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The ComfyUI-Stream-Pack is in active development and not yet stable. We welcome your feedback as we continue to improve it.
The ComfyUI-Stream-Pack provides a custom node pack for ComfyUI, designed specifically for building real-time video, audio, and data pipelines. These tools enhance output quality, optimize performance, and include benchmarking and profiling features to help users create and refine efficient AI-driven workflows.

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Installation

We are actively working on publishing the StreamPack as a ComfyUI registry node. Once available, you will be able to install it directly via the ComfyUI Manager for a more streamlined setup process.
To use the StreamPack nodes, you need to install the StreamPack repository in your ComfyUI setup.
1

Navigate to the custom_nodes directory

Open a terminal and navigate to the custom_nodes directory in your ComfyUI workspace:
cd /workspace/ComfyUI/custom_nodes
2

Clone the StreamPack repository

Clone the StreamPack repository from GitHub:
git clone https://github.com/livepeer/ComfyUI-Stream-Pack.git
cd ComfyUI-Stream-Pack
3

Install dependencies

Activate your ComfyUI environment and install the required dependencies:
conda activate comfyui
pip install -r requirements.txt
4

Restart ComfyUI

Restart your ComfyUI server to load the new nodes.

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StreamPack Nodes Overview

We also recommend third-party nodes from other teams that work well with real-time workflows. While not maintained by the ComfyStream team, these nodes are highly compatible and can enhance your pipelines. Learn more on the Third-Party Nodes page.
StreamPack includes a variety of custom nodes grouped into four main categories: Video Quality Nodes, which enhance video output; Performance Nodes, which optimize real-time workflows; Benchmarking and Profiling Tools, which help analyze and refine workflow efficiency; and Task-Specific Nodes, which provide specialized functionality for real-time video workflows.
  • Feature Bank: Improves video quality by using information from previous frames to reduce flickering and ensure smoother transitions.
  • Super Resolution: A high-performance upscaling node that uses neural network models like FSRCNN and EDSR to enhance video resolution in real-time, balancing speed and quality.
The nodes in this category are still under development and will be released soon.
The nodes in this category are still under development and will be released soon.
  • Facial Mesh: A MediaPipe Face Mesh node that detects and tracks facial landmarks. It can be used as an additional ControlNet input to enhance facial tracking in real-time workflows.