面试题库
共 328 题,当前筛选 1 题。
课程全部30 天从前端工程师到 Agent 工程师5 天提示词工程零基础Claude 高效使用:从对话到 Claude CodeCodex 与 OpenAI Agents SDK 高效使用7 天 MCP:把工具接进任何 Agent7 天 Agent Skills:把经验做成可复用能力5 天上下文工程14 天 RAG:从检索到可信回答14 天用 Agent 搭一条 AI 短剧生产线
标签
全部#frontend1#architecture8#cost4#multi-agent4#agent-skills3#context3#evaluation3#llm-basics3#pipeline-design3#security3#system-design3#tool-design3
还有 125 个标签收起标签
#abstention2#agent-loop2#behavioral2#claude-md2#coding-agent2#consistency2#context-engineering2#context-window2#distributed-systems2#embeddings2#framework-design2#interview-prep2#interview-process2#mcp2#memory2#observability2#orchestration2#prompt-engineering2#provider-abstraction2#rag2#resume2#scalability2#scheduling2#skills2#sse2#streaming2#structured-output2#tool-calling2#agent-basics1#agent-design1#agent-sdk1#agentic-rag1#agents-md1#api-design1#async-task1#auth1#backoff1#bi-encoder1#build-vs-buy1#career1#chunking1#communication1#concurrency1#configuration1#consistent-hashing1#content-safety1#context-assembly1#context-management1#coreference1#cost-accounting1#cost-analysis1#cross-encoder1#data-quality1#encoding1#failure-analysis1#fairness1#few-shot1#ffmpeg1#fine-tuning1#global-market1#golden-set1#hooks1#human-in-the-loop1#hybrid-search1#image-generation1#ingestion1#json-schema1#jwt1#langgraph1#long-context1#long-term-memory1#maintenance1#mcp-basics1#media-pipeline1#mental-model1#message-bus1#messages-api1#migration1#model-routing1#moderation1#modularity1#multi-turn1#normalisation1#openai1#operations1#ordering1#overlap1#primitives1#prioritization1#priority-queue1#proactive-messaging1#product-engineering1#project-storytelling1#prompt1#prompt-basics1#prompt-bloat1#prompt-design1#prompt-injection1#prompt-surface1#prompt-techniques1#prompting1#protocol1#query-rewriting1#rag-basics1#rate-limiting1#redis-streams1#reliability1#responses-api1#retrieval1#routing1#sampling1#schema-validation1#scripts1#server-design1#sharding1#similarity1#skill-design1#stakeholder-communication1#star1#state-machine1#system-prompt1#test-set1#token-budget1#tts1#workflow-engine1
30 天从前端工程师到 Agent 工程师
D25 前端侧 Agent 体验:流式渲染、工具调用可视化、打断/重试、SSE hooks
前端怎么消费 SSE 并实现打字机效果?为什么一般不用浏览器自带的 EventSource?How does a frontend consume SSE to render a typewriter effect, and why do people usually avoid the built-in EventSource?
国内高频海外高频基础#sse#streaming#frontend分析过程 · 先想清楚再作答
- 这题是送分题,但送分点在后半句。只答「用 EventSource 监听 message 事件」的,面试官会立刻追问鉴权怎么办——答不上来就说明没在真项目里接过。
- 先给正面答案的骨架:`fetch` 拿到响应后读 `res.body` 这个 ReadableStream,`TextDecoder` 解码成文本,按空行切帧,逐帧解析出 `event` 与 `data`,把文本增量追加到当前这条消息上。
- 为什么不用 `EventSource`,三个硬伤要一口气说全:只能发 GET、不能带自定义请求头(也就是放不进 Authorization)、不能带请求体。Agent 场景里消息体、幂等键、会话 id 都得走 body,三条全撞上。
- 紧接着说代价,这是区分「用过」和「读过」的地方:手写解析意味着 `EventSource` 自带的自动重连、`Last-Event-ID` 续传都要自己实现。不过带鉴权的场景里那个自动重连本来就不好用(它重连时同样带不了头),所以损失没听起来那么大。
- 可预期的追问一:帧被网络切成两半怎么办?答缓冲——按空行切完之后,最后一段可能是半截,`pop` 出来留到下一块再拼。**这个 bug 在本机直连时几乎不出现**,所以要专门构造切碎的报文来测。
- 可预期的追问二:为什么不用 WebSocket?答:SSE 是单向下行、走普通 HTTP、天然过代理和 CDN、实现和运维都更轻;只有需要频繁上行(协同编辑、语音)才值得上 WebSocket。这一条能主动说出来会很加分。
How to reason about it · think before answering
- This is a warm-up question, but the second half is where it bites. Answering only 'use EventSource and listen for message events' invites an immediate follow-up about auth, and not having one shows you never wired it in a real project.
- Sketch the positive answer first: fetch the response, read res.body as a ReadableStream, decode with TextDecoder, split on blank lines into frames, parse event and data per frame, and append the text delta onto the current message.
- Then the three hard blockers on EventSource, stated together: GET only, no custom request headers (so no Authorization), and no request body. Agent requests need all of a message payload, an idempotency key and a session id in the body, so all three bite at once.
- Name the cost next — this separates having used it from having read about it. Hand-rolling means you also reimplement EventSource's auto-reconnect and Last-Event-ID resume. That said, its auto-reconnect is already unusable under auth because reconnects cannot carry headers either, so the loss is smaller than it sounds.
- Expected follow-up 1: what if a frame is split across chunks? Buffer it — after splitting on blank lines, pop the trailing partial segment and prepend it to the next chunk. This bug almost never reproduces on localhost, so you must feed deliberately fragmented payloads to test it.
- Expected follow-up 2: why not WebSocket? SSE is one-way downstream over plain HTTP, passes proxies and CDNs, and is far lighter to run. WebSocket earns its keep only when you need frequent upstream traffic such as collaborative editing or voice. Volunteering this scores well.
答题要点
- 用 fetch 读 res.body 这个 ReadableStream,TextDecoder 解码,按空行切帧,增量追加文本。
- EventSource 三个硬伤:只能 GET、不能带自定义头(放不进 Authorization)、不能带请求体。
- 代价是自动重连和 Last-Event-ID 续传要自己写——但带鉴权时那个自动重连本来也用不了。
- 必须处理跨块的半截帧:切完之后最后一段留到下一块再拼,本机直连测不出这个 bug。
- 不用 WebSocket 是因为 SSE 单向下行、走普通 HTTP、过代理和 CDN 更省事;需要频繁上行才换 WebSocket。
Key points
- Use fetch, read res.body as a ReadableStream, decode with TextDecoder, split frames on blank lines, append deltas.
- EventSource has three blockers: GET only, no custom headers (no Authorization), no request body.
- The cost is reimplementing auto-reconnect and Last-Event-ID resume — though auto-reconnect is unusable under auth anyway.
- You must buffer partial frames across chunks; localhost testing will not surface this bug.
- SSE beats WebSocket here: one-way, plain HTTP, proxy and CDN friendly. Switch only when you need frequent upstream messages.