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Increase reference images limit to 14 and prompt limit to 10000 for image inference

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This commit is contained in:
Sirshendu Ganguly
2026-01-14 20:30:18 -05:00
parent d7754e06cc
commit 5beb48676b
5 changed files with 65 additions and 85 deletions
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modules/imageInference.py
+4 -4
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@@ -206,11 +206,11 @@ class txt2img:
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 positivePrompt and len(positivePrompt) > 10000:
return "Positive Prompt is too long. Maximum length is 10000 characters."
if negativePrompt and len(negativePrompt) > 2000:
return "Negative Prompt is too long. Maximum length is 2000 characters."
if negativePrompt and len(negativePrompt) > 10000:
return "Negative Prompt is too long. Maximum length is 10000 characters."
return True
modules/imageInferenceInputs.py
+33 -55
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@@ -4,43 +4,29 @@ from .utils import runwareUtils as rwUtils
class imageInferenceInputs:
"""Image Inference Inputs node for configuring image generation inputs"""
MAX_REFERENCE_IMAGES = 14
@classmethod
def INPUT_TYPES(cls):
optionalInputs = {
"image": ("IMAGE", {
"tooltip": "Specifies an image input for the inference process."
}),
}
for i in range(1, cls.MAX_REFERENCE_IMAGES + 1):
ordinal = rwUtils.getOrdinal(i)
optionalInputs[f"Reference Image {i}"] = ("IMAGE", {
"tooltip": f"Specifies {ordinal.capitalize()} Reference Image for the inputs. These reference images help guide the image generation process."
})
optionalInputs[f"Reference Tag {i}"] = ("STRING", {
"tooltip": f"Optional tag describing {ordinal.capitalize()} Reference Image. Leave empty to omit.",
"default": "",
})
return {
"required": {},
"optional": {
"image": ("IMAGE", {
"tooltip": "Specifies an image input for the inference process."
}),
"Reference Image 1": ("IMAGE", {
"tooltip": "Specifies Reference Image 1 for the inputs. These reference images help guide the image generation process."
}),
"Reference Tag 1": ("STRING", {
"tooltip": "Optional tag describing Reference Image 1. Leave empty to omit.",
"default": "",
}),
"Reference Image 2": ("IMAGE", {
"tooltip": "Specifies Reference Image 2 for the inputs. These reference images help guide the image generation process."
}),
"Reference Tag 2": ("STRING", {
"tooltip": "Optional tag describing Reference Image 2. Leave empty to omit.",
"default": "",
}),
"Reference Image 3": ("IMAGE", {
"tooltip": "Specifies Reference Image 3 for the inputs. These reference images help guide the image generation process."
}),
"Reference Tag 3": ("STRING", {
"tooltip": "Optional tag describing Reference Image 3. Leave empty to omit.",
"default": "",
}),
"Reference Image 4": ("IMAGE", {
"tooltip": "Specifies Reference Image 4 for the inputs. These reference images help guide the image generation process."
}),
"Reference Tag 4": ("STRING", {
"tooltip": "Optional tag describing Reference Image 4. Leave empty to omit.",
"default": "",
}),
}
"optional": optionalInputs
}
DESCRIPTION = "Configure custom inputs for Runware Image Inference, including reference images that can be passed to the inference node."
@@ -52,36 +38,32 @@ class imageInferenceInputs:
def createInputs(self, **kwargs):
"""Create image inference inputs from provided parameters"""
image = kwargs.get("image", None)
refImage1 = kwargs.get("Reference Image 1", None)
refTag1 = kwargs.get("Reference Tag 1", "")
refImage2 = kwargs.get("Reference Image 2", None)
refTag2 = kwargs.get("Reference Tag 2", "")
refImage3 = kwargs.get("Reference Image 3", None)
refTag3 = kwargs.get("Reference Tag 3", "")
refImage4 = kwargs.get("Reference Image 4", None)
refTag4 = kwargs.get("Reference Tag 4", "")
inputs = {}
if image is not None:
inputs["image"] = rwUtils.convertTensor2IMG(image)
references = self._collectReferences(
refImage1, refTag1,
refImage2, refTag2,
refImage3, refTag3,
refImage4, refTag4,
)
references = self._collectReferences(kwargs)
if len(references) > 0:
inputs["referenceImages"] = references
return (inputs,)
def _collectReferences(self, *referenceArgs):
def _collectReferences(self, kwargs):
"""Collect and convert reference images to list"""
# Build list of (image, tag) pairs from the flat arguments
referencePairs = list(zip(referenceArgs[0::2], referenceArgs[1::2]))
referencePairs = []
# Collect all reference image and tag pairs
for i in range(1, self.MAX_REFERENCE_IMAGES + 1):
image = kwargs.get(f"Reference Image {i}", None)
tag = kwargs.get(f"Reference Tag {i}", "")
if image is not None:
referencePairs.append((image, tag))
if not referencePairs:
return []
# Determine if any tag is provided
hasTags = any(
isinstance(tag, str) and tag.strip() != ""
@@ -93,14 +75,10 @@ class imageInferenceInputs:
return [
rwUtils.convertTensor2IMG(image)
for image, _ in referencePairs
if image is not None
]
references = []
for image, tag in referencePairs:
if image is None:
continue
entry = {"image": rwUtils.convertTensor2IMG(image)}
if isinstance(tag, str) and tag.strip() != "":
entry["tag"] = tag.strip()
modules/referenceImages.py
+26 -24
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@@ -4,25 +4,26 @@ from .utils import runwareUtils as rwUtils
class referenceImages:
"""Reference Images node for providing reference images for identity consistency"""
MAX_IMAGES = 14
@classmethod
def INPUT_TYPES(cls):
requiredInputs = {
"Image 1": ("IMAGE", {
"tooltip": "Specifies Reference Image 1 that will be used as reference for the subject. These reference images help the AI to maintain identity consistency during the generation process."
}),
}
optionalInputs = {}
for i in range(2, cls.MAX_IMAGES + 1):
ordinal = rwUtils.getOrdinal(i)
optionalInputs[f"Image {i}"] = ("IMAGE", {
"tooltip": f"Specifies {ordinal.capitalize()} Reference Image that will be used as reference for the subject. These reference images help the AI to maintain identity consistency during the generation process."
})
return {
"required": {
"Image 1": ("IMAGE", {
"tooltip": "Specifies Reference Image 1 that will be used as reference for the subject. These reference images help the AI to maintain identity consistency during the generation process."
}),
},
"optional": {
"Image 2": ("IMAGE", {
"tooltip": "Specifies Reference Image 2 that will be used as reference for the subject. These reference images help the AI to maintain identity consistency during the generation process."
}),
"Image 3": ("IMAGE", {
"tooltip": "Specifies Reference Image 3 that will be used as reference for the subject. These reference images help the AI to maintain identity consistency during the generation process."
}),
"Image 4": ("IMAGE", {
"tooltip": "Specifies Reference Image 4 that will be used as reference for the subject. These reference images help the AI to maintain identity consistency during the generation process."
}),
}
"required": requiredInputs,
"optional": optionalInputs
}
DESCRIPTION = "Used With Runware Tasks To Provide Reference Images For The Subject. These Reference Images Help The AI To Maintain Identity Consistency During The Generation Process."
@@ -33,15 +34,16 @@ class referenceImages:
def referenceImages(self, **kwargs):
"""Collect and convert reference images to list"""
image1 = kwargs.get("Image 1")
image2 = kwargs.get("Image 2", None)
image3 = kwargs.get("Image 3", None)
image4 = kwargs.get("Image 4", None)
imageList = [rwUtils.convertTensor2IMG(image1)]
imageList = []
optionalImages = [image2, image3, image4]
for image in optionalImages:
# Always include Image 1 (required)
image1 = kwargs.get("Image 1")
if image1 is not None:
imageList.append(rwUtils.convertTensor2IMG(image1))
# Add optional images 2 through MAX_IMAGES
for i in range(2, self.MAX_IMAGES + 1):
image = kwargs.get(f"Image {i}", None)
if image is not None:
imageList.append(rwUtils.convertTensor2IMG(image))
workflows/Runware_Basic_Image_Inference_NanoBanana2.json
+1 -1
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workflows/Runware_Image_Inference_ seedream_v4_5.json
+1 -1
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