Diffusion Studio Core: Browser-Based Video Compositing Engine
This repository profile is provided by osrepos.com, an open source repository discovery platform.

Summary
Diffusion Studio Core is a powerful, browser-based video compositing engine built with TypeScript. It leverages WebCodecs and Canvas2D for hardware-accelerated media processing directly within the browser. Designed for developers building non-linear editors, it supports both interactive playback for editing and high-fidelity rendering for final output across video, audio, and image workloads.
Repository Information
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Introduction
Diffusion Studio Core is a powerful, browser-based video compositing engine written in TypeScript. It provides a robust framework for fast media composition, optimized for video, audio, and image workloads. Leveraging the WebCodecs API and Canvas2DContext, it taps directly into hardware-accelerated processing within the browser, enabling both interactive playback for editing and high-fidelity rendering for final output. Developers often use it to build non-linear editors or other timeline-based media applications.
Installation
To get started with Diffusion Studio Core, you can install it via npm:
npm install @diffusionstudio/core
Once installed, you can import and use it in your TypeScript project:
import *s core from "@diffusionstudio/core";
const composition = new core.Composition();
Examples
Diffusion Studio Core offers a rich set of features for manipulating media. Here are a few examples demonstrating its capabilities:
Concatenate two videos
const sources = await Promise.all([
core.Source.from<core.VideoSource>('/intro.webm'),
core.Source.from<core.VideoSource>('/outro.mp4'),
]);
const layer = await composition.add(
new core.Layer({
mode: 'SEQUENTIAL'
})
);
await layer.add(
new core.VideoClip(sources[0], {
range: [2, 8],
})
);
await layer.add(
new core.VideoClip(sources[1], {
range: [2, 12],
})
);
Apply basic transitions
new core.VideoClip(/** source **/, {
transition: {
duration: 1,
type: 'dissolve',
}
})
Mask an image
const mask = new core.RectangleMask({
width: 640,
height: 1080,
radius: 100,
});
new core.ImageClip(/** source **/, { mask });
Animate your clips with key frames
new core.TextClip({
text: "Hello World",
align: 'center',
baseline: 'middle',
position: 'center',
animations: [
{
key: 'rotation',
frames: [
{ time: 0, value: 0 },
{ time: 2, value: 720 },
],
},
]
});
Add basic effects to visual clips
new core.RectangleClip({
position: 'center',
delay: 6,
duration: 4,
effects: [
{
type: 'blur',
value: 10,
},
{
type: 'hue-rotate',
value: 90
}
]
})
Why use Diffusion Studio Core
Diffusion Studio Core is ideal if you are building a timeline-based application, such as a Non-Linear Editor (NLE), that requires in-browser video rendering. It's perfect for composing multiple assets into video or audio outputs and offers a framework-agnostic, efficient video engine compatible with popular frameworks like Svelte, Vue, Solid, and Angular.
Links
- GitHub Repository: diffusionstudio/core
- Documentation: Diffusion Studio Docs
- Discord: Join the Discord
Related repositories
Similar repositories that may be relevant next.

MetaMCP: Unifying Model Context Protocol Servers with an All-in-One Gateway
August 19, 2026
MetaMCP is a powerful, self-hosted solution that acts as an aggregator, orchestrator, middleware, and gateway for Model Context Protocol (MCP) servers. It allows developers to dynamically combine multiple MCP servers into a single, unified endpoint, enhancing tool management and agent development. This TypeScript-based project simplifies the deployment and management of AI tools within a Dockerized environment.

microsoft/skills: Empowering AI Coding Agents with Domain-Specific Knowledge
August 19, 2026
The microsoft/skills repository provides a comprehensive collection of skills, custom agents, and configurations designed to enhance AI coding agents. It offers domain-specific knowledge for working with Azure SDKs and Microsoft AI Foundry, enabling more effective and context-driven development. Developers can leverage these resources to ground agents like GitHub Copilot with specialized expertise.

ClawHub: The Public Skill and Plugin Registry for OpenClaw
August 19, 2026
ClawHub is the public skill and plugin registry for OpenClaw, designed for publishing, versioning, and searching text-based agent skills and code plugins. It offers fast browsing, a CLI-friendly API, moderation hooks, and vector search capabilities. This platform streamlines the discovery and management of resources for the OpenClaw ecosystem.

code-session-memory: Automatic Vector Memory for AI Coding Sessions
August 15, 2026
code-session-memory provides automatic vector memory for various AI coding tools like OpenCode, Claude Code, Cursor, VS Code, Codex, and Gemini CLI. It indexes new messages into a vector database after each AI agent turn, enabling semantic search across all your past coding sessions. This tool ensures memory is shared across different platforms, enhancing developer productivity.
Source repository
Open the original repository on GitHub.
17 counted GitHub visits