Pi-generative-UI: Claude.ai's generative UI reverse-engineered, rebuilt for pi

2026-03-132:3310github.com

Claude.ai's generative UI — reverse-engineered, rebuilt for pi. Interactive HTML/SVG widgets in native macOS windows. - Michaelliv/pi-generative-ui

Claude.ai's generative UI - reverse-engineered, rebuilt for pi.

Ask pi to "show me how compound interest works" and get a live interactive widget - sliders, charts, animations - rendered in a native macOS window. Not a screenshot. Not a code block. A real HTML application with JavaScript, streaming live as the LLM generates it.

On claude.ai, when you ask Claude to visualize something, it calls a tool called show_widget that renders HTML inline in the conversation. The HTML streams live - you see cards, charts, and sliders appear as tokens arrive.

This extension replicates that system for pi:

  1. LLM calls visualize_read_me - loads design guidelines (lazy, only the relevant modules)
  2. LLM calls show_widget - generates an HTML fragment as a tool call parameter
  3. Extension intercepts the stream - opens a native macOS window via Glimpse and feeds partial HTML as tokens arrive
  4. morphdom diffs the DOM - new elements fade in smoothly, unchanged elements stay untouched
  5. Scripts execute on completion - Chart.js, D3, Three.js, anything from CDN

The widget window has full browser capabilities (WKWebView) and a bidirectional bridge - window.glimpse.send(data) sends data back to the agent.

pi install git:github.com/user/pi-generative-ui

macOS only. Requires Swift toolchain (ships with Xcode or Xcode Command Line Tools).

Just ask pi to visualize things. The extension adds two tools that the LLM calls automatically:

  • "Show me how compound interest works" → interactive explainer with sliders and Chart.js
  • "Visualize the architecture of a transformer" → SVG diagram with labeled components
  • "Create a dashboard for this data" → metric cards, charts, tables
  • "Draw a particle system" → Canvas animation

The LLM decides when to use widgets vs text based on the request. Explanatory/visual requests trigger widgets; code/text requests stay in the terminal.

The design guidelines aren't hand-written. They're extracted verbatim from claude.ai.

Here's the trick: you can export any claude.ai conversation as JSON. The export includes full tool call payloads - including the complete read_me tool results containing Anthropic's actual design system. 72K of production rules covering typography, color palettes, streaming-safe CSS patterns, Chart.js configuration, SVG diagram engineering, and more.

We triggered read_me with each module combination, exported the conversation, parsed the JSON, split the responses into deduplicated sections, and verified byte-level accuracy against the originals. The result: our LLM gets the exact same instructions Claude gets on claude.ai.

Five modules, loaded on demand:

Module Size What it covers
interactive 19KB Sliders, metric cards, live calculations
chart 22KB Chart.js setup, custom legends, number formatting
mockup 19KB UI component tokens, cards, forms, skeleton loading
art 17KB SVG illustration, Canvas animation, creative patterns
diagram 59KB Flowcharts, architecture diagrams, SVG arrow systems

The extension intercepts pi's streaming events (toolcall_start / toolcall_delta / toolcall_end) to render the widget live as tokens arrive:

toolcall_start    → initialize streaming state
toolcall_delta    → debounce 150ms, open window, morphdom diff
toolcall_end      → final diff + execute <script> tags
execute()         → reuse window, wait for interaction or close

Key details:

  • Shell HTML + JS eval - window opens with an empty shell; content injected via win.send(), not setHTML(), to avoid full-page flashes
  • morphdom DOM diffing - only changed nodes update; new nodes get a 0.3s fade-in animation
  • pi-ai's parseStreamingJson - no need for a partial JSON parser; pi already provides parsed arguments on every delta
  • 150ms debounce - batches rapid token updates for smooth visual rendering
  • Dark mode by default - #1a1a1a background, designed for macOS WKWebView

Glimpse is a native macOS micro-UI library. It opens a WKWebView window in under 50ms via a tiny Swift binary. No Electron, no browser tab, no runtime dependencies beyond the system WebKit.

The Swift source compiles automatically on npm install via postinstall.

pi-generative-ui/
├── .pi/extensions/generative-ui/
│   ├── index.ts              # Extension: tools, streaming, Glimpse integration
│   ├── guidelines.ts         # 72K of verbatim claude.ai design guidelines
│   └── claude-guidelines/    # Raw extracted markdown (reference)
│       ├── art.md
│       ├── chart.md
│       ├── diagram.md
│       ├── interactive.md
│       ├── mockup.md
│       └── sections/         # Deduplicated sections
└── package.json              # pi-package manifest
  1. Start a conversation on claude.ai that triggers show_widget
  2. Call read_me with each module combination (art, chart, diagram, interactive, mockup)
  3. Export the conversation as JSON from claude.ai settings
  4. Parse the JSON - every tool_result for visualize:read_me contains the complete guidelines
  5. Split each response at ## heading boundaries
  6. Deduplicate shared sections (e.g., "Color palette" appears in chart, mockup, interactive, diagram)
  7. Verify reconstruction matches the originals (4/5 exact, 1 has a single whitespace char difference)

The raw read_me responses are preserved in claude-guidelines/ - the original markdown exactly as claude.ai returned it, before splitting and deduplication. The conversation export JSON is not included in this repo.

  • pi - the extensible coding agent that makes this possible
  • Glimpse - native macOS WKWebView windows
  • morphdom - DOM diffing for smooth streaming
  • Anthropic - for building the generative UI system we reverse-engineered

MIT


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