163 lines
6.6 KiB
Python
163 lines
6.6 KiB
Python
class videoModelSearch:
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# Define the video models by architecture with their default dimensions
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VIDEO_MODELS = {
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"KlingAI": [
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"klingai:1@2 (KlingAI V1.0 Pro)",
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"klingai:1@1 (KlingAI V1 Standard)",
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"klingai:2@2 (KlingAI V1.5 Pro)",
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"klingai:2@1 (KlingAI V1.5 Standard)",
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"klingai:3@1 (KlingAI V1.6 Standard)",
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"klingai:3@2 (KlingAI V1.6 Pro)",
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"klingai:4@3 (KlingAI V2.1 Master)",
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"klingai:5@1 (KlingAI V2.1 Standard (I2V))",
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"klingai:5@2 (KlingAI V2.1 Pro (I2V))",
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"klingai:5@3 (KlingAI V2.0 Master)",
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],
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"Veo": [
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"google:2@0 (Veo 2.0)",
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"google:3@0 (Veo 3.0)",
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"google:3@1 (Veo 3.0 Fast)",
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],
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"Seedance": [
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"bytedance:2@1 (Seedance 1.0 Pro)",
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"bytedance:1@1 (Seedance 1.0 Lite)",
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],
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"MiniMax": [
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"minimax:1@1 (MiniMax 01 Base)",
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"minimax:2@1 (MiniMax 01 Director)",
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"minimax:2@3 (MiniMax I2V 01 Live)",
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"minimax:3@1 (MiniMax 02 Hailuo)",
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],
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"PixVerse": [
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"pixverse:1@1 (PixVerse v3.5)",
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"pixverse:1@2 (PixVerse v4)",
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"pixverse:1@3 (PixVerse v4.5)",
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],
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"Vidu": [
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"vidu:1@0 (Vidu Q1 Classic)",
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"vidu:1@1 (Vidu Q1)",
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"vidu:1@5 (Vidu 1.5)",
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"vidu:2@0 (Vidu 2.0)",
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],
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"Wan": [
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"runware:200@1 (Wan 2.1 1.3B)",
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"runware:200@2 (Wan 2.1 14B)",
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],
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}
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# Model dimensions mapping
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MODEL_DIMENSIONS = {
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# KlingAI Models
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"klingai:1@2": {"width": 1280, "height": 720}, # KlingAI V1.0 Pro
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"klingai:1@1": {"width": 1280, "height": 720}, # KlingAI V1 Standard
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"klingai:2@2": {"width": 1920, "height": 1080}, # KlingAI V1.5 Pro
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"klingai:2@1": {"width": 1280, "height": 720}, # KlingAI V1.5 Standard
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"klingai:3@1": {"width": 1280, "height": 720}, # KlingAI V1.6 Standard
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"klingai:3@2": {"width": 1920, "height": 1080}, # KlingAI V1.6 Pro
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"klingai:4@3": {"width": 1280, "height": 720}, # KlingAI V2.1 Master
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"klingai:5@1": {"width": 1280, "height": 720}, # KlingAI V2.1 Standard (I2V)
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"klingai:5@2": {"width": 1920, "height": 1080}, # KlingAI V2.1 Pro (I2V)
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"klingai:5@3": {"width": 1920, "height": 1080}, # KlingAI V2.0 Master
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# Veo Models
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"google:2@0": {"width": 1280, "height": 720}, # Veo 2.0
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"google:3@0": {"width": 1280, "height": 720}, # Veo 3.0
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"google:3@1": {"width": 1280, "height": 720}, # Veo 3.0 Fast
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# Seedance Models
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"bytedance:2@1": {"width": 864, "height": 480}, # Seedance 1.0 Pro
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"bytedance:1@1": {"width": 864, "height": 480}, # Seedance 1.0 Lite
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# MiniMax Models
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"minimax:1@1": {"width": 1366, "height": 768}, # MiniMax 01 Base
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"minimax:2@1": {"width": 1366, "height": 768}, # MiniMax 01 Director
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"minimax:2@3": {"width": 1366, "height": 768}, # MiniMax I2V 01 Live
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"minimax:3@1": {"width": 1366, "height": 768}, # MiniMax 02 Hailuo
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# PixVerse Models
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"pixverse:1@1": {"width": 640, "height": 360}, # PixVerse v3.5
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"pixverse:1@2": {"width": 640, "height": 360}, # PixVerse v4
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"pixverse:1@3": {"width": 640, "height": 360}, # PixVerse v4.5
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# Vidu Models
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"vidu:1@0": {"width": 1920, "height": 1080}, # Vidu Q1 Classic
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"vidu:1@1": {"width": 1920, "height": 1080}, # Vidu Q1
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"vidu:1@5": {"width": 1920, "height": 1080}, # Vidu 1.5
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"vidu:2@0": {"width": 1920, "height": 1080}, # Vidu 2.0
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# Wan Models
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"runware:200@1": {"width": 853, "height": 480}, # Wan 2.1 1.3B
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"runware:200@2": {"width": 853, "height": 480}, # Wan 2.1 14B
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}
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# Models that support seed parameter
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SEED_SUPPORTED_MODELS = [
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"runware:200@1", # Wan 2.1 1.3B
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"runware:200@2", # Wan 2.1 14B
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]
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@classmethod
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def INPUT_TYPES(cls):
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# Get all models for "All" option
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all_models = []
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for models in cls.VIDEO_MODELS.values():
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all_models.extend(models)
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return {
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"required": {
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"Model Search": ("STRING", {
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"tooltip": "Search For Specific Video Model By Name Or Civit AIR Code (eg: KlingAI, Veo).",
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}),
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"Model Architecture": ([
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"All",
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"KlingAI",
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"Veo",
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"Seedance",
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"MiniMax",
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"PixVerse",
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"Vidu",
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"Wan"
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], {
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"tooltip": "Choose Video Model Architecture To Filter Results.",
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"default": "KlingAI",
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}),
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"VideoList": (all_models, {
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"tooltip": "Video Model Results Will Show UP Here So You Could Choose From.",
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"default": "klingai:5@3 (KlingAI V2.0 Master)",
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}),
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"Use Search Value": ("BOOLEAN", {
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"tooltip": "When Enabled, the value you've set in the search input will be used instead.\n\nThis is useful in case the model search API is down or you prefer to set the model manually.",
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"default": False,
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"label_on": "Enabled",
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"label_off": "Disabled",
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}),
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},
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}
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DESCRIPTION = "Directly Search and Connect Video Models to Runware Video Inference Nodes In ComfyUI."
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FUNCTION = "videoModelSearch"
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RETURN_TYPES = ("RUNWAREVIDEOMODEL", "INT", "INT")
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RETURN_NAMES = ("Runware Video Model", "Width", "Height")
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CATEGORY = "Runware"
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@classmethod
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def VALIDATE_INPUTS(cls, VideoList):
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return True
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def videoModelSearch(self, **kwargs):
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enableSearchValue = kwargs.get("Use Search Value", False)
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searchInput = kwargs.get("Model Search")
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if enableSearchValue:
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modelAIRCode = searchInput
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else:
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crModel = kwargs.get("VideoList")
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# Extract the full AIR identifier (everything before the first space)
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modelAIRCode = crModel.split(" (")[0]
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# Get dimensions for the selected model
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dimensions = self.MODEL_DIMENSIONS.get(modelAIRCode, {"width": 1024, "height": 576})
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return ({
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"model": modelAIRCode,
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}, dimensions["width"], dimensions["height"]) |