ComfyUI Node: Primere Lora Keyword Merger

Primere Lora Keyword Merger:

The PrimereLoraKeywordMerger node is designed to streamline the process of merging keywords from various sources related to Lora models. This node is particularly useful for AI artists who work with different Lora models and need to consolidate keywords from multiple sources such as Stable Diffusion (SD), Stable Diffusion XL (SDXL), and tag loaders. By merging these keywords, the node helps in organizing and managing model-specific keywords efficiently, ensuring that the right keywords are associated with the correct models. This can significantly enhance the workflow by reducing the manual effort required to manage keywords and improving the accuracy of keyword assignments.

Primere Lora Keyword Merger Input Parameters:

lora_keyword_SD

This parameter accepts a list of keywords related to the Lora model for Stable Diffusion (SD). The function filters out any None values and expects exactly two valid keywords to proceed. The first keyword represents the model keyword, and the second indicates its placement. If the input does not meet these criteria, it is ignored. This parameter helps in specifying keywords that are specifically tailored for the SD model, ensuring accurate keyword management.

lora_keyword_SDXL

Similar to lora_keyword_SD, this parameter accepts a list of keywords for the Lora model in Stable Diffusion XL (SDXL). The function filters out any None values and requires exactly two valid keywords to proceed. The first keyword is the model keyword, and the second is its placement. This parameter is crucial for managing keywords specific to the SDXL model, allowing for precise keyword assignments.

lora_keyword_tagloader

This parameter takes a list of keywords from a tag loader related to the Lora model. The function filters out any None values and expects exactly two valid keywords to proceed. The first keyword is the model keyword, and the second is its placement. This parameter is useful for incorporating keywords from external tag loaders, providing a flexible way to manage and merge keywords from various sources.

Primere Lora Keyword Merger Output Parameters:

model_keyword

The output parameter model_keyword is a tuple containing two elements: the model keyword and its placement. This output is derived from the input parameters, prioritizing the keywords from lora_keyword_SD, lora_keyword_SDXL, and lora_keyword_tagloader in that order. If valid keywords are found in any of the input parameters, they are returned as the output. This output is essential for ensuring that the correct keywords are associated with the respective Lora models, facilitating better keyword management and organization.

Primere Lora Keyword Merger Usage Tips:

• Ensure that each input parameter (lora_keyword_SD, lora_keyword_SDXL, lora_keyword_tagloader) contains exactly two valid keywords to be processed correctly.
• Use this node to consolidate keywords from different sources, which can help in maintaining a well-organized keyword database for various Lora models.
• Prioritize the input parameters based on your workflow needs, as the node processes lora_keyword_SD first, followed by lora_keyword_SDXL, and then lora_keyword_tagloader.

Primere Lora Keyword Merger Common Errors and Solutions:

Invalid input length

• Explanation: The input list does not contain exactly two valid keywords.
• Solution: Ensure that each input parameter (lora_keyword_SD, lora_keyword_SDXL, lora_keyword_tagloader) contains exactly two valid keywords.

NoneType error

• Explanation: One or more input parameters contain None values.
• Solution: Filter out None values from the input lists before passing them to the node.

No valid keywords found

• Explanation: None of the input parameters contain valid keywords.
• Solution: Verify that the input lists are correctly populated with valid keywords and that they meet the required criteria.