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

• messages 里的 system / user / assistant 三种角色各起什么作用？为什么要有 system？What do the system / user / assistant roles do, and why does system exist?

  国内高频海外高频基础#llm-basics#prompt

  分析过程 · 先想清楚再作答

  1. 题眼在后半句「为什么要有 system」——前半句是送分，后半句才是区分度所在。
  2. 先说清三者构成一段可被模型续写的完整文本，角色是给这段文本打的结构化标记。
  3. 再回答「为什么」：如果把规则写进 user，它就只是对话里的一句话，会被后续几十轮对话稀释；放进 system 才能保持稳定权重，且便于产品侧统一管控、单独灰度。
  4. 补一条生产视角：真实的 system prompt 通常是模板拼出来的——人设 + 工具说明 + 记忆片段 + 当前时间，而不是一个写死的字符串。
  5. 常见追问：能不能把 system 放在最后？可以但不推荐，多数模型对靠前的指令更敏感，且会破坏缓存前缀。

  How to reason about it · think before answering

  1. The discriminating half is 'why does system exist'; the first half is a warm-up.
  2. Explain that the three roles are structural markers over one continuous text the model continues.
  3. Then the why: rules placed in user are just another turn and get diluted over dozens of turns; system keeps stable weight and can be governed centrally.
  4. Add production nuance: a real system prompt is templated — persona plus tool docs plus memory plus runtime facts.
  5. Likely follow-up: can system go last? Possible but unwise — models weight earlier instructions more and it breaks prompt-cache prefixes.

  答题要点

  • system 设定身份、边界与输出格式，通常放在最前面，权重高于普通对话
  • user 是用户输入，assistant 是模型历史回复，两者交替构成对话记录
  • 把规则放 system 而不是 user，是为了让规则不被后续对话冲淡，也便于产品统一管控
  • 生产里 system prompt 往往由模板拼接：人设 + 工具说明 + 记忆 + 当前时间等动态信息

  Key points

  • system sets identity, constraints and output format; it sits first and carries more weight
  • user is the human turn, assistant is the model's prior replies; they alternate
  • Rules live in system so they are not diluted by later turns and can be controlled centrally
  • In production the system prompt is templated: persona + tool docs + memory + runtime facts