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Randomly selects text entries from inputs for varied text outputs with replicable randomness for AI artists.
The Bjornulf_RandomTexts
node is designed to randomly select a specified number of text entries from a given set of inputs. This node is particularly useful for scenarios where you need to introduce variability or randomness into your text-based projects, such as generating random prompts, selecting random quotes, or creating diverse text outputs for creative applications. By leveraging a seed value, the node ensures that the randomness can be replicated, allowing for consistent results when needed. This feature is beneficial for AI artists who want to experiment with different text combinations while maintaining control over the randomness for reproducibility.
This parameter specifies the total number of text inputs that the node will consider for random selection. It determines the pool size from which the random texts will be drawn. The minimum value is 2, the maximum is 30, and the default is set to 2. Increasing this number allows for a larger variety of potential outputs, while a smaller number limits the selection pool.
This parameter defines how many random text entries will be selected from the available inputs. It directly impacts the number of outputs generated by the node. The minimum value is 1, the maximum is 30, and the default is 1. Adjusting this parameter allows you to control the extent of randomness and the number of different text outputs you receive.
The seed parameter is used to initialize the random number generator, ensuring that the selection process can be replicated if needed. By setting a specific seed value, you can achieve consistent random selections across different runs. The default value is 0, which means the node will use the current time to generate a seed if none is provided. This parameter is crucial for maintaining reproducibility in your projects.
The output of this node is a list of randomly selected text entries. Each entry in the list corresponds to one of the randomly chosen texts from the input pool. This output is essential for applications that require a varied set of text options, providing flexibility and creativity in text generation tasks.
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