                        "SDXL 1.0 LCM",
+                        "SDXL Distilled",
+                        "SDXL Hyper",
+                        "SDXL Lightning",
+                        "SDXL Turbo",
+                    ], {
+                    "tooltip": "Choose VAE's Model Architecture To Filter Out The Results.",
+                    "default": "SD 1.5",
+                }),
+                "VAEList": ([
+                        "civitai:23906@28569 (kl-f8-anime2 VAE)",
+                        "civitai:22354@88156 (ClearVAE(SD1.5))",
+                        "civitai:276082@311162 (vae-ft-mse-840000-ema-pruned | 840000 | 840k SD1.5 VAE)",
+                        "civitai:70248@83798 (Color101 VAE)",
+                        "civitai:22354@26689 (ClearVAE (SD1.5))",
+                        "civitai:88390@94036 (difConsistency RAW VAE (Pack))",
+                    ], {
+                    "tooltip": "VAE Results Will Show UP Here So You Could Choose From.",
+                    "default": "civitai:23906@28569 (kl-f8-anime2 VAE)",
+                })
+            },
+        }
+
+    DESCRIPTION = "Directly Search and Connect VAE's to Runware Inference Nodes In ComfyUI."
+    FUNCTION = "vaeSearch"
+    RETURN_TYPES = ("RUNWAREVAE",)
+    RETURN_NAMES = ("Runware VAE",)
+    CATEGORY = "Runware"
+
+    @classmethod
+    def VALIDATE_INPUTS(cls, VAEList):
+        return True
+
+    def vaeSearch(self, **kwargs):
+        currentModel = kwargs.get("VAEList")
+        vaeAIRCode = currentModel.split(" ")[0]
+        return (vaeAIRCode,)
\ No newline at end of file
diff --git a/workflows/Runware_Adetailer.json b/workflows/Runware_Adetailer.json
index a3b83f6..2a16489 100644
--- a/workflows/Runware_Adetailer.json
+++ b/workflows/Runware_Adetailer.json
@@ -1 +1 @@
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\ No newline at end of file
+{"last_node_id":7,"last_link_id":8,"nodes":[{"id":4,"type":"Runware Image Masking","pos":[351.7330627441406,132.90028381347656],"size":[315,194],"flags":{},"order":4,"mode":0,"inputs":[{"name":"Image","type":"IMAGE","link":3}],"outputs":[{"name":"Image","type":"IMAGE","links":[4],"slot_index":0},{"name":"Mask Preview","type":"IMAGE","links":null},{"name":"Mask","type":"MASK","links":[5],"slot_index":2}],"properties":{"Node name for S&R":"Runware Image Masking"},"widgets_values":["face_yolov8n",0.25,6,4,4],"bgcolor":"#6c5ce7"},{"id":2,"type":"Runware Model Search","pos":[-75.49443817138672,-288.33795166015625],"size":[315,130],"flags":{"collapsed":true},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"Runware Model","type":"RUNWAREMODEL","links":[2],"slot_index":0}],"properties":{"Node name for S&R":"Runware Model Search"},"widgets_values":["","All","Base Model","civitai:101055@128078 (SDXL v1.0 VAE fix)"],"bgcolor":"#6c5ce7"},{"id":6,"type":"PreviewImage","pos":[1151.2889404296875,-264.380859375],"size":[552.3806762695312,564.0267944335938],"flags":{},"order":6,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":7}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":1,"type":"PreviewImage","pos":[357.7220764160156,-258.3918762207031],"size":[307.82305908203125,331.447509765625],"flags":{},"order":3,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":1}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":7,"type":"Runware Model Search","pos":[691.1177978515625,-322.2765808105469],"size":[315,130],"flags":{"collapsed":true},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"Runware Model","type":"RUNWAREMODEL","links":[8],"slot_index":0}],"properties":{"Node name for S&R":"Runware Model Search"},"widgets_values":["","All","Base Model","runware:101@1 (Flux Dev)"],"bgcolor":"#6c5ce7"},{"id":3,"type":"Runware Image Inference","pos":[-77.49113464355469,-239.42645263671875],"size":[400,602],"flags":{},"order":2,"mode":0,"inputs":[{"name":"Model","type":"RUNWAREMODEL","link":2},{"name":"Lora","type":"RUNWARELORA","link":null,"shape":7},{"name":"ControlNet","type":"RUNWARECONTROLNET","link":null,"shape":7},{"name":"Refiner","type":"RUNWAREREFINER","link":null,"shape":7},{"name":"seedImage","type":"IMAGE","link":null,"shape":7},{"name":"maskImage","type":"MASK","link":null,"shape":7},{"name":"Embeddings","type":"RUNWAREEMBEDDING","link":null,"shape":7},{"name":"VAE","type":"RUNWAREVAE","link":null,"shape":7}],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[1,3],"slot_index":0}],"properties":{"Node name for S&R":"Runware Image Inference"},"widgets_values":["a man standing in the woods and looking serious, wide screen, zoomed out, realistic, HD, details","","Disabled","Square HD (1024x1024)",1024,1024,20,"Default",4.5,502840077979554,"randomize",0,0.8,false,32,1],"bgcolor":"#6c5ce7"},{"id":5,"type":"Runware Image Inference","pos":[700.1026611328125,-276.35955810546875],"size":[421.96026611328125,602],"flags":{},"order":5,"mode":0,"inputs":[{"name":"Model","type":"RUNWAREMODEL","link":8},{"name":"Lora","type":"RUNWARELORA","link":null,"shape":7},{"name":"ControlNet","type":"RUNWARECONTROLNET","link":null,"shape":7},{"name":"Refiner","type":"RUNWAREREFINER","link":null,"shape":7},{"name":"seedImage","type":"IMAGE","link":4,"shape":7},{"name":"maskImage","type":"MASK","link":5,"shape":7},{"name":"Embeddings","type":"RUNWAREEMBEDDING","link":null,"shape":7},{"name":"VAE","type":"RUNWAREVAE","link":null,"shape":7}],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[7],"slot_index":0}],"properties":{"Node name for S&R":"Runware Image Inference"},"widgets_values":["a man standing in the woods and looking serious, wide screen, zoomed out, realistic, HD, details","","Disabled","Square HD (1024x1024)",1024,1024,30,"Default",2,1108798832542204,"randomize",0,0.8,true,32,1],"bgcolor":"#6c5ce7"}],"links":[[1,3,0,1,0,"IMAGE"],[2,2,0,3,0,"RUNWAREMODEL"],[3,3,0,4,0,"IMAGE"],[4,4,0,5,4,"IMAGE"],[5,4,2,5,5,"MASK"],[7,5,0,6,0,"IMAGE"],[8,7,0,5,0,"RUNWAREMODEL"]],"groups":[],"config":{},"extra":{"ds":{"scale":1.001808834538306,"offset":[518.6927968058118,348.6661916601252]}},"version":0.4}
\ No newline at end of file
diff --git a/workflows/Runware_Basic_Image_Inference.json b/workflows/Runware_Basic_Image_Inference.json
index 91bd028..ffff184 100644
--- a/workflows/Runware_Basic_Image_Inference.json
+++ b/workflows/Runware_Basic_Image_Inference.json
@@ -1 +1 @@
-{"last_node_id":79,"last_link_id":52,"nodes":[{"id":76,"type":"PreviewImage","pos":[890.173095703125,-194.4432373046875],"size":[442.2727355957031,469.6363525390625],"flags":{},"order":3,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":51}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"}},{"id":77,"type":"Runware Image Inference","pos":[401.4457092285156,-337.6249694824219],"size":[420,608],"flags":{},"order":2,"mode":0,"inputs":[{"name":"Model","type":"RUNWAREMODEL","link":52},{"name":"Lora","type":"RUNWARELORA","link":null,"shape":7},{"name":"ControlNet","type":"RUNWARECONTROLNET","link":null,"shape":7},{"name":"Refiner","type":"RUNWAREREFINER","link":null,"shape":7},{"name":"seedImage","type":"IMAGE","link":null,"shape":7},{"name":"maskImage","type":"MASK","link":null,"shape":7}],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[51],"slot_index":0}],"properties":{"Node name for S&R":"Runware Image Inference"},"widgets_values":["A rebellious model with sharp features adorned with gold make-up and black eyeliner with lavander bob cut. A black off-shoulder top with a pink cats print pattern and choker. She posing in a vibrant, vivid color palette setting with ambient lighting, her expression calm and composed. The scene is painted in Patrick Nagel's painting style, with rich, smooth brushstrokes and a soft, warm color grading. The lighting is soft and diffused, creating a gentle glow around her. ArcaneFGTNR, Niji Stan Katayama Style, cyb3rp0p","",false,"Square (512x512)",512,512,4,"Default",6.5,697387220709399,"randomize",2,0.8,false,32,1],"bgcolor":"#6c5ce7"},{"id":79,"type":"Note","pos":[-46.554290771484375,-124.62498474121094],"size":[418,327],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["Hello there! 🌟\n\nWelcome to the Runware Image Inference workflow. 🎉\n\nHere’s what you need to know to get started:  \n\n- You can explore and search from a variety of models. 🧠✨\n  \n- Remember to adjust the settings appropriately to achieve the desired results. ⚙️✅\n\n- Don’t forget to tweak the **\"steps\"** for optimal performance. 🛠️📈\n\nThe best part? We support a wide range of models, so dive in and have fun experimenting! 🚀❤️\n\nEnjoy your creative journey! 💡😊\n\n\ntip: Press \"Ctrl + Alt + E\" To Automatically Enhance Your Prompt\n\ntip: You can reset the model, lora search by clearing the search input and everything will get back to defaults."],"color":"#432","bgcolor":"#653"},{"id":78,"type":"Runware Model Search","pos":[5.445709228515625,-324.625],"size":[315,130],"flags":{"collapsed":false},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"Runware Model","type":"RUNWAREMODEL","links":[52],"slot_index":0}],"properties":{"Node name for S&R":"Runware Model Search"},"widgets_values":["","All","Base Model","runware:100@1 (Flux Schnell)"],"bgcolor":"#6c5ce7"}],"links":[[51,77,0,76,0,"IMAGE"],[52,78,0,77,0,"RUNWAREMODEL"]],"groups":[],"config":{},"extra":{"ds":{"scale":1,"offset":[260.5542915265911,467.0624812864706]}},"version":0.4}
\ No newline at end of file
+{"last_node_id":79,"last_link_id":52,"nodes":[{"id":76,"type":"PreviewImage","pos":[890.173095703125,-194.4432373046875],"size":[442.2727355957031,469.6363525390625],"flags":{},"order":3,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":51}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":78,"type":"Runware Model Search","pos":[5.445709228515625,-324.625],"size":[315,130],"flags":{"collapsed":false},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"Runware Model","type":"RUNWAREMODEL","links":[52],"slot_index":0}],"properties":{"Node name for S&R":"Runware Model Search"},"widgets_values":["","All","Base Model","runware:100@1 (Flux Schnell)"],"bgcolor":"#6c5ce7"},{"id":77,"type":"Runware Image Inference","pos":[401.4457092285156,-337.6249694824219],"size":[462.1487731933594,735.272705078125],"flags":{},"order":2,"mode":0,"inputs":[{"name":"Model","type":"RUNWAREMODEL","link":52},{"name":"Lora","type":"RUNWARELORA","link":null,"shape":7},{"name":"ControlNet","type":"RUNWARECONTROLNET","link":null,"shape":7},{"name":"Refiner","type":"RUNWAREREFINER","link":null,"shape":7},{"name":"seedImage","type":"IMAGE","link":null,"shape":7},{"name":"maskImage","type":"MASK","link":null,"shape":7},{"name":"Embeddings","type":"RUNWAREEMBEDDING","link":null,"shape":7},{"name":"VAE","type":"RUNWAREVAE","link":null,"shape":7}],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[51],"slot_index":0}],"properties":{"Node name for S&R":"Runware Image Inference"},"widgets_values":["abstract, 1girl, solo, 25 years old, perfect face, close view, dark purple hair, spiked hair, ear piercing, spiked collar, black hoodie, winter, blush, shy smile, portrait, face focus, depth of field, looking at viewer, cinematic lighting, studio quality, symmetrical centered symmetrical artwork, style of krenz cushart, Jordan Grimmer, donato giancola, wlop, artgerm, ultra delicate minimalism, ilya kuvshinov, rossdraws, Norman Rockwell,","","Disabled","Square (512x512)",512,512,4,"Default",6.5,1115161573669306,"randomize",2,0.8,false,32,1],"bgcolor":"#6c5ce7"},{"id":79,"type":"Note","pos":[-61.95427703857422,-118.02499389648438],"size":[432.87603759765625,351.79339599609375],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["Hello there! 🌟\n\nWelcome to the Runware Image Inference workflow. 🎉\n\nHere’s what you need to know to get started:  \n\n- You will need to add your API Key just run the workflow and you will be prompted for that, if you don't have an account you can create a new account and you will get \"Free Credits\" to start :)\n\n- You can explore and search from a variety of models. 🧠✨\n  \n- Remember to adjust the settings appropriately to achieve the desired results. ⚙️✅\n\n- Don’t forget to tweak the \"steps\" for optimal performance. 🛠️📈\n\nThe best part? We support a wide range of models, so dive in and have fun experimenting! 🚀❤️\n\ntip: Press \"Ctrl + Alt + E\" To Automatically Enhance Your Prompt\n\ntip: You can reset the model, lora search by clearing the search input and everything will get back to defaults."],"color":"#432","bgcolor":"#653"}],"links":[[51,77,0,76,0,"IMAGE"],[52,78,0,77,0,"RUNWAREMODEL"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.9090909090909091,"offset":[533.379187367039,448.4813355624458]}},"version":0.4}
\ No newline at end of file
diff --git a/workflows/Runware_Basic_Image_Inference_Lora.json b/workflows/Runware_Basic_Image_Inference_Lora.json
index b5f194d..c6e4e6c 100644
--- a/workflows/Runware_Basic_Image_Inference_Lora.json
+++ b/workflows/Runware_Basic_Image_Inference_Lora.json
@@ -1 +1 @@
-{"last_node_id":4,"last_link_id":3,"nodes":[{"id":3,"type":"Runware Model Search","pos":[-170.87696838378906,-336.2454528808594],"size":[315,130],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"Runware Model","type":"RUNWAREMODEL","links":[2],"slot_index":0}],"properties":{"Node name for S&R":"Runware Model Search"},"widgets_values":["","All","Base Model","runware:100@1 (Flux Schnell)"],"bgcolor":"#6c5ce7"},{"id":2,"type":"Runware Image Inference","pos":[191.5845489501953,-370.3477478027344],"size":[410.71795654296875,598.05126953125],"flags":{},"order":2,"mode":0,"inputs":[{"name":"Model","type":"RUNWAREMODEL","link":2},{"name":"Lora","type":"RUNWARELORA","link":3,"shape":7},{"name":"ControlNet","type":"RUNWARECONTROLNET","link":null,"shape":7},{"name":"Refiner","type":"RUNWAREREFINER","link":null,"shape":7},{"name":"seedImage","type":"IMAGE","link":null,"shape":7},{"name":"maskImage","type":"MASK","link":null,"shape":7}],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[1],"slot_index":0}],"properties":{"Node name for S&R":"Runware Image Inference"},"widgets_values":["a guy wearing red glasses, anime, pixiv top monthly, trending on artstation, cinematic, danbooru, zerochan art, kyoto animation, niji","",false,"Square (512x512)",512,512,4,"Default",6.5,258656211183721,"randomize",0,0.8,false,32,1],"bgcolor":"#6c5ce7"},{"id":4,"type":"Runware Lora Search","pos":[-162.10772705078125,-143.322265625],"size":[315,154],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"Runware Lora","type":"RUNWARELORA","links":[3],"slot_index":0}],"properties":{"Node name for S&R":"Runware Lora Search"},"widgets_values":["niji","FLUX.1-Schnell","Lora","civitai:768440@859463 (Flux-Better-Art-With-Niji Schnell)",1],"bgcolor":"#6c5ce7"},{"id":1,"type":"PreviewImage","pos":[627.12255859375,-365.4764404296875],"size":[458.46142578125,484.9228515625],"flags":{},"order":3,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":1}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"}}],"links":[[1,2,0,1,0,"IMAGE"],[2,3,0,2,0,"RUNWAREMODEL"],[3,4,0,2,1,"RUNWARELORA"]],"groups":[],"config":{},"extra":{"ds":{"scale":1.0263162364614136,"offset":[606.4152342088262,463.3381111055449]}},"version":0.4}
\ No newline at end of file
+{"last_node_id":4,"last_link_id":3,"nodes":[{"id":3,"type":"Runware Model Search","pos":[-170.87696838378906,-336.2454528808594],"size":[315,130],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"Runware Model","type":"RUNWAREMODEL","links":[2],"slot_index":0}],"properties":{"Node name for S&R":"Runware Model Search"},"widgets_values":["","All","Base Model","runware:100@1 (Flux Schnell)"],"bgcolor":"#6c5ce7"},{"id":4,"type":"Runware Lora Search","pos":[-162.10772705078125,-143.322265625],"size":[315,196],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"Runware Lora","type":"RUNWARELORA","links":[3],"slot_index":0}],"properties":{"Node name for S&R":"Runware Lora Search"},"widgets_values":["niji","FLUX.1-Schnell","Lora","civitai:768440@859463 (Flux-Better-Art-With-Niji Schnell)",1,null],"bgcolor":"#6c5ce7"},{"id":1,"type":"PreviewImage","pos":[627.12255859375,-365.4764404296875],"size":[458.46142578125,484.9228515625],"flags":{},"order":3,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":1}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":2,"type":"Runware Image Inference","pos":[191.5845489501953,-370.3477478027344],"size":[411.69232177734375,628.3076782226562],"flags":{},"order":2,"mode":0,"inputs":[{"name":"Model","type":"RUNWAREMODEL","link":2},{"name":"Lora","type":"RUNWARELORA","link":3,"shape":7},{"name":"ControlNet","type":"RUNWARECONTROLNET","link":null,"shape":7},{"name":"Refiner","type":"RUNWAREREFINER","link":null,"shape":7},{"name":"seedImage","type":"IMAGE","link":null,"shape":7},{"name":"maskImage","type":"MASK","link":null,"shape":7},{"name":"Embeddings","type":"RUNWAREEMBEDDING","link":null,"shape":7},{"name":"VAE","type":"RUNWAREVAE","link":null,"shape":7}],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[1],"slot_index":0}],"properties":{"Node name for S&R":"Runware Image Inference"},"widgets_values":["a guy wearing red glasses, anime, pixiv top monthly, trending on artstation, cinematic, danbooru, zerochan art, kyoto animation, niji","","Disabled","Square (512x512)",512,512,4,"Default",6.5,258656211183721,"randomize",0,0.8,false,32,1],"bgcolor":"#6c5ce7"}],"links":[[1,2,0,1,0,"IMAGE"],[2,3,0,2,0,"RUNWAREMODEL"],[3,4,0,2,1,"RUNWARELORA"]],"groups":[],"config":{},"extra":{"ds":{"scale":1.0263162364614136,"offset":[606.4152342088262,463.3381111055449]}},"version":0.4}
\ No newline at end of file
diff --git a/workflows/Runware_Basic_Image_Upscaling.json b/workflows/Runware_Basic_Image_Upscaling.json
index edc4f0d..c995eec 100644
--- a/workflows/Runware_Basic_Image_Upscaling.json
+++ b/workflows/Runware_Basic_Image_Upscaling.json
@@ -1 +1 @@
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diff --git a/workflows/Runware_ControlNet.json b/workflows/Runware_ControlNet.json
index 99618f8..5a1a6dd 100644
--- a/workflows/Runware_ControlNet.json
+++ b/workflows/Runware_ControlNet.json
@@ -1 +1 @@
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diff --git a/workflows/Runware_Image_Inference_Embedding.json b/workflows/Runware_Image_Inference_Embedding.json
new file mode 100644
index 0000000..4007012
--- /dev/null
+++ b/workflows/Runware_Image_Inference_Embedding.json
@@ -0,0 +1 @@
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diff --git a/workflows/Runware_Image_Inference_Refiner.json b/workflows/Runware_Image_Inference_Refiner.json
index 20c63b8..437cbec 100644
--- a/workflows/Runware_Image_Inference_Refiner.json
+++ b/workflows/Runware_Image_Inference_Refiner.json
@@ -1 +1 @@
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diff --git a/workflows/Runware_Image_Inference_VAE.json b/workflows/Runware_Image_Inference_VAE.json
new file mode 100644
index 0000000..cb00458
--- /dev/null
+++ b/workflows/Runware_Image_Inference_VAE.json
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/workflows/Runware_Inpainting.json b/workflows/Runware_Inpainting.json
index d290f39..b734973 100644
--- a/workflows/Runware_Inpainting.json
+++ b/workflows/Runware_Inpainting.json
@@ -1 +1 @@
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\ No newline at end of file
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\ No newline at end of file
diff --git a/workflows/Runware_PhotoMaker_v2.json b/workflows/Runware_PhotoMaker_v2.json
index a14adee..2503548 100644
--- a/workflows/Runware_PhotoMaker_v2.json
+++ b/workflows/Runware_PhotoMaker_v2.json
@@ -1 +1 @@
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\ No newline at end of file
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