# vLLM-Omni ComfyUI Integration

vLLM-Omni offers a ComfyUI integration on top of its online serving API.
It can send model inference requests to either a locally running vLLM-Omni service or a remote one.

## Requirement

- Python 3.12 or above
- [ComfyUI installed](https://docs.comfy.org/installation/system_requirements)
- [vLLM-Omni installed](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/installation/) on either the same device or another device discoverable via the internet.
- No need to install additional packages apart from those already required by ComfyUI.

!!! tip
    If you run both ComfyUI and vLLM-Omni on the same device, you can create separate virtual environments and use different Python versions for them.


## Installation

Copy the `apps/ComfyUI-vLLM-Omni` folder to the `custom_nodes` subfolder of your ComfyUI installation. Your directory should look like `ComfyUI/custom_nodes/ComfyUI-vLLM-Omni`.

If you are running ComfyUI during copying, you should restart ComfyUI to load this extension.

!!! tip
    You can use utility websites such as https://download-directory.github.io/ to download a subdirectory of a repo. Also checkout community discussions (e.g., https://stackoverflow.com/questions/7106012/download-a-single-folder-or-directory-from-a-github-repository) for more info.

On the device and virtual environment you run ComfyUI, launch ComfyUI with
```bash
cd ComfyUI

# The regular way
python main.py

# If you are mainly using this node, launch it faster with
python main.py --cpu
```

On the device and virtual environment you run vLLM-Omni, start a model service with
```bash
vllm serve The_Model_ID_to_Serve --omni --port 8000
```

Check **ComfyUI's sidebar -> Node Library**. There should be a new folder named **vLLM-Omni**.
If no, check your shell running the ComfyUI process. There may be some error messages before the line `Import times for custom nodes:` and the line `To see the GUI go to: http://127.0.0.1:8188`.

## Quickstart

This extension offers the following nodes based on the output modalities:

- **Generate Image** for text-to-image and image-to-image tasks
- **Generate Video** for text-to-video and image-to-video tasks
- **Multimodality Understanding** for multimodality-to-text and multimodality-to-audio tasks
- **TTS** and **TTS Voice Clone** for TTS tasks

This extension also offers example workflows (at **ComfyUI sidebar -> Templates -> vLLM-Omni**)

!!! info
    The node UI and feature designs are intended to match vLLM-Omni online serving interfaces. It cannot offer more than what the interfaces support.

To build a simple workflow yourself,

- Drag a generation node onto the canvas.
- Depending on your need, grab built-in multimedia file loader nodes, such as **image->Load Image**, **image->video->Load Video**, **audio->Load Audio**
- Depending on your need, grab built-in multimedia file preview nodes, such as **image->Preview Image**, **image->video->Save Video**, **audio->Preview Audio**, **utils->Preview as Text**.
- If you want to tune sampling parameters, grab corresponding nodes from **vLLM-Omni-> Sampling Params**.
    - For multi-stage models, you can connect multiple **AR Sampling Params** and **Diffusion Sampling Params** nodes to a **Multi-Stage Sampling Params List** node, and connect this node to the generation node.
    - For some multi-stage models like BAGEL, [only one stage's sampling parameters are exposed and tunable via vLLM-Omni's online serving API](https://docs.vllm.ai/projects/vllm-omni/en/latest/user_guide/examples/online_serving/bagel/). Thus, these models are treated as single-stage ones. Please check the vLLM-Omni documentation on how to correctly set each model's sampling parameters.
    - For multi-stage models where all stages are either autoregression or diffusion, you can also connect only a single Sampling Params node, indicating that this set of sampling parameters will be used for all stages.

## Examples & Screenshots

Please read the [ComfyUI integration's README](https://github.com/vllm-project/vllm-omni/tree/main/apps/ComfyUI-vLLM-Omni) for more info.