React Components for AI Chat Applications

Building AI chat interfaces in 2024 means handling streaming responses, tool calls, reasoning panels, and message threads. Most UI libraries weren't designed for these conversational AI patterns.

AI Elements provides purpose-built React components like <Message>, <Response>, and <Branch> that integrate seamlessly with the Vercel AI SDK. Built on shadcn/ui principles, you get complete control over every component while handling AI's complexity.

The best component library for AI applications isn't the one with the most features—it's the one that gives you complete ownership while solving AI-specific challenges.

Why generic UI libraries fail for conversational AI

Building AI chat applications with generic UI libraries means implementing everything from scratch. Streaming text, tool calls, reasoning blocks, citations—every AI feature becomes a custom implementation challenge.

The Vercel AI SDK provides useChat for state management, but most UI components don't understand AI-specific patterns. You end up manually parsing message parts, handling stream updates, and managing scroll behavior.

Want branching for multiple AI responses? Build it from scratch. Need tool call displays? Custom implementation required. AI Elements solves this by providing components designed specifically for conversational AI interfaces.

AI Elements + shadcn/ui = the perfect match

Here's what AI Elements does differently. It takes shadcn/ui's philosophy—giving you the actual code—and applies it to AI-specific components.

import { Message, MessageContent } from "@/components/ai/message";
import { Response } from "@/components/ai/response";
import { useChat } from "@ai-sdk/react";

export default function Chat() {
  const { messages } = useChat();

  return messages.map((message) => (
    <Message from={message.role} key={message.id}>
      <MessageContent>
        <Response>{message.content}</Response>
      </MessageContent>
    </Message>
  ));
}

Every component lives in your codebase. Want to customize how messages look? Open message.tsx and change it. Need special handling for tool calls? The code's right there. No black boxes, no rigid APIs.

Built on shadcn/ui means you get Tailwind styling, full TypeScript support, and that same copy-paste simplicity. But now with components designed specifically for AI patterns.

How AI Elements handles conversational AI complexity

AI chat applications require streaming responses, tool calls, reasoning blocks, citations, and branching conversations. Each feature typically needs custom implementation with standard React components.

AI Elements provides purpose-built TypeScript components for each pattern. <Branch> for navigating response variations. <Tool> for displaying function calls. <Reasoning> for collapsible thinking processes. <Sources> for citations.

// Handle streaming with proper markdown rendering
<Response>{streamingMessage}</Response>

// Display tool calls with status
<Tool name="search" status="complete">
  {toolResult}
</Tool>

// Show reasoning that auto-collapses when done
<Reasoning isStreaming={false}>
  {reasoningContent}
</Reasoning>

These aren't rigid black boxes. They're shadcn/ui components you own and can modify. Need a different tool call layout? Change it. Want custom reasoning animations? Add them. Your codebase, your rules.

What this means for your conversational AI applications

AI Elements seamlessly integrates with the Vercel AI SDK while giving you complete control over the UI in your Next.js and TypeScript projects.

Use useChat from the AI SDK for state management and streaming. Render with AI Elements components. Everything just works together. No fighting between your state management and UI components. No manual stream parsing. No custom scroll handling.

const { messages, append, isLoading } = useChat();

// AI SDK handles the state, AI Elements handles the UI
return (
  <Conversation>
    <ConversationContent>
      {messages.map((message) => (
        <Message from={message.role}>
          <MessageContent>
            {message.parts.map((part) => {
              if (part.type === "text") return <Response>{part.text}</Response>;
              if (part.type === "tool-call") return <Tool {...part} />;
            })}
          </MessageContent>
        </Message>
      ))}
    </ConversationContent>
  </Conversation>
);

The architectural pattern for AI applications

The best conversational AI experiences come from purpose-built React components, not generic UI libraries trying to handle everything.

The winning pattern: Vercel AI SDK for state management, AI Elements for UI components, shadcn/ui for the foundation. Each tool excels at one responsibility instead of doing everything poorly.

AI Elements focuses purely on UI components for AI chat applications. It doesn't manage AI state or handle API calls—it provides beautiful, customizable TypeScript components that integrate perfectly with your existing Next.js and Vercel AI SDK setup.

Building the future of AI interfaces

AI Elements establishes patterns for conversational AI applications. Consistent message components, standardized tool call displays, and reliable reasoning interfaces across the AI ecosystem.

As more developers build AI chat applications with React, Next.js, and the Vercel AI SDK, we'll expand the component library. More patterns, more solutions, all following shadcn/ui's philosophy of code ownership and TypeScript-first development.

We're building a shared foundation for AI applications using modern web technologies.

Component ownership for AI applications

AI Elements works exactly like shadcn/ui for conversational AI. Copy the React components you need. Customize them for your AI chat application. They're your TypeScript components now.

No lock-in to design decisions. No waiting for feature additions. No fighting with rigid APIs. Clean, readable React components that handle AI complexity while giving you complete control over your Next.js application.

Build production-ready AI interfaces quickly. When you need customization, the TypeScript code is in your project, ready to modify for your conversational AI requirements.

Essential AI Components

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