Streaming LLM Frontend Patterns

For frontend apps consuming streaming LLM responses, well-built abstractions matter for UX. The React (or framework-equivalent) patterns are mature in 2026; standard libraries handle most cases.

React hook

import { useChat } from '@ai-sdk/react';

export default function Chat() {
  const { messages, input, handleInputChange, handleSubmit, isLoading, stop } = useChat({
    api: '/api/chat',
  });

  return (
    <div>
      {messages.map(m => <div key={m.id}>{m.role}: {m.content}</div>)}
      <form onSubmit={handleSubmit}>
        <input value={input} onChange={handleInputChange} />
        {isLoading && <button onClick={stop}>Stop</button>}
      </form>
    </div>
  );
}

UX patterns

• Typing indicator while waiting for first token (~150-500ms TTFT)
• Streaming text reveal as tokens arrive
• Abort button visible during generation
• Final state with copy / regenerate buttons after generation completes
• Error state with retry option on failure
• Markdown rendering as text streams (incremental rendering)

Verdict

For React frontends consuming streaming LLM responses, Vercel AI SDK's useChat hook is the standard primitive. Handles SSE complexity; provides clean state for UI. For other frameworks (Vue, Svelte), equivalent libraries exist. Don't roll your own SSE parsing — the abstractions are mature.