This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHubThe TextEncodeQwenImageEdit node processes text prompts and optional images to generate conditioning data for image generation or editing. It uses a CLIP model to tokenize the input and can optionally encode reference images using a VAE to create reference latents. When an image is provided, it automatically resizes the image to maintain consistent processing dimensions.
Inputs
| Parameter | Data Type | Required | Range | Description |
|---|---|---|---|---|
clip | CLIP | Yes | - | The CLIP model used for text and image tokenization |
prompt | STRING | Yes | - | Text prompt for conditioning generation, supports multiline input and dynamic prompts |
vae | VAE | No | - | Optional VAE model for encoding reference images into latents |
image | IMAGE | No | - | Optional input image for reference or editing purposes |
image and vae are provided, the node encodes the image into reference latents and attaches them to the conditioning output. The image is automatically resized to maintain a consistent processing scale of approximately 1024x1024 pixels.
Outputs
| Output Name | Data Type | Description |
|---|---|---|
CONDITIONING | CONDITIONING | Conditioning data containing text tokens and optional reference latents for image generation |