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AI/TLDR

AntV Infographic

A declarative infographic engine whose syntax is tuned for models to stream

Generative UI SDKsOpen source
Language
TypeScript
License
MIT
$npm install @antv/infographic

Overview

Preview of infographics rendered by AntV Infographic in several layouts and visual styles
Sample infographics rendered by AntV InfographicAntV Infographic README ↗

AntV Infographic is AntV's declarative infographic visualisation engine. Instead of hand-placing shapes, you write a short indentation-based document that names a template and supplies the data, and the engine renders a finished infographic from it. The syntax was designed to be written by a model as much as by a person: it is concise enough to fit in a prompt and deliberately fault-tolerant.

That fault tolerance is what makes it a generative-UI component rather than a chart library. Because a partial document still parses, you can append an LLM's output chunk by chunk and re-render on every chunk, so the infographic builds itself in front of the user as the model writes it. Around 200 built-in templates, data-item components and layouts cover the common shapes, and a theme system supplies hand-drawn, gradient and pattern presets before you start customising.

Output is SVG by default, which keeps the result crisp and editable rather than baked into pixels, and the package ships a built-in editor so a user can adjust whatever the model produced. AntV also publishes a set of agent skills — infographic-creator, infographic-syntax-creator, infographic-structure-creator and infographic-item-creator — that teach a coding agent the syntax, installable from a Claude Code plugin marketplace.

What it does

Animation of an infographic rendering progressively while AI output streams in
Streaming rendering as tokens arriveAntV Infographic README ↗
  • Declarative, indentation-based infographic syntax designed to be generated by a model
  • Highly fault-tolerant parsing, so a streaming LLM response can be re-rendered on every chunk
  • ~200 built-in infographic templates, data-item components and layouts
  • Theme system with hand-drawn, gradient and pattern presets plus deep customisation
  • A built-in editor so AI-generated infographics can be edited afterwards
  • SVG rendering by default for visual fidelity and downstream editing

Getting started

Infographic ships as the @antv/infographic npm package. You create an instance bound to a container element and call render with an infographic document.

Install the package

bashbash
npm install @antv/infographic

Render your first infographic

Construct an Infographic bound to a container, then pass a document naming a template and its data. Setting editable: true turns on the built-in editor.

tsts
import { Infographic } from '@antv/infographic';

const infographic = new Infographic({
  container: '#container',
  width: '100%',
  height: '100%',
  editable: true,
});

infographic.render(`
infographic list-row-simple-horizontal-arrow
data
  lists
    - label Step 1
      desc Start
    - label Step 2
      desc In Progress
    - label Step 3
      desc Complete
`);
The infographic rendered from the README's quick-start syntax example
What step 2 rendersAntV Infographic README ↗

Stream a model's output into it

Because a partial document still parses, you can accumulate chunks from an LLM and re-render each time to get progressive rendering.

tsts
let buffer = '';
for (const chunk of chunks) {
  buffer += chunk;
  infographic.render(buffer);
}

Install the agent skills

AntV publishes skills that teach a coding agent the syntax and the structure/item design system. They are available from a Claude Code plugin marketplace.

texttext
/plugin marketplace add https://github.com/antvis/Infographic.git
/plugin install antv-infographic-skills@antv-infographic

Commands and code are distilled from the project's own documentation — always check the official repo for the latest.

When to use it

  • Reach for it when a chat product should answer with a rendered infographic instead of a wall of bullet points
  • Reach for it when you want the visual to appear progressively as the model streams, rather than after the response completes
  • Reach for it when generated visuals need to stay editable — SVG output plus a built-in editor lets a user fix what the model got wrong
  • Reach for it to give a coding agent a constrained visual vocabulary, so it produces a consistent deck of infographics rather than ad-hoc SVG

How AntV Infographic compares

AntV Infographic alongside other open-source generative ui sdks tools AI/TLDR tracks, ranked by GitHub stars.

ToolStarsWhat it does
CopilotKit★ 38.2kA frontend framework for adding in-app AI copilots and agent-driven generative UI to React and other apps, and the maker of the AG-UI protocol.
Vercel AI SDK★ 27.5kA TypeScript toolkit for building AI apps and agents that includes streaming helpers and generative-UI features for rendering model output as React components.
OpenUI★ 22.7kOpenUI lets you describe a UI in plain language, see it rendered live, ask for changes, and convert the result to React, Svelte, or Web Components.
json-render★ 18.8kVercel Labs' generative UI framework: you declare a catalog of allowed components, a model emits JSON constrained to it, and renderers for React, Vue, Svelte, Solid, React Native, PDF, email and whole Next.js or TanStack Start apps draw it.
AG-UI Protocol★ 16.8kAn open protocol that standardizes how AI agents stream events and UI to frontend applications, with SDKs across multiple languages and frameworks.
OpenUI (Thesys)★ 13.5kAn open standard and runtime for generative UI that uses a compact streaming language to let models emit interactive charts, forms, tables, and cards.
assistant-ui★ 12.7kA TypeScript/React library of composable chat primitives for building AI chat apps that can render tool calls and JSON as interactive React components.
AntV Infographic★ 7kA declarative infographic engine whose syntax is tuned for models to stream