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Mastering Claude: From Conversation to Claude Code in 5 Days

D2 Long Documents, Multimodal Input, and a First Look at the API: Using Large Context, Saving Money With Prompt Caching, PDF and Image Input, Citation-Backed Answers; a Minimal Messages API Call

• How do API citations fundamentally differ from prompting the model to quote sources with page numbers, and when can't you use them?citations 和在提示词里要求模型「引用原文并注明页码」有什么本质区别？什么场景下不能用 citations？

  Common in ChinaCommon overseasIntermediate#citations#grounding

  How to reason about it · think before answering

  1. The question is about where trust comes from. 'Citations are more convenient' is surface; the real difference is who guarantees the quote is real.
  2. With prompting, both the quote and the page number are free text the model generates — it may paraphrase, it may misremember the page, and you cannot tell a real quote from an imagined one. With citations, the model emits citation intent in a standard format, the API parses and verifies it server-side, cited_text is guaranteed to exist in the document, and page_location comes from the API. Fidelity is enforced by the API rather than promised by the model.
  3. Two side benefits: cited_text does not count toward output tokens, so it is cheaper than asking the model to copy; and the result is structured content blocks your UI can highlight and jump to without regex guessing.
  4. When you can't: citations are incompatible with structured outputs (JSON Schema) — enabling both returns a 400. Either drop API-level citations and add a page field to the schema (one notch less reliable), or split into two calls: citations for facts, structured output for shaping.
  5. Follow-ups: page semantics — start_page_number is 1-indexed and end_page_number is exclusive; document_index distinguishes sources. Can you audit citation quality? Yes — string-match cited_text against the source, or sample manually.

  分析过程 · 先想清楚再作答

  1. 这题考的是「可信度从哪来」。答成「citations 更方便」是表面；本质区别是谁来保证引用的真实性。
  2. 拆法：提示词方案里，引用和页码都是模型生成的自由文本——它可能顺手改写原文、可能记错页码，你无法区分「真引用」和「自以为引用」。citations 方案里，模型内部以标准格式输出引用意图，API 在服务端解析并核对，返回的 cited_text 一定是文档里真实存在的段落，page_location 的页码由 API 给出。真实性由 API 保证而不是由模型自觉保证。
  3. 附带的两点好处：cited_text 不计入输出 token，比让模型抄原文便宜；返回是结构化的内容块，程序可以直接高亮、跳转，不用正则去猜「第 3 页」出现在哪。
  4. 不能用的场景：与结构化输出（JSON Schema）不兼容，二者同开会报 400；此时要么放弃 API 级引用、在 schema 里留 page 字段让模型自己填（可靠性差一档），要么分两步：先 citations 拿事实，再用结构化输出整理。
  5. 可预期的追问：页码字段的语义？start_page_number 从 1 开始，end_page_number 不包含；多文档时 document_index 区分来源。再追问「能否验证引用质量」——能，用 cited_text 与原文做字符串比对，或抽样人工核对。

  Key points

  • Prompted quotes are free text the model generates — it may paraphrase or misplace pages, and you can't tell
  • Citations are parsed and verified server-side; cited_text is guaranteed to exist and page numbers come from the API
  • cited_text is free of output-token cost and the structured blocks enable highlighting and navigation
  • Mutually exclusive with structured outputs; split into two calls or add a page field to the schema

  答题要点

  • 提示词引用是模型生成的自由文本，可能改写、记错页码，无法区分真假
  • citations 由 API 在服务端解析核对，cited_text 一定存在于文档中，页码由 API 给出
  • cited_text 不计输出 token，返回结构化便于高亮跳转
  • 与结构化输出互斥；需要两者时分两步或在 schema 留 page 字段