diff --git a/.DS_Store b/.DS_Store
index 44ce87d..efed26e 100644
Binary files a/.DS_Store and b/.DS_Store differ
diff --git a/__init__.py b/__init__.py
index 509bb5b..4d45665 100644
--- a/__init__.py
+++ b/__init__.py
@@ -40,6 +40,13 @@ from .modules.elevenlabsProviderSettingsSections import RunwareElevenLabsProvide
 from .modules.acceleratorOptions import acceleratorOptions
 from .modules.viduProviderSettings import RunwareViduProviderSettings
 from .modules.mediaUpload import runwareMediaUpload
+from .modules.inputAudios import inputAudios
+from .modules.referenceVideos import referenceVideos
+from .modules.videoInferenceInputs import videoInferenceInputs
+from .modules.lightricksProviderSettings import RunwareLightricksProviderSettings
+from .modules.vectorize import vectorize
+from .modules.videoBgRemoval import videoBgRemoval
+from .modules.videoUpscaler import videoUpscaler
 
 RUNWARE_COMFYUI_VERSION = "1.4.0 Beta"
 
@@ -94,6 +101,13 @@ NODE_CLASS_MAPPINGS = {
     "Runware Accelerator Options": acceleratorOptions,
     "Runware Vidu Provider Settings": RunwareViduProviderSettings,
     "Runware Media Upload": runwareMediaUpload,
+    "Runware Input Audios": inputAudios,
+    "Runware Reference Videos": referenceVideos,
+    "Runware Video Inference Inputs": videoInferenceInputs,
+    "Runware Lightricks Provider Settings": RunwareLightricksProviderSettings,
+    "Runware Vectorize": vectorize,
+    "Runware Video Background Removal": videoBgRemoval,
+    "Runware Video Upscaler": videoUpscaler,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
diff --git a/clientlibs/main.js b/clientlibs/main.js
index 4fe1045..6fe9ecb 100644
--- a/clientlibs/main.js
+++ b/clientlibs/main.js
@@ -29,6 +29,15 @@ app.registerExtension({
             captionInput.style.outline = "none";
             captionInput.readOnly = true;
             return;
+        } else if(nodeClass === RUNWARE_NODE_TYPES.MEDIAUPLOAD) {
+            // Style the mediaUUID widget to show full UUID
+            const mediaUUIDWidget = node.widgets.find(widget => widget.name === "mediaUUID");
+            if(mediaUUIDWidget && mediaUUIDWidget.inputEl) {
+                mediaUUIDWidget.inputEl.style.width = "100%";
+                mediaUUIDWidget.inputEl.style.minWidth = "300px";
+                mediaUUIDWidget.inputEl.style.fontSize = "11px";
+                mediaUUIDWidget.inputEl.style.fontFamily = "monospace";
+            }
         }
 
         if(crNodeProps.colorModeOnly === true) return;
diff --git a/clientlibs/types.js b/clientlibs/types.js
index 5d24174..7ae05cc 100644
--- a/clientlibs/types.js
+++ b/clientlibs/types.js
@@ -89,6 +89,13 @@ const RUNWARE_NODE_TYPES = {
     ELEVENLABSPROVIDERSETTINGSSECTIONS: "Runware ElevenLabs Provider Settings Sections",
     VIDUPROVIDERSETTINGS: "Runware Vidu Provider Settings",
     MEDIAUPLOAD: "Runware Media Upload",
+    INPUTAUDIOS: "Runware Input Audios",
+    REFERENCEVIDEOS: "Runware Reference Videos",
+    VIDEOINFERENCEINPUTS: "Runware Video Inference Inputs",
+    LIGHTRICKSPROVIDERSETTINGS: "Runware Lightricks Provider Settings",
+    VECTORIZE: "Runware Vectorize",
+    VIDEOBGREMOVAL: "Runware Video Background Removal",
+    VIDEOUPSCALER: "Runware Video Upscaler",
 };
 
 const RUNWARE_NODE_PROPS = {
@@ -259,6 +266,31 @@ const RUNWARE_NODE_PROPS = {
         bgColor: DEFAULT_BGCOLOR,
         colorModeOnly: true,
     },
+    [RUNWARE_NODE_TYPES.INPUTAUDIOS]: {
+        bgColor: DEFAULT_BGCOLOR,
+        colorModeOnly: true,
+    },
+    [RUNWARE_NODE_TYPES.REFERENCEVIDEOS]: {
+        bgColor: DEFAULT_BGCOLOR,
+        colorModeOnly: true,
+    },
+    [RUNWARE_NODE_TYPES.VIDEOINFERENCEINPUTS]: {
+        bgColor: DEFAULT_BGCOLOR,
+        colorModeOnly: true,
+    },
+    [RUNWARE_NODE_TYPES.LIGHTRICKSPROVIDERSETTINGS]: {
+        bgColor: DEFAULT_BGCOLOR,
+        colorModeOnly: true,
+    },
+    [RUNWARE_NODE_TYPES.VECTORIZE]: {
+        bgColor: DEFAULT_BGCOLOR,
+    },
+    [RUNWARE_NODE_TYPES.VIDEOBGREMOVAL]: {
+        bgColor: DEFAULT_BGCOLOR,
+    },
+    [RUNWARE_NODE_TYPES.VIDEOUPSCALER]: {
+        bgColor: DEFAULT_BGCOLOR,
+    },
 };
 
 export {
diff --git a/clientlibs/utils.js b/clientlibs/utils.js
index a1e63a5..dd05aa6 100644
--- a/clientlibs/utils.js
+++ b/clientlibs/utils.js
@@ -47,11 +47,23 @@ function mediaUUIDHandler(msgEvent) {
     
     if(mediaData.success) {
         const mediaNode = app.graph.getNodeById(mediaNodeID);
+        
         if(mediaNode !== null && mediaNode !== undefined) {
             // Find the mediaUUID widget specifically
             const mediaUUIDWidget = mediaNode.widgets.find(widget => widget.name === "mediaUUID");
-            if(mediaUUIDWidget && mediaUUIDWidget.inputEl) {
-                mediaUUIDWidget.inputEl.value = mediaUUID;
+            
+            if(mediaUUIDWidget) {
+                // Update both widget.value and inputEl.value for STRING widgets
+                if(mediaUUIDWidget.value !== undefined) {
+                    mediaUUIDWidget.value = mediaUUID;
+                }
+                
+                if(mediaUUIDWidget.inputEl) {
+                    mediaUUIDWidget.inputEl.value = mediaUUID;
+                    // Trigger change events to update the UI
+                    mediaUUIDWidget.inputEl.dispatchEvent(new Event('input', { bubbles: true }));
+                    mediaUUIDWidget.inputEl.dispatchEvent(new Event('change', { bubbles: true }));
+                }
             }
         }
     }
diff --git a/modules/bytedanceImageProviderSettings.py b/modules/bytedanceImageProviderSettings.py
index 9bf8529..4daa5c7 100644
--- a/modules/bytedanceImageProviderSettings.py
+++ b/modules/bytedanceImageProviderSettings.py
@@ -3,7 +3,6 @@ Runware Bytedance Image Provider Settings Node
 Provides Bytedance-specific settings for image generation
 """
 
-import torch
 from typing import Optional, Dict, Any
 
 class RunwareBytedanceProviderSettings:
@@ -14,16 +13,32 @@ class RunwareBytedanceProviderSettings:
         return {
             "required": {},
             "optional": {
+                "useCameraFixed": ("BOOLEAN", {
+                    "tooltip": "Enable to include cameraFixed parameter in provider settings",
+                    "default": False,
+                }),
                 "cameraFixed": ("BOOLEAN", {
                     "tooltip": "Enable to fix camera position during video generation",
                     "default": False,
                 }),
+                "useMaxSequentialImages": ("BOOLEAN", {
+                    "tooltip": "Enable to include maxSequentialImages parameter in provider settings",
+                    "default": False,
+                }),
                 "maxSequentialImages": ("INT", {
                     "tooltip": "Maximum number of sequential images to generate (1-15)",
                     "default": 1,
                     "min": 1,
                     "max": 15,
                 }),
+                "useFastMode": ("BOOLEAN", {
+                    "tooltip": "Enable to include fastMode parameter in provider settings",
+                    "default": False,
+                }),
+                "fastMode": ("BOOLEAN", {
+                    "tooltip": "When enabled, speeds up generation by sacrificing some effects. Default: false. RTF: 25-28 (fast) vs 35 (normal). Supported by OmniHuman 1.5.",
+                    "default": False,
+                }),
             }
         }
     
@@ -35,21 +50,31 @@ class RunwareBytedanceProviderSettings:
     def create_provider_settings(self, **kwargs) -> tuple[Dict[str, Any]]:
         """Create Bytedance provider settings"""
         
-        # Get parameters
+        # Get control parameters
+        useCameraFixed = kwargs.get("useCameraFixed", False)
+        useMaxSequentialImages = kwargs.get("useMaxSequentialImages", False)
+        useFastMode = kwargs.get("useFastMode", False)
+        
+        # Get value parameters
         cameraFixed = kwargs.get("cameraFixed", False)
         maxSequentialImages = kwargs.get("maxSequentialImages", 1)
+        fastMode = kwargs.get("fastMode", False)
         
-        # Build settings dictionary
+        # Build settings dictionary - only include what is enabled
         settings = {}
         
-        # Add cameraFixed only if it's true
-        if cameraFixed is True:
+        # Add cameraFixed only if useCameraFixed is enabled
+        if useCameraFixed:
             settings["cameraFixed"] = cameraFixed
         
-        # Add maxSequentialImages if provided and valid
-        if maxSequentialImages is not None and 1 <= maxSequentialImages <= 15:
+        # Add maxSequentialImages only if useMaxSequentialImages is enabled
+        if useMaxSequentialImages:
             settings["maxSequentialImages"] = maxSequentialImages
         
+        # Add fastMode only if useFastMode is enabled
+        if useFastMode:
+            settings["fastMode"] = fastMode
+        
         # Clean up None values
         settings = {k: v for k, v in settings.items() if v is not None}
         
diff --git a/modules/inputAudios.py b/modules/inputAudios.py
new file mode 100644
index 0000000..bee8968
--- /dev/null
+++ b/modules/inputAudios.py
@@ -0,0 +1,39 @@
+from .utils import runwareUtils as rwUtils
+from typing import List, Dict, Any
+
+class inputAudios:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {},
+            "optional": {
+                "Audio1": ("STRING", {
+                    "tooltip": "MediaUUID for the first audio file from Runware Media Upload node.",
+                }),
+                "Audio2": ("STRING", {
+                    "tooltip": "MediaUUID for the second audio file from Runware Media Upload node.",
+                }),
+                "Audio3": ("STRING", {
+                    "tooltip": "MediaUUID for the third audio file from Runware Media Upload node.",
+                }),
+                "Audio4": ("STRING", {
+                    "tooltip": "MediaUUID for the fourth audio file from Runware Media Upload node.",
+                }),
+            }
+        }
+
+    DESCRIPTION = "Configure multiple audio inputs (mediaUUIDs) for video generation with audio synchronization."
+    FUNCTION = "createInputAudios"
+    RETURN_TYPES = ("RUNWAREINPUTAUDIOS",)
+    RETURN_NAMES = ("Input Audios",)
+    CATEGORY = "Runware"
+
+    def createInputAudios(self, **kwargs) -> tuple[List[str]]:
+        audio_list = []
+        for i in range(1, 5):
+            audio_key = f"Audio{i}"
+            audio_uuid = kwargs.get(audio_key)
+            if audio_uuid and audio_uuid.strip() != "":
+                audio_list.append(audio_uuid.strip())
+        return (audio_list,)
+
diff --git a/modules/lightricksProviderSettings.py b/modules/lightricksProviderSettings.py
new file mode 100644
index 0000000..feed2ef
--- /dev/null
+++ b/modules/lightricksProviderSettings.py
@@ -0,0 +1,51 @@
+"""
+Runware Lightricks Provider Settings Node
+Provides Lightricks-specific settings for video generation
+"""
+
+from typing import Optional, Dict, Any
+
+class RunwareLightricksProviderSettings:
+    """Runware Lightricks Provider Settings Node"""
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {},
+            "optional": {
+                "generateAudio": ("BOOLEAN", {
+                    "tooltip": "Enable to generate audio for the video. Default: false.",
+                    "default": False,
+                }),
+            }
+        }
+    
+    RETURN_TYPES = ("RUNWAREPROVIDERSETTINGS",)
+    RETURN_NAMES = ("providerSettings",)
+    FUNCTION = "create_provider_settings"
+    CATEGORY = "Runware/Provider Settings"
+    
+    def create_provider_settings(self, **kwargs) -> tuple[Dict[str, Any]]:
+        """Create Lightricks provider settings"""
+        
+        # Get value parameters
+        generateAudio = kwargs.get("generateAudio", False)
+        
+        # Build settings dictionary
+        settings = {}
+        
+        # Add generateAudio if it's True
+        if generateAudio:
+            settings["generateAudio"] = generateAudio
+        
+        return (settings,)
+
+# Node class mappings
+NODE_CLASS_MAPPINGS = {
+    "RunwareLightricksProviderSettings": RunwareLightricksProviderSettings,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "RunwareLightricksProviderSettings": "Runware Lightricks Provider Settings",
+}
+
diff --git a/modules/mediaUpload.py b/modules/mediaUpload.py
index c974a4e..6a65baa 100644
--- a/modules/mediaUpload.py
+++ b/modules/mediaUpload.py
@@ -29,7 +29,6 @@ class RunwareMediaUpload:
                     "tooltip": "Media tensor from ComfyUI load video or audio node",
                 }),
                 "mediaUUID": ("STRING", {
-                    "multiline": True,
                     "placeholder": "Generated media UUID will appear here automatically.",
                     "tooltip": "This field will be automatically populated with the generated media UUID after upload.",
                 }),
diff --git a/modules/referenceVideos.py b/modules/referenceVideos.py
new file mode 100644
index 0000000..f89c2ca
--- /dev/null
+++ b/modules/referenceVideos.py
@@ -0,0 +1,39 @@
+from .utils import runwareUtils as rwUtils
+from typing import List, Dict, Any
+
+class referenceVideos:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {},
+            "optional": {
+                "Video1": ("STRING", {
+                    "tooltip": "MediaUUID for the first reference video from Runware Media Upload node.",
+                }),
+                "Video2": ("STRING", {
+                    "tooltip": "MediaUUID for the second reference video from Runware Media Upload node.",
+                }),
+                "Video3": ("STRING", {
+                    "tooltip": "MediaUUID for the third reference video from Runware Media Upload node.",
+                }),
+                "Video4": ("STRING", {
+                    "tooltip": "MediaUUID for the fourth reference video from Runware Media Upload node.",
+                }),
+            }
+        }
+
+    DESCRIPTION = "Configure multiple reference video inputs (mediaUUIDs) for video generation."
+    FUNCTION = "createReferenceVideos"
+    RETURN_TYPES = ("RUNWAREREFERENCEVIDEOS",)
+    RETURN_NAMES = ("Reference Videos",)
+    CATEGORY = "Runware"
+
+    def createReferenceVideos(self, **kwargs) -> tuple[List[str]]:
+        video_list = []
+        for i in range(1, 5):
+            video_key = f"Video{i}"
+            video_uuid = kwargs.get(video_key)
+            if video_uuid and video_uuid.strip() != "":
+                video_list.append(video_uuid.strip())
+        return (video_list,)
+
diff --git a/modules/vectorize.py b/modules/vectorize.py
new file mode 100644
index 0000000..f37b3ab
--- /dev/null
+++ b/modules/vectorize.py
@@ -0,0 +1,93 @@
+from .utils import runwareUtils as rwUtils
+import json
+
+class vectorize:
+    RUNWARE_VECTORIZE_MODELS = {
+        "recraft:1@1": "recraft:1@1",
+        "picsart:1@1": "picsart:1@1",
+    }
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "Image": ("IMAGE", {
+                    "tooltip": "Input image to be vectorized."
+                }),
+                "Model": (list(cls.RUNWARE_VECTORIZE_MODELS.keys()), {
+                    "tooltip": "Select the vectorization model to use.",
+                    "default": "recraft:1@1",
+                }),
+            },
+        }
+
+    DESCRIPTION = "Convert images to vector format using Runware's vectorization service."
+    FUNCTION = "vectorizeImage"
+    RETURN_TYPES = ("IMAGE", "STRING")
+    RETURN_NAMES = ("IMAGE", "Vector Data")
+    CATEGORY = "Runware"
+
+    def vectorizeImage(self, **kwargs):
+        image = kwargs.get("Image")
+        modelName = kwargs.get("Model", "recraft:1@1")
+        
+        # Get the model AIR code
+        model = self.RUNWARE_VECTORIZE_MODELS.get(modelName, "recraft:1@1")
+        
+        # Convert image to UUID
+        image_uuid = rwUtils.convertTensor2IMG(image)
+        
+        # Build the API request
+        genConfig = [
+            {
+                "taskType": "vectorize",
+                "taskUUID": rwUtils.genRandUUID(),
+                "model": model,
+                "inputs": {
+                    "image": image_uuid
+                },
+            }
+        ]
+        
+        try:
+            # Debug: Print the request being sent
+            print(f"[DEBUG] Sending Vectorize Request:")
+            print(f"[DEBUG] Request Payload: {json.dumps(genConfig, indent=2)}")
+            
+            genResult = rwUtils.inferenecRequest(genConfig)
+            
+            # Debug: Print the response received
+            print(f"[DEBUG] Received Vectorize Response:")
+            print(f"[DEBUG] Response: {json.dumps(genResult, indent=2)}")
+            
+            # Check for errors
+            if "errors" in genResult:
+                error_message = genResult["errors"][0]["message"]
+                raise Exception(f"Vectorization failed: {error_message}")
+            
+            # Extract the result
+            if "data" in genResult and len(genResult["data"]) > 0:
+                result_data = genResult["data"][0]
+                
+                # Return the vectorized image URL
+                if "imageURL" in result_data:
+                    vector_url = result_data["imageURL"]
+                    return (image, vector_url)
+                else:
+                    raise Exception("imageURL not found in response")
+            else:
+                raise Exception("No data returned from vectorization API")
+                
+        except Exception as e:
+            print(f"[Error] Vectorization failed: {str(e)}")
+            raise e
+
+# Node class mappings
+NODE_CLASS_MAPPINGS = {
+    "RunwareVectorize": vectorize,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "RunwareVectorize": "Runware Vectorize",
+}
+
diff --git a/modules/videoBgRemoval.py b/modules/videoBgRemoval.py
new file mode 100644
index 0000000..7801fb7
--- /dev/null
+++ b/modules/videoBgRemoval.py
@@ -0,0 +1,155 @@
+from .utils import runwareUtils as rwUtils
+import json
+import comfy.model_management
+
+class videoBgRemoval:
+    RUNWARE_VRMBG_MODELS = {
+        "bria:51@1": "bria:51@1",
+    }
+    
+    BACKGROUND_COLORS = {
+        "Transparent": [0, 0, 0, 0],
+        "Black": [0, 0, 0, 1],
+        "White": [255, 255, 255, 0],
+        "Gray": [128, 128, 128, 0],
+        "Red": [255, 0, 0, 0],
+        "Green": [0, 255, 0, 0],
+        "Blue": [0, 0, 255, 0],
+        "Yellow": [255, 255, 0, 0],
+        "Cyan": [0, 255, 255, 0],
+        "Magenta": [255, 0, 255, 0],
+        "Orange": [255, 165, 0, 0],
+    }
+    
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "Video": ("STRING", {
+                    "tooltip": "MediaUUID from Runware Media Upload node for the video to process (max 30 seconds). Supports resolution up to 16000x16000 (16K)."
+                }),
+                "Model": (list(cls.RUNWARE_VRMBG_MODELS.keys()), {
+                    "tooltip": "Select the video background removal model to use.",
+                    "default": "Bria Video Background Removal",
+                }),
+            },
+            "optional": {
+                "Background Color": (list(cls.BACKGROUND_COLORS.keys()), {
+                    "default": "Transparent",
+                    "tooltip": "Background color preset to use. Hex values are not supported.",
+                }),
+                "Output Format": (["mp4", "webm", "mov"], {
+                    "default": "mp4",
+                    "tooltip": "Choose the output video format.",
+                }),
+            }
+        }
+
+    DESCRIPTION = "Remove complex or moving video backgrounds in real time, isolating subjects with clean alpha channels for seamless compositing."
+    FUNCTION = "removeBackground"
+    RETURN_TYPES = ("VIDEO",)
+    RETURN_NAMES = ("VIDEO",)
+    CATEGORY = "Runware"
+
+    def removeBackground(self, **kwargs):
+        video_uuid = kwargs.get("Video")
+        modelName = kwargs.get("Model", "Bria Video Background Removal")
+        backgroundColor = kwargs.get("Background Color", "Transparent")
+        outputFormat = kwargs.get("Output Format", "mp4")
+        
+        # Validate mediaUUID
+        if not video_uuid or video_uuid.strip() == "":
+            raise ValueError("Video mediaUUID is required")
+        
+        # Get the model AIR code
+        modelAIR = self.RUNWARE_VRMBG_MODELS.get(modelName, "bria:51@1")
+        
+        # Get background color RGBA
+        rgba_color = self.BACKGROUND_COLORS.get(backgroundColor, [0, 0, 0, 0])
+        
+        # Build the API request
+        genConfig = [
+            {
+                "taskType": "removeBackground",
+                "taskUUID": rwUtils.genRandUUID(),
+                "inputs": {
+                    "video": video_uuid
+                },
+                "model": modelAIR,
+                "outputFormat": outputFormat,
+                "settings": {
+                    "rgba": rgba_color
+                }
+            }
+        ]
+        
+        try:
+            # Debug: Print the request being sent
+            print(f"[DEBUG] Sending Video Background Removal Request:")
+            print(f"[DEBUG] Request Payload: {json.dumps(genConfig, indent=2)}")
+            
+            genResult = rwUtils.inferenecRequest(genConfig)
+            
+            # Debug: Print the response received
+            print(f"[DEBUG] Received Video Background Removal Response:")
+            print(f"[DEBUG] Response: {json.dumps(genResult, indent=2)}")
+            
+            # Check for errors
+            if "errors" in genResult:
+                error_message = genResult["errors"][0]["message"]
+                raise Exception(f"Video background removal failed: {error_message}")
+            
+            # Extract task UUID for polling
+            taskUUID = genConfig[0]["taskUUID"]
+            
+            # Poll for video completion
+            while True:
+                # Check for interrupt before each poll
+                comfy.model_management.throw_exception_if_processing_interrupted()
+                
+                # Poll for video result
+                pollResult = rwUtils.pollVideoResult(taskUUID)
+                print(f"[Debugging] Poll result: {pollResult}")
+                
+                # Check for errors first
+                if pollResult and "errors" in pollResult and len(pollResult["errors"]) > 0:
+                    error_info = pollResult["errors"][0]
+                    error_message = error_info.get("message", "Unknown error")
+                    raise Exception(f"Video background removal failed: {error_message}")
+                
+                if pollResult and "data" in pollResult and len(pollResult["data"]) > 0:
+                    video_data = pollResult["data"][0]
+                    
+                    # Check status directly
+                    if "status" in video_data:
+                        status = video_data["status"]
+                        
+                        if status == "success":
+                            if "videoURL" in video_data or "videoBase64Data" in video_data:
+                                videos = rwUtils.convertVideoB64List(pollResult, 1920, 1080)
+                                return videos
+                        
+                        # If status is "processing", continue polling
+                
+                # Check for interrupt before waiting
+                comfy.model_management.throw_exception_if_processing_interrupted()
+                
+                # Wait before next poll
+                for _ in range(10):  # 10 x 0.1 second = 1 second total
+                    comfy.model_management.throw_exception_if_processing_interrupted()
+                    rwUtils.time.sleep(0.1)
+                        
+        except Exception as e:
+            print(f"[Error] Video background removal failed: {str(e)}")
+            raise e
+
+# Node class mappings
+NODE_CLASS_MAPPINGS = {
+    "RunwareVideoBgRemoval": videoBgRemoval,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "RunwareVideoBgRemoval": "Runware Video Background Removal",
+}
+
diff --git a/modules/videoInference.py b/modules/videoInference.py
index 5979e8f..07ac61f 100644
--- a/modules/videoInference.py
+++ b/modules/videoInference.py
@@ -84,16 +84,6 @@ class txt2vid:
                 "Model": ("RUNWAREVIDEOMODEL", {
                     "tooltip": "Connect a Runware Video Model From Runware Video Model Search Node.",
                 }),
-                "positivePrompt": ("STRING", {
-                    "multiline": True,
-                    "placeholder": "Positive Prompt: a text instruction to guide the model on generating the video. It is usually a sentence or a paragraph that provides positive guidance for the task. This parameter is essential to shape the desired results.\n\nYou Can Press (Ctrl + Alt + E) To Enhance The Prompt!",
-                    "tooltip": "Positive Prompt: a text instruction to guide the model on generating the video. You Can Also Press (Ctrl + Alt + E) To Enhance The Prompt!"
-                }),
-                "negativePrompt": ("STRING", {
-                    "multiline": True,
-                    "placeholder": "Negative Prompt: a text instruction to guide the model on generating the video. It is usually a sentence or a paragraph that provides negative guidance for the task. This parameter helps to avoid certain undesired results.",
-                    "tooltip": "Negative Prompt: a text instruction to guide the model on generating the video."
-                }),
                 "Multi Inference Mode": ("BOOLEAN", {
                     "tooltip": "If Enabled the node will skip the video generation process and will only return the Runware Task Object to be used in the Multi Inference Node.",
                     "default": False,
@@ -162,6 +152,16 @@ class txt2vid:
                 }),
             },
             "optional": {
+                "positivePrompt": ("STRING", {
+                    "multiline": True,
+                    "placeholder": "Positive Prompt: a text instruction to guide the model on generating the video. It is usually a sentence or a paragraph that provides positive guidance for the task. This parameter is essential to shape the desired results.\n\nYou Can Press (Ctrl + Alt + E) To Enhance The Prompt!",
+                    "tooltip": "Positive Prompt: a text instruction to guide the model on generating the video. You Can Also Press (Ctrl + Alt + E) To Enhance The Prompt!"
+                }),
+                "negativePrompt": ("STRING", {
+                    "multiline": True,
+                    "placeholder": "Negative Prompt: a text instruction to guide the model on generating the video. It is usually a sentence or a paragraph that provides negative guidance for the task. This parameter helps to avoid certain undesired results.",
+                    "tooltip": "Negative Prompt: a text instruction to guide the model on generating the video."
+                }),
                 "frameImages": ("RUNWAREFRAMEIMAGES", {
                     "tooltip": "Frame images configuration from Runware Frame Images node. Allows precise control over frame positioning.",
                 }),
@@ -174,17 +174,31 @@ class txt2vid:
                 "inputAudios": ("RUNWAREINPUTAUDIOS", {
                     "tooltip": "Connect input audio files for video generation with audio synchronization.",
                 }),
+                "referenceVideos": ("RUNWAREREFERENCEVIDEOS", {
+                    "tooltip": "Connect reference video files for video generation.",
+                }),
+                "speechVoice": ("STRING", {
+                    "tooltip": "Voice for speech synthesis. Specify the voice to use for text-to-speech generation.",
+                }),
+                "speechText": ("STRING", {
+                    "multiline": True,
+                    "tooltip": "Text for speech synthesis. The text that will be converted to speech using the specified voice.",
+                }),
+                "inputs": ("RUNWAREVIDEOINFERENCEINPUTS", {
+                    "tooltip": "Connect a Runware Video Inference Inputs node to provide custom inputs like image, audio, mask, and parameters for OmniHuman 1.5 and other video models.",
+                }),
             }
         }
 
     @classmethod
-    def VALIDATE_INPUTS(cls, positivePrompt, negativePrompt):
-        if (positivePrompt is not None and (positivePrompt == "" or len(positivePrompt) < 3 or len(positivePrompt) > 2000)):
-            raise Exception(
-                "Positive Prompt Must Be Between 3 And 2000 characters!")
-        if (negativePrompt is not None and negativePrompt != "" and (len(negativePrompt) < 3 or len(negativePrompt) > 2000)):
-            raise Exception(
-                "Negative Prompt Must Be Between 3 And 2000 characters!")
+    def VALIDATE_INPUTS(cls, positivePrompt=None, negativePrompt=None):
+        # Only validate if prompts are provided and not empty
+        if positivePrompt is not None and positivePrompt.strip() != "":
+            if len(positivePrompt) < 3 or len(positivePrompt) > 2000:
+                raise Exception("Positive Prompt Must Be Between 3 And 2000 characters!")
+        if negativePrompt is not None and negativePrompt.strip() != "":
+            if len(negativePrompt) < 3 or len(negativePrompt) > 2000:
+                raise Exception("Negative Prompt Must Be Between 3 And 2000 characters!")
         return True
 
     DESCRIPTION = "Generates Videos Lightning Fast With Runware Video Inference Engine."
@@ -203,6 +217,10 @@ class txt2vid:
         frameImages = kwargs.get("frameImages", None)
         referenceImages = kwargs.get("referenceImages", None)
         inputAudios = kwargs.get("inputAudios", None)
+        referenceVideos = kwargs.get("referenceVideos", None)
+        speechVoice = kwargs.get("speechVoice", None)
+        speechText = kwargs.get("speechText", None)
+        inputs = kwargs.get("inputs", None)
         useCustomDimensions = kwargs.get("useCustomDimensions", False)
         customWidth = kwargs.get("width", 864)
         customHeight = kwargs.get("height", 480)
@@ -235,7 +253,6 @@ class txt2vid:
             {
                 "taskType": "videoInference",
                 "taskUUID": rwUtils.genRandUUID(),
-                "positivePrompt": positivePrompt,
                 "height": height,
                 "width": width,
                 "model": model,
@@ -245,6 +262,10 @@ class txt2vid:
             }
         ]
         
+        # Only add positivePrompt if it's not empty
+        if positivePrompt and positivePrompt.strip() != "":
+            genConfig[0]["positivePrompt"] = positivePrompt
+        
         # Add fps parameter only if enabled
         if useFps:
             genConfig[0]["fps"] = fps
@@ -276,6 +297,37 @@ class txt2vid:
         if inputAudios is not None and len(inputAudios) > 0:
             genConfig[0]["inputAudios"] = inputAudios
             print(f"[Debugging] Input audios array: {inputAudios}")
+        
+        # Add referenceVideos if provided and not empty
+        if referenceVideos is not None:
+            # Handle both single mediaUUID (string) and multiple mediaUUIDs (list)
+            if isinstance(referenceVideos, str) and referenceVideos.strip() != "":
+                genConfig[0]["referenceVideos"] = [referenceVideos.strip()]
+                print(f"[Debugging] Reference videos: {genConfig[0].get('referenceVideos', [])}")
+            elif isinstance(referenceVideos, list) and len(referenceVideos) > 0:
+                genConfig[0]["referenceVideos"] = referenceVideos
+                print(f"[Debugging] Reference videos: {genConfig[0].get('referenceVideos', [])}")
+        
+        # Add speech parameters if both voice and text are provided
+        if speechVoice and speechVoice.strip() != "" and speechText and speechText.strip() != "":
+            genConfig[0]["speech"] = {
+                "voice": speechVoice.strip(),
+                "text": speechText.strip()
+            }
+            print(f"[Debugging] Speech parameters: voice='{speechVoice.strip()}', text='{speechText.strip()[:50]}...'")
+        
+        # Handle inputs - merge custom inputs from Video Inference Inputs node
+        if inputs is not None:
+            # Merge inputs from video inference inputs node
+            if "inputs" not in genConfig[0]:
+                genConfig[0]["inputs"] = {}
+            
+            # Merge each input from inputs (only actual input data, not provider settings)
+            for key, value in inputs.items():
+                genConfig[0]["inputs"][key] = value
+            
+            print(f"[Debugging] Video inference inputs merged: {inputs}")
+        
         # Handle providerSettings - extract provider name from model and merge with custom settings
         if providerSettings is not None:
             # Extract provider name from model (e.g., "pixverse:1@1" -> "pixverse")
diff --git a/modules/videoInferenceInputs.py b/modules/videoInferenceInputs.py
new file mode 100644
index 0000000..b9c79c6
--- /dev/null
+++ b/modules/videoInferenceInputs.py
@@ -0,0 +1,46 @@
+from .utils import runwareUtils as rwUtils
+
+class videoInferenceInputs:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {},
+            "optional": {
+                "Image": ("IMAGE", {
+                    "tooltip": "Portrait image for video generation. This will be the main subject that will speak and move in the generated video."
+                }),
+                "Audio": ("STRING", {
+                    "tooltip": "Connect the mediaUUID output from Runware Media Upload node with audio file. This audio will be synchronized with the generated video."
+                }),
+                "Mask": ("IMAGE", {
+                    "tooltip": "Mask image to specify a specific subject in the image to speak. Use white/black mask format."
+                }),
+            }
+        }
+
+    DESCRIPTION = "Configure custom inputs for Runware Video Inference with OmniHuman 1.5 support, including image, audio, and mask inputs."
+    FUNCTION = "createInputs"
+    RETURN_TYPES = ("RUNWAREVIDEOINFERENCEINPUTS",)
+    RETURN_NAMES = ("Video Inference Inputs",)
+    CATEGORY = "Runware"
+
+    def createInputs(self, **kwargs):
+        image = kwargs.get("Image", None)
+        audio = kwargs.get("Audio", None)
+        mask = kwargs.get("Mask", None)
+
+        inputs = {}
+
+        if image is not None:
+            image_uuid = rwUtils.convertTensor2IMG(image)
+            inputs["image"] = image_uuid
+
+        if audio is not None and audio.strip() != "":
+            inputs["audio"] = audio.strip()
+
+        if mask is not None:
+            mask_uuid = rwUtils.convertTensor2IMG(mask)
+            inputs["mask"] = mask_uuid
+
+        return (inputs,)
+
diff --git a/modules/videoModelSearch.py b/modules/videoModelSearch.py
index e44d4ae..db06efe 100644
--- a/modules/videoModelSearch.py
+++ b/modules/videoModelSearch.py
@@ -21,6 +21,8 @@ class videoModelSearch:
         "Seedance": [
             "bytedance:2@1 (Seedance 1.0 Pro)",
             "bytedance:1@1 (Seedance 1.0 Lite)",
+            "bytedance:5@1 (OmniHuman 1)",
+            "bytedance:5@2 (OmniHuman 1.5)",
         ],
         "MiniMax": [
             "minimax:1@1 (MiniMax 01 Base)",
@@ -32,6 +34,7 @@ class videoModelSearch:
             "pixverse:1@1 (PixVerse v3.5)",
             "pixverse:1@2 (PixVerse v4)",
             "pixverse:1@3 (PixVerse v4.5)",
+            "pixverse:lipsync@1 (PixVerse LipSync)",
         ],
         "Vidu": [
             "vidu:1@0 (Vidu Q1 Classic)",
@@ -47,6 +50,9 @@ class videoModelSearch:
             "openai:3@1 (OpenAI Sora 3.1)",
             "openai:3@0 (OpenAI Sora 3.0)",
         ],
+        "Lightricks": [
+            "lightricks:2@1 (LTX)",
+        ],
     }
     
     # Model dimensions mapping
@@ -71,6 +77,8 @@ class videoModelSearch:
         # Seedance Models
         "bytedance:2@1": {"width": 864, "height": 480},  # Seedance 1.0 Pro
         "bytedance:1@1": {"width": 864, "height": 480},  # Seedance 1.0 Lite
+        "bytedance:5@1": {"width": 1024, "height": 1024},  # OmniHuman 1
+        "bytedance:5@2": {"width": 1024, "height": 1024},  # OmniHuman 1.5
         
         # MiniMax Models
         "minimax:1@1": {"width": 1366, "height": 768},  # MiniMax 01 Base
@@ -82,6 +90,7 @@ class videoModelSearch:
         "pixverse:1@1": {"width": 640, "height": 360},  # PixVerse v3.5
         "pixverse:1@2": {"width": 640, "height": 360},  # PixVerse v4
         "pixverse:1@3": {"width": 640, "height": 360},  # PixVerse v4.5
+        "pixverse:lipsync@1": {"width": 640, "height": 360},  # PixVerse LipSync
         
         # Vidu Models
         "vidu:1@0": {"width": 1920, "height": 1080},    # Vidu Q1 Classic
@@ -96,6 +105,9 @@ class videoModelSearch:
         # OpenAI Models
         "openai:3@1": {"width": 1280, "height": 720}, # OpenAI Sora 3.1
         "openai:3@0": {"width": 1280, "height": 720}, # OpenAI Sora 3.0
+        
+        # Lightricks Models
+        "lightricks:2@1": {"width": 1920, "height": 1080}, # Lightricks v2.1
     }
     
     
@@ -120,7 +132,8 @@ class videoModelSearch:
                         "PixVerse",
                         "Vidu",
                         "Wan",
-                        "OpenAI"
+                        "OpenAI",
+                        "Lightricks"
                     ], {
                     "tooltip": "Choose Video Model Architecture To Filter Results.",
                     "default": "KlingAI",
diff --git a/modules/videoUpscaler.py b/modules/videoUpscaler.py
new file mode 100644
index 0000000..23478cf
--- /dev/null
+++ b/modules/videoUpscaler.py
@@ -0,0 +1,137 @@
+from .utils import runwareUtils as rwUtils
+import json
+import comfy.model_management
+
+class videoUpscaler:
+    RUNWARE_VUPSCALER_MODELS = {
+        "Bria Video Upscaler": "bria:50@1",
+    }
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "Video": ("STRING", {
+                    "tooltip": "MediaUUID from Runware Media Upload node for the video to upscale."
+                }),
+                "upscaleFactor": ([2, 4], {
+                    "tooltip": "Integer scale factor for upscaling (2x or 4x).",
+                    "default": 2,
+                }),
+                "Model": (list(cls.RUNWARE_VUPSCALER_MODELS.keys()), {
+                    "tooltip": "Select the video upscaler model to use.",
+                    "default": "Bria Video Upscaler",
+                }),
+            },
+            "optional": {
+                "Output Format": (["mp4", "webm"], {
+                    "default": "mp4",
+                    "tooltip": "Choose the output video format.",
+                }),
+            }
+        }
+
+    DESCRIPTION = "Enhance the resolution and quality of your videos using Runware's advanced upscaling API."
+    FUNCTION = "upscale"
+    RETURN_TYPES = ("VIDEO",)
+    RETURN_NAMES = ("VIDEO",)
+    CATEGORY = "Runware"
+
+    def upscale(self, **kwargs):
+        video_uuid = kwargs.get("Video")
+        upscaleFactor = kwargs.get("upscaleFactor", 2)
+        modelName = kwargs.get("Model", "Bria Video Upscaler")
+        outputFormat = kwargs.get("Output Format", "mp4")
+        
+        # Validate mediaUUID
+        if not video_uuid or video_uuid.strip() == "":
+            raise ValueError("Video mediaUUID is required")
+        
+        # Get the model AIR code
+        modelAIR = self.RUNWARE_VUPSCALER_MODELS.get(modelName, "bria:50@1")
+        
+        # Build the API request
+        genConfig = [
+            {
+                "taskType": "upscale",
+                "taskUUID": rwUtils.genRandUUID(),
+                "upscaleFactor": upscaleFactor,
+                "inputs": {
+                    "video": video_uuid
+                },
+                "outputType": "URL",
+                "outputFormat": outputFormat.upper(),
+                "model": modelAIR,
+                "includeCost": True
+            }
+        ]
+        
+        try:
+            # Debug: Print the request being sent
+            print(f"[DEBUG] Sending Video Upscale Request:")
+            print(f"[DEBUG] Request Payload: {json.dumps(genConfig, indent=2)}")
+            
+            genResult = rwUtils.inferenecRequest(genConfig)
+            
+            # Debug: Print the response received
+            print(f"[DEBUG] Received Video Upscale Response:")
+            print(f"[DEBUG] Response: {json.dumps(genResult, indent=2)}")
+            
+            # Check for errors
+            if "errors" in genResult:
+                error_message = genResult["errors"][0]["message"]
+                raise Exception(f"Video upscale failed: {error_message}")
+            
+            # Extract task UUID for polling
+            taskUUID = genConfig[0]["taskUUID"]
+            
+            # Poll for video completion
+            while True:
+                # Check for interrupt before each poll
+                comfy.model_management.throw_exception_if_processing_interrupted()
+                
+                # Poll for video result
+                pollResult = rwUtils.pollVideoResult(taskUUID)
+                print(f"[Debugging] Poll result: {pollResult}")
+                
+                # Check for errors first
+                if pollResult and "errors" in pollResult and len(pollResult["errors"]) > 0:
+                    error_info = pollResult["errors"][0]
+                    error_message = error_info.get("message", "Unknown error")
+                    raise Exception(f"Video upscale failed: {error_message}")
+                
+                if pollResult and "data" in pollResult and len(pollResult["data"]) > 0:
+                    video_data = pollResult["data"][0]
+                    
+                    # Check status directly
+                    if "status" in video_data:
+                        status = video_data["status"]
+                        
+                        if status == "success":
+                            if "videoURL" in video_data or "videoBase64Data" in video_data:
+                                videos = rwUtils.convertVideoB64List(pollResult, 1920, 1080)
+                                return videos
+                        
+                        # If status is "processing", continue polling
+                
+                # Check for interrupt before waiting
+                comfy.model_management.throw_exception_if_processing_interrupted()
+                
+                # Wait before next poll
+                for _ in range(10):  # 10 x 0.1 second = 1 second total
+                    comfy.model_management.throw_exception_if_processing_interrupted()
+                    rwUtils.time.sleep(0.1)
+                        
+        except Exception as e:
+            print(f"[Error] Video upscale failed: {str(e)}")
+            raise e
+
+# Node class mappings
+NODE_CLASS_MAPPINGS = {
+    "RunwareVideoUpscaler": videoUpscaler,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "RunwareVideoUpscaler": "Runware Video Upscaler",
+}
+
diff --git a/workflows/Runware_Image_to_Video.json b/workflows/Runware_Image_to_Video.json
index de8a111..b3a103c 100644
--- a/workflows/Runware_Image_to_Video.json
+++ b/workflows/Runware_Image_to_Video.json
@@ -1 +1 @@
-{"id":"5cf854c6-824e-4e51-995c-a2c146c44890","revision":0,"last_node_id":12,"last_link_id":15,"nodes":[{"id":1,"type":"SaveVideo","pos":[899.7476806640625,376.3740539550781],"size":[270,368],"flags":{},"order":6,"mode":0,"inputs":[{"localized_name":"video","name":"video","type":"VIDEO","link":15},{"localized_name":"filename_prefix","name":"filename_prefix","type":"STRING","widget":{"name":"filename_prefix"},"link":null},{"localized_name":"format","name":"format","type":"COMBO","widget":{"name":"format"},"link":null},{"localized_name":"codec","name":"codec","type":"COMBO","widget":{"name":"codec"},"link":null}],"outputs":[],"properties":{"cnr_id":"comfy-core","ver":"0.3.46","Node name for S&R":"SaveVideo"},"widgets_values":["video/ComfyUI","mp4","auto"]},{"id":9,"type":"LoadImage","pos":[-192.8682861328125,723.959716796875],"size":[274.080078125,314],"flags":{},"order":0,"mode":0,"inputs":[{"localized_name":"image","name":"image","type":"COMBO","widget":{"name":"image"},"link":null},{"localized_name":"choose file to upload","name":"upload","type":"IMAGEUPLOAD","widget":{"name":"upload"},"link":null}],"outputs":[{"localized_name":"IMAGE","name":"IMAGE","type":"IMAGE","links":[5]},{"localized_name":"MASK","name":"MASK","type":"MASK","links":null}],"properties":{"cnr_id":"comfy-core","ver":"0.3.46","Node name for S&R":"LoadImage"},"widgets_values":["car.jpg","image"]},{"id":10,"type":"LoadImage","pos":[107.18201446533203,834.20556640625],"size":[274.080078125,314],"flags":{},"order":1,"mode":0,"inputs":[{"localized_name":"image","name":"image","type":"COMBO","widget":{"name":"image"},"link":null},{"localized_name":"choose file to upload","name":"upload","type":"IMAGEUPLOAD","widget":{"name":"upload"},"link":null}],"outputs":[{"localized_name":"IMAGE","name":"IMAGE","type":"IMAGE","links":[9]},{"localized_name":"MASK","name":"MASK","type":"MASK","links":null}],"properties":{"cnr_id":"comfy-core","ver":"0.3.46","Node name for S&R":"LoadImage"},"widgets_values":["rain.jpg","image"]},{"id":6,"type":"Note","pos":[451.5391540527344,931.1026000976562],"size":[387.0979309082031,231.9747314453125],"flags":{},"order":2,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["Hello there! 🌟\n\nWelcome to the Runware Video 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. ⚙️✅"],"color":"#432","bgcolor":"#653"},{"id":5,"type":"Runware Video Model Search","pos":[110.46113586425781,356.1772766113281],"size":[270,170],"flags":{},"order":3,"mode":0,"inputs":[{"localized_name":"Model Search","name":"Model Search","type":"STRING","widget":{"name":"Model Search"},"link":null},{"localized_name":"Model Architecture","name":"Model Architecture","type":"COMBO","widget":{"name":"Model Architecture"},"link":null},{"localized_name":"VideoList","name":"VideoList","type":"COMBO","widget":{"name":"VideoList"},"link":null},{"localized_name":"Use Search Value","name":"Use Search Value","type":"BOOLEAN","widget":{"name":"Use Search Value"},"link":null}],"outputs":[{"localized_name":"Runware Video Model","name":"Runware Video Model","type":"RUNWAREVIDEOMODEL","links":[13]},{"localized_name":"Width","name":"Width","type":"INT","links":null},{"localized_name":"Height","name":"Height","type":"INT","links":null}],"properties":{"cnr_id":"ComfyUI-Runware","ver":"4d74f59820ad59af31176536118380f7e9f0374c","Node name for S&R":"Runware Video Model Search"},"widgets_values":["","MiniMax","minimax:3@1 (MiniMax 02 Hailuo)",false],"bgcolor":"#5345bf"},{"id":8,"type":"Runware Frame Images","pos":[104.67301177978516,588.6543579101562],"size":[270,190],"flags":{},"order":4,"mode":0,"inputs":[{"localized_name":"image1","name":"image1","shape":7,"type":"IMAGE","link":5},{"localized_name":"image2","name":"image2","shape":7,"type":"IMAGE","link":9},{"localized_name":"image3","name":"image3","shape":7,"type":"IMAGE","link":null},{"localized_name":"image4","name":"image4","shape":7,"type":"IMAGE","link":null},{"localized_name":"frame1_position","name":"frame1_position","shape":7,"type":"COMBO","widget":{"name":"frame1_position"},"link":null},{"localized_name":"frame2_position","name":"frame2_position","shape":7,"type":"COMBO","widget":{"name":"frame2_position"},"link":null},{"localized_name":"frame3_position","name":"frame3_position","shape":7,"type":"COMBO","widget":{"name":"frame3_position"},"link":null},{"localized_name":"frame4_position","name":"frame4_position","shape":7,"type":"COMBO","widget":{"name":"frame4_position"},"link":null}],"outputs":[{"localized_name":"Frame Images","name":"Frame Images","type":"RUNWAREFRAMEIMAGES","links":[14]}],"properties":{"cnr_id":"ComfyUI-Runware","ver":"655118a9a1cddbf1a3de1d9d7dfa51311df49fe5","Node name for S&R":"Runware Frame Images"},"widgets_values":["auto","auto","auto","auto"],"bgcolor":"#5345bf"},{"id":12,"type":"Runware Video Inference","pos":[471.7605895996094,346.677490234375],"size":[400,534],"flags":{},"order":5,"mode":0,"inputs":[{"localized_name":"Model","name":"Model","type":"RUNWAREVIDEOMODEL","link":13},{"localized_name":"frameImages","name":"frameImages","shape":7,"type":"RUNWAREFRAMEIMAGES","link":14},{"localized_name":"referenceImages","name":"referenceImages","shape":7,"type":"RUNWAREREFERENCEIMAGES","link":null},{"localized_name":"providerSettings","name":"providerSettings","shape":7,"type":"RUNWAREPROVIDERSETTINGS","link":null},{"localized_name":"inputAudios","name":"inputAudios","shape":7,"type":"RUNWAREINPUTAUDIOS","link":null},{"localized_name":"positivePrompt","name":"positivePrompt","type":"STRING","widget":{"name":"positivePrompt"},"link":null},{"localized_name":"negativePrompt","name":"negativePrompt","type":"STRING","widget":{"name":"negativePrompt"},"link":null},{"localized_name":"Multi Inference Mode","name":"Multi Inference Mode","type":"BOOLEAN","widget":{"name":"Multi Inference Mode"},"link":null},{"localized_name":"Prompt Weighting","name":"Prompt Weighting","type":"COMBO","widget":{"name":"Prompt Weighting"},"link":null},{"localized_name":"useCustomDimensions","name":"useCustomDimensions","type":"BOOLEAN","widget":{"name":"useCustomDimensions"},"link":null},{"localized_name":"width","name":"width","type":"INT","widget":{"name":"width"},"link":null},{"localized_name":"height","name":"height","type":"INT","widget":{"name":"height"},"link":null},{"localized_name":"duration","name":"duration","type":"INT","widget":{"name":"duration"},"link":null},{"localized_name":"useFps","name":"useFps","type":"BOOLEAN","widget":{"name":"useFps"},"link":null},{"localized_name":"fps","name":"fps","type":"INT","widget":{"name":"fps"},"link":null},{"localized_name":"outputFormat","name":"outputFormat","type":"COMBO","widget":{"name":"outputFormat"},"link":null},{"localized_name":"useSeed","name":"useSeed","type":"BOOLEAN","widget":{"name":"useSeed"},"link":null},{"localized_name":"seed","name":"seed","type":"INT","widget":{"name":"seed"},"link":null},{"localized_name":"batchSize","name":"batchSize","type":"INT","widget":{"name":"batchSize"},"link":null}],"outputs":[{"localized_name":"VIDEO","name":"VIDEO","type":"VIDEO","links":[15]},{"localized_name":"RW-Task","name":"RW-Task","type":"RUNWARETASK","links":null}],"properties":{"cnr_id":"ComfyUI-Runware","ver":"16016793b1e66f9b7bf364643bdf36447a35d5c9","Node name for S&R":"Runware Video Inference"},"widgets_values":["Car speeding on highway next to beach, in rain. 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\ No newline at end of file
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diff --git a/workflows/Runware_Image_to_Video_Pixverse.json b/workflows/Runware_Image_to_Video_Pixverse.json
index e6ae06f..545fbb1 100644
--- a/workflows/Runware_Image_to_Video_Pixverse.json
+++ b/workflows/Runware_Image_to_Video_Pixverse.json
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\ No newline at end of file
diff --git a/workflows/Runware_Media_Upload.json b/workflows/Runware_Media_Upload.json
index be4c2b7..1ad7118 100644
--- a/workflows/Runware_Media_Upload.json
+++ b/workflows/Runware_Media_Upload.json
@@ -1 +1 @@
-{"id":"7493d64d-0c0c-40ca-a1df-816552f0526b","revision":0,"last_node_id":6,"last_link_id":3,"nodes":[{"id":3,"type":"LoadVideo","pos":[252.06771850585938,646.0390625],"size":[274.080078125,279.56005859375],"flags":{},"order":0,"mode":0,"inputs":[{"localized_name":"file","name":"file","type":"COMBO","widget":{"name":"file"},"link":null},{"localized_name":"choose file to upload","name":"upload","type":"IMAGEUPLOAD","widget":{"name":"upload"},"link":null}],"outputs":[{"localized_name":"VIDEO","name":"VIDEO","type":"VIDEO","links":[3]}],"properties":{"cnr_id":"comfy-core","ver":"0.3.46","Node name for S&R":"LoadVideo"},"widgets_values":["test_video.mp4","image"]},{"id":6,"type":"Runware Media Upload","pos":[558.8807373046875,651.7319946289062],"size":[400,200],"flags":{},"order":1,"mode":0,"inputs":[{"localized_name":"media","name":"media","shape":7,"type":"VIDEO,AUDIO","link":3},{"localized_name":"mediaUUID","name":"mediaUUID","shape":7,"type":"STRING","widget":{"name":"mediaUUID"},"link":null}],"outputs":[{"localized_name":"mediaUUID","name":"mediaUUID","type":"STRING","links":null}],"properties":{"cnr_id":"ComfyUI-Runware","ver":"16016793b1e66f9b7bf364643bdf36447a35d5c9","Node name for S&R":"Runware Media Upload"},"widgets_values":["254f37d6-98dc-4333-a530-232ea5847cce"],"bgcolor":"#5345bf"}],"links":[[3,3,0,6,0,"VIDEO,AUDIO"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.8264462809917354,"offset":[439.5536367488321,-167.09876328463446]}},"version":0.4}
\ No newline at end of file
+{"id":"7493d64d-0c0c-40ca-a1df-816552f0526b","revision":0,"last_node_id":11,"last_link_id":8,"nodes":[{"id":10,"type":"LoadVideo","pos":[115.29751586914062,485.1632995605469],"size":[274.080078125,279.56005859375],"flags":{},"order":0,"mode":0,"inputs":[{"localized_name":"file","name":"file","type":"COMBO","widget":{"name":"file"},"link":null},{"localized_name":"choose file to upload","name":"upload","type":"IMAGEUPLOAD","widget":{"name":"upload"},"link":null}],"outputs":[{"localized_name":"VIDEO","name":"VIDEO","type":"VIDEO","links":[8]}],"properties":{"cnr_id":"comfy-core","ver":"0.3.46","Node name for S&R":"LoadVideo"},"widgets_values":["test_video.mp4","image"]},{"id":11,"type":"Runware Media Upload","pos":[448.4990234375,623.826416015625],"size":[270,58],"flags":{},"order":1,"mode":0,"inputs":[{"localized_name":"media","name":"media","shape":7,"type":"VIDEO,AUDIO","link":8},{"localized_name":"mediaUUID","name":"mediaUUID","shape":7,"type":"STRING","widget":{"name":"mediaUUID"},"link":null}],"outputs":[{"localized_name":"mediaUUID","name":"mediaUUID","type":"STRING","links":null}],"properties":{"cnr_id":"ComfyUI-Runware","ver":"1c7da18f11d51514140944e0f9f90e62ae99572c","Node name for S&R":"Runware Media Upload"},"widgets_values":["254f37d6-98dc-4333-a530-232ea5847cce"],"bgcolor":"#5345bf"}],"links":[[8,10,0,11,0,"VIDEO,AUDIO"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.8264462809917354,"offset":[453.6411562800821,-175.4364195346344]}},"version":0.4}
\ No newline at end of file
diff --git a/workflows/Runware_Text_To_Video.json.json b/workflows/Runware_Text_To_Video.json.json
index 0d0effa..f27c8b9 100644
--- a/workflows/Runware_Text_To_Video.json.json
+++ b/workflows/Runware_Text_To_Video.json.json
@@ -1 +1 @@
-{"id":"00000000-0000-0000-0000-000000000000","revision":0,"last_node_id":31,"last_link_id":33,"nodes":[{"id":6,"type":"SaveVideo","pos":[462.1513671875,86.5411376953125],"size":[270,249.875],"flags":{},"order":0,"mode":0,"inputs":[{"localized_name":"video","name":"video","type":"VIDEO","link":33},{"localized_name":"filename_prefix","name":"filename_prefix","type":"STRING","widget":{"name":"filename_prefix"},"link":null},{"localized_name":"format","name":"format","type":"COMBO","widget":{"name":"format"},"link":null},{"localized_name":"codec","name":"codec","type":"COMBO","widget":{"name":"codec"},"link":null}],"outputs":[],"properties":{"cnr_id":"comfy-core","ver":"0.3.46","Node name for S&R":"SaveVideo"},"widgets_values":["video/ComfyUI","mp4","auto"]},{"id":24,"type":"Note","pos":[-470.805908203125,338.4525146484375],"size":[387.0979309082031,231.9747314453125],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["Hello there! 🌟\n\nWelcome to the 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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_Vectorize.json b/workflows/Runware_Vectorize.json
new file mode 100644
index 0000000..e2deaaf
--- /dev/null
+++ b/workflows/Runware_Vectorize.json
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/workflows/Runware_VideoInference_LTX.json b/workflows/Runware_VideoInference_LTX.json
new file mode 100644
index 0000000..192e048
--- /dev/null
+++ b/workflows/Runware_VideoInference_LTX.json
@@ -0,0 +1 @@
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diff --git a/workflows/Runware_Video_Background_Removal.json b/workflows/Runware_Video_Background_Removal.json
new file mode 100644
index 0000000..e6024bf
--- /dev/null
+++ b/workflows/Runware_Video_Background_Removal.json
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diff --git a/workflows/Runware_Video_Inference_Omnihuman1_5.json b/workflows/Runware_Video_Inference_Omnihuman1_5.json
new file mode 100644
index 0000000..d78ca9a
--- /dev/null
+++ b/workflows/Runware_Video_Inference_Omnihuman1_5.json
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diff --git a/workflows/Runware_Video_Inference_PixverseLipSync.json b/workflows/Runware_Video_Inference_PixverseLipSync.json
new file mode 100644
index 0000000..f8bb010
--- /dev/null
+++ b/workflows/Runware_Video_Inference_PixverseLipSync.json
@@ -0,0 +1 @@
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diff --git a/workflows/Runware_Video_Inference_PixverseLipSyncSpeech.json b/workflows/Runware_Video_Inference_PixverseLipSyncSpeech.json
new file mode 100644
index 0000000..ff44214
--- /dev/null
+++ b/workflows/Runware_Video_Inference_PixverseLipSyncSpeech.json
@@ -0,0 +1 @@
+{"id":"37e58abe-b6f0-4f32-a551-22cc274a425e","revision":0,"last_node_id":10,"last_link_id":9,"nodes":[{"id":5,"type":"LoadVideo","pos":[-247.41175842285156,272.1563720703125],"size":[274.080078125,279.56005859375],"flags":{},"order":0,"mode":0,"inputs":[{"localized_name":"file","name":"file","type":"COMBO","widget":{"name":"file"},"link":null},{"localized_name":"choose file to upload","name":"upload","type":"IMAGEUPLOAD","widget":{"name":"upload"},"link":null}],"outputs":[{"localized_name":"VIDEO","name":"VIDEO","type":"VIDEO","links":[2]}],"properties":{"cnr_id":"comfy-core","ver":"0.3.46","Node name for S&R":"LoadVideo"},"widgets_values":["test_video.mp4","image"]},{"id":6,"type":"Runware Media 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\ No newline at end of file
diff --git a/workflows/Runware_Video_Upscale.json b/workflows/Runware_Video_Upscale.json
new file mode 100644
index 0000000..8264684
--- /dev/null
+++ b/workflows/Runware_Video_Upscale.json
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/workflows/Runware_Vidu_Video_Template.json b/workflows/Runware_Vidu_Video_Template.json
index 3afa36a..c050949 100644
--- a/workflows/Runware_Vidu_Video_Template.json
+++ b/workflows/Runware_Vidu_Video_Template.json
@@ -1 +1 @@
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