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Runware-ComfyUI-Runware/modules/videoModelSearch.py
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Sirshendu Ganguly 8d75a6933f 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
2025-10-23 22:36:24 -04:00

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class videoModelSearch:
# Define the video models by architecture with their default dimensions
VIDEO_MODELS = {
"KlingAI": [
"klingai:1@2 (KlingAI V1.0 Pro)",
"klingai:1@1 (KlingAI V1 Standard)",
"klingai:2@2 (KlingAI V1.5 Pro)",
"klingai:2@1 (KlingAI V1.5 Standard)",
"klingai:3@1 (KlingAI V1.6 Standard)",
"klingai:3@2 (KlingAI V1.6 Pro)",
"klingai:4@3 (KlingAI V2.1 Master)",
"klingai:5@1 (KlingAI V2.1 Standard (I2V))",
"klingai:5@2 (KlingAI V2.1 Pro (I2V))",
"klingai:5@3 (KlingAI V2.0 Master)",
],
"Veo": [
"google:2@0 (Veo 2.0)",
"google:3@0 (Veo 3.0)",
"google:3@1 (Veo 3.0 Fast)",
],
"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)",
"minimax:2@1 (MiniMax 01 Director)",
"minimax:2@3 (MiniMax I2V 01 Live)",
"minimax:3@1 (MiniMax 02 Hailuo)",
],
"PixVerse": [
"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)",
"vidu:1@1 (Vidu Q1)",
"vidu:1@5 (Vidu 1.5)",
"vidu:2@0 (Vidu 2.0)",
],
"Wan": [
"runware:200@1 (Wan 2.1 1.3B)",
"runware:200@2 (Wan 2.1 14B)",
],
"OpenAI": [
"openai:3@1 (OpenAI Sora 3.1)",
"openai:3@0 (OpenAI Sora 3.0)",
],
"Lightricks": [
"lightricks:2@1 (LTX)",
],
}
# Model dimensions mapping
MODEL_DIMENSIONS = {
# KlingAI Models
"klingai:1@2": {"width": 1280, "height": 720}, # KlingAI V1.0 Pro
"klingai:1@1": {"width": 1280, "height": 720}, # KlingAI V1 Standard
"klingai:2@2": {"width": 1920, "height": 1080}, # KlingAI V1.5 Pro
"klingai:2@1": {"width": 1280, "height": 720}, # KlingAI V1.5 Standard
"klingai:3@1": {"width": 1280, "height": 720}, # KlingAI V1.6 Standard
"klingai:3@2": {"width": 1920, "height": 1080}, # KlingAI V1.6 Pro
"klingai:4@3": {"width": 1280, "height": 720}, # KlingAI V2.1 Master
"klingai:5@1": {"width": 1280, "height": 720}, # KlingAI V2.1 Standard (I2V)
"klingai:5@2": {"width": 1920, "height": 1080}, # KlingAI V2.1 Pro (I2V)
"klingai:5@3": {"width": 1920, "height": 1080}, # KlingAI V2.0 Master
# Veo Models
"google:2@0": {"width": 1280, "height": 720}, # Veo 2.0
"google:3@0": {"width": 1280, "height": 720}, # Veo 3.0
"google:3@1": {"width": 1280, "height": 720}, # Veo 3.0 Fast
# 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
"minimax:2@1": {"width": 1366, "height": 768}, # MiniMax 01 Director
"minimax:2@3": {"width": 1366, "height": 768}, # MiniMax I2V 01 Live
"minimax:3@1": {"width": 1366, "height": 768}, # MiniMax 02 Hailuo
# PixVerse Models
"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
"vidu:1@1": {"width": 1920, "height": 1080}, # Vidu Q1
"vidu:1@5": {"width": 1920, "height": 1080}, # Vidu 1.5
"vidu:2@0": {"width": 1920, "height": 1080}, # Vidu 2.0
# Wan Models
"runware:200@1": {"width": 853, "height": 480}, # Wan 2.1 1.3B
"runware:200@2": {"width": 853, "height": 480}, # Wan 2.1 14B
# 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
}
@classmethod
def INPUT_TYPES(cls):
# Get all models for "All" option
all_models = []
for models in cls.VIDEO_MODELS.values():
all_models.extend(models)
return {
"required": {
"Model Search": ("STRING", {
"tooltip": "Search For Specific Video Model By Name Or Civit AIR Code (eg: KlingAI, Veo).",
}),
"Model Architecture": ([
"All",
"KlingAI",
"Veo",
"Seedance",
"MiniMax",
"PixVerse",
"Vidu",
"Wan",
"OpenAI",
"Lightricks"
], {
"tooltip": "Choose Video Model Architecture To Filter Results.",
"default": "KlingAI",
}),
"VideoList": (all_models, {
"tooltip": "Video Model Results Will Show UP Here So You Could Choose From.",
"default": "klingai:5@3 (KlingAI V2.0 Master)",
}),
"Use Search Value": ("BOOLEAN", {
"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.",
"default": False,
"label_on": "Enabled",
"label_off": "Disabled",
}),
},
}
DESCRIPTION = "Directly Search and Connect Video Models to Runware Video Inference Nodes In ComfyUI."
FUNCTION = "videoModelSearch"
RETURN_TYPES = ("RUNWAREVIDEOMODEL", "INT", "INT")
RETURN_NAMES = ("Runware Video Model", "Width", "Height")
CATEGORY = "Runware"
@classmethod
def VALIDATE_INPUTS(cls, VideoList):
return True
def videoModelSearch(self, **kwargs):
enableSearchValue = kwargs.get("Use Search Value", False)
searchInput = kwargs.get("Model Search")
if enableSearchValue:
modelAIRCode = searchInput
else:
crModel = kwargs.get("VideoList")
# Extract the full AIR identifier (everything before the first space)
modelAIRCode = crModel.split(" (")[0]
# Get dimensions for the selected model
dimensions = self.MODEL_DIMENSIONS.get(modelAIRCode, {"width": 1024, "height": 576})
return ({
"model": modelAIRCode,
}, dimensions["width"], dimensions["height"])
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