LLM Content Block

English · 中文

Paste AI conversations into Obsidian as a scrollable, format-safe card.

Why

We're entering a phase where more of what we want to keep is conversations with AI — a Q&A, a brainstorm, a debugging session. These conversations are themselves worth saving, the way we used to save articles, web pages, book notes.

But pasting them straight into Obsidian breaks immediately:

• It wrecks your formatting. An AI reply is itself markdown — headings, lists, code blocks, math. Once pasted, Obsidian treats it as your note's own structure: a ## heading inside the reply becomes a level-2 heading in your note, its lists merge into your lists, its ``` fences can even cut off your other blocks. Paste a few conversations and the whole note's hierarchy is scrambled — you can no longer tell what's your note and what's the AI's answer.
• It doesn't fit. A good AI reply is often hundreds of words; it fills the screen and stretches the note endlessly.
• No structure. A conversation is back-and-forth turns; flattened into one blob, the dialogue is lost.

LLM Content Block gives AI conversations their own container, fixing all three:

• The conversation lives inside a card; its markdown renders only inside the card and never leaks into the note body — the AI's headings don't become your headings, its code blocks don't slice your note. Your note stays clean.
• The card has a max height and scrolls internally; long AI answers even collapse by default — click Expand for the full text.
• Turns are recognized as user / AI bubbles, with a source tag (GPT / Claude / …).

In one line: make AI-generated content a self-contained, collectible, format-safe block in Obsidian — like a callout is a container for emphasis, this is a container for AI conversations.

Usage

Write a fenced code block with language aicard and paste the conversation:

```aicard
source: Claude
You: What's the difference between RSC and SSR?
Claude: The essence is **where it renders and when it hydrates**… (markdown, code, LaTeX all fine)
```

• source: (optional): the model — click the pill at the card's top-right to switch or type any name (presets: GPT / Gemini / Claude / DeepSeek / Qwen / ERNIE / Kimi / Doubao / Gemma / GLM / Grok / Llama, plus custom).
• Lines starting with Role: split into left/right bubbles: me/you/user → right, Claude/GPT/AI/assistant → left; other roles get a neutral bubble.
• Plain text with no role prefix becomes one clean content card.
• Full markdown support: code blocks, tables, LaTeX ($...$ / $$...$$), callouts, wiki links.
• Edit button (top-right) edits the conversation and source in place — the edit box is plain text, so pasting won't scramble formatting.

If the conversation itself contains ``` code blocks, use **4 backticks** ````aicard for the outer fence to avoid truncation. There's also a command Insert AI chat block: with text selected → wrap it into a card; no selection → insert a skeleton. Bind a hotkey in Settings → Hotkeys.

Features

• Format isolation: the AI content's markdown is contained in the card and never pollutes your note.
• Scroll + collapse: the card is height-limited and scrolls; long AI answers collapse to a preview.
• Rich text: code highlighting, LaTeX, tables, callouts, wiki links.
• Dialogue structure: auto user/AI bubbles; recognizes Chinese & English role names.
• Source management: 12 preset models + custom; one-click switch via the pill, written back to the note.
• Theme-aware: built entirely on Obsidian CSS variables; follows dark/light automatically.
• i18n: UI follows Obsidian's current language (中文 / English).

Settings

• Card max height, body font size, body font family (empty = follow theme).
• Custom sources (name + optional brand color).

View

Reading view renders perfectly. In Live Preview, very long blocks may need scrolling near the block's end to trigger rendering — for archived content, read in Reading view for the best experience.

Development

npm install
npm run build          # type-check + bundle
npm run build:deploy   # bundle + deploy to vault
npm run dev            # watch

The deploy target is set via env var or a local file (the repo itself contains no personal path):

export OBSIDIAN_VAULT=/path/to/your/vault   # option 1
echo /path/to/your/vault > .deploy-vault     # option 2 (.deploy-vault is gitignored)

License

MIT License — see LICENSE.

LLM Content Block（中文）

English · 中文

把和 AI 的对话装进 Obsidian 里一张可滚动、不破坏格式的卡片。

为什么需要它

我们正进入这样一个阶段：日常获取、并想收藏下来的内容，越来越多是和 AI 的对话——一次问答、一段头脑风暴、一个解题或写代码的过程。这些对话本身就是值得保存的知识，就像从前收藏文章、网页、书摘。

但把它们直接粘进 Obsidian，会立刻出问题：

• 格式被冲乱。AI 的回答本身就是 markdown：标题、列表、代码块、数学公式。粘进笔记后，这些会被 Obsidian 当成笔记自己的结构展开——AI 回答里的 ## 标题 变成笔记的二级标题，AI 的列表嵌进笔记的列表，AI 的 ``` 代码块还可能截断笔记的其它围栏。粘几段对话，整篇笔记的层级和格式就全乱了，再也分不清"哪段是我的笔记、哪段是 AI 的回答"。
• 一屏装不下。一段精彩的 AI 回答动辄几百上千字，铺满整屏，笔记被撑得很长，翻找费劲。
• 没有边界。对话是来回多轮（你问、AI 答），扁平地粘成一大段文字，读不出对话结构，也不像一条可被引用的"记录"。

LLM Content Block 给 AI 对话一个独立容器，一次解决这三点：

• 对话被装进一张卡片，它的 markdown 只在卡片内部渲染，绝不外泄到笔记主体——AI 的标题不会变成笔记标题，AI 的代码块不会截断笔记。笔记结构保持干净。
• 卡片有最大高度、内部可滚动；较长的 AI 回答还能默认折叠，点「展开」看全文。长对话不再霸占屏幕。
• 多轮对话自动识别成 user / AI 气泡，带来源标签（GPT / Claude / …）。

一句话：让 AI 生成的内容，成为 Obsidian 里一个自包含、可收藏、不破坏格式的块——就像 callout 是"强调"的容器，它是"AI 对话"的容器。

用法

写一个 fenced code block，语言填 aicard，把对话粘进去：

```aicard
source: Claude
你: RSC 和 SSR 什么区别？
Claude: 本质区别在于**在哪里渲染、何时 hydrate**……（可含 markdown、代码块、LaTeX）
```

• source:（可选）：来源模型，点击卡片右上角胶囊可切换或直接输入（预置 GPT / Gemini / Claude / DeepSeek / Qwen / ERNIE / Kimi / Doubao / Gemma / GLM / Grok / Llama，也可自定义）。
• 以 角色: 开头的行分成左右气泡：我/你/user 靠右，Claude/GPT/AI/助手 靠左；其它角色走中性气泡。
• 没有角色前缀的纯文本，整段成一个干净的内容卡片。
• 完整支持 markdown：代码块、表格、LaTeX（$...$ / $$...$$）、callout、wiki link 等。
• 右上角编辑按钮可就地编辑对话与来源（编辑框是纯文本，粘贴不会冲乱格式）。

对话里如果自带 ``` 代码块，外层围栏用 **4 个反引号** ````aicard 防止截断。 也可以用命令「插入 AI 对话块」：选中已有文本→包成卡片；没选中→插入骨架。在设置→快捷键里给它绑个键。

特性

• 格式隔离：AI 内容的 markdown 困在卡片内，不污染笔记结构。
• 可滚动 + 折叠：卡片限高、内部滚动；长 AI 回答默认折叠预览。
• 富文本：代码高亮、LaTeX、表格、callout、wiki link 全支持。
• 对话结构：自动 user/AI 气泡，中英文角色名都能识别。
• 来源管理：12 个预置模型 + 自定义，胶囊一键切换并写回。
• 主题协调：全程使用 Obsidian CSS 变量，dark / light 自动跟随。
• 多语言：界面跟随 Obsidian 当前语言（中文 / English）。

设置

• 卡片最大高度、正文字号、正文字体（留空跟随主题）。
• 自定义来源（名称 + 可选品牌色）。

视图

阅读视图完美渲染。Live Preview 下超长对话可能需要滚到块尾附近才触发渲染——归档后主要在阅读视图查看，体验最佳。

开发

npm install
npm run build          # 类型检查 + 打包
npm run build:deploy   # 打包 + 部署到 vault
npm run dev            # 监听打包

部署目标通过环境变量或本地文件指定（仓库本身不含任何个人路径）：

export OBSIDIAN_VAULT=/path/to/your/vault   # 方式一
echo /path/to/your/vault > .deploy-vault     # 方式二（.deploy-vault 已 gitignore）

License

MIT License，详见 LICENSE。