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Merge pull request #45 from Runware/fix-Runway

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Fix runway, positivePrompt( optional), add Safety
This commit is contained in:
Sirshendu Ganguly
2025-11-17 21:40:39 -05:00
committed by GitHub
parent efd7f0b0be a3813ad747
commit a3e3181ec2
9 changed files with 55 additions and 18 deletions
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clientlibs/utils.js
+3
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@@ -1347,6 +1347,7 @@ function videoInferenceDimensionsHandler(videoInferenceNode) {
"klingai:3@1": {width: 1280, height: 720}, "klingai:3@2": {width: 1920, height: 1080},
"klingai:4@3": {width: 1280, height: 720}, "klingai:5@1": {width: 1280, height: 720},
"klingai:5@2": {width: 1920, height: 1080}, "klingai:5@3": {width: 1920, height: 1080},
"klingai:6@1": {width: 1920, height: 1080},
"klingai:7@1": {width: 0, height: 0},
"google:2@0": {width: 1280, height: 720}, "google:3@0": {width: 1280, height: 720},
"google:3@1": {width: 1280, height: 720}, "google:3@2": {width: 1280, height: 720},
@@ -1568,6 +1569,7 @@ function videoModelSearchFilterHandler(videoModelSearchNode) {
"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)",
"klingai:6@1 (KlingAI 2.5 Turbo Pro)",
"klingai:7@1 (KlingAI Lip-Sync)",
],
"Veo": [
@@ -1626,6 +1628,7 @@ function videoModelSearchFilterHandler(videoModelSearchNode) {
"klingai:5@1": {"width": 1280, "height": 720},
"klingai:5@2": {"width": 1920, "height": 1080},
"klingai:5@3": {"width": 1920, "height": 1080},
"klingai:6@1": {"width": 1920, "height": 1080},
"klingai:7@1": {"width": 0, "height": 0},
"google:2@0": {"width": 1280, "height": 720},
"google:3@0": {"width": 1280, "height": 720},
modules/frameImages.py
+1 -1
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@@ -50,7 +50,7 @@ class RunwareFrameImages:
def _createFrameData(self, image, position):
"""Create frame data object from image and position"""
imageData = rwUtils.convertTensor2IMG(image)
imageData = rwUtils.convertTensor2IMGBase64Only(image)
frameData = {"inputImage": imageData}
if position != "auto":
modules/imageInference.py
+30 -14
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@@ -6,9 +6,6 @@ class txt2img:
def INPUT_TYPES(cls):
return {
"required": {
"Model": ("RUNWAREMODEL", {
"tooltip": "Connect a Runware Model From Runware Model Node.",
}),
"positivePrompt": ("STRING", {
"multiline": True,
"placeholder": "Positive Prompt: a text instruction to guide the model on generating the image. It is usually a sentence or a paragraph that provides positive guidance for the task. This parameter is essential to shape the desired results.\n\nYou Can Press (Ctrl + Alt + E) To Enhance The Prompt!",
@@ -19,6 +16,9 @@ class txt2img:
"placeholder": "Negative Prompt: a text instruction to guide the model on generating the image. It is usually a sentence or a paragraph that provides negative guidance for the task. This parameter helps to avoid certain undesired results.",
"tooltip": "Negative Prompt: a text instruction to guide the model on generating the image."
}),
"Model": ("RUNWAREMODEL", {
"tooltip": "Connect a Runware Model From Runware Model Node.",
}),
"Multi Inference Mode": ("BOOLEAN", {
"tooltip": "If Enabled the node will skip the image generation process and will only return the Runware Task Object to be used in the Multi Inference Node.",
"default": False,
@@ -175,25 +175,32 @@ class txt2img:
"providerSettings": ("RUNWAREPROVIDERSETTINGS", {
"tooltip": "Connect a Runware Provider Settings Node to configure provider-specific parameters.",
}),
"safetyInputs": ("RUNWARESAFETYINPUTS", {
"tooltip": "Connect Runware Safety Inputs node to configure safety and content moderation settings.",
}),
}
}
@classmethod
def VALIDATE_INPUTS(cls, positivePrompt, negativePrompt):
if (positivePrompt is not None and (positivePrompt == "" or len(positivePrompt) < 3 or len(positivePrompt) > 2000)):
raise Exception(
"Positive Prompt Must Be Between 3 And 2000 characters!")
if (negativePrompt is not None and negativePrompt != "" and (len(negativePrompt) < 3 or len(negativePrompt) > 2000)):
raise Exception(
"Negative Prompt Must Be Between 3 And 2000 characters!")
return True
DESCRIPTION = "Generates Images Lightning Fast With Runware Image Inference Sonic Engine."
FUNCTION = "generateImage"
RETURN_TYPES = ("IMAGE", "RUNWARETASK")
RETURN_NAMES = ("IMAGE", "RW-Task")
CATEGORY = "Runware"
@classmethod
def VALIDATE_INPUTS(cls, **kwargs):
positivePrompt = kwargs.get("positivePrompt", "")
negativePrompt = kwargs.get("negativePrompt", "")
# Only validate positivePrompt length if it's provided
if positivePrompt and len(positivePrompt) > 2000:
return "Positive Prompt is too long. Maximum length is 2000 characters."
if negativePrompt and len(negativePrompt) > 2000:
return "Negative Prompt is too long. Maximum length is 2000 characters."
return True
def generateImage(self, **kwargs):
runwareModel = kwargs.get("Model")
positivePrompt = kwargs.get("positivePrompt")
@@ -211,6 +218,7 @@ class txt2img:
referenceImages = kwargs.get("referenceImages", None)
inputs = kwargs.get("inputs", None)
providerSettings = kwargs.get("providerSettings", None)
safetyInputs = kwargs.get("safetyInputs", None)
seedImage = kwargs.get("seedImage", None)
seedImageStrength = kwargs.get("strength", 0.8)
maskImage = kwargs.get("maskImage", None)
@@ -240,7 +248,6 @@ class txt2img:
{
"taskType": "imageInference",
"taskUUID": rwUtils.genRandUUID(),
"positivePrompt": positivePrompt,
"model": runwareModel,
"outputType": "base64Data",
"outputFormat": outputFormat,
@@ -248,6 +255,11 @@ class txt2img:
"numberResults": batchSize,
}
]
# Add positivePrompt only if provided
if positivePrompt is not None and positivePrompt != "":
genConfig[0]["positivePrompt"] = positivePrompt
# For Debugging Purposes Only
print(f"[Debugging] Task UUID: {genConfig[0]['taskUUID']}")
@@ -344,6 +356,10 @@ class txt2img:
# If it's already in the correct format, use it directly
genConfig[0]["providerSettings"] = providerSettings
# Add safety inputs if provided
if safetyInputs is not None and isinstance(safetyInputs, dict) and len(safetyInputs) > 0:
genConfig[0]["safety"] = safetyInputs
if (multiInferenceMode):
return (None, genConfig)
else:
modules/utils/runwareUtils.py
+14
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@@ -467,6 +467,20 @@ def convertTensor2IMG(tensorImage):
def convertTensor2IMGBase64Only(tensorImage):
"""Convert tensor to base64 data URI without caching - for frame images"""
imageNP = (tensorImage.squeeze().numpy() * 255).astype(np.uint8)
image = Image.fromarray(imageNP)
with io.BytesIO() as buffer:
image.save(buffer, format="PNG")
imageRawData = buffer.getvalue()
imgb64 = base64.b64encode(imageRawData).decode("utf-8")
imgDataUri = f"data:image/png;base64,{imgb64}"
return imgDataUri
def convertTensor2IMGForVideo(tensorImage):
"""Convert tensor to image and force upload to get UUID for video frame images"""
imageNP = (tensorImage.squeeze().numpy() * 255).astype(np.uint8)
modules/videoInputsFrame.py
+2 -2
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@@ -49,8 +49,8 @@ class RunwareVideoInputsFrameImages:
return (frameImages,)
def _createFrameEntry(self, image, frameLabel):
imageData = rwUtils.convertTensor2IMG(image)
entry = {"image": imageData}
imageData = rwUtils.convertTensor2IMGBase64Only(image)
entry = {"inputImage": imageData}
if isinstance(frameLabel, str) and frameLabel.strip() != "":
if frameLabel.strip().isdigit():
modules/videoModelSearch.py
+2
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@@ -14,6 +14,7 @@ class videoModelSearch:
"klingai:5@1 (KlingAI V2.1 Standard (I2V))",
"klingai:5@2 (KlingAI V2.1 Pro (I2V))",
"klingai:5@3 (KlingAI V2.0 Master)",
"klingai:6@1 (KlingAI 2.5 Turbo Pro)",
"klingai:7@1 (KlingAI Lip-Sync)",
],
"Veo": [
@@ -89,6 +90,7 @@ class videoModelSearch:
"klingai:5@1": {"width": 1280, "height": 720},
"klingai:5@2": {"width": 1920, "height": 1080},
"klingai:5@3": {"width": 1920, "height": 1080},
"klingai:6@1": {"width": 1920, "height": 1080},
"klingai:7@1": {"width": 0, "height": 0},
# Veo Models
workflows/Runware_Basic_Image_Inference_Runway_Gen_4.json
+1 -1
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workflows/Runware_Image_Inference_Bria_ReplaceBackground.json
+1
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workflows/Runware_Image_to_Video_Kling2.5.json
+1
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