Streaming AI Output in the Browser: A ReadableStream and Vue Walkthrough
The jump from a single JSON response to a streaming response is the difference between an AI product that feels broken and one that feels alive. The technique itself is a small configuration change and a standard browser API, but it's now a baseline expectation for any chat interface.
A plain-Vue project built with Vite demonstrates how to replace the standard `response.json()` call with a streaming pipeline. The server-side DeepSeek API is told to stream tokens by adding `stream: true` to the request body. On the client, a `TextDecoder` and a `while` loop over `reader.read()` append each chunk to a reactive `ref`, which Vue's template interpolation renders immediately.
The walkthrough also lays out the Vue fundamentals that make this work: mounting an app to a single `<div>`, using Single File Components, and binding data with `{{ }}`, `v-model`, and `v-if`. The result is a typewriter effect that turns a 10-second wait into a continuous, visible stream of text.
Every piece of the data flow is traced, from the user's input through `v-model` into the fetch call, through the `ReadableStream` reader, and back into the reactive `content` variable that drives the UI.
Streaming is often framed as a complex real-time protocol, but for LLM APIs it's just an HTTP request with a flag and a standard browser stream reader.
The tutorial's value is in demystifying the pipeline: the server-side contract (`stream: true`) and the client-side mechanism (`ReadableStream`) are independent concerns that happen to pair perfectly.
By grounding the explanation in Vue's reactivity system, the walkthrough shows that the frontend framework does the heavy lifting of keeping the UI in sync; the developer only needs to push bytes into a variable.