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ComfyUI Node: Apply VisualStyle Prompting ♾️Mixlab

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shadowcz007 (Account age: 3323 days)
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How to Install comfyui-mixlab-nodes

Install this extension via the ComfyUI Manager by searching for  comfyui-mixlab-nodes
  • 1. Click the Manager button in the main menu
  • 2. Select Custom Nodes Manager button
  • 3. Enter comfyui-mixlab-nodes in the search bar
After installation, click the  Restart button to restart ComfyUI. Then, manually refresh your browser to clear the cache and access the updated list of nodes.

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Apply VisualStyle Prompting ♾️Mixlab Description

Enhance AI-generated artwork with specific visual styles using advanced attention mechanisms and style processing techniques.

Apply VisualStyle Prompting ♾️Mixlab:

The ApplyVisualStylePrompting_ node is designed to enhance your AI-generated artwork by applying specific visual styles to your prompts. This node leverages advanced attention mechanisms and style processing techniques to modify the visual attributes of your input data, ensuring that the output aligns with the desired artistic style. By integrating this node into your workflow, you can achieve more consistent and visually appealing results, making it an essential tool for AI artists looking to refine their creations. The primary goal of this node is to provide a seamless way to incorporate complex visual styles into your prompts, thereby elevating the overall quality and coherence of your generated images.

Apply VisualStyle Prompting ♾️Mixlab Input Parameters:


This parameter represents the conditioning input, which is essential for guiding the visual style application process. It typically includes the initial prompt or context that you want to style. The conditioning input ensures that the visual style is applied in a manner that is coherent with the original content.


The clip parameter refers to the CLIP model used for processing the input data. CLIP (Contrastive Language-Image Pre-Training) is a powerful model that understands both images and text, enabling it to effectively guide the visual style application. This parameter ensures that the style is applied in a way that is contextually relevant to the input data.


This parameter specifies the GLIGEN model used for text box processing. GLIGEN (Generative Language-Image Generation) is a model that helps in generating images based on textual descriptions. By using this model, the node can better understand and apply the desired visual style to the input prompt.


The grids parameter represents a collection of rectangular boxes that define specific areas within the input data. These grids help in localizing the application of the visual style, ensuring that it is applied precisely where needed. This parameter is crucial for tasks that require detailed and localized style adjustments.


This parameter consists of a set of labels corresponding to each rectangular box in the grids. These labels provide additional context and guidance for the visual style application, ensuring that each area is styled appropriately based on its label. The labels can be multiline strings, allowing for detailed descriptions.

Apply VisualStyle Prompting ♾️Mixlab Output Parameters:


The prompt output parameter is a string that represents the modified prompt after the visual style has been applied. This output is crucial as it provides the final styled prompt that can be used for further processing or directly as input for image generation. The prompt ensures that the visual style is consistently and accurately reflected in the final output.

Apply VisualStyle Prompting ♾️Mixlab Usage Tips:

  • To achieve the best results, ensure that your conditioning input is well-defined and provides clear context for the desired visual style.
  • Experiment with different CLIP and GLIGEN models to find the combination that best suits your artistic needs and enhances the visual style application.
  • Utilize the grids and labels parameters to localize and fine-tune the application of the visual style, especially for complex prompts that require detailed adjustments.

Apply VisualStyle Prompting ♾️Mixlab Common Errors and Solutions:

"Invalid conditioning input"

  • Explanation: This error occurs when the conditioning input is not properly defined or is incompatible with the node's requirements.
  • Solution: Ensure that your conditioning input is a well-structured prompt or context that provides clear guidance for the visual style application.

"CLIP model not found"

  • Explanation: This error indicates that the specified CLIP model is not available or cannot be loaded.
  • Solution: Verify that the CLIP model path is correct and that the model is properly installed. Consider using a different CLIP model if the issue persists.

"GLIGEN model not found"

  • Explanation: This error occurs when the specified GLIGEN model is not available or cannot be loaded.
  • Solution: Check the GLIGEN model path and ensure that the model is correctly installed. Try using an alternative GLIGEN model if necessary.

"Grid dimensions mismatch"

  • Explanation: This error indicates that the dimensions of the grids do not match the input data or are incorrectly defined.
  • Solution: Review the grid dimensions and ensure they align with the input data. Adjust the grid sizes and positions as needed to match the input.

"Label format error"

  • Explanation: This error occurs when the labels provided are not in the correct format or do not correspond to the grids.
  • Solution: Ensure that the labels are properly formatted and correspond to each grid. Use multiline strings if necessary to provide detailed descriptions.

Apply VisualStyle Prompting ♾️Mixlab Related Nodes

Go back to the extension to check out more related nodes.

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