Add video background removal and video upscaler nodes
- Add Runware Video Background Removal node with Bria support - Add Runware Video Upscaler node with Bria support - Add Runware Vectorize node for image vectorization - Add Lightricks Provider Settings node - Add Video Inference Inputs node for structured inputs - Add Input Audios and Reference Videos nodes - Update video inference with speech support and reference videos - Add new video models: OmniHuman 1/1.5, PixVerse LipSync, LTX - Update Bytedance provider settings with boolean controls - Add corresponding workflow examples
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from .utils import runwareUtils as rwUtils
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from typing import List, Dict, Any
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class referenceVideos:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {},
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"optional": {
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"Video1": ("STRING", {
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"tooltip": "MediaUUID for the first reference video from Runware Media Upload node.",
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}),
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"Video2": ("STRING", {
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"tooltip": "MediaUUID for the second reference video from Runware Media Upload node.",
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}),
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"Video3": ("STRING", {
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"tooltip": "MediaUUID for the third reference video from Runware Media Upload node.",
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}),
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"Video4": ("STRING", {
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"tooltip": "MediaUUID for the fourth reference video from Runware Media Upload node.",
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}),
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}
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}
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DESCRIPTION = "Configure multiple reference video inputs (mediaUUIDs) for video generation."
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FUNCTION = "createReferenceVideos"
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RETURN_TYPES = ("RUNWAREREFERENCEVIDEOS",)
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RETURN_NAMES = ("Reference Videos",)
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CATEGORY = "Runware"
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def createReferenceVideos(self, **kwargs) -> tuple[List[str]]:
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video_list = []
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for i in range(1, 5):
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video_key = f"Video{i}"
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video_uuid = kwargs.get(video_key)
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if video_uuid and video_uuid.strip() != "":
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video_list.append(video_uuid.strip())
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return (video_list,)
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