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Enhance flexibility in AI art conditioning by adding and scaling two sets of data for nuanced model inputs.
The ConditioningAdd
node is designed to enhance the flexibility and control over conditioning data in AI art generation. It allows you to combine two sets of conditioning data by adding them together, with the option to scale the contribution of the second set using a multiplier. This node is particularly useful when you want to blend different conditioning influences or adjust the strength of one conditioning set relative to another. By providing a straightforward method to manipulate conditioning data, ConditioningAdd
helps you fine-tune the inputs to your AI models, potentially leading to more nuanced and desired outputs in your creative projects.
This parameter represents the first set of conditioning data that you want to modify. It serves as the base to which the scaled second conditioning set will be added. The data type is CONDITIONING
, which is a structured format used to influence the behavior of AI models.
This parameter is the second set of conditioning data that will be added to the first. Its contribution to the final result is controlled by the multiplier
. Like conditioning_1
, it is of the CONDITIONING
type, allowing for structured and complex data inputs.
The multiplier
is a floating-point value that scales the influence of conditioning_2
when it is added to conditioning_1
. It allows you to adjust the strength of the second conditioning set, with a default value of 1.0. The range is extensive, from -1,000,000,000.0 to 1,000,000,000.0, with a step of 0.01, providing fine-grained control over the addition process.
The output is a single CONDITIONING
type, which is the result of adding the scaled conditioning_2
to conditioning_1
. This output can be used as input for further processing or directly in AI models to influence their behavior. The resulting conditioning data reflects the combined influence of both input sets, adjusted by the multiplier.
multiplier
to control the influence of conditioning_2
. A value greater than 1 will amplify its effect, while a value between 0 and 1 will reduce it.multiplier
to subtract the influence of conditioning_2
from conditioning_1
, which can be useful for counteracting unwanted effects.NoneType
being encountered during the addition.conditioning_1
and conditioning_2
are correctly formatted and initialized before using them in the node.multiplier
value is set outside the allowed range.multiplier
is within the specified range of -1,000,000,000.0 to 1,000,000,000.0 and adjust it accordingly.RunComfy is the premier ComfyUI platform, offering ComfyUI online environment and services, along with ComfyUI workflows featuring stunning visuals. RunComfy also provides AI Playground, enabling artists to harness the latest AI tools to create incredible art.