面试题库

30 天从前端工程师到 Agent 工程师

D1 LLM API 基础：messages/roles、token、流式、temperature；Agent 到底是什么

• 用户主动点「停止生成」和网络意外断开，在服务端看起来都是连接没了，怎么区分处理？A user pressing stop and a dropped connection both look like a closed connection server-side. How do you tell them apart?

  国内高频海外高频深入#streaming#reliability#ux

  分析过程 · 先想清楚再作答

  1. 先点破为什么要区分：主动停止是「用户不想要了」，应当立即释放算力并结束这轮；意外断开是「用户还想要」，理应保留结果供恢复。处理反了，用户要么白花钱，要么回来发现内容没了。
  2. 所以不能只靠 TCP 连接状态判断——它对两种情况的表现是一样的。必须有一个显式信号。
  3. 做法是给「停止」单独一个接口：前端点停止时先调这个接口，带上 run id，服务端据此把该轮标记为「用户取消」，再中止上游模型调用。
  4. 而单纯的连接关闭一律按「意外断开」处理：继续把已生成内容落盘、保留可恢复的流，等客户端回来续。
  5. 补一个现实约束：停止请求本身也可能因为断网而发不出去。所以服务端还需要兜底——比如流没有任何消费者超过一定时间就自行结束，避免算力空转。
  6. 延伸到计费：两种情况都要为已经产生的 token 计费，因为上游厂商已经收了钱；区别只在于要不要保留结果和是否继续生成。

  How to reason about it · think before answering

  1. Say why it matters: stop means the user no longer wants the output, so free compute and end the run; a drop means they still want it, so preserve the result for resumption.
  2. Connection state alone cannot distinguish them — it looks identical — so you need an explicit signal.
  3. Give stop its own endpoint: the client calls it with the run id before closing, and the server marks the run as user-cancelled and aborts the upstream call.
  4. Treat a bare connection close as an unexpected drop: keep persisting output and hold the stream for resumption.
  5. Add the real-world caveat: the stop request itself may fail to send when the network is down, so the server needs a fallback — end a stream with no consumer after a timeout.
  6. Extend to billing: both cases still owe for tokens already produced, since the upstream provider has charged; they differ only in whether output is retained.

  答题要点

  • 两者语义相反：主动停止要立即释放算力并结束，意外断开要保留结果等待恢复
  • TCP 连接状态无法区分，必须有显式信号：给停止单独一个接口，带 run id 标记为用户取消
  • 只收到连接关闭一律按意外断开处理，继续落盘并保留可恢复的流
  • 兜底：停止请求本身也可能发不出去，服务端需对长时间无消费者的流自行结束
  • 计费上两者都要为已产生的 token 记账，区别只在于是否保留结果、是否继续生成

  Key points

  • The semantics are opposite: stop frees compute immediately, a drop preserves output for resumption
  • Connection state cannot distinguish them, so add an explicit stop endpoint carrying the run id
  • Treat a bare close as an unexpected drop: keep persisting and hold the stream for resume
  • Fallback: the stop call may itself fail to send, so end streams with no consumer after a timeout
  • Both still bill for tokens already produced; they differ only in retention and whether generation continues