# BerniniConditioning

The BerniniConditioning node prepares video and image conditioning data for the Wan2.2-A14B model. It encodes source videos, reference videos, and reference images using the provided VAE, then attaches them to the conditioning data for in-context generation tasks. The task is automatically inferred from which inputs are connected.

## Inputs

| Parameter | Description | Data Type | Required | Range |
|-----------|-------------|-----------|----------|-------|
| `positive` | Positive conditioning data | CONDITIONING | Yes | - |
| `negative` | Negative conditioning data | CONDITIONING | Yes | - |
| `vae` | VAE model used to encode video and image inputs | VAE | Yes | - |
| `width` | Width of the output latent (default: 832) | INT | Yes | 16 to 8192 (step: 16) |
| `height` | Height of the output latent (default: 480) | INT | Yes | 16 to 8192 (step: 16) |
| `length` | Number of frames in the output latent (default: 81) | INT | Yes | 1 to 8192 (step: 4) |
| `batch_size` | Number of videos to generate in a single batch (default: 1) | INT | Yes | 1 to 4096 |
| `source_video` | Source video to edit or restyle (v2v, rv2v). Resized to width/height and trimmed to length. | IMAGE | No | - |
| `reference_video` | Video to insert into the source video (ads2v). | IMAGE | No | - |
| `reference_images` | Reference images injected as in-context tokens (r2v, rv2v). Up to 8 images can be provided. | IMAGE | No | 0 to 8 images |
| `ref_max_size` | Max size for the long edge of reference_video and reference_images. Resized with preserved aspect ratio and snapped to 16px (default: 848). | INT | No | 16 to 8192 (step: 16) |

**Note:** The task is inferred from which inputs are connected:
- No inputs connected → text-to-video (t2v)
- `source_video` only → video-to-video (v2v)
- `source_video` + `reference_images` → reference-guided video editing (rv2v)
- `reference_images` only → reference-to-video (r2v)
- `source_video` + `reference_video` → insert image/video into video (ads2v)

## Outputs

| Output Name | Description | Data Type |
|-------------|-------------|-----------|
| `positive` | Positive conditioning with context latents attached | CONDITIONING |
| `negative` | Negative conditioning with context latents attached | CONDITIONING |
| `latent` | Empty latent tensor with dimensions matching the specified width, height, length, and batch size | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BerniniConditioning/en.md)

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