ComfyUI-IPAdapterWAN

ComfyUI-IPAdapter-WAN

This extension adapts the InstantX IP-Adapter for SD3.5-Large to work with Wan 2.1 and other UNet-based video/image models in ComfyUI.

Unlike the original SD3 version (which depends on joint_blocks from MMDiT), this version performs sampling-time identity conditioning by dynamically injecting into attention layers — making it compatible with models like Wan 2.1, AnimateDiff, and other non-SD3 pipelines.

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🚀 Features

• 🔁 Injects identity embeddings during sampling via attention block patching
• 🧠 Works with Wan 2.1 and other UNet-style models (no SD3/MMDiT required)
• 🛠️ Built on top of ComfyUI's IPAdapter framework
• 🎨 Enables consistent face/identity across frames in video workflows

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📦 Installation

1. Clone the repo into your ComfyUI custom nodes directory:

git clone https://github.com/your-username/ComfyUI-IPAdapter-WAN.git

2. Download the required model weights:

• Download the IP-Adapter weights:

  • ip-adapter.bin

  • Place it in: ComfyUI/models/ipadapter/

• Download the CLIP Vision model:

  • siglip_vision_patch14_384.safetensors

  • Place it in: ComfyUI/models/clip_vision/

(Note: This model is based on google/siglip-so400m-patch14-384. The rehosted version yields nearly identical results.)

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🧠 How It Works

Wan models use a UNet structure instead of the DiT transformer blocks used in SD3. To make IPAdapter work with Wan:

• The extension scans all attention blocks (modules with .to_q and .to_k) dynamically.

• It injects IPAdapter's attention processors (IPAttnProcessor) directly into those blocks.

• Identity embeddings are updated based on the current sampling timestep using a learned resampler.

This means it works without requiring joint_blocks or specific architectural assumptions — making it plug-and-play for many custom models.

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🛠 Usage

1. In ComfyUI, use the following nodes:

   • Load IPAdapter WAN Model

   • Apply IPAdapter WAN Model

2. Connect the CLIP Vision embedding (from a face image) and your diffusion model to the adapter.

3. Use a weight of ~0.5 as a good starting point.

4. You can apply this in video workflows to maintain consistent identity across frames.

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📁 Example Workflows

Example .json workflows will be available soon in the workflows/ folder.

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✅ Compatibility

| Model | Status | | ---------------- | ------------------- | | Wan 2.1 | ✅ Works | | AnimateDiff | ✅ Works | | SD3 / SDXL | ❌ Use original repo | | Any UNet variant | ✅ Likely to work |

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🔧 TODOs

• Allow multiple adapters without conflict

• Auto-detect model parameters (hidden size, num layers)

• Convert .bin to safetensors format

• Add more workflows for different models

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🧑‍💻 Credits

• Adapted from: InstantX IPAdapter for SD3.5

• ComfyUI extensions by: your name / handle here

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Feel free to contribute or suggest improvements via GitHub Issues or Pull Requests.