Skip to main content
The CLIPTextEncodeControlnet node processes text input using a CLIP model and combines it with existing conditioning data to create enhanced conditioning output for controlnet applications. It tokenizes the input text, encodes it through the CLIP model, and adds the resulting embeddings to the provided conditioning data as cross-attention controlnet parameters.

​
Inputs

ParameterDescriptionData TypeRequiredRange
clipThe CLIP model used for text tokenization and encodingCLIPYes-
conditioningExisting conditioning data to be enhanced with controlnet parametersCONDITIONINGYes-
textText input to be processed by the CLIP model. Supports multiline text and dynamic promptsSTRINGYes-
Note: This node requires all three inputs (clip, conditioning, and text) to function properly. The text input supports dynamic prompts and multiline text for flexible text processing.

​
Outputs

Output NameDescriptionData Type
CONDITIONINGEnhanced conditioning data with added controlnet cross-attention parameters (cross_attn_controlnet and pooled_output_controlnet) derived from the CLIP text encodingCONDITIONING
This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHub
Source fingerprint (SHA-256): 36f0c9b7d3f3187bcf794c71e8a261d456972a41c079ddaca0cb5117912e9685