add workflows, etc

__init__.py

@@ -27,6 +27,7 @@ from .modules.referenceImages import referenceImages
 from .modules.imageInferenceInputs import imageInferenceInputs
 from .modules.videoInference import txt2vid
 from .modules.videoModelSearch import videoModelSearch
+from .modules.videoSettings import RunwareVideoSettings
 from .modules.frameImages import RunwareFrameImages
 from .modules.providerSettings.pixverseProviderSettings import RunwarePixverseProviderSettings
 from .modules.providerSettings.openaiProviderSettings import RunwareOpenAIProviderSettings
@@ -159,6 +160,7 @@ NODE_CLASS_MAPPINGS = {
     "Runware Reference Videos": referenceVideos,
     "Runware Reference Voices": referenceVoices,
     "Runware Video Inference Inputs": videoInferenceInputs,
+    "Runware Video Inference Settings": RunwareVideoSettings,
     "Runware Lightricks Provider Settings": RunwareLightricksProviderSettings,
     "Runware MiniMax Provider Settings": RunwareMiniMaxProviderSettings,
     "Runware Luma Provider Settings": RunwareLumaProviderSettings,

clientlibs/main.js

@@ -1,6 +1,6 @@
 import { app } from "../../scripts/app.js";
 import { api } from "../../scripts/api.js";
-import { promptEnhanceHandler, syncDimensionsNodeHandler, searchNodeHandler, APIKeyHandler, captionNodeHandler, mediaUUIDHandler, save3DFilepathHandler, videoTranscriptionHandler, videoOutputsHandler, handleCustomErrors, videoInferenceDimensionsHandler, videoModelSearchFilterHandler, audioModelSearchFilterHandler, useParameterToggleHandler, imageInferenceToggleHandler, upscalerToggleHandler, videoUpscalerToggleHandler, audioInferenceToggleHandler, audioInferenceSpeechToggleHandler, audioSettingsToggleHandler, acceleratorOptionsToggleHandler, bytedanceProviderSettingsToggleHandler, xaiProviderSettingsToggleHandler, viduProviderSettingsToggleHandler, sourcefulProviderSettingsToggleHandler, sourcefulProviderSettingsFontsToggleHandler, threeDInferenceToggleHandler, threeDInferenceSettingsToggleHandler, threeDInferenceSettingsLatToggleHandler, ultralyticsProviderSettingsToggleHandler, openaiProviderSettingsToggleHandler, lightricksProviderSettingsToggleHandler, klingProviderSettingsToggleHandler, lumaProviderSettingsToggleHandler, briaProviderSettingsToggleHandler, pixverseProviderSettingsToggleHandler, alibabaProviderSettingsToggleHandler, mireloProviderSettingsToggleHandler, googleProviderSettingsToggleHandler, syncProviderSettingsToggleHandler, syncSegmentToggleHandler, settingsToggleHandler, audioInputToggleHandler, speechInputToggleHandler, briaProviderMaskToggleHandler, wanAnimateAdvancedFeatureSettingsToggleHandler, videoAdvancedFeatureInputsToggleHandler, audioInferenceInputsToggleHandler } from "./utils.js";
+import { promptEnhanceHandler, syncDimensionsNodeHandler, searchNodeHandler, APIKeyHandler, captionNodeHandler, mediaUUIDHandler, save3DFilepathHandler, videoTranscriptionHandler, videoOutputsHandler, handleCustomErrors, videoInferenceDimensionsHandler, videoModelSearchFilterHandler, audioModelSearchFilterHandler, vectorizeModelSearchFilterHandler, vectorizeToggleHandler, useParameterToggleHandler, imageInferenceToggleHandler, upscalerToggleHandler, videoUpscalerToggleHandler, audioInferenceToggleHandler, audioInferenceSpeechToggleHandler, audioSettingsToggleHandler, videoSettingsToggleHandler, acceleratorOptionsToggleHandler, bytedanceProviderSettingsToggleHandler, xaiProviderSettingsToggleHandler, viduProviderSettingsToggleHandler, sourcefulProviderSettingsToggleHandler, sourcefulProviderSettingsFontsToggleHandler, threeDInferenceToggleHandler, threeDInferenceSettingsToggleHandler, threeDInferenceSettingsLatToggleHandler, ultralyticsProviderSettingsToggleHandler, openaiProviderSettingsToggleHandler, lightricksProviderSettingsToggleHandler, klingProviderSettingsToggleHandler, lumaProviderSettingsToggleHandler, briaProviderSettingsToggleHandler, pixverseProviderSettingsToggleHandler, alibabaProviderSettingsToggleHandler, mireloProviderSettingsToggleHandler, googleProviderSettingsToggleHandler, syncProviderSettingsToggleHandler, syncSegmentToggleHandler, settingsToggleHandler, audioInputToggleHandler, speechInputToggleHandler, briaProviderMaskToggleHandler, wanAnimateAdvancedFeatureSettingsToggleHandler, videoAdvancedFeatureInputsToggleHandler, audioInferenceInputsToggleHandler } from "./utils.js";
 import { RUNWARE_NODE_TYPES, RUNWARE_NODE_PROPS, SEARCH_TERMS } from "./types.js";
 
 const nodeInitList = [];
@@ -82,6 +82,8 @@ app.registerExtension({
             audioInferenceSpeechToggleHandler(node);
         } else if(nodeClass === RUNWARE_NODE_TYPES.AUDIOSETTINGS) {
             audioSettingsToggleHandler(node);
+        } else if(nodeClass === RUNWARE_NODE_TYPES.VIDEOSETTINGS) {
+            videoSettingsToggleHandler(node);
         } else if(nodeClass === RUNWARE_NODE_TYPES.ACCELERATOROPTIONS) {
             acceleratorOptionsToggleHandler(node);
         } else if(nodeClass === RUNWARE_NODE_TYPES.BYTEDANCEPROVIDERSETTINGS) {
@@ -149,6 +151,9 @@ app.registerExtension({
             videoModelSearchFilterHandler(node);
         } else if(nodeClass === RUNWARE_NODE_TYPES.AUDIOMODELSEARCH) {
             audioModelSearchFilterHandler(node);
+        } else if(nodeClass === RUNWARE_NODE_TYPES.VECTORIZE) {
+            vectorizeModelSearchFilterHandler(node);
+            vectorizeToggleHandler(node);
         }
 
         for(const nodeWidget of nodeWidgets) {

clientlibs/types.js

@@ -101,6 +101,7 @@ const RUNWARE_NODE_TYPES = {
     REFERENCEVIDEOS: "Runware Reference Videos",
     REFERENCEVOICES: "Runware Reference Voices",
     VIDEOINFERENCEINPUTS: "Runware Video Inference Inputs",
+    VIDEOSETTINGS: "Runware Video Inference Settings",
     LIGHTRICKSPROVIDERSETTINGS: "Runware Lightricks Provider Settings",
     KLINGPROVIDERSETTINGS: "Runware KlingAI Provider Settings",
     KLINGMULTIPROMPTSEGMENT: "Runware Kling MultiPrompt Segment",
@@ -427,6 +428,7 @@ const RUNWARE_NODE_PROPS = {
     },
     [RUNWARE_NODE_TYPES.VECTORIZE]: {
         bgColor: DEFAULT_BGCOLOR,
+        liveDimensions: true,
     },
     [RUNWARE_NODE_TYPES.VIDEOBGREMOVAL]: {
         bgColor: DEFAULT_BGCOLOR,
@@ -452,6 +454,9 @@ const RUNWARE_NODE_PROPS = {
     [RUNWARE_NODE_TYPES.AUDIOSETTINGSVOICEMODIFY]: {
         bgColor: DEFAULT_BGCOLOR,
     },
+    [RUNWARE_NODE_TYPES.VIDEOSETTINGS]: {
+        bgColor: DEFAULT_BGCOLOR,
+    },
     [RUNWARE_NODE_TYPES.ACCELERATOROPTIONS]: {
         bgColor: DEFAULT_BGCOLOR,
         colorModeOnly: true,

clientlibs/utils.js

@@ -419,8 +419,9 @@ async function syncDimensionsNodeHandler(node, dimensionsWidget) {
 
     appendWidgetCB(dimensionsWidget, function(...args) {
         const chosenDimension = args[0];
-        if(chosenDimension === "Custom") return;
+        if(chosenDimension === "Custom" || chosenDimension === "None") return;
         const dimensionValue = DEFAULT_DIMENSIONS_LIST[chosenDimension];
+        if(!dimensionValue) return;
         const [width, height] = dimensionValue.split("x");
         widthWidget.callback(width, "customSetOperation");
         heightWidget.callback(height, "customSetOperation");
@@ -1162,6 +1163,37 @@ function audioSettingsToggleHandler(settingsNode) {
     if (useTurboWidget && turboWidget) toggleWidgetState(useTurboWidget, turboWidget, "turbo");
 }
 
+function videoSettingsToggleHandler(settingsNode) {
+    if (!settingsNode?.widgets) return;
+
+    const useDraftWidget = settingsNode.widgets.find(w => w && w.name === "useDraft");
+    const draftWidget = settingsNode.widgets.find(w => w && w.name === "draft");
+    const useAudioWidget = settingsNode.widgets.find(w => w && w.name === "useAudio");
+    const audioWidget = settingsNode.widgets.find(w => w && w.name === "audio");
+    const usePromptUpsamplingWidget = settingsNode.widgets.find(w => w && w.name === "usePromptUpsampling");
+    const promptUpsamplingWidget = settingsNode.widgets.find(w => w && w.name === "promptUpsampling");
+
+    function toggleWidgetState(useWidget, paramWidget, paramName) {
+        if (!useWidget || !paramWidget) return;
+        function applyState() {
+            const enabled = useWidget.value === true;
+            toggleWidgetEnabled(paramWidget, enabled, settingsNode);
+            if (paramWidget.options && paramWidget.options.element) {
+                paramWidget.options.element.disabled = !enabled;
+                paramWidget.options.element.style.opacity = enabled ? "1" : "0.5";
+                paramWidget.options.element.style.pointerEvents = enabled ? "auto" : "none";
+            }
+            settingsNode.setDirtyCanvas(true);
+        }
+        setTimeout(applyState, 100);
+        appendWidgetCB(useWidget, () => setTimeout(applyState, 50));
+    }
+
+    if (useDraftWidget && draftWidget) toggleWidgetState(useDraftWidget, draftWidget, "draft");
+    if (useAudioWidget && audioWidget) toggleWidgetState(useAudioWidget, audioWidget, "audio");
+    if (usePromptUpsamplingWidget && promptUpsamplingWidget) toggleWidgetState(usePromptUpsamplingWidget, promptUpsamplingWidget, "promptUpsampling");
+}
+
 function audioInferenceSpeechToggleHandler(speechNode) {
     if (!speechNode?.widgets) return;
 
@@ -2323,6 +2355,9 @@ function videoModelSearchFilterHandler(videoModelSearchNode) {
         "VEED": [
             "veed:fabric@1.0 (VEED Fabric 1.0)",
         ],
+        "Pruna": [
+            "prunaai:p-video@0 (P-Video)",
+        ],
     };
 
     const MODEL_DIMENSIONS = {
@@ -2402,6 +2437,7 @@ function videoModelSearchFilterHandler(videoModelSearchNode) {
         "runware:210@1": {"width": 512, "height": 512},
         "xai:grok-imagine@video": {"width": 480, "height": 480},
         "veed:fabric@1.0": {"width": 1280, "height": 720},
+        "prunaai:p-video@0": {"width": 1280, "height": 720},
     };
 
     const MODEL_RESOLUTIONS = {
@@ -2481,6 +2517,7 @@ function videoModelSearchFilterHandler(videoModelSearchNode) {
         "runware:210@1": null,  // No resolution support (fixed 512x512)
         "xai:grok-imagine@video": "480p",
         "veed:fabric@1.0": "720p",
+        "prunaai:p-video@0": "720p",
     };
 
     const DEFAULT_DIMENSIONS = {"width": 1024, "height": 576};
@@ -2728,6 +2765,105 @@ function audioModelSearchFilterHandler(audioModelSearchNode) {
     filterModelList();
 }
 
+function vectorizeModelSearchFilterHandler(vectorizeNode) {
+    const modelArchWidget = vectorizeNode.widgets.find(w => w.name === "Model Architecture");
+    const vectorListWidget = vectorizeNode.widgets.find(w => w.name === "Vector Model List");
+
+    if (!modelArchWidget || !vectorListWidget) return;
+
+    const VECTORIZE_MODELS = {
+        "Recraft": [
+            "recraft:1@1 (Recraft 1)",
+            "recraft:v4-pro@vector (Recraft V4 Pro Vector)",
+            "recraft:v4@vector (Recraft V4 Vector)",
+        ],
+        "Picsart": [
+            "picsart:1@1 (Picsart 1)",
+        ],
+    };
+
+    function filterModelList() {
+        const selectedArch = modelArchWidget.value;
+        let filteredModels = [];
+
+        if (selectedArch === "All") {
+            Object.values(VECTORIZE_MODELS).forEach(models => filteredModels.push(...models));
+        } else if (VECTORIZE_MODELS[selectedArch]) {
+            filteredModels = VECTORIZE_MODELS[selectedArch];
+        }
+
+        if (filteredModels.length > 0) {
+            const currentValue = vectorListWidget.value;
+            vectorListWidget.options.values = filteredModels;
+
+            if (!filteredModels.includes(currentValue)) {
+                vectorListWidget.value = filteredModels[0];
+            }
+
+            vectorizeNode.setDirtyCanvas(true);
+        }
+    }
+
+    appendWidgetCB(modelArchWidget, filterModelList);
+    filterModelList();
+}
+
+function vectorizeToggleHandler(vectorizeNode) {
+    const usePositivePromptWidget = vectorizeNode.widgets.find(w => w.name === "Use Positive Prompt");
+    const positivePromptWidget = vectorizeNode.widgets.find(w => w.name === "positivePrompt");
+    const dimensionsWidget = vectorizeNode.widgets.find(w => w.name === "dimensions");
+    const widthWidget = vectorizeNode.widgets.find(w => w.name === "width");
+    const heightWidget = vectorizeNode.widgets.find(w => w.name === "height");
+
+    function toggleWidgetState(useWidget, paramWidget, paramName) {
+        if (!useWidget || !paramWidget) return;
+        function applyState() {
+            const enabled = useWidget.value === true;
+            if (paramWidget.inputEl) {
+                paramWidget.inputEl.disabled = !enabled;
+                paramWidget.inputEl.style.opacity = enabled ? "1" : "0.5";
+                paramWidget.inputEl.style.cursor = enabled ? "text" : "not-allowed";
+            }
+        }
+        applyState();
+        appendWidgetCB(useWidget, applyState);
+    }
+
+    if (usePositivePromptWidget && positivePromptWidget) {
+        toggleWidgetState(usePositivePromptWidget, positivePromptWidget, "positivePrompt");
+    }
+
+    // Disable width/height when dimensions is "None" (same as image inference)
+    if (dimensionsWidget && widthWidget && heightWidget) {
+        function toggleDimensionsState() {
+            const dimensionsValue = dimensionsWidget.value;
+            const enabled = dimensionsValue !== "None";
+
+            if (widthWidget.inputEl) {
+                widthWidget.inputEl.disabled = !enabled;
+                widthWidget.inputEl.style.opacity = enabled ? "1" : "0.5";
+                widthWidget.inputEl.style.cursor = enabled ? "text" : "not-allowed";
+                widthWidget.inputEl.readOnly = !enabled;
+            }
+            widthWidget.disabled = !enabled;
+
+            if (heightWidget.inputEl) {
+                heightWidget.inputEl.disabled = !enabled;
+                heightWidget.inputEl.style.opacity = enabled ? "1" : "0.5";
+                heightWidget.inputEl.style.cursor = enabled ? "text" : "not-allowed";
+                heightWidget.inputEl.readOnly = !enabled;
+            }
+            heightWidget.disabled = !enabled;
+
+            vectorizeNode.setDirtyCanvas(true);
+        }
+        appendWidgetCB(dimensionsWidget, () => {
+            setTimeout(toggleDimensionsState, 50);
+        });
+        setTimeout(toggleDimensionsState, 100);
+    }
+}
+
 function klingProviderSettingsToggleHandler(klingNode) {
     // Find all "use" parameter widgets for KlingAI Provider Settings (EXACT same pattern as imageInferenceToggleHandler)
     const useCameraControlWidget = klingNode.widgets.find(w => w.name === "useCameraControl");
@@ -3794,6 +3930,8 @@ export {
     videoInferenceDimensionsHandler,
     videoModelSearchFilterHandler,
     audioModelSearchFilterHandler,
+    vectorizeModelSearchFilterHandler,
+    vectorizeToggleHandler,
     useParameterToggleHandler,
     imageInferenceToggleHandler,
     upscalerToggleHandler,
@@ -3801,6 +3939,7 @@ export {
     audioInferenceToggleHandler,
     audioInferenceSpeechToggleHandler,
     audioSettingsToggleHandler,
+    videoSettingsToggleHandler,
     acceleratorOptionsToggleHandler,
     bytedanceProviderSettingsToggleHandler,
     xaiProviderSettingsToggleHandler,

modules/saveImage.py

@@ -8,13 +8,25 @@ from PIL import Image
 from datetime import datetime
 
 
+def _is_svg_url(url: str) -> bool:
+    """True if URL points to SVG (e.g. from Runware Vectorize)."""
+    u = (url or "").split("?")[0].lower()
+    return u.endswith(".svg")
+
+
 def _bytes_to_image_tensor(img_data: bytes):
-    """Decode image bytes to ComfyUI IMAGE tensor [1, H, W, C] float32 0-1."""
+    """Decode image bytes to ComfyUI IMAGE tensor [1, H, W, C] float32 0-1. Fails on SVG (use placeholder for SVG)."""
     pil = Image.open(io.BytesIO(img_data)).convert("RGB")
     arr = np.array(pil).astype(np.float32) / 255.0
     return torch.from_numpy(arr).unsqueeze(0)
 
 
+def _placeholder_image_tensor():
+    """Return a 1x1 RGB placeholder tensor [1, 1, 1, 3] for non-raster outputs (e.g. SVG from Vectorize)."""
+    arr = np.ones((1, 1, 3), dtype=np.float32) * 0.5  # grey
+    return torch.from_numpy(arr).unsqueeze(0)
+
+
 class RunwareSaveImage:
     """Runware Save Image: download from URL(s), save/preview to disk, and forward as IMAGE for chaining."""
 
@@ -23,7 +35,7 @@ class RunwareSaveImage:
         return {
             "required": {
                 "Images": ("STRING", {
-                    "tooltip": "Image URL(s) from Runware Image Inference node. For multiple images, URLs should be comma-separated."
+                    "tooltip": "Image URL(s) from Runware Image Inference or Runware Vectorize node. For multiple images, URLs should be comma-separated. SVG URLs (e.g. from Vectorize) are saved as .svg files; a placeholder tensor is passed for the IMAGE output."
                 }),
                 "filenamePrefix": ("STRING", {
                     "default": "ComfyUI",
@@ -69,10 +81,14 @@ class RunwareSaveImage:
             response.raise_for_status()
             img_data = response.content
 
-            tensors.append(_bytes_to_image_tensor(img_data))
+            # SVG (e.g. from Runware Vectorize) cannot be opened by PIL; save as file and use placeholder tensor
+            if _is_svg_url(image_url):
+                tensors.append(_placeholder_image_tensor())
+            else:
+                tensors.append(_bytes_to_image_tensor(img_data))
 
             url_without_params = image_url.split("?")[0]
-            ext = url_without_params.split(".")[-1].lstrip(".") or "png"
+            ext = url_without_params.split(".")[-1].lstrip(".").lower() or "png"
             extension = "." + ext
             if len(image_urls) > 1:
                 filename = f"{filenamePrefix}_{timestamp}_{i+1:03}{extension}"

modules/vectorize.py

@@ -1,24 +1,97 @@
+import re
+
 from .utils import runwareUtils as rwUtils
 
 
 class vectorize:
     """Vectorize node for converting images to vector format"""
-    
-    RUNWARE_VECTORIZE_MODELS = {
-        "recraft:1@1": "recraft:1@1",
-        "picsart:1@1": "picsart:1@1",
+
+    # Models grouped by architecture (provider), same pattern as video model search
+    VECTORIZE_MODELS = {
+        "Recraft": [
+            "recraft:1@1 (Recraft 1)",
+            "recraft:v4-pro@vector (Recraft V4 Pro Vector)",
+            "recraft:v4@vector (Recraft V4 Vector)",
+        ],
+        "Picsart": [
+            "picsart:1@1 (Picsart 1)",
+        ],
     }
-    
+
+    MODEL_ARCHITECTURES = [
+        "All",
+        "Recraft",
+        "Picsart",
+    ]
+
+    @classmethod
+    def _getAllModels(cls):
+        """Get all models from all architectures"""
+        all_models = []
+        for models in cls.VECTORIZE_MODELS.values():
+            all_models.extend(models)
+        return all_models
+
     @classmethod
     def INPUT_TYPES(cls):
+        all_models = cls._getAllModels()
+        default_model = all_models[0] if all_models else "recraft:1@1 (Recraft 1)"
         return {
             "required": {
-                "Image": ("IMAGE", {
-                    "tooltip": "Input image to be vectorized."
+                "Model Search": ("STRING", {
+                    "tooltip": "Search for a vectorization model by name or AIR code (e.g. recraft, picsart).",
                 }),
-                "Model": (list(cls.RUNWARE_VECTORIZE_MODELS.keys()), {
-                    "tooltip": "Select the vectorization model to use.",
-                    "default": "recraft:1@1",
+                "Model Architecture": (cls.MODEL_ARCHITECTURES, {
+                    "tooltip": "Choose model architecture to filter the model list.",
+                    "default": "Recraft",
+                }),
+                "Vector Model List": (all_models, {
+                    "tooltip": "Select the vectorization model. Filter by Model Architecture above.",
+                    "default": default_model,
+                }),
+                "Use Search Value": ("BOOLEAN", {
+                    "tooltip": "When enabled, the value in Model Search is used as the model AIR code instead of the list selection.",
+                    "default": False,
+                    "label_on": "Enabled",
+                    "label_off": "Disabled",
+                }),
+            },
+            "optional": {
+                "Image": ("IMAGE", {
+                    "tooltip": "Optional input image to be vectorized."
+                }),
+                "dimensions": ([
+                    "None", "Square HD (1024x1024)", "Custom"
+                ], {
+                    "default": "None",
+                    "tooltip": "Output dimensions preset. Select 'None' for model default, or a preset to set width/height. Use 'Custom' with width/height inputs.",
+                }),
+                "width": ("INT", {
+                    "tooltip": "Width in pixels. Used when dimensions is not 'None' (or with Custom).",
+                    "default": 1024,
+                    "min": 128,
+                    "max": 6048,
+                    "step": 1,
+                }),
+                "height": ("INT", {
+                    "tooltip": "Height in pixels. Used when dimensions is not 'None' (or with Custom).",
+                    "default": 1024,
+                    "min": 128,
+                    "max": 6048,
+                    "step": 1,
+                }),
+                "Use positivePrompt": ("BOOLEAN", {
+                    "tooltip": "When enabled, include positivePrompt in the vectorize request.",
+                    "default": False,
+                    "label_on": "Enabled",
+                    "label_off": "Disabled",
+                }),
+                "positivePrompt": ("STRING", {
+                    "multiline": True,
+                    "tooltip": "Optional text prompt for vectorization. Only sent when Use Positive Prompt is enabled.",
+                }),
+                "providerSettings": ("RUNWAREPROVIDERSETTINGS", {
+                    "tooltip": "Connect a Runware Provider Settings Node to configure provider-specific parameters (e.g. Recraft, Picsart).",
                 }),
             },
         }
@@ -29,51 +102,104 @@ class vectorize:
     RETURN_NAMES = ("IMAGE",)
     CATEGORY = "Runware"
 
+    @classmethod
+    def VALIDATE_INPUTS(cls, **kwargs):
+        return True
+
     def vectorizeImage(self, **kwargs):
         """Vectorize image and return SVG URL"""
         image = kwargs.get("Image")
-        modelName = kwargs.get("Model", "recraft:1@1")
-        
-        model = self.RUNWARE_VECTORIZE_MODELS.get(modelName, "recraft:1@1")
-        imageUuid = rwUtils.convertTensor2IMG(image)
-        
-        genConfig = self._buildGenConfig(model, imageUuid)
-        
+        use_search_value = kwargs.get("Use Search Value", False)
+        search_input = kwargs.get("Model Search", "")
+        current_model = kwargs.get("Vector Model List", "recraft:1@1 (Recraft 1)")
+
+        if use_search_value and search_input and str(search_input).strip():
+            model_air_code = str(search_input).strip()
+        else:
+            # Extract AIR code from "airId (Display Name)" format
+            model_air_code = current_model.split(" (")[0].strip()
+
+        image_uuid = rwUtils.convertTensor2IMG(image) if image is not None else None
+        width = kwargs.get("width")
+        height = kwargs.get("height")
+        dimensions = kwargs.get("dimensions", "None")
+        use_positive_prompt = kwargs.get("Use positivePrompt", False)
+        positive_prompt = kwargs.get("positivePrompt")
+        provider_settings = kwargs.get("providerSettings")
+        gen_config = self._buildGenConfig(
+            model_air_code, image_uuid,
+            width=width, height=height, dimensions=dimensions,
+            use_positive_prompt=use_positive_prompt, positive_prompt=positive_prompt,
+            provider_settings=provider_settings,
+        )
+
         print(f"[DEBUG] Sending Vectorize Request:")
-        print(f"[DEBUG] Request Payload: {rwUtils.safe_json_dumps(genConfig, indent=2)}")
-        
-        genResult = rwUtils.inferenecRequest(genConfig)
-        
+        print(f"[DEBUG] Request Payload: {rwUtils.safe_json_dumps(gen_config, indent=2)}")
+
+        gen_result = rwUtils.inferenecRequest(gen_config)
         print(f"[DEBUG] Received Vectorize Response:")
-        print(f"[DEBUG] Response: {rwUtils.safe_json_dumps(genResult, indent=2)}")
-        
-        self._validateResponse(genResult)
-        
-        svg_url = rwUtils.extractImageURLs(genResult)
-        
+        print(f"[DEBUG] Response: {rwUtils.safe_json_dumps(gen_result, indent=2)}")
+
+        self._validateResponse(gen_result)
+        svg_url = rwUtils.extractImageURLs(gen_result)
         return (svg_url,)
 
-    def _buildGenConfig(self, model, imageUuid):
-        """Build generation configuration for API request"""
-        return [{
+    @staticmethod
+    def _parseDimensionsPreset(dimensions):
+        """Parse 'Label (WxH)' to (width, height) or None if not a preset."""
+        if not dimensions or dimensions in ("None", "Custom"):
+            return None, None
+        m = re.search(r"\((\d+)x(\d+)\)", dimensions)
+        if m:
+            return int(m.group(1)), int(m.group(2))
+        return None, None
+
+    def _buildGenConfig(self, model, image_uuid, width=None, height=None, dimensions="None",
+                        use_positive_prompt=False, positive_prompt=None, provider_settings=None):
+        """Build generation configuration for API request. image_uuid, width, height, positivePrompt, providerSettings are optional."""
+        inputs = {}
+        if image_uuid is not None:
+            inputs["image"] = image_uuid
+        payload = {
             "taskType": "vectorize",
             "taskUUID": rwUtils.genRandUUID(),
             "model": model,
-            "inputs": {
-                "image": imageUuid
-            },
+            "inputs": inputs,
             "outputType": "URL",
             "outputFormat": "svg",
-        }]
+        }
+        if dimensions and dimensions != "None":
+            w, h = width, height
+            if w is None or h is None:
+                pw, ph = self._parseDimensionsPreset(dimensions)
+                if pw is not None and ph is not None:
+                    w, h = pw, ph
+            if w is not None and h is not None:
+                payload["width"] = w
+                payload["height"] = h
+        if use_positive_prompt and positive_prompt is not None and str(positive_prompt).strip():
+            payload["positivePrompt"] = str(positive_prompt).strip()
+        # Handle providerSettings - extract provider name from model and merge (same as image inference)
+        if provider_settings is not None:
+            provider_name = model.split(":")[0] if ":" in model else model
+            if isinstance(provider_settings, dict):
+                if any(key in provider_settings for key in ["alibaba", "bytedance", "klingai", "openai", "pixverse",
+                                                            "bria", "lightricks", "luma", "minimax", "runway", "vidu",
+                                                            "elevenlabs", "bfl", "xai", "recraft", "picsart", "sourceful"]):
+                    payload["providerSettings"] = provider_settings
+                else:
+                    payload["providerSettings"] = {provider_name: provider_settings}
+            else:
+                payload["providerSettings"] = provider_settings
+        return [payload]
 
-    def _validateResponse(self, genResult):
+    def _validateResponse(self, gen_result):
         """Validate API response"""
-        if "errors" in genResult:
-            errorMessage = genResult["errors"][0]["message"]
-            raise Exception(f"Vectorization failed: {errorMessage}")
+        if "errors" in gen_result:
+            error_message = gen_result["errors"][0]["message"]
+            raise Exception(f"Vectorization failed: {error_message}")
 
 
-# Node class mappings
 NODE_CLASS_MAPPINGS = {
     "RunwareVectorize": vectorize,
 }

modules/videoInference.py

@@ -144,6 +144,9 @@ class txt2vid:
                 "Accelerator": ("RUNWAREACCELERATOR", {
                     "tooltip": "Connect a Runware Accelerator Options Node to configure caching and acceleration settings.",
                 }),
+                "settings": ("RUNWAREVIDEOSETTINGS", {
+                    "tooltip": "Connect a Runware Video Inference Settings node to configure draft, audio, and promptUpsampling.",
+                }),
             }
         }
 
@@ -181,6 +184,7 @@ class txt2vid:
         safetyInputs = kwargs.get("safetyInputs", None)
         videoAdvancedFeatureInputs = kwargs.get("videoAdvancedFeatureInputs", None)
         runwareAccelerator = kwargs.get("Accelerator", None)
+        settings = kwargs.get("settings", None)
         useDuration = kwargs.get("useDuration", True)
         duration = kwargs.get("duration", 5)
         fps = kwargs.get("fps", 24)
@@ -350,6 +354,10 @@ class txt2vid:
         # Add accelerator options if provided
         if runwareAccelerator is not None and isinstance(runwareAccelerator, dict) and len(runwareAccelerator) > 0:
             genConfig[0]["acceleratorOptions"] = runwareAccelerator
+
+        # Add settings if provided (draft, audio, promptUpsampling)
+        if settings is not None and isinstance(settings, dict) and len(settings) > 0:
+            genConfig[0]["settings"] = settings
         
         # Add acceleration if not "none"
         if acceleration and acceleration != "none":

modules/videoModelSearch.py

@@ -117,6 +117,9 @@ class videoModelSearch:
         "VEED": [
             "veed:fabric@1.0 (VEED Fabric 1.0)",
         ],
+        "Pruna": [
+            "prunaai:p-video@0 (P-Video)",
+        ],
     }
     
     # Model dimensions mapping
@@ -234,6 +237,9 @@ class videoModelSearch:
 
         # VEED Models (preserves input aspect ratio; resolution = shorter side)
         "veed:fabric@1.0": {"width": 1280, "height": 720},
+
+        # Pruna Models (720p)
+        "prunaai:p-video@0": {"width": 1280, "height": 720},
     }
     
     # Model resolutions mapping
@@ -349,10 +355,13 @@ class videoModelSearch:
         # xAI Models
         "xai:grok-imagine@video": "480p",
 
-        # VEED Models 
+        # VEED Models
         "veed:fabric@1.0": "720p",
+
+        # Pruna Models
+        "prunaai:p-video@0": "720p",
     }
-    
+
     MODEL_ARCHITECTURES = [
         "All",
         "KlingAI",
@@ -373,7 +382,8 @@ class videoModelSearch:
         "Hunyuan",
         "Kandinsky",
         "xAI",
-        "VEED"
+        "VEED",
+        "Pruna",
     ]
     
     DEFAULT_DIMENSIONS = {"width": 1024, "height": 576}

modules/videoSettings.py

@@ -0,0 +1,83 @@
+"""
+Runware Video Inference Settings Node
+Provides settings (draft, audio, promptUpsampling) for Runware Video Inference.
+"""
+
+from typing import Dict, Any
+
+
+class RunwareVideoSettings:
+    """Runware Video Inference Settings Node"""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {},
+            "optional": {
+                "useDraft": ("BOOLEAN", {
+                    "tooltip": "Enable to include draft (lower-quality preview mode) in video inference settings.",
+                    "default": False,
+                }),
+                "draft": ("BOOLEAN", {
+                    "tooltip": "Draft mode for lower-quality preview. Only used when 'Use Draft' is enabled.",
+                    "default": False,
+                    "label_on": "Enabled",
+                    "label_off": "Disabled",
+                }),
+                "useAudio": ("BOOLEAN", {
+                    "tooltip": "Enable to include audio (save video with audio) in video inference settings.",
+                    "default": True,
+                }),
+                "audio": ("BOOLEAN", {
+                    "tooltip": "Save the video with audio. Only used when 'Use Audio' is enabled.",
+                    "default": True,
+                    "label_on": "Enabled",
+                    "label_off": "Disabled",
+                }),
+                "usePromptUpsampling": ("BOOLEAN", {
+                    "tooltip": "Enable to include promptUpsampling (enhance prompt automatically) in video inference settings.",
+                    "default": True,
+                }),
+                "promptUpsampling": ("BOOLEAN", {
+                    "tooltip": "Enhance prompt automatically for better results. Only used when 'Use Prompt Upsampling' is enabled.",
+                    "default": True,
+                    "label_on": "Enabled",
+                    "label_off": "Disabled",
+                }),
+            }
+        }
+
+    RETURN_TYPES = ("RUNWAREVIDEOSETTINGS",)
+    RETURN_NAMES = ("settings",)
+    FUNCTION = "createSettings"
+    CATEGORY = "Runware"
+    DESCRIPTION = "Configure video inference settings (draft, audio, promptUpsampling) for Runware Video Inference. Connect to Runware Video Inference node."
+
+    def createSettings(self, **kwargs) -> tuple:
+        """Create settings dict for Video Inference API"""
+        use_draft = kwargs.get("useDraft", False)
+        draft = kwargs.get("draft", False)
+        use_audio = kwargs.get("useAudio", True)
+        audio = kwargs.get("audio", True)
+        use_prompt_upsampling = kwargs.get("usePromptUpsampling", True)
+        prompt_upsampling = kwargs.get("promptUpsampling", True)
+
+        settings: Dict[str, Any] = {}
+
+        if use_draft:
+            settings["draft"] = bool(draft)
+        if use_audio:
+            settings["audio"] = bool(audio)
+        if use_prompt_upsampling:
+            settings["promptUpsampling"] = bool(prompt_upsampling)
+
+        return (settings,)
+
+
+NODE_CLASS_MAPPINGS = {
+    "RunwareVideoSettings": RunwareVideoSettings,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "RunwareVideoSettings": "Runware Video Inference Settings",
+}

workflows/Runware_Vectorize_Recraft.json

@@ -0,0 +1 @@
+{"id":"993f4b88-acb5-4f70-968f-e3a2c9c1c5b4","revision":0,"last_node_id":19,"last_link_id":17,"nodes":[{"id":9,"type":"Runware Save Image","pos":[541.6531372070312,656.4539184570312],"size":[270,318],"flags":{},"order":3,"mode":0,"inputs":[{"localized_name":"Images","name":"Images","type":"STRING","widget":{"name":"Images"},"link":15},{"localized_name":"filenamePrefix","name":"filenamePrefix","type":"STRING","widget":{"name":"filenamePrefix"},"link":null},{"localized_name":"saveImage","name":"saveImage","type":"BOOLEAN","widget":{"name":"saveImage"},"link":null}],"outputs":[{"localized_name":"IMAGE","name":"IMAGE","type":"IMAGE","links":null}],"properties":{"cnr_id":"ComfyUI-Runware","ver":"91646ada844167e36188b535ff60063735d10ca3","Node name for S&R":"Runware Save Image"},"widgets_values":["","ComfyUI",true],"bgcolor":"#5345bf"},{"id":19,"type":"Runware Provider Settings Recraft Color","pos":[-305.0177001953125,914.2234497070312],"size":[352.7818298339844,106],"flags":{},"order":0,"mode":0,"inputs":[{"localized_name":"r","name":"r","shape":7,"type":"INT","widget":{"name":"r"},"link":null},{"localized_name":"g","name":"g","shape":7,"type":"INT","widget":{"name":"g"},"link":null},{"localized_name":"b","name":"b","shape":7,"type":"INT","widget":{"name":"b"},"link":null}],"outputs":[{"localized_name":"Color","name":"Color","type":"RUNWARERECRAFTCOLOR","links":[16]}],"properties":{"cnr_id":"ComfyUI-Runware","ver":"dee0949f78f02adb54037e1df1cc2bf7df7b4bfe","Node name for S&R":"Runware Provider Settings Recraft Color"},"widgets_values":[0,0,128],"bgcolor":"#5345bf"},{"id":18,"type":"Runware Recraft Provider Settings","pos":[-282.6740417480469,646.2836303710938],"size":[315.4371032714844,182],"flags":{},"order":1,"mode":0,"inputs":[{"localized_name":"color1","name":"color1","shape":7,"type":"RUNWARERECRAFTCOLOR","link":null},{"localized_name":"color2","name":"color2","shape":7,"type":"RUNWARERECRAFTCOLOR","link":null},{"localized_name":"color3","name":"color3","shape":7,"type":"RUNWARERECRAFTCOLOR","link":null},{"localized_name":"color4","name":"color4","shape":7,"type":"RUNWARERECRAFTCOLOR","link":null},{"localized_name":"color5","name":"color5","shape":7,"type":"RUNWARERECRAFTCOLOR","link":null},{"localized_name":"backgroundColor","name":"backgroundColor","shape":7,"type":"RUNWARERECRAFTCOLOR","link":16},{"localized_name":"useStyleId","name":"useStyleId","shape":7,"type":"BOOLEAN","widget":{"name":"useStyleId"},"link":null},{"localized_name":"styleId","name":"styleId","shape":7,"type":"STRING","widget":{"name":"styleId"},"link":null}],"outputs":[{"localized_name":"Provider Settings","name":"Provider Settings","type":"RUNWAREPROVIDERSETTINGS","links":[17]}],"properties":{"cnr_id":"ComfyUI-Runware","ver":"dee0949f78f02adb54037e1df1cc2bf7df7b4bfe","Node name for S&R":"Runware Recraft Provider Settings"},"widgets_values":[false,""],"bgcolor":"#5345bf"},{"id":17,"type":"Runware Vectorize","pos":[72.84228515625,650.274658203125],"size":[400,300],"flags":{},"order":2,"mode":0,"inputs":[{"localized_name":"Image","name":"Image","shape":7,"type":"IMAGE","link":null},{"localized_name":"providerSettings","name":"providerSettings","shape":7,"type":"RUNWAREPROVIDERSETTINGS","link":17},{"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":"Vector Model List","name":"Vector Model List","type":"COMBO","widget":{"name":"Vector Model List"},"link":null},{"localized_name":"Use Search Value","name":"Use Search Value","type":"BOOLEAN","widget":{"name":"Use Search Value"},"link":null},{"localized_name":"dimensions","name":"dimensions","shape":7,"type":"COMBO","widget":{"name":"dimensions"},"link":null},{"localized_name":"width","name":"width","shape":7,"type":"INT","widget":{"name":"width"},"link":null},{"localized_name":"height","name":"height","shape":7,"type":"INT","widget":{"name":"height"},"link":null},{"localized_name":"Use positivePrompt","name":"Use positivePrompt","shape":7,"type":"BOOLEAN","widget":{"name":"Use positivePrompt"},"link":null},{"localized_name":"positivePrompt","name":"positivePrompt","shape":7,"type":"STRING","widget":{"name":"positivePrompt"},"link":null}],"outputs":[{"localized_name":"IMAGE","name":"IMAGE","type":"STRING","links":[15]}],"properties":{"cnr_id":"ComfyUI-Runware","ver":"dee0949f78f02adb54037e1df1cc2bf7df7b4bfe","Node name for S&R":"Runware Vectorize"},"widgets_values":["","Recraft","recraft:v4@vector (Recraft V4 Vector)",false,"Square HD (1024x1024)",1024,1024,true,"Retro 1970s style poster with the text 'Recraft V4'"],"bgcolor":"#5345bf"}],"links":[[15,17,0,9,0,"STRING"],[16,19,0,18,5,"RUNWARERECRAFTCOLOR"],[17,18,0,17,1,"RUNWAREPROVIDERSETTINGS"]],"groups":[],"config":{},"extra":{"ds":{"scale":1.02884607845781,"offset":[484.37043720120533,-463.73196868190934]}},"version":0.4}