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Merge branch 'main' into fix-tiffNode/feature-outputNode

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This commit is contained in:
Sirshendu Ganguly
2026-01-29 15:23:43 -05:00
committed by GitHub
parent 7fee4c9575 938185cd42
commit faa6a499bf
15 changed files with 212 additions and 21 deletions
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modules/providerSettings/bytedanceImageProviderSettings.py
+14
View File
@@ -47,6 +47,14 @@ class RunwareBytedanceProviderSettings:
"tooltip": "Enable audio generation support when available.",
"default": False,
}),
"useDraft": ("BOOLEAN", {
"tooltip": "Enable to include draft parameter in provider settings",
"default": False,
}),
"draft": ("BOOLEAN", {
"tooltip": "Enable draft mode for Bytedance provider",
"default": False,
}),
}
}
@@ -63,12 +71,14 @@ class RunwareBytedanceProviderSettings:
useMaxSequentialImages = kwargs.get("useMaxSequentialImages", False)
useFastMode = kwargs.get("useFastMode", False)
useAudio = kwargs.get("useAudio", False)
useDraft = kwargs.get("useDraft", False)
# Get value parameters
cameraFixed = kwargs.get("cameraFixed", False)
maxSequentialImages = kwargs.get("maxSequentialImages", 1)
fastMode = kwargs.get("fastMode", False)
audio = kwargs.get("audio", False)
draft = kwargs.get("draft", False)
# Build settings dictionary - only include what is enabled
settings = {}
@@ -88,6 +98,10 @@ class RunwareBytedanceProviderSettings:
# Add audio only if useAudio is enabled
if useAudio:
settings["audio"] = audio
# Add draft only if useDraft is enabled
if useDraft:
settings["draft"] = draft
# Clean up None values
settings = {k: v for k, v in settings.items() if v is not None}
modules/utils/runwareUtils.py
+13
View File
@@ -317,6 +317,19 @@ def sendVideoTranscription(transcriptionText, nodeID):
},
)
def sendVideoOutputs(draftId, videoId, nodeID):
"""Send draftId and videoId to frontend for display in Video Inference Outputs node textboxes."""
PromptServer.instance.send_sync(
"runwareVideoOutputs",
{
"success": True,
"draftId": draftId or "",
"videoId": videoId or "",
"nodeID": nodeID,
},
)
def inferenecRequest(genConfig):
global RUNWARE_API_KEY, RUNWARE_API_BASE_URL, SESSION_TIMEOUT
RUNWARE_API_KEY = os.getenv("RUNWARE_API_KEY")
modules/videoBgRemoval.py
+2 -1
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@@ -125,7 +125,8 @@ class videoBgRemoval:
if status == "success":
if "videoURL" in videoData or "videoBase64Data" in videoData:
videos = rwUtils.convertVideoB64List(pollResult, 1920, 1080)
return videos
# SaveVideo expects a single video object, not a tuple
return (videos[0],) if len(videos) > 0 else (None,)
comfy.model_management.throw_exception_if_processing_interrupted()
modules/videoInference.py
+6 -4
View File
@@ -141,8 +141,8 @@ class txt2vid:
DESCRIPTION = "Generates Videos Lightning Fast With Runware Video Inference Engine."
FUNCTION = "generateVideo"
RETURN_TYPES = ("VIDEO", "RUNWARETASK")
RETURN_NAMES = ("VIDEO", "RW-Task")
RETURN_TYPES = ("VIDEO", "RUNWARETASK", "RUNWARETASK")
RETURN_NAMES = ("VIDEO", "RW-Task", "OUTPUT")
CATEGORY = "Runware"
def generateVideo(self, **kwargs):
@@ -325,7 +325,7 @@ class txt2vid:
genConfig[0]["acceleration"] = acceleration
if (multiInferenceMode):
return (None, genConfig)
return (None, genConfig, None)
else:
try:
# Debug: Print the request being sent
@@ -388,7 +388,9 @@ class txt2vid:
if status == "success":
if "videoURL" in video_data or "videoBase64Data" in video_data:
videos = rwUtils.convertVideoB64List(pollResult, width, height)
return videos
# SaveVideo expects a single video object, not a tuple
video_output = videos[0] if len(videos) > 0 else None
return (video_output, genConfig, pollResult)
# If status is "processing", continue polling
modules/videoInferenceInputs.py
+18
View File
@@ -43,6 +43,16 @@ class videoInferenceInputs:
"Reference Voices": ("RUNWAREREFERENCEVOICES", {
"tooltip": "Connect the Reference Voices node to provide reference voice URLs or mediaUUIDs."
}),
"draftId": ("STRING", {
"default": "",
"multiline": False,
"tooltip": "Draft ID from a previous Bytedance video generation. Used when continuing or extending a draft output",
}),
"videoId": ("STRING", {
"default": "",
"multiline": False,
"tooltip": "Video ID from a previous generation. Used when extending or editing an existing OpenAI Sora video",
}),
}
}
@@ -65,6 +75,8 @@ class videoInferenceInputs:
references = kwargs.get("References", None)
referenceVideos = kwargs.get("Reference Videos", None)
referenceVoices = kwargs.get("Reference Voices", None)
draftId = kwargs.get("draftId", "")
videoId = kwargs.get("videoId", "")
inputs = {}
@@ -112,4 +124,10 @@ class videoInferenceInputs:
if referenceVoices is not None and len(referenceVoices) > 0:
inputs["referenceVoices"] = referenceVoices
if draftId is not None and draftId.strip() != "":
inputs["draftId"] = draftId.strip()
if videoId is not None and videoId.strip() != "":
inputs["videoId"] = videoId.strip()
return (inputs,)
modules/videoModelSearch.py
+10 -13
View File
@@ -47,6 +47,7 @@ class videoModelSearch:
"pixverse:1@3 (PixVerse v4.5)",
"pixverse:1@5-fast (PixVerse v5 Fast)",
"pixverse:1@6 (PixVerse v5.5)",
"pixverse:1@7 (PixVerse v5.6)",
"pixverse:lipsync@1 (PixVerse LipSync)",
],
"Vidu": [
@@ -148,6 +149,7 @@ class videoModelSearch:
"pixverse:1@3": {"width": 640, "height": 360},
"pixverse:1@5-fast": {"width": 640, "height": 360},
"pixverse:1@6": {"width": 640, "height": 360},
"pixverse:1@7": {"width": 640, "height": 360},
"pixverse:lipsync@1": {"width": 640, "height": 360},
# Vidu Models
@@ -248,6 +250,7 @@ class videoModelSearch:
"pixverse:1@3": "360p",
"pixverse:1@5-fast": "360p",
"pixverse:1@6": "360p",
"pixverse:1@7": "360p",
"pixverse:lipsync@1": "360p",
# Vidu Models
@@ -390,8 +393,8 @@ class videoModelSearch:
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")
RETURN_TYPES = ("RUNWAREVIDEOMODEL",)
RETURN_NAMES = ("Runware Video Model",)
CATEGORY = "Runware"
@classmethod
@@ -421,33 +424,27 @@ class videoModelSearch:
# Use custom dimensions from Width/Height widgets
width = customWidth
height = customHeight
returnWidth = width
returnHeight = height
elif useCustomDimensions == "Disabled":
# Don't pass width/height (use None in dict, but return 0 for INT output)
# Don't pass width/height (use None in dict)
width = None
height = None
returnWidth = 0
returnHeight = 0
else: # "Model Default"
# Use model default dimensions
width = dimensions["width"]
height = dimensions["height"]
returnWidth = width
returnHeight = height
resultDict = {
"model": modelAirCode,
"useCustomDimensions": useCustomDimensions,
"width": width,
"height": height,
}
# Add resolution if enabled and model supports it
if useResolution and modelResolution is not None:
resultDict["resolution"] = resolution
resultDict["useResolution"] = True
else:
resultDict["useResolution"] = False
return (resultDict, returnWidth, returnHeight)
return (resultDict,)
modules/videoOutputs.py
+75
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@@ -0,0 +1,75 @@
from .utils import runwareUtils as rwUtils
class RunwareVideoInferenceOutputs:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"Output": (
"RUNWARETASK",
{
"tooltip": "Connect the OUTPUT from Runware Video Inference.",
},
),
},
"optional": {
"draftId": ("STRING", {
"placeholder": "Draft ID will appear here after generation.",
"tooltip": "This field will be automatically populated with the draft ID from the video inference output.",
}),
"videoId": ("STRING", {
"placeholder": "Video ID will appear here after generation.",
"tooltip": "This field will be automatically populated with the video ID from the video inference output.",
}),
},
"hidden": {"node_id": "UNIQUE_ID"},
}
DESCRIPTION = "Extracts Runware video inference outputs such as draftId and videoId."
FUNCTION = "get_outputs"
RETURN_TYPES = ("STRING", "STRING")
RETURN_NAMES = ("draftID", "videoID")
CATEGORY = "Runware"
OUTPUT_NODE = True # Ensure node executes even if outputs aren't used
def get_outputs(self, Output, draftId=None, videoId=None, **kwargs):
draft_id = ""
video_id = ""
try:
data_list = None
# Handle different possible response shapes defensively
if isinstance(Output, dict):
if "data" in Output:
data_list = Output.get("data", [])
elif "response" in Output and isinstance(Output["response"], dict):
data_list = Output["response"].get("data", [])
if data_list and len(data_list) > 0:
first = data_list[0]
outputs = first.get("outputs") or {}
if isinstance(outputs, dict):
# draftId is used by some providers
draft_id = outputs.get("draftId", "") or outputs.get("draftID", "")
# videoId / videoID used by other providers
video_id = outputs.get("videoId", "") or outputs.get("videoID", "")
# Send to frontend so values appear in textboxes (like Media Upload)
rwUtils.sendVideoOutputs(draft_id, video_id, kwargs.get("node_id"))
except Exception as e:
print(f"[Runware Video Outputs] Failed to parse outputs: {e}")
return (draft_id, video_id)
NODE_CLASS_MAPPINGS = {
"RunwareVideoInferenceOutputs": RunwareVideoInferenceOutputs,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"RunwareVideoInferenceOutputs": "Runware Video Inference Outputs",
}
modules/videoUpscaler.py
+2 -1
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@@ -121,7 +121,8 @@ class videoUpscaler:
if status == "success":
if "mediaURL" in video_data or "videoURL" in video_data or "videoBase64Data" in video_data:
videos = rwUtils.convertVideoB64List(pollResult, 1920, 1080)
return videos
# SaveVideo expects a single video object, not a tuple
return (videos[0],) if len(videos) > 0 else (None,)
# If status is "processing", continue polling