InContext — 划词释义（基于全文理解）

About

Most "explain" or "translate selection" extensions send only the highlighted snippet to the AI, so the explanation is out of context.

InContext is different: it first extracts the WHOLE article (via Mozilla Readability) and feeds it to the model as grounding. So it explains what your selection actually means IN THIS article — the author's intent, the implied meaning, and what each term refers to here.

★ Whole‑page grounding — the entire article is the context, not the isolated snippet.
★ Three‑step explanations — term definition → meaning in context → example when helpful.
★ Multi‑turn — keep asking follow‑up questions about the same passage.
★ Any language — explain in Chinese, English, Japanese, and more.
★ Cited web search (optional) — a search engine fetches live facts and your model writes the answer with [n] cited sources. Context‑aware, bilingual queries that disambiguate homonyms.
★ Works with any OpenAI-compatible model service, plus native Anthropic — Bring Your Own Key. Keys are stored locally in your browser and never sent to any third party.
★ Per‑tab conversations — each tab keeps its own thread; switching tabs never interrupts a running explanation.

Privacy: InContext has no backend. Your API keys and conversations stay in your browser. Page text is sent only to the model endpoint you configure yourself.

How to use: select text → click the floating Explain button (or right‑click / Ctrl+Shift+E) → read the grounded explanation in the side panel → ask follow‑ups. Toggle Web for cited, up‑to‑date answers.

Open source (MIT): https://github.com/qucooln/incontext

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普通划词翻译/解释只把选中的一小段发给 AI，解释脱离语境。
InContext 不一样：先用 Readability 抽取【整篇文章】喂给模型做背景，所以它解释的是这段话【在这篇文章里】到底什么意思——作者意图、隐含信息、专有名词的真实所指。
★ 基于全文，而非孤立片段
★ 三步式解释：术语释义 → 全文语境 → 必要时举例
★ 多轮追问、多语种输出
★ 可选联网：搜索引擎取数、你的模型作答并标注 [n] 来源；检索词结合上下文、中英双语、自动消歧
★ 兼容任意 OpenAI 格式的大模型服务，并支持 Anthropic 原生接口，自带 key（BYOK）；key 仅存本地，不传第三方
★ 按标签页独立对话，切换不打断
隐私：无后端，key 与对话只存在你浏览器，正文只发往你自己配置的模型接口。
开源(MIT)：https://github.com/qucooln/incontext