Streaming LLM responses in TypeScript: SSE, ReadableStream, and the React 19 useChat hook.

Streaming LLM responses in TypeScript: SSE, ReadableStream, and the React 19 useChat hook. The first time I wired an LLM response that streamed token by token instead of arriving as one lump after 4 seconds, I shipped it to production the same afternoon. The difference in perceived speed is that obvious to anyone who has used ChatGPT and then tried a non-streaming competitor. Users will wait 8 seconds if they can see the cursor moving. They will not wait 4 seconds for a blank screen. This tutorial walks the full stack from scratch. By the end you have a working Next.js API route that streams from an LLM over Server-Sent Events, a frontend that parses the stream manually with ReadableStream , and then the same UI rebuilt with the Vercel AI SDK's useChat hook so you can see what the abstraction actually buys you. TL;DR Layer What you build Key API Next.js route Streams LLM output as SSE streamText + toUIMessageStreamResponse Vanilla client Parses the stream by hand ReadableStream , TextDecoderStream React 19 client Managed state + cancellation useChat from ai/react Edge cases Backpressure, cancel, tool chunks AbortController , partial JSON guard 1. Why streaming matters A standard fetch returns after the entire response body is ready. For short completions, that is fine. For anything over 100 tokens, users see a spinner, then a wall of text, then confusion about whether the app is fast or slow. Streaming changes the shape of that experience. The first token lands in under 300ms for most hosted models. The user starts reading while the model is still writing. Perceived latency drops by 60 to 70 percent even if the total time to complete the response does not change. Cost transparency is the second reason to care. When you stream, you count tokens as they arrive. If your route has a budget ceiling and the response is going to blow past it, you can cut the stream at 800 tokens without ever waiting for the full completion. That cut is not possible with a blocking call. 2.