ComfyUI Node: 🏴 LoRA Selector

🏴 LoRA Selector:

The LoraSelector node is designed to help you easily query and select from a list of all the LoRA (Low-Rank Adaptation) models available in ComfyUI. This node simplifies the process of choosing a specific LoRA model to apply to your diffusion or CLIP models, which can be used to alter the way in which latents are denoised, such as applying different styles. The primary goal of this node is to streamline the selection process, making it more efficient and user-friendly, especially for those who may not have a deep technical background. Additionally, it offers an optional parameter to ensure the node executes after a specified node, providing more control over the execution flow.

🏴 LoRA Selector Input Parameters:

lora_name

This parameter allows you to select the name of the LoRA model you wish to use from a pre-sorted list of available LoRA models. The list is generated dynamically based on the LoRA models present in the specified directory. Selecting a specific LoRA model will enable you to apply it to your diffusion or CLIP models, thereby modifying their behavior according to the characteristics of the chosen LoRA. This parameter does not have minimum or maximum values but offers a list of available options to choose from.

run_after

This is an optional input parameter used to ensure that the LoraSelector node executes after the node it is connected to. It is primarily used to control the execution order in complex workflows. This parameter does not affect the output of the node directly but can be useful in scenarios where the order of operations is crucial. The default value is an empty string, and it is forced to be an input to ensure proper execution sequencing.

🏴 LoRA Selector Output Parameters:

LoRA

The output parameter LoRA provides the name of the selected LoRA model. This output can be used as an input to other nodes that require a LoRA model, such as loaders or processors. The output is essential for linking the selected LoRA model to subsequent nodes in your workflow, enabling the application of the chosen LoRA's characteristics to your models.

🏴 LoRA Selector Usage Tips:

• Ensure that the directory containing your LoRA models is correctly set up so that the LoraSelector can generate an accurate list of available models.
• Use the run_after parameter to control the execution order in complex workflows, ensuring that the LoraSelector node runs after the necessary preceding nodes.

🏴 LoRA Selector Common Errors and Solutions:

"LoRA model not found"

• Explanation: This error occurs when the specified LoRA model name does not exist in the directory.
• Solution: Verify that the LoRA model name is correct and that the model file is present in the designated directory.

"Execution order issue"

• Explanation: This error happens when the node does not execute in the intended order, potentially due to the run_after parameter not being set correctly.
• Solution: Ensure that the run_after parameter is connected to the appropriate preceding node to control the execution flow properly.