BeefTV Turns AI Video Production Into a Visual Node Graph

An open-source desktop canvas lets creators chain prompts, images, and video models into reusable AI storyboarding workflows, with assets stored locally.

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PRO
  • BeefTV is an open-source, MIT-licensed AI video workspace built on an infinite node canvas.
  • Desktop client for macOS and Windows, built with React, Go, and Wails, with Docker Compose for server pieces.
  • Users plug in their own text, image, video, and audio model API keys with no provider lock-in.
  • Local-first storage keeps projects, canvases, assets, and tasks on disk for migration and privacy.
  • Targets AI short-drama and storyboard creators doing batch shot generation from character references.
  • Repo has crossed 1,300 stars and 260 forks, with an active issues and PR queue.

BeefTV turns AI video work into a node graph

BeefTV is a new MIT-licensed desktop workspace that arranges AI video production on a zoomable, node-based canvas. At publication, its GitHub repository had 1.1k stars and 218 forks. The project combines prompts, reference media, scripts, generated assets, and automated agents in one local workspace, giving developers an extensible foundation for short-form video pipelines.

The canvas preserves the recipe

Each BeefTV node can hold text, images, audio, video, or processing instructions, and connections record how those inputs produce subsequent assets. A storyboard can therefore retain its character references, prompts, shot descriptions, and generated clips as a reusable graph.

  • Create: Generate text, images, video, and audio from prompts or reference assets.
  • Connect: Link nodes to establish creative context, dependencies, and generation order.
  • Process: Crop, annotate, inpaint, split, reference, and combine media.
  • Iterate: Branch workflows, reuse assets, and preserve the steps behind each result.

Four pieces under the hood

BeefTV targets macOS and Windows and uses React, Go, and Wails, a framework that packages a web interface and Go services as a native desktop application. The repository separates the interface, backend, agent runtime, and extension packages.

Component Role
React frontend Renders the canvas, nodes, previews, and workspace controls.
Go backend Handles desktop services, task coordination, and application logic.

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