UIX

The Last Mile from AI to Human

AI-to-UI Intermediate Representation (IR) Protocol & Conversion Engine

What UIX Is (and What It Is Not)

UIX is a protocol layer and conversion engine, not a Chat UI framework.

If you need a full-featured React chat interface, use assistant-ui — it's excellent and battle-tested. UIX solves a different problem: normalizing AI output from any source into a single, stable format.

                      ┌─────────────────────────┐
Vercel AI SDK ──────→ │                         │
AgentX ─────────────→ │   UIX IR                │ ──→ assistant-ui
AG-UI (CopilotKit) ─→ │   (unified format)      │ ──→ your own renderer
A2UI (Google) ──────→ │                         │ ──→ any UI framework
                      └─────────────────────────┘

Think of UIX as Babel for AI output — Babel normalizes JavaScript across engines; UIX normalizes AI output across providers.

The Problem

AI backends all speak different formats:

Source	Message Format	Tool Call Format	Streaming Protocol
Vercel AI SDK	`UIMessage.parts[]`	`ToolInvocationPart`	Data Stream
AgentX	`Conversation.blocks[]`	`ToolBlock`	WebSocket events
AG-UI (CopilotKit)	AG-UI events	`ToolCallStart/End`	SSE events
A2UI (Google)	Declarative UI payload	Component-based	gRPC stream

If you build a chat UI, you're locked into one format. Switch backends? Rewrite your UI layer.

UIX IR eliminates this coupling. Your UI only knows LucidConversation and LucidBlock — adapters handle the rest.

Architecture

┌─────────────────────────────────────────────────────────────────┐
│  AI Backends (upstream)                                         │
│  Vercel AI SDK · AgentX · AG-UI · A2UI · LangChain · ...        │
└──────────────────────────┬──────────────────────────────────────┘
                           │
                    UIX Adapters (ACL)
                    Pure functions, zero side effects
                           │
                           ▼
┌─────────────────────────────────────────────────────────────────┐
│  UIX IR  (@uix-ai/core)                                         │
│  LucidConversation → LucidBlock[]                               │
│  7 block types: text · tool · thinking · image · file · error · │
│  source                                                         │
│  JSON Schema + TypeScript types + type guards                   │
└──────────────────────────┬──────────────────────────────────────┘
                           │
               ┌───────────┴───────────┐
               ▼                       ▼
┌──────────────────────┐  ┌──────────────────────────────────────┐
│  assistant-ui        │  │  UIX Reference Renderer              │
│  (recommended)       │  │  @uix-ai/stream (StreamMarkdown)     │
│  Full chat UI runtime│  │  @uix-ai/agent (ChatBubble, etc.)    │
│  via ExternalStore   │  │  Lightweight, zero-runtime           │
└──────────────────────┘  └──────────────────────────────────────┘

Why Adapters Instead of Direct Integration?

In DDD terms, each AI backend is a separate Bounded Context. UIX adapters are the Anti-Corruption Layer (ACL) — the downstream consumer (UI) protects itself from upstream format changes.

Upstream (AgentX, Vercel, etc.) owns its own types — no pressure to change
Downstream (UI) only depends on UIX IR — immune to backend switches
Adapters are pure functions: fromX(input) → LucidConversation[]

UIX IR Specification

Core Types

interface LucidConversation {
  id: string
  role: 'user' | 'assistant' | 'system'
  status: 'streaming' | 'completed' | 'error'
  blocks: LucidBlock[]
  timestamp: number
}

interface LucidBlock<T extends BlockType> {
  id: string
  type: T  // 'text' | 'tool' | 'thinking' | 'image' | 'file' | 'error' | 'source'
  status: 'streaming' | 'completed' | 'error'
  content: ContentByType<T>  // conditional type, inferred from T
}

Block Types

Type	Description	Content
`text`	Text content (supports streaming)	`{ text: string }`
`tool`	Tool/function call	`{ name, input, output, status }` — 9-state lifecycle
`thinking`	AI reasoning process	`{ reasoning: string }`
`image`	Image content	`{ url, alt, width, height }`
`file`	File attachment	`{ name, type, url, size }`
`error`	Error message	`{ code, message, details }`
`source`	Source citation	`{ sourceId, title, url, excerpt }`

Tool Lifecycle (9 states)

pending → streaming → ready → running → success
                                ↓
                        approval-required → approved → success
                                         → denied
                                ↓
                               error

Packages

Core (the value)

Package	Description	Status
`@uix-ai/core`	UIX IR types, JSON Schema, type guards	✅ v0.0.2

Adapters (the bridge)

Package	Converts From	Status
`@uix-ai/adapter-vercel`	Vercel AI SDK 4.x / 6.x	✅ v0.0.2
`@uix-ai/adapter-agui`	AG-UI protocol (CopilotKit)	🚧 Alpha
`@uix-ai/adapter-a2ui`	A2UI protocol (Google)	🧪 Experimental
`@uix-ai/adapter-agentx`	AgentX Presentation	🔜 Planned

Reference Renderers (optional)

These are not the core value of UIX. They are lightweight reference implementations. For production chat UI, we recommend assistant-ui.

Package	Description	Status
`@uix-ai/stream`	Streaming Markdown renderer (Streamdown + Shiki + KaTeX + Mermaid, self-healing)	✅ v0.0.2
`@uix-ai/agent`	Chat components (MessageList, ChatBubble, ToolResult, ThinkingIndicator)	✅ v0.0.2
`@uix-ai/react`	Base UI components (Button, Input, Badge, Card)	✅ v0.0.2
`@uix-ai/tokens`	Lucid design tokens (Tailwind preset)	✅ v0.0.2

Relationship with Other Projects

vs assistant-ui

	UIX	assistant-ui
Solves	"How to normalize AI output"	"How to render AI chat in React"
Core artifact	JSON Schema + TypeScript types	React components + Runtime
State management	Stateless (pure conversion)	Full runtime (Thread, messages, branching)
Relationship	Data source for assistant-ui	Rendering layer for UIX IR

They are complementary. Use UIX to normalize your AI backend, then feed the result into assistant-ui's ExternalStoreRuntime.

vs AG-UI / A2UI / MCP Apps

These are transport protocols (how AI talks to frontend). UIX IR is an internal representation (how your app stores and renders AI output). UIX adapters bridge the gap:

AG-UI events → adapter-agui → UIX IR → your UI
A2UI payload → adapter-a2ui → UIX IR → your UI

Within the Deepractice Ecosystem

AgentX  — AI Agent runtime (the engine)
UIX     — AI output protocol (the translator)
PromptX — AI application (the product, built with both)

Project	Role
AgentX	AI Agent runtime — create, drive, and manage agents
PromptX	AI-powered application platform
PromptML	Prompt markup language

Quick Start

Normalize Vercel AI SDK output

import { fromVercelMessages } from '@uix-ai/adapter-vercel'
import type { LucidConversation } from '@uix-ai/core'

// Your Vercel AI SDK messages
const vercelMessages = useChat().messages

// Convert to UIX IR — one line
const conversations: LucidConversation[] = fromVercelMessages(vercelMessages)

// Now render with any UI framework
conversations.forEach(conv => {
  conv.blocks.forEach(block => {
    if (block.type === 'text') console.log(block.content.text)
    if (block.type === 'tool') console.log(block.content.name, block.content.output)
  })
})

Use with assistant-ui (recommended for production)

import { fromVercelMessages } from '@uix-ai/adapter-vercel'
import { useExternalStoreRuntime } from '@assistant-ui/react'

// UIX IR as the data layer, assistant-ui as the rendering layer
const runtime = useExternalStoreRuntime({
  messages: fromVercelMessages(vercelMessages),
  onNew: (message) => { /* send to backend */ }
})

Use reference renderer (lightweight / prototyping)

import { fromVercelMessages } from '@uix-ai/adapter-vercel'
import { StreamMarkdown } from '@uix-ai/stream'

const conversations = fromVercelMessages(messages)
const lastBlock = conversations.at(-1)?.blocks.at(-1)

if (lastBlock?.type === 'text') {
  return <StreamMarkdown content={lastBlock.content.text} />
}

UIX IR Format

A complete UIX IR document:

{
  "conversations": [
    {
      "id": "conv-1",
      "role": "user",
      "status": "completed",
      "blocks": [
        { "id": "b1", "type": "text", "status": "completed", "content": { "text": "Explain quicksort" } }
      ],
      "timestamp": 1710000000000
    },
    {
      "id": "conv-2",
      "role": "assistant",
      "status": "completed",
      "blocks": [
        { "id": "b2", "type": "thinking", "status": "completed", "content": { "reasoning": "User wants an algorithm explanation..." } },
        { "id": "b3", "type": "text", "status": "completed", "content": { "text": "Quicksort is a divide-and-conquer algorithm..." } },
        { "id": "b4", "type": "tool", "status": "completed", "content": { "name": "run_code", "input": { "code": "..." }, "output": "[3,5,7,9]", "status": "success" } }
      ],
      "timestamp": 1710000001000
    }
  ]
}

AI Skills

UIX provides AI-readable design rules that work with any AI coding tool. No npm install needed — just copy a Markdown file.

Skill	For	Description
`lucid-ui`	Everyone	Professional design system that replaces AI purple cliché
`uix-components`	UIX users	Component API, adapter patterns, IR type reference

Supported platforms: Claude Code, Claude.ai, Cursor, OpenAI Codex, Windsurf, GitHub Copilot, Cline, Gemini Code Assist

See skills/README.md for installation instructions.

Roadmap

Phase 1: Foundation ✅

UIX IR JSON Schema + TypeScript types (@uix-ai/core)
Design token system (@uix-ai/tokens)
Reference React components (@uix-ai/react, @uix-ai/agent)
Streaming Markdown renderer (@uix-ai/stream)

Phase 2: Adapters ✅

Vercel AI SDK adapter (@uix-ai/adapter-vercel, SDK 4.x & 6.x)
AG-UI protocol adapter (@uix-ai/adapter-agui)
A2UI protocol adapter (@uix-ai/adapter-a2ui, experimental)

Phase 3: Ecosystem Integration (current)

AgentX adapter (@uix-ai/adapter-agentx)
assistant-ui integration guide
IR validation CLI tool
Live demo with real AI agent
More adapters (LangChain, CrewAI, etc.)

Development

git clone https://github.com/Deepractice/UIX.git
cd UIX
pnpm install
pnpm dev

License

MIT - see LICENSE

Built with clarity by Deepractice

Name		Name	Last commit message	Last commit date
Latest commit History 108 Commits
.changeset		.changeset
.github		.github
apps		apps
docs		docs
examples		examples
packages		packages
skills		skills
.gitignore		.gitignore
.npmrc		.npmrc
CLAUDE.md		CLAUDE.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
README.md		README.md
README.zh-CN.md		README.zh-CN.md
package.json		package.json
pnpm-lock.yaml		pnpm-lock.yaml
pnpm-workspace.yaml		pnpm-workspace.yaml
tsconfig.json		tsconfig.json

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Repository files navigation

UIX

What UIX Is (and What It Is Not)

The Problem

Architecture

Why Adapters Instead of Direct Integration?

UIX IR Specification

Core Types

Block Types

Tool Lifecycle (9 states)

Packages

Core (the value)

Adapters (the bridge)

Reference Renderers (optional)

Relationship with Other Projects

vs assistant-ui

vs AG-UI / A2UI / MCP Apps

Within the Deepractice Ecosystem

Quick Start

Normalize Vercel AI SDK output

Use with assistant-ui (recommended for production)

Use reference renderer (lightweight / prototyping)

UIX IR Format

AI Skills

Roadmap

Phase 1: Foundation ✅

Phase 2: Adapters ✅

Phase 3: Ecosystem Integration (current)

Development

License

About

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Repository files navigation

UIX

What UIX Is (and What It Is Not)

The Problem

Architecture

Why Adapters Instead of Direct Integration?

UIX IR Specification

Core Types

Block Types

Tool Lifecycle (9 states)

Packages

Core (the value)

Adapters (the bridge)

Reference Renderers (optional)

Relationship with Other Projects

vs assistant-ui

vs AG-UI / A2UI / MCP Apps

Within the Deepractice Ecosystem

Quick Start

Normalize Vercel AI SDK output

Use with assistant-ui (recommended for production)

Use reference renderer (lightweight / prototyping)

UIX IR Format

AI Skills

Roadmap

Phase 1: Foundation ✅

Phase 2: Adapters ✅

Phase 3: Ecosystem Integration (current)

Development

License

About

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