Ross ROSS = Recommend OSS · open-source software intelligence for agents

google/visualblocks

Visual Blocks for ML is a Google visual programming framework that lets you create ML pipelines in a no-code graph editor. You – and your users – can quickly prototype workflows by connecting drag-and-drop ML components, including models, user inputs, processors, and visualizations. observed · 2026-08-28

github.com/google/visualblocks · homepage · TypeScript · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

71/100

  • Activity 90
  • Release rhythm 35
  • Longevity 89

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1253
  • days_rel: n/a
  • days_push: 64
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1361 stars · 176 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Visual Blocks for ML is a Google visual programming framework that provides a no-code node graph editor for building ML pipelines from drag-and-drop components like models, inputs, processors, and visualizations. It ships as a JavaScript front-end library for embedding the editing experience, plus a Python package for use in Google Colaboratory notebooks.

Use cases

  • build ML pipelines without writing code
  • prototype AI workflows with a drag-and-drop node editor
  • embed a visual ML pipeline editor in my web app
  • connect ML models, camera inputs, and visualizations in a graph
  • register notebook functions as nodes in a visual pipeline UI
  • rapidly experiment with multimedia ML application pipelines

When to choose

  • you want no-code/low-code visual prototyping of ML pipelines
  • you need to embed a node graph editor in a web platform
  • you work in Google Colab and want an interactive pipeline UI over notebook functions
  • you are iterating on multimedia ML app ideas like camera or image pipelines

When to avoid

  • you need production-grade, code-first ML orchestration with full programmatic control
  • your pipelines require custom node types not supported by the library
  • you need a backend-heavy workflow engine rather than a browser-based editor

Facets

framework · maturity active

machine-learning data-visualization frontend-framework ui-components workflow-automation machine-learning artificial-intelligence developer-tools data-science web-development browser python no-code visual-programming node-graph-editor ml-pipelines prototyping google angular colab web-server typescript

2 sources

Member repositories

RepositoryRoleHealth v2
google/visualblocksmain71

For agents

markdown · JSON · MCP: product_card(name="google/visualblocks")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem