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Posted on • Originally published at aitechconnect.in

How to Stream LLM Responses at Scale: SSE & Backpressure

Originally published on AI Tech Connect.

What you need to know before you build this Streaming is one of those features that looks like a nice-to-have and turns out to be load-bearing. A non-streaming chat endpoint that takes eight seconds to return a full answer feels broken. The same answer, streamed token by token so the first words appear in under a second, feels fast — even though the total time is identical. The whole game is perceived latency, and streaming is how you win it. The hard part is not emitting tokens; any tutorial can show you a generator that yields strings. The hard part is everything around it: the proxy that silently buffers your whole response, the user who closes the tab while you keep paying a model provider to generate tokens nobody will read, the load balancer that kills the connection after sixty…


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