Source: https://ai-sdk.dev/elements/components/loader

Vercel

Slash Forward

Sparkles

AI SDK

Docs Cookbook Providers Playground AI ElementsAI ElementsLeft sparkleRight sparkle AI GatewayGateway

Search...⌘KFeedback GitHub Vercel LogoSign in with Vercel

Utilities

Loader

A spinning loader component for indicating loading states in AI applications.

The Loader component provides a spinning animation to indicate loading states in your AI applications. It includes both a customizable wrapper component and the underlying icon for flexible usage.

Preview

Code

Loader

Installation

AI Elements

shadcn CLI

Manual

npx ai-elements@latest add loader

Usage with AI SDK

Build a simple chat app that displays a loader before the response starts streaming by using status === "submitted".

Add the following component to your frontend:

app/page.tsx

'use client';

import {
  Conversation,
  ConversationContent,
  ConversationScrollButton,
} from '@/components/ai-elements/conversation';
import { Message, MessageContent } from '@/components/ai-elements/message';
import {
  Input,
  PromptInputTextarea,
  PromptInputSubmit,
} from '@/components/ai-elements/prompt-input';
import { Loader } from '@/components/ai-elements/loader';
import { useState } from 'react';
import { useChat } from '@ai-sdk/react';

const LoaderDemo = () => {
  const [input, setInput] = useState('');
  const { messages, sendMessage, status } = useChat();

  const handleSubmit = (e: React.FormEvent) => {
    e.preventDefault();
    if (input.trim()) {
      sendMessage({ text: input });
      setInput('');
    }
  };

  return (
    <div className="max-w-4xl mx-auto p-6 relative size-full rounded-lg border h-[600px]">
      <div className="flex flex-col h-full">
        <Conversation>
          <ConversationContent>
            {messages.map((message) => (
              <Message from={message.role} key={message.id}>
                <MessageContent>
                  {message.parts.map((part, i) => {
                    switch (part.type) {
                      case 'text':
                        return (
                          <div key={`${message.id}-${i}`}>{part.text}</div>
                        );
                      default:
                        return null;
                    }
                  })}
                </MessageContent>
              </Message>
            ))}
            {status === 'submitted' && <Loader />}
          </ConversationContent>
          <ConversationScrollButton />
        </Conversation>

        <Input
          onSubmit={handleSubmit}
          className="mt-4 w-full max-w-2xl mx-auto relative"
        >
          <PromptInputTextarea
            value={input}
            placeholder="Say something..."
            onChange={(e) => setInput(e.currentTarget.value)}
            className="pr-12"
          />
          <PromptInputSubmit
            status={status === 'streaming' ? 'streaming' : 'ready'}
            disabled={!input.trim()}
            className="absolute bottom-1 right-1"
          />
        </Input>
      </div>
    </div>
  );
};

export default LoaderDemo;

Add the following route to your backend:

app/api/chat/route.ts

import { streamText, UIMessage, convertToModelMessages } from 'ai';

// Allow streaming responses up to 30 seconds
export const maxDuration = 30;

export async function POST(req: Request) {
  const { model, messages }: { messages: UIMessage[]; model: string } =
    await req.json();

  const result = streamText({
    model: 'openai/gpt-4o',
    messages: convertToModelMessages(messages),
  });

  return result.toUIMessageStreamResponse();
}

Features