TextEncodeBooguEdit - ComfyUI Built-in Node Documentation

This node prepares conditioning for image editing with Boogu. It processes reference images to create both positive and negative conditioning outputs. The reference image is used twice: vision tokens from the image are added only to the positive conditioning to amplify the edit instruction, while a VAE reference latent is added to both positive and negative conditioning so it cancels out under CFG, preserving the original image identity.

Inputs

Parameter	Description	Data Type	Required	Range
`clip`	The CLIP model used for text encoding	CLIP	Yes
`prompt`	The text prompt describing the desired edit	STRING	Yes
`negative_prompt`	The text prompt describing what to avoid in the edit	STRING	No
`vae`	The VAE model used to encode reference images into latent space	VAE	No
`images`	Reference image(s) to edit. Boogu focuses on one reference per sample; more are allowed.	IMAGE	No	Up to 16 images

Outputs

Output Name	Description	Data Type
`positive`	Conditioning containing both the text prompt with vision tokens and the reference latents	CONDITIONING
`negative`	Conditioning containing the negative text prompt and the reference latents	CONDITIONING

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Outputs