Streaming is enabled for long AI responses

LLM generation at 50 tokens per second means a 1,000-token response takes 20 seconds. Without streaming, the user sees a spinner for the entire duration and receives no indication that anything is happening. Perceived latency is the primary driver of AI application abandonment. Research consistently shows that time-to-first-token is the latency metric users notice most — streaming brings it from 20 seconds to under 2. ISO 25010 performance-efficiency requires that user-facing response times be minimized; non-streaming chat interfaces fail this benchmark for any response over a sentence.

Replace generateText with streamText in user-facing route handlers and return result.toDataStreamResponse(). Use the useChat hook on the frontend to consume the stream and render tokens as they arrive.

// src/app/api/chat/route.ts
import { streamText } from "ai";
import { openai } from "@ai-sdk/openai";

export async function POST(req: Request) {
  const { messages } = await req.json();
  const result = await streamText({
    model: openai("gpt-4o"),
    messages,
    maxTokens: 1000,
  });
  return result.toDataStreamResponse();
}

// src/components/chat.tsx
import { useChat } from "ai/react";

export function Chat() {
  const { messages, input, handleInputChange, handleSubmit } = useChat();
  return (
    <form onSubmit={handleSubmit}>
      {messages.map(m => <div key={m.id}>{m.content}</div>)}
      <input value={input} onChange={handleInputChange} />
      <button type="submit">Send</button>
    </form>
  );
}

Verify by submitting a prompt that generates a long response and confirming that text begins appearing within 2 seconds of submission.