@gravity-ui/aikit

AIKit ·

UI component library for AI chats built with Atomic Design principles.

Resources

Website

Storybook

Community

Description

@gravity-ui/aikit is a flexible and extensible React component library for building AI chats of any complexity. The library provides a set of ready-made components that can be used as-is or customized to fit your needs.

Key Features

• 🎨 Atomic Design — clear component hierarchy from atoms to pages
• 🔧 SDK Agnostic — independent of specific AI SDKs
• 🎭 Two-Level Approach — ready-made components + hooks for customization
• 🎨 CSS Variables — easy theming without component overrides
• 📦 TypeScript — full type safety out of the box
• 🔌 Extensible — custom message type registration system

Project Structure

src/
├── components/
│   ├── atoms/          # Basic indivisible UI elements
│   ├── molecules/      # Simple groups of atoms
│   ├── organisms/      # Complex components with logic
│   ├── templates/      # Complete layouts
│   └── pages/          # Full integrations with data
├── hooks/              # General purpose hooks
├── types/              # TypeScript types
├── utils/              # Utilities
└── themes/             # CSS themes and variables

Installation

npm install @gravity-ui/aikit

Quick Start

import { ChatContainer } from '@gravity-ui/aikit';
import type { ChatType, TChatMessage } from '@gravity-ui/aikit';

function App() {
    const [messages, setMessages] = useState<TChatMessage[]>([]);
    const [chats, setChats] = useState<ChatType[]>([]);
    const [activeChat, setActiveChat] = useState<ChatType | null>(null);

    return (
        <ChatContainer
            chats={chats}
            activeChat={activeChat}
            messages={messages}
            onSendMessage={async (data) => {
                // Your sending logic
                console.log('Message:', data.content);
            }}
            onSelectChat={setActiveChat}
            onCreateChat={() => {
                // Create new chat
            }}
            onDeleteChat={(chat) => {
                // Delete chat
            }}
        />
    );
}

Architecture

The library is built on Atomic Design principles:

🔹 Atoms

Basic indivisible UI elements without business logic:

• ActionButton — button with integrated tooltip
• Alert — alert messages with variants
• ChatDate — date formatting with relative dates
• ContextIndicator — token context usage indicator
• ContextItem — context label with remove action
• DiffStat — code change statistics display
• Disclaimer — disclaimer text component
• InlineCitation — text citations
• Loader — loading indicator
• MarkdownRenderer — Yandex Flavored Markdown renderer
• MessageBalloon — message wrapper
• Shimmer — loading animation effect
• SubmitButton — submit button with states
• ToolIndicator — tool execution status indicator

🔸 Molecules

Simple combinations of atoms:

• BaseMessage — base wrapper for all message types
• ButtonGroup — button group with orientation support
• InputContext — context management
• PromptInputBody — textarea with auto-growing
• PromptInputFooter — footer with action icons and submit button
• PromptInputHeader — header with context items and indicator
• PromptInputPanel — panel container for custom content
• Suggestions — clickable suggestion buttons
• Tabs — navigation tabs with delete functionality
• ToolFooter — tool message footer with actions
• ToolHeader — tool message header with icon and actions

🔶 Organisms

Complex components with internal logic:

• AssistantMessage — AI assistant message
• Header — chat header
• MessageList — message list
• PromptInput — message input field
• ThinkingMessage — AI thinking process
• ToolMessage — tool execution
• UserMessage — user message

📄 Templates

Complete layouts:

• ChatContent — main chat content
• EmptyContainer — empty state
• History — chat history

📱 Pages

Full integrations:

• ChatContainer — fully assembled chat

Documentation

• Quick Start Guide
• Architecture
• Project Structure
• Testing Guide
• Playwright Guide

Testing

The project uses Playwright Component Testing for visual regression testing.

Run tests

Important: All tests must be run via Docker to ensure consistent screenshots across different environments.

# Run all component tests in Docker (recommended)
npm run playwright:docker

# Update screenshot baselines in Docker
npm run playwright:docker:update

# Run specific test by grep pattern in Docker
npm run playwright:docker -- --grep "@ComponentName"

# Clear Docker cache if needed
npm run playwright:docker:clear-cache

Local testing (Linux only)

If you're on Linux, you can run tests locally:

# Install Playwright browsers (run once)
npm run playwright:install

# Run all component tests
npm run playwright

# Update screenshot baselines
npm run playwright:update

For detailed testing documentation, see Playwright Guide.

Development

Development and contribution instructions are available in CONTRIBUTING.md.

License

MIT