[Frontend] Add ComfyUI FastH3 node, fix t2va aspect ratio and dropped audio (#7456)

Signed-off-by: princepride <wangzhipeng628@gmail.com>
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
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汪志鹏andClaude Opus 5 authored and GitHub committed 2026-09-14 11:22:05 +08:00
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@@ -13,7 +13,6 @@ It can send model inference requests to either a locally running vLLM-Omni servi
!!! 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`.
@@ -21,9 +20,10 @@ Copy the `apps/ComfyUI-vLLM-Omni` folder to the `custom_nodes` subfolder of your
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.
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
@@ -35,6 +35,7 @@ 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
```
@@ -56,6 +57,20 @@ This extension also offers example workflows (at **ComfyUI sidebar -> Templates
!!! 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.
Every node carries the vLLM-Omni mark in its title bar and is tinted by what it outputs, so a graph is readable at a glance:
| Colour | Nodes | What they produce |
| --- | --- | --- |
| Blue | Generate Image, Generate Video, Multimodality Understanding, TTS, TTS Voice Clone | A generated image, video, audio, or text. These are the only nodes that reach a server. |
| Amber | AR / Diffusion / Multi-Stage Sampling Params | Sampling parameters that apply to any model |
| Purple | Qwen TTS Params, Wan Video Params, MiniMax-H3 Video Params | Parameters that only one model family accepts |
| Red | LoRA, FastH3 Deployment | Which weights the server is expected to have loaded |
| Teal | Video References | Reference media |
Recolouring a node by hand (right click -> Colors) overrides its tint, and the choice is kept.
**Generate Video** takes a clip length in seconds (`duration`), not a frame count. Frames stay the wire unit and are derived with the node's `fps`, so the length is always measured against the rate that is actually served; models that accept only certain frame counts still round to their own lattice server-side. Graphs saved before this widget existed stored `num_frames` in its place and are converted on load, using the fps recorded alongside it -- the browser console names every node it rewrites.
To build a simple workflow yourself,
- Drag a generation node onto the canvas.