In production, the painful part is not “streaming is slow.” It’s “streaming breaks and then duplicates output after reconnect.” This guide gives you a practical recovery loop: delta persistence + resume token + idempotent dedup, so reconnection does not replay garbage. ...
生产里最难受的不是“流式返回慢”，而是“流式返回断了还重复”，用户看到半句、重连后又从中间重喷一遍。 这篇给一套可落地的恢复闭环：delta 持久化 + resume token + 幂等去重，目标是“断线可续，重放不重字”。 ...
线上最可怕的不是一次失败，而是失败后被重试放大。 在 OpenAI Responses + Go 的工具调用链路里，如果没有幂等键、退避抖动和熔断阈值，10 个请求很快就能打成 1000 个下游调用，账单和延迟一起爆炸。 ...
The most expensive outage is not a single failure — it is a failure amplified by retries. In an OpenAI Responses + Go tool-calling stack, missing idempotency, jittered backoff, and breaker thresholds can turn 10 failing requests into 1000 downstream calls in minutes. ...