Maple syrup 居然都见底了 🇨🇦🇨🇦🇨🇦

尼古猫有点意思，有种 family guy 的感觉

今天又周四了又有梦限大看了有没有懂的 🤤

这些音乐和章节设计都很有情绪表现力，这是我觉得很有意思的

尤其是对同一段基础旋律的变奏，在同一主题下塑造出不同的情绪，我特别喜欢这种表现方式

如果听整轨的话，不同曲目时间还是有过渡的，就好像是目睹克服内心困难的历程 😇

确实有相同的感受，只是我难受的时候经常听的东西会让我回忆起难受的感觉，反而有点恐怖 🫠

我特别喜欢的：

• Resurrections
• Awake
• Quiet and Falling
• In the Mirror
• Reach for the Summit
• My Dearest Friends

Celeste Original Soundtrack - Lena Raine

吓哭了 😭

分享一点新加坡特色食物（搬运自水源，一些图床没法平移过来，所以是单独复制的）

价位：整体在 1.2-2x 上海物价，在外面吃对应这个倍率的上海商圈物价，在学校吃对应这个倍率的交大食堂价格，小于 1.2x 的时候不多（也就是说跟国内相同单品一个价，个别这边产量大的可能有），翻一番还要多的情况也没咋见过

特色菜：我朋友圈里发了几个
不能说很好吃但绝对不算难吃，不是猎奇取向但足够新奇

这几天吃下来比较有特色的：

叉烧/脆皮烧肉/海南鸡^[1]/烧鸭——四选一/二——饭/面 🤣

各种小炸物蒸物，类似广东早茶（？）

肉骨茶

奇怪的没有萝卜的萝卜糕，包括炒制和泡汤里多种做法，ref：

各种椰浆椰奶衍生物：
椰浆饭

各种虾衍生物：
加奶油蘑菇汤配上当地特色香料叶子的也有，炸虾卷/球也有，制烧麦啥的也有

各种咖喱衍生物（不赘）

集以上之大成者：请输入文本

总结

在住处附近食阁要了个 Lontong（椰奶蔬菜咖喱泡米糕 + 酱炸小鱼），又要了对炸鸡翅，4+1.5 新

总结

咸蛋黄鱼皮

Summary

---

1. （区别于交大四餐一楼和六餐二楼豉油鸡，虽然这里有的地方也有“豉油鸡饭”） ↩︎

晚上好，很久很久很久没有见到鱼鱼了~甚至包括微信与朋友圈

这个可爱宝宝（ok 你销号那会我应该还叫 Jackeiner）最终去了 nus 水一年硕士，未来怎么样，只有天知道（

以及，xjtu discourse 的页面怎么又大改了🫠 在 Singapore 这里上西交门不需要梯子，但是依然很卡，呜

康桥绿豆冰沙 😇

后排cy

ok 呀人际关系只是人生的小点心而已，我还是要找点自己的事情做
得到是喜悦，失去是修行
经历的一切没有白费，都会成为经验和教训
好像有点想开了
匿名状态下发的东西好像删不掉的，希望西迁的水源大军别回来看到就好，不然我就彻底社死了

Summary

我真的应该从心底接受任何关系的流动。风来疏竹，风过而竹不留声；雁渡寒潭，雁去而潭不留影。只有打心底接受了这些，放下自己的执念，才能自在地活在世界上。
社交中我总是太过认真和执着地经营，把“别人的看法”看得比天还大，和别人互相比较互相较劲。其实这些人都不重要，根本不值得如此在意。他们对我印象好，又如何呢？
说白了就是自己执念太重，想要关系长长久久反而不如顺其自然。拿个友谊地久天长的剧本然后开始表演的自己是很幼稚的。关系又不是财产，断了就断了，又怎么样呢？一位伟人说所有事物都会走向灭亡什么的。关键是不要委屈自己，一直压着自己，让它自然发生。
可能还是要多发展功能性的社交而不是情感性的社交，培养一下自己的 te 思维才是出路。用 fi 社交简直就是自毁。把关系分级，不是每个人都值得印象管理。我应该以成为一名”棋手“为目标而不是入戏的”演员“。
云五的故事适合收藏但不适合表演，既然回忆已在我心中，而其余四人并没有那么在意，我也不必较真了。毕竟这世界那么多人。

还有就是血的教训：只筛选不改变。还是要有更多的手段。

这首也好听，尤其 MV 给人印象深刻 😇

我是垃圾桶，这写的就是垃圾

前言

本站使用的软件也运行了好多天了，目前各种小bug不断，但是好在没有什么致命的问题。
为了帮助用户更好地理解本软件的开发情况，所以写一篇文章，介绍有哪些功能，数据是怎么迁移的。

设计理念

简单，好用
侧重点：易用 > 易开发维护 > 拥有各种功能

实现的功能

本软件的设计，高度受Discourse启发。但不谋求实现Discourse的全部功能。

Murmur: Modern Discussion Forum

murmur is a high-performance, features-rich, Discourse/NimForum-style discussion forum. It is engineered with a hybrid SSR-First (Server-Side Rendering) architecture, delivering instant page loads and optimal SEO crawlers accessibility, while layering on real-time interactive widgets as progressive client-side enhancements.

---

🛠️ The Tech Stack

Murmur's architecture is divided into a high-performance web core, a relational database, and a specialized asset caching layer:

• Web Core: SvelteKit 2 utilizing Svelte 5 Runes for robust state management.
• Database & ORM: Drizzle ORM managing SQLite (better-sqlite3 driver) for synchronous operations.
• Asset Performance: A custom caching proxy written in Rust using Axum (uploads-proxy).
• Search Subsystem: SQLite FTS5 index combined with the sqlite-vec extension for vector operations, and @node-rs/jieba CJK tokenizer.
• Real-time Features: Server-Sent Events (SSE) for pub/sub notifications, and Yjs text structures for wiki collaboration.
• Styling: TailwindCSS v4 with Flowbite Svelte.

---

🏛️ System Architecture Preview

Murmur is designed to maximize speed by avoiding clientside rendering overhead during initial page loads.

graph TD
    Client[Browser Client]
    SvelteKit[SvelteKit Node.js Server]
    SQLite[(SQLite DB / local.db)]
    Proxy[Rust Uploads-Proxy]
    Upstream[Upstream Assets Server]
    LLM[LLM API / Ollama / Gemini / OpenAI / Anthropic]

    Client -->|1. HTTP Page Request / SSE Stream| SvelteKit
    Client -->|2. HTTP Uploaded Files| Proxy
    Proxy -->|3. Cache Miss Fetch| Upstream
    Proxy -->|4. Save locally| Disk[(Local Uploads)]
    SvelteKit -->|5. Synchronous DB Queries| SQLite
    SvelteKit -->|6. Vectors & Generation| LLM

1. Server-Side Rendering: SvelteKit processes the request, queries the SQLite database synchronously through the repository layer, compiles the page into static HTML, and responds.
2. Client Hydration: The browser displays the HTML, downloads the JavaScript bundles, and hydrates components (e.g. Composer, Likes, Chat).
3. Live Updates: An SSE connection is established to stream live updates (new posts, edits) to active tabs.
4. Asset Offloading: The Rust uploads-proxy handles asset queries. If a file is cached locally on disk, it is served; otherwise, the proxy downloads it from the upstream server with retry logic, saves it locally, and serves it.

---

📚 Documentation Index

Below is the directory map of the Murmur system documentation. Click on any link to view detailed guides:

⚙️ [System Architecture & Scaling](file:///f/murmur/doc/architecture.md)

• Detailed breakdown of the request-response lifecycle and hydration.
• Rust uploads-proxy microservice design (thundering herd protection, atomic writes).
• Horizontal scaling recommendations (reconciliation, moving from memory SSE to Redis pub/sub, object storage).

Murmur: System Architecture

This document describes the high-level architecture of Murmur, including the frontend framework, backend data flow, integration with external services, and horizontal scaling patterns.

---

Technical Stack

Murmur is built using a modern, lightweight JavaScript stack, layered with a high-performance Rust microservice:

• Frontend / Meta-framework: SvelteKit 2 using Svelte 5 (Runes mode).
• Styling: TailwindCSS v4 (CSS-first, no tailwind.config.js) & Flowbite Svelte components.
• Database: SQLite (better-sqlite3 driver) wrapped with Drizzle ORM.
• Search Vector calculations: SQLite extension sqlite-vec.
• Search tokenization: @node-rs/jieba for CJK languages.
• Real-Time Communication: Server-Sent Events (SSE).
• Collaboration: Yjs text types synced stateless-ly over HTTP.
• Assets Proxy: Custom Axum-based Rust microservice (uploads-proxy).

---

Component Layout & Data Flow

Murmur leverages Server-Side Rendering (SSR) by default to deliver HTML instantly to crawlers and users. Clientside Svelte components progressively hydrate the page to enable real-time messaging, infinite scroll, and rich editing.

graph TD
    Client[Browser Client]
    SvelteKit[SvelteKit Node.js Server]
    SQLite[(SQLite DB / local.db)]
    Proxy[Rust Uploads-Proxy]
    Upstream[Upstream Assets Server]
    LLM[LLM API / Ollama / Gemini / OpenAI / Anthropic]

    Client -->|1. HTTP / SSE| SvelteKit
    Client -->|2. HTTP Static Assets| Proxy
    Proxy -->|3. Fetch cache miss| Upstream
    Proxy -->|4. Save locally| Disk[(Local Uploads)]
    SvelteKit -->|5. Synchronous Queries| SQLite
    SvelteKit -->|6. Vectors & Generation| LLM

1. Request Lifecycle

1. The browser requests a page (e.g., /t/slug/id).
2. SvelteKit's routing resolves the path and calls the server-side load function (+page.server.ts), which queries the database synchronously via the repository layer (src/lib/server/repo.ts).
3. SvelteKit renders the page as static HTML (SSR-first) and returns it.
4. The client browser parses the HTML, displays it immediately, and fetches Svelte bundles to hydrate active widgets (e.g., the composer, emoji picker, likes).
5. The client initiates a Server-Sent Events (SSE) connection to listen to live updates.

---

Node.js & Rust uploads-proxy Integration

User-uploaded attachments and legacy images are cached locally on disk. To prevent heavy Node.js threads from blocking on large file IO operations:

• Node.js Server: Serves core HTML/JS payloads and handles API mutations.
• Rust uploads-proxy: Serves files located under /uploads/. It listens on 127.0.0.1:4119 and handles file lookups.
  • Cache Hit: Serves the local file immediately using high-speed async file streaming via tokio-util.
  • Cache Miss: Downloads the asset from the configured upstream server (attempts up to 3 times, with a 2-second sleep duration between attempts), saves it locally, and serves it to the user.
  • Thundering Herd Coalesce: Employs a mutex and tokio::sync::Notify to block duplicate concurrent requests for the same missing asset, ensuring only one download request hits the upstream server.

---

Real-Time Engine (SSE Pub/Sub)

Murmur uses a single-process in-memory pub/sub pattern implemented in [events.ts](file:///f/murmur/src/lib/server/events.ts):

• Route handlers or repository mutations call publish(topicId, event).
• The Server-Sent Events endpoint [events/+server.ts](file:///f/murmur/src/routes/t/[slug]/[id]/events/+server.ts) subscribes to updates for a specific topic.
• It streams JSON-LD chunk lines to the browser's EventSource instance.
• The UI handles the event reactively to append new posts, update counts, or delete posts without page reloads.

---

Horizontal Scaling Strategy

Because SQLite and the SSE pub/sub system operate within a single process, horizontal scaling (running multiple instances of the Node.js process) requires:

1. Database Layer: Replace the local better-sqlite3 instance with a replicated SQLite setup (such as LiteFS) or migrate Drizzle configuration to PostgreSQL.
2. Pub/Sub Layer: Replace the in-memory singleton in [events.ts](file:///f/murmur/src/lib/server/events.ts) with a Redis or RabbitMQ pub/sub server. Route connections to the pub/sub interface so that messages publish across all Node server processes.
3. Uploads caching: Ensure the uploads-proxy instances point to a shared directory (e.g., NFS, GlusterFS) or replace the local filesystem storage with an Object Store (like AWS S3) by modifying the SvelteKit file upload API.

🗄️ [Data Model & Database Schema](file:///f/murmur/doc/data-model.md)

• Relational schema definitions for SQLite.
• Data design conventions (auto-increments, ISO-8601 timestamps, soft-deletions).
• Database tables, relationships, and indices optimization.

Murmur: Data Model & Database Schema

This document details the database schema, SQLite conventions, and tables managed by Drizzle ORM in Murmur. The database schema is located in [schema.ts](file:///f/murmur/src/lib/server/db/schema.ts).

---

Data Layer Conventions

To simplify imports, backups, and exports from active Discourse installations, Murmur maintains the following database patterns:

1. Integer Auto-increment Primary Keys: All tables use auto-increment integers. The system user is seeded with ID -1 (matching Discourse conventions).
2. ISO-8601 Timestamps: Timestamps are stored as text (e.g. 2026-07-15T22:00:00.000Z) rather than SQLite Unix integers. They default to the current time via $defaultFn(() => new Date().toISOString()). This allows lexicographical sorting and matches Discourse CSV files.
3. Booleans: Stored as integers (0 or 1) using Drizzle's integer(..., { mode: 'boolean' }).
4. Post Rendering: Posts store both the raw Markdown text (raw) and the cooked sanitized HTML (cooked). Rendering is done via {@html cooked} without dynamic clientside compilation.
5. Soft Deletions: Deleting topics or posts updates a deletedAt ISO timestamp column instead of deleting database rows.

---

Database Tables

Below is an overview of the Drizzle tables:

1. users

Represents forum members, administrators, and moderators.

• id: Integer primary key (Auto-increment).
• username: Unique username (Text).
• name: Full display name (Text, nullable).
• avatarUrl: URL of the user's avatar.
• email: User email address.
• githubId: Bound GitHub ID for SSO.
• admin / moderator: Role toggles (Booleans).
• trustLevel: Trust system ranking (0 to 4).
• silencedUntil: ISO timestamp until which the user is banned from posting.
• signatureRaw / signatureCooked: Markdown/HTML for post signatures.
• chatGlobalMuted: Toggle to silence all chat badge notifications (Boolean).

2. sessions & ssoSyncTickets

Authentication sessions matching Oslo specifications.

• sessions.id: SHA-256 hash of the session token.
• sessions.userId: References users.id (on cascade delete).
• sessions.expiresAt: Expiration timestamp.

3. categories & categoryGroups

Discussion categories which support nesting.

• categories.id: Integer primary key.
• categories.slug: Unique URL slug.
• categories.parentCategoryId: Self-referential FK targeting the parent category.
• categories.readRestricted: If true, restricts read permissions.
• categoryGroups: Maps categoryId to groupId and defines permissionType (Read, Create, Reply).

4. topics & posts

Forum threads and post items.

• topics.userId: Thread creator.
• topics.bumpedAt: ISO timestamp updated on every reply to drive sorting.
• topics.closed / topics.pinned: State flags.
• posts.topicId: Parent thread.
• posts.postNumber: 1-based sequential position within the topic (OP is 1).
• posts.raw / posts.cooked: Markdown/cooked text.
• posts.replyToPostNumber: Identifies the post being replied to.
• posts.wiki: Toggle indicating if the post is editable by non-creators.

5. postRevisions

History of edits made outside the grace period.

• postId: References posts.id.
• userId: Author of the edit.
• modifications: JSON string of modified properties (e.g. raw, cooked, title).
• number: Version sequence number.
• hidden: If true, hides modifications from normal users.

6. postEmbeddings & topicRecommendations

Vector semantic search embeddings and precomputed suggestions.

• postEmbeddings.postId: References posts.id.
• postEmbeddings.embedding: Raw vector float buffer (Float32Array).
• topicRecommendations.topicId: References topics.id.
• topicRecommendations.recommendations: JSON string list of recommended topic IDs.

7. chatChannels, chatChannelMembers & chatMessages

Real-time messaging channels.

• chatMessages.channelId: Parent channel.
• chatMessages.message / chatMessages.cooked: Raw/cooked text.
• chatChannelMembers.muted: Individual channel muting preference.

---

Schema DDL & Indices

Drizzle automatically creates indices to optimize query performance and prevent database locks:

• posts_topic_number_idx on (posts.topicId, posts.postNumber).
• topics_category_bumped_idx on (topics.categoryId, topics.bumpedAt).
• likes_post_user_unq unique index on (likes.postId, likes.userId).
• topic_recommendations and post_embeddings map primary keys to their parent components to enable swift joins.

✍️ [Reply Composer, Drafts & Uploads](file:///f/murmur/doc/features/composer.md)

• Composer UI controls (height adjustments, split ratios, fullscreen mode).
• Local storage autosave and server-side syncing database logic.
• Formatting toolbar helpers, emoji picker, and attachments uploads.
• Kate-style whole-line keyboard shortcuts (Ctrl+X / Ctrl+C).

Composer UI, Attachments & Draft Syncing

This document describes the reply composer UI, clientside formatting shortcuts, the draft autosave engine, and the multi-file attachment pipeline.

---

Composer Layout & Controls

The composer component [Composer.svelte](file:///f/murmur/src/lib/components/Composer.svelte) is modeled after the Discourse editor. It resides in a sticky drawer at the bottom of the screen.

+-------------------------------------------------------------------+
|  [v] Drag Handle (Height)                                         |
+-------------------------------------------------------------------+
|  Title / Action Summary                      [ ] Full [ _ ] Min  |
+-------------------------------------------------------------------+
|  [ B ] [ I ] [ Link ] [ Quote ] [ Tt v ] [ + v ] [ Undo ] [ Redo ]|
+-------------------------------------------------------------------+
|  Textarea Input (Markdown)         |  Live HTML Preview           |
|                                    |                              |
|                                    |                              |
|                                    |<---> Vertical Split Resizer  |
+-------------------------------------------------------------------+

Resizing Features

• Height Resizing: Users can click and drag the top border handle. The chosen height is written to localStorage.
• Split ratio Resizing: A vertical split bar sits between the editor and preview panels. Dragging it updates the split percentage dynamically.
• Fullscreen mode: Toggles the composer to fill the viewport.
• Minimization drawer: Minimizes the composer into a small, floating status bar at the bottom right.

---

Rich Formatting Toolbar & Emojis

1. Heading Selector (Tt)

Inserts heading markdown (# to ####) at the cursor selection.

2. Actions Selector (+)

• Hide Details: Inserts a folding BBCode detail block:

  <details><summary>Summary</summary>
  
  
  content
  
  
  

``` - **Footnote**: Inserts inline footnote syntax (`^[footnote]`). - **LaTeX Math**: Inserts standard math symbols wrapper (`$x^2## 前言 本站使用的软件也运行了好多天了，目前各种小bug不断，但是好在没有什么致命的问题。 为了帮助用户更好地理解本软件的开发情况，所以写一篇文章，介绍有哪些功能，数据是怎么迁移的。

设计理念

简单，好用
侧重点：易用 > 易开发维护 > 拥有各种功能

实现的功能

本软件的设计，高度受Discourse启发。但不谋求实现Discourse的全部功能。

Murmur: Modern Discussion Forum

murmur is a high-performance, features-rich, Discourse/NimForum-style discussion forum. It is engineered with a hybrid SSR-First (Server-Side Rendering) architecture, delivering instant page loads and optimal SEO crawlers accessibility, while layering on real-time interactive widgets as progressive client-side enhancements.

---

🛠️ The Tech Stack

Murmur's architecture is divided into a high-performance web core, a relational database, and a specialized asset caching layer:

• Web Core: SvelteKit 2 utilizing Svelte 5 Runes for robust state management.
• Database & ORM: Drizzle ORM managing SQLite (better-sqlite3 driver) for synchronous operations.
• Asset Performance: A custom caching proxy written in Rust using Axum (uploads-proxy).
• Search Subsystem: SQLite FTS5 index combined with the sqlite-vec extension for vector operations, and @node-rs/jieba CJK tokenizer.
• Real-time Features: Server-Sent Events (SSE) for pub/sub notifications, and Yjs text structures for wiki collaboration.
• Styling: TailwindCSS v4 with Flowbite Svelte.

---

🏛️ System Architecture Preview

Murmur is designed to maximize speed by avoiding clientside rendering overhead during initial page loads.

graph TD
    Client[Browser Client]
    SvelteKit[SvelteKit Node.js Server]
    SQLite[(SQLite DB / local.db)]
    Proxy[Rust Uploads-Proxy]
    Upstream[Upstream Assets Server]
    LLM[LLM API / Ollama / Gemini / OpenAI / Anthropic]

    Client -->|1. HTTP Page Request / SSE Stream| SvelteKit
    Client -->|2. HTTP Uploaded Files| Proxy
    Proxy -->|3. Cache Miss Fetch| Upstream
    Proxy -->|4. Save locally| Disk[(Local Uploads)]
    SvelteKit -->|5. Synchronous DB Queries| SQLite
    SvelteKit -->|6. Vectors & Generation| LLM

1. Server-Side Rendering: SvelteKit processes the request, queries the SQLite database synchronously through the repository layer, compiles the page into static HTML, and responds.
2. Client Hydration: The browser displays the HTML, downloads the JavaScript bundles, and hydrates components (e.g. Composer, Likes, Chat).
3. Live Updates: An SSE connection is established to stream live updates (new posts, edits) to active tabs.
4. Asset Offloading: The Rust uploads-proxy handles asset queries. If a file is cached locally on disk, it is served; otherwise, the proxy downloads it from the upstream server with retry logic, saves it locally, and serves it.

---

📚 Documentation Index

Below is the directory map of the Murmur system documentation. Click on any link to view detailed guides:

⚙️ [System Architecture & Scaling](file:///f/murmur/doc/architecture.md)

• Detailed breakdown of the request-response lifecycle and hydration.
• Rust uploads-proxy microservice design (thundering herd protection, atomic writes).
• Horizontal scaling recommendations (reconciliation, moving from memory SSE to Redis pub/sub, object storage).

Murmur: System Architecture

This document describes the high-level architecture of Murmur, including the frontend framework, backend data flow, integration with external services, and horizontal scaling patterns.

---

Technical Stack

Murmur is built using a modern, lightweight JavaScript stack, layered with a high-performance Rust microservice:

• Frontend / Meta-framework: SvelteKit 2 using Svelte 5 (Runes mode).
• Styling: TailwindCSS v4 (CSS-first, no tailwind.config.js) & Flowbite Svelte components.
• Database: SQLite (better-sqlite3 driver) wrapped with Drizzle ORM.
• Search Vector calculations: SQLite extension sqlite-vec.
• Search tokenization: @node-rs/jieba for CJK languages.
• Real-Time Communication: Server-Sent Events (SSE).
• Collaboration: Yjs text types synced stateless-ly over HTTP.
• Assets Proxy: Custom Axum-based Rust microservice (uploads-proxy).

---

Component Layout & Data Flow

Murmur leverages Server-Side Rendering (SSR) by default to deliver HTML instantly to crawlers and users. Clientside Svelte components progressively hydrate the page to enable real-time messaging, infinite scroll, and rich editing.

graph TD
    Client[Browser Client]
    SvelteKit[SvelteKit Node.js Server]
    SQLite[(SQLite DB / local.db)]
    Proxy[Rust Uploads-Proxy]
    Upstream[Upstream Assets Server]
    LLM[LLM API / Ollama / Gemini / OpenAI / Anthropic]

    Client -->|1. HTTP / SSE| SvelteKit
    Client -->|2. HTTP Static Assets| Proxy
    Proxy -->|3. Fetch cache miss| Upstream
    Proxy -->|4. Save locally| Disk[(Local Uploads)]
    SvelteKit -->|5. Synchronous Queries| SQLite
    SvelteKit -->|6. Vectors & Generation| LLM

1. Request Lifecycle

1. The browser requests a page (e.g., /t/slug/id).
2. SvelteKit's routing resolves the path and calls the server-side load function (+page.server.ts), which queries the database synchronously via the repository layer (src/lib/server/repo.ts).
3. SvelteKit renders the page as static HTML (SSR-first) and returns it.
4. The client browser parses the HTML, displays it immediately, and fetches Svelte bundles to hydrate active widgets (e.g., the composer, emoji picker, likes).
5. The client initiates a Server-Sent Events (SSE) connection to listen to live updates.

---

Node.js & Rust uploads-proxy Integration

User-uploaded attachments and legacy images are cached locally on disk. To prevent heavy Node.js threads from blocking on large file IO operations:

• Node.js Server: Serves core HTML/JS payloads and handles API mutations.
• Rust uploads-proxy: Serves files located under /uploads/. It listens on 127.0.0.1:4119 and handles file lookups.
  • Cache Hit: Serves the local file immediately using high-speed async file streaming via tokio-util.
  • Cache Miss: Downloads the asset from the configured upstream server (attempts up to 3 times, with a 2-second sleep duration between attempts), saves it locally, and serves it to the user.
  • Thundering Herd Coalesce: Employs a mutex and tokio::sync::Notify to block duplicate concurrent requests for the same missing asset, ensuring only one download request hits the upstream server.

---

Real-Time Engine (SSE Pub/Sub)

Murmur uses a single-process in-memory pub/sub pattern implemented in [events.ts](file:///f/murmur/src/lib/server/events.ts):

• Route handlers or repository mutations call publish(topicId, event).
• The Server-Sent Events endpoint [events/+server.ts](file:///f/murmur/src/routes/t/[slug]/[id]/events/+server.ts) subscribes to updates for a specific topic.
• It streams JSON-LD chunk lines to the browser's EventSource instance.
• The UI handles the event reactively to append new posts, update counts, or delete posts without page reloads.

---

Horizontal Scaling Strategy

Because SQLite and the SSE pub/sub system operate within a single process, horizontal scaling (running multiple instances of the Node.js process) requires:

1. Database Layer: Replace the local better-sqlite3 instance with a replicated SQLite setup (such as LiteFS) or migrate Drizzle configuration to PostgreSQL.
2. Pub/Sub Layer: Replace the in-memory singleton in [events.ts](file:///f/murmur/src/lib/server/events.ts) with a Redis or RabbitMQ pub/sub server. Route connections to the pub/sub interface so that messages publish across all Node server processes.
3. Uploads caching: Ensure the uploads-proxy instances point to a shared directory (e.g., NFS, GlusterFS) or replace the local filesystem storage with an Object Store (like AWS S3) by modifying the SvelteKit file upload API.

🗄️ [Data Model & Database Schema](file:///f/murmur/doc/data-model.md)

• Relational schema definitions for SQLite.
• Data design conventions (auto-increments, ISO-8601 timestamps, soft-deletions).
• Database tables, relationships, and indices optimization.

Murmur: Data Model & Database Schema

This document details the database schema, SQLite conventions, and tables managed by Drizzle ORM in Murmur. The database schema is located in [schema.ts](file:///f/murmur/src/lib/server/db/schema.ts).

---

Data Layer Conventions

To simplify imports, backups, and exports from active Discourse installations, Murmur maintains the following database patterns:

1. Integer Auto-increment Primary Keys: All tables use auto-increment integers. The system user is seeded with ID -1 (matching Discourse conventions).
2. ISO-8601 Timestamps: Timestamps are stored as text (e.g. 2026-07-15T22:00:00.000Z) rather than SQLite Unix integers. They default to the current time via $defaultFn(() => new Date().toISOString()). This allows lexicographical sorting and matches Discourse CSV files.
3. Booleans: Stored as integers (0 or 1) using Drizzle's integer(..., { mode: 'boolean' }).
4. Post Rendering: Posts store both the raw Markdown text (raw) and the cooked sanitized HTML (cooked). Rendering is done via {@html cooked} without dynamic clientside compilation.
5. Soft Deletions: Deleting topics or posts updates a deletedAt ISO timestamp column instead of deleting database rows.

---

Database Tables

Below is an overview of the Drizzle tables:

1. users

Represents forum members, administrators, and moderators.

• id: Integer primary key (Auto-increment).
• username: Unique username (Text).
• name: Full display name (Text, nullable).
• avatarUrl: URL of the user's avatar.
• email: User email address.
• githubId: Bound GitHub ID for SSO.
• admin / moderator: Role toggles (Booleans).
• trustLevel: Trust system ranking (0 to 4).
• silencedUntil: ISO timestamp until which the user is banned from posting.
• signatureRaw / signatureCooked: Markdown/HTML for post signatures.
• chatGlobalMuted: Toggle to silence all chat badge notifications (Boolean).

2. sessions & ssoSyncTickets

Authentication sessions matching Oslo specifications.

• sessions.id: SHA-256 hash of the session token.
• sessions.userId: References users.id (on cascade delete).
• sessions.expiresAt: Expiration timestamp.

3. categories & categoryGroups

Discussion categories which support nesting.

• categories.id: Integer primary key.
• categories.slug: Unique URL slug.
• categories.parentCategoryId: Self-referential FK targeting the parent category.
• categories.readRestricted: If true, restricts read permissions.
• categoryGroups: Maps categoryId to groupId and defines permissionType (Read, Create, Reply).

4. topics & posts

Forum threads and post items.

• topics.userId: Thread creator.
• topics.bumpedAt: ISO timestamp updated on every reply to drive sorting.
• topics.closed / topics.pinned: State flags.
• posts.topicId: Parent thread.
• posts.postNumber: 1-based sequential position within the topic (OP is 1).
• posts.raw / posts.cooked: Markdown/cooked text.
• posts.replyToPostNumber: Identifies the post being replied to.
• posts.wiki: Toggle indicating if the post is editable by non-creators.

5. postRevisions

History of edits made outside the grace period.

• postId: References posts.id.
• userId: Author of the edit.
• modifications: JSON string of modified properties (e.g. raw, cooked, title).
• number: Version sequence number.
• hidden: If true, hides modifications from normal users.

6. postEmbeddings & topicRecommendations

Vector semantic search embeddings and precomputed suggestions.

• postEmbeddings.postId: References posts.id.
• postEmbeddings.embedding: Raw vector float buffer (Float32Array).
• topicRecommendations.topicId: References topics.id.
• topicRecommendations.recommendations: JSON string list of recommended topic IDs.

7. chatChannels, chatChannelMembers & chatMessages

Real-time messaging channels.

• chatMessages.channelId: Parent channel.
• chatMessages.message / chatMessages.cooked: Raw/cooked text.
• chatChannelMembers.muted: Individual channel muting preference.

---

Schema DDL & Indices

Drizzle automatically creates indices to optimize query performance and prevent database locks:

• posts_topic_number_idx on (posts.topicId, posts.postNumber).
• topics_category_bumped_idx on (topics.categoryId, topics.bumpedAt).
• likes_post_user_unq unique index on (likes.postId, likes.userId).
• topic_recommendations and post_embeddings map primary keys to their parent components to enable swift joins.

✍️ [Reply Composer, Drafts & Uploads](file:///f/murmur/doc/features/composer.md)

• Composer UI controls (height adjustments, split ratios, fullscreen mode).
• Local storage autosave and server-side syncing database logic.
• Formatting toolbar helpers, emoji picker, and attachments uploads.
• Kate-style whole-line keyboard shortcuts (Ctrl+X / Ctrl+C).

Composer UI, Attachments & Draft Syncing

This document describes the reply composer UI, clientside formatting shortcuts, the draft autosave engine, and the multi-file attachment pipeline.

---

Composer Layout & Controls

The composer component [Composer.svelte](file:///f/murmur/src/lib/components/Composer.svelte) is modeled after the Discourse editor. It resides in a sticky drawer at the bottom of the screen.

+-------------------------------------------------------------------+
|  [v] Drag Handle (Height)                                         |
+-------------------------------------------------------------------+
|  Title / Action Summary                      [ ] Full [ _ ] Min  |
+-------------------------------------------------------------------+
|  [ B ] [ I ] [ Link ] [ Quote ] [ Tt v ] [ + v ] [ Undo ] [ Redo ]|
+-------------------------------------------------------------------+
|  Textarea Input (Markdown)         |  Live HTML Preview           |
|                                    |                              |
|                                    |                              |
|                                    |<---> Vertical Split Resizer  |
+-------------------------------------------------------------------+

Resizing Features

• Height Resizing: Users can click and drag the top border handle. The chosen height is written to localStorage.
• Split ratio Resizing: A vertical split bar sits between the editor and preview panels. Dragging it updates the split percentage dynamically.
• Fullscreen mode: Toggles the composer to fill the viewport.
• Minimization drawer: Minimizes the composer into a small, floating status bar at the bottom right.

---

Rich Formatting Toolbar & Emojis

1. Heading Selector (Tt)

Inserts heading markdown (# to ####) at the cursor selection.

2. Actions Selector (+)

• Hide Details: Inserts a folding BBCode detail block:

  <details><summary>Summary</summary>
  
  
  content
  
  
  

``` - **Footnote**: Inserts inline footnote syntax (`^[footnote]`). - **LaTeX Math**: Inserts standard math symbols wrapper (). - **Mermaid Flowchart**: Inserts standard Mermaid graphs template. - **Table / Date**: Generates formatted markdown tables or inserts local timestamps.

3. Emoji Picker

A custom Svelte 5 component [EmojiPicker.svelte](file:///f/murmur/src/lib/components/EmojiPicker.svelte) displays emoji categories. It supports text-based query filtering and inserts the selected emoji at the cursor.

---

Kate-Like Whole Line Editing

When typing inside the editor, Murmur supports KDE Kate-style shortcuts:

• Ctrl+C (Copy): If no characters are selected (collapsed selection), copies the entire line containing the cursor (including the newline character).
• Ctrl+X (Cut): If no selection is active, cuts the entire line and moves lines below it up.
• Cursor Repositioning: After cutting, the cursor automatically snaps to the start of the next line, saving keystrokes.

This logic is bound to the handleKeyDown function in the composer. It interacts directly with the browser's clipboard API and forces a tick update on Svelte's reactive states to maintain history.

---

Draft Autosave & Database Synchronization

To prevent data loss, the composer synchronizes drafts using a hybrid approach:

sequenceDiagram
    participant Client as Browser Textarea
    participant Local as localStorage Cache
    participant API as /api/drafts/sync
    participant DB as SQLite drafts Table

    Client->>Local: Save drafts instantly on keystroke (Keydown)
    Client->>API: Periodic debounced save (Every 5 seconds)
    API->>DB: Write draft using compound key (userId + key)
    Note over API, DB: Last-write-wins merging by timestamp

• LocalStorage: Serves as the primary cache to save text instantaneously.
• Database Synchronization: Every 5 seconds (debounced), the client makes an HTTP POST request to /api/drafts/sync. It pushes drafts to the SQLite database, ensuring edits are preserved across devices.
• Draft Disposal: Submitting a post deletes both the local storage key and the database row.

---

Clipboard Paste & Attachment Pipeline

The upload interface is triggered by clicking the paperclip icon or pasting an image directly from the clipboard into the editor:

1. Upload Initiation: An async file reader creates a unique placeholder: [Uploading image.png...] at the current cursor position.
2. Chromium List safeguard: Before beginning async processing, the file list is cloned into a static array. This prevents Chromium browsers from resetting the active input files when the input element value is cleared.
3. API Upload: The file is sent via multipart POST to /api/upload. The endpoint validates files against allowed formats (e.g. jpg, png, gif, svg).
4. Link Replacement: Once the API returns the permanent URL, the placeholder is replaced with the correct Markdown markup: ![filename|widthxheight](url).

Codeblocks

• auto-detection of codeblocks based on the first line of the codeblock.
• mermaid flowcharts.
• toggle line numbers
• copy and full-screen buttons

🔍 [Full-Text & Semantic Search (RAG)](file:///f/murmur/doc/features/search-and-rag.md)

• SQLite FTS5 full-text indexing with Porter stemming.
• CJK search query segmentation using Jieba tokenizer.
• sqlite-vec semantic vector distance search pipeline.
• RAG AI chatbot integration and context permission safeguards.

Full-Text & Semantic Search (RAG)

This document describes the search subsystem in Murmur, including full-text indexing, CJK segmentation, vector semantic calculations, and the RAG (Retrieval-Augmented Generation) chatbot.

---

1. Full-Text Search Index (FTS5)

Full-text search is powered by SQLite's FTS5 extension. During database initialization in [index.ts](file:///f/murmur/src/lib/server/db/index.ts), Murmur configures the virtual table search_index with Porter stemming to enable English word matching (e.g. "runs" matches "running"):

CREATE VIRTUAL TABLE IF NOT EXISTS search_index USING fts5(
    title,
    content,
    topic_id UNINDEXED,
    post_id UNINDEXED,
    post_number UNINDEXED,
    user_id UNINDEXED,
    category_id UNINDEXED,
    created_at UNINDEXED,
    tokenize = 'porter unicode61'
);

CJK Query Segmentation (Jieba)

Standard FTS5 tokenizers do not split Chinese, Japanese, or Korean (CJK) characters into individual words because they lack space boundaries.

To solve this, Murmur intercepts search requests in [repo.ts](file:///f/murmur/src/lib/server/repo.ts) and parses queries using Jieba (@node-rs/jieba):

1. RegEx Splitting: The query is split into CJK and non-CJK blocks.
2. Segmentation: CJK blocks are parsed using jieba.cutAll() to extract words.
3. FTS5 Wrapping: Extracted tokens are wrapped in double quotes and separated by spaces, converting the search into an implicit AND condition (e.g. 学习 Svelte becomes "学习" "Svelte").

---

2. Semantic Search (sqlite-vec)

Semantic search finds matches based on conceptual similarity rather than exact keyword matches. It uses the sqlite-vec extension to run vector operations inside SQLite.

• Storage: Embeddings are stored as raw binary BLOBs (Float32Array) in the post_embeddings table to prevent thread blocking (converting JSON strings to arrays in JavaScript is CPU intensive).
• Startup Migration: On startup, Murmur checks the database. If it finds legacy JSON string representations in the embeddings table, it converts them to binary buffers in batches of 500 rows.
• Query Resolution: Employs a cosine similarity calculation in SQLite:

  SELECT post_id, vec_distance_cosine(embedding, ?) AS distance
  FROM post_embeddings
  ORDER BY distance ASC
  LIMIT 20;
  

---

3. RAG Chatbot Integration

When a user runs a search query, Murmur displays a RAG chatbot assistant panel next to the search results:

+-----------------------------------------------------------------+
| Search Results                     |  🤖 Chatbot Reply          |
|------------------------------------|----------------------------|
| 1. Topic: How to run Murmur        |  To run Murmur, execute:   |
|    By user1 - "Run pnpm dev..."    |  `pnpm dev`. Refer to      |
|                                    |  /t/murmur/1 for details.  |
| 2. Topic: Production Setup         |                            |
|    By user2 - "Compile build..."   |  [ AI thinking indicator ] |
+-----------------------------------------------------------------+

LLM Streaming client

The server client in [chatLlm.ts](file:///f/murmur/src/lib/server/chatLlm.ts) streams responses from different providers:

• Ollama: Parses line-by-line NDJSON chunks.
• Gemini / OpenAI / Anthropic: Parses Server-Sent Events (SSE) data streams.

SSE Stream Synthesis

When a search is requested, the search API endpoint [stream/+server.ts](file:///f/murmur/src/routes/api/search/stream/+server.ts) initiates an SSE stream:

1. It queries FTS5 and semantic databases for matches.
2. Results are formatted as Markdown context blocks.
3. It asks the LLM to summarize the findings and include links to the matched topics (e.g. /t/slug/id/post_number).
4. It streams response tokens to the client browser via ai_answer_chunk events, which are compiled and rendered in the UI using markdown-it.

---

4. Privacy & Permission Filtering

To prevent information leaks (e.g., exposing private messages or restricted categories in search results or AI summaries):

• Permission Checking: The search service retrieves category permission rules via getPermittedCategoryIds(user).
• Pre-filtering: Topics and posts belonging to restricted categories are filtered out of the results before the data is cached or sent to the LLM.
• RAG Security: The LLM context contains only the results the user has permission to read.

✍️ [Revisions & Wiki Editing](file:///f/murmur/doc/features/revisions-and-wiki.md)

• Post edit revisions, grace period overrides, and modifications storage.
• Myers split-diff comparison modal and revision rollbacks.
• Wiki post permissions and stateless Yjs collaborative sync protocol.

Revisions, Wiki Posts & Yjs Collaborative Editing

This document explains the version control system for post edits, wiki post privileges, and the collaborative Yjs document synchronization engine.

---

1. Post Revisions System

Murmur tracks the history of changes made to posts and topic details (titles and categories) over time.

Grace Period & Versioning

• Editing Grace Period: Managed by the editing_grace_period site setting. If a user edits a post within this threshold (e.g. 5 minutes) after creation, modifications are overwritten without creating a new revision.
• Revision Capture: Edits made after the grace period increment the post's version (and publicVersion) and save the differences to post_revisions.
• Modifications Storage: Differences are stored as JSON-serialized change objects containing the previous values of modified fields:

  {
  	"raw": ["Old post raw markdown", "New post raw markdown"],
  	"title": ["Old topic title", "New topic title"]
  }
  

---

2. Visual Diff Comparison Modal

When a post contains revisions, a clickable edit counter (e.g., ✍️ 2) is displayed next to the post's timestamp. Clicking it opens the [PostRevisionsModal.svelte](file:///f/murmur/src/lib/components/PostRevisionsModal.svelte) component:

• Myers Diff Algorithm: Compares line-by-line differences in raw markdown or HTML tags.
• Cooked HTML Preview: Toggles to render the formatted HTML output.
• Reversion: Users with edit permissions can click the "Revert" button to roll back the post to a chosen revision.
• Visibility controls: Staff members (administrators and moderators) can toggle the visibility of individual revisions to hide sensitive information.

---

3. Wiki Posts

Wiki posts allow collaborative editing by members of the community rather than just the author.

• Wiki Toggle: Staff members can convert any post into a wiki post.
• Permissions: Admins can configure the minimum user group or trust level required to edit wiki posts (defaults to staff and trust_level_2 users).
• Indicators: Displays a wiki badge next to the post to show users they have permission to edit it.

---

4. Stateless Yjs HTTP Sync Protocol

To enable concurrent collaborative editing without keeping persistent WebSocket connections open, Murmur uses a stateless HTTP synchronization protocol:

sequenceDiagram
    participant Client as Browser Editor
    participant Server as /api/posts/[id]/wiki-sync
    participant DB as SQLite DB

    Client->>Server: Send stateVector (base64) & update (base64)
    Server->>DB: Fetch post yjsState BLOB
    Server->>Server: Apply client update to Y.Doc
    Server->>Server: Compute diff using client stateVector
    Server->>DB: Save updated Y.Doc buffer to yjs_state
    Server->>Client: Return update (base64) & merged text

Protocol Steps

1. Initiation: The editor initializes a Yjs document (Y.Doc) and extracts the text content.
2. Synchronization Request: The client sends an HTTP POST request to /api/posts/[id]/wiki-sync containing its local Yjs state vector and updates, encoded in base64.
3. Server Merge:
   • The server loads the post's current yjsState from SQLite.
   • It instantiates a server-side Y.Doc and applies the database state.
   • It applies the base64 update received from the client.
4. Calculations: The server computes the missing updates for the client using the client's state vector.
5. DB Update: If the merged text differs from the post's current content, the server runs editPost() to update raw/cooked columns and saves the new Yjs state buffer.
6. Response: The server returns the missing updates and the updated text to the client.

💬 [Real-Time Chat & Badges](file:///f/murmur/doc/features/chat.md)

• Public channels, direct message groups, and message management.
• Svelte 5 runes unread badge calculation and global/channel muting.

Real-Time Chat & Unread Badge system

This document describes the real-time chat subsystem in Murmur, including channels, user privileges, message edits, and the Svelte 5 runes unread badge system.

---

1. Chat Channels & DM Rooms

Murmur includes a built-in real-time chat workspace. It supports two channel types:

• Public Channels: General channels accessible by all registered members.
• Direct Messages (DMs): Private chat rooms created between two or more users.

---

2. Real-Time Message Flow

The chat interface streams updates in real time using Server-Sent Events (SSE):

sequenceDiagram
    participant ClientA as Sender Browser
    participant API as /api/chat/messages
    participant DB as SQLite DB
    participant SSE as SSE Stream Channel
    participant ClientB as Receiver Browser

    ClientA->>API: POST send message
    API->>DB: Write message to chat_messages
    API->>SSE: Publish message event
    SSE->>ClientB: Stream JSON event
    Note over ClientB: Append message to UI

Message Modifications

Users can edit or delete their own messages after they are sent. Moderators and administrators can edit or delete any message. Modifying a message updates the database and publishes an update event over SSE to sync all active clients.

---

3. Svelte 5 Runes Unread Badge System

To manage notification badges dynamically across the app, Murmur uses a client-side global state store powered by Svelte 5 runes:

• State Store: Defined in a client-safe state module. It tracks active channels, members, read states, and global mute preferences.
• Dynamic Badge calculations: Unread counts are computed using $derived values:

  // Simplified logic
  const unreadCount = $derived(() => {
  	if (globalMuted) return 0;
  	return channels
  		.filter((c) => !c.muted)
  		.reduce((sum, c) => sum + (c.messagesCount - c.lastReadMessageId), 0);
  });
  

• Real-Time Updates: When a new message event is received via the SSE connection, the client-side store increments the channel's message count. The UI updates the unread badge automatically.
• Read State Sync: Reading a channel updates the client-side state and sends an API call to save the lastReadMessageId in the database, syncing the read state across devices.

---

4. Muting Preferences

To prevent notification fatigue, users can configure their alert preferences:

• Channel Muting: Users can mute individual channels. Muted channels do not trigger badge alerts or red dot indicators.
• Global Muting: Users can enable global muting in their profile settings. This silences all chat notifications across the site.

💻 [Developer Guide & Conventions](file:///f/murmur/doc/developer-guide.md)

• Coding standards (runes, TailwindCSS v4, synchronous queries, types).
• File-based routing structure.
• ESLint and Prettier code formatting standards.

Developer Guide & Conventions

This document outlines the coding standards, repository layout, and development guidelines for developers working on the Murmur project.

---

1. Project Conventions

Svelte 5 Runes Mode

• Murmur uses Svelte 5 runes. Use $props(), $state(), $derived(), and $effect() for state management.
• Do not use legacy Svelte APIs (such as export let, $:, or store.subscribe).
• The compiler options are inlined in the vite.config.ts file under the Svelte plugin configurations.

Database Layer

• SQLite database operations run synchronously.
• Do not await database queries: Drizzle queries use .all(), .get(), and .run() synchronously.
• Implement database mutations in [repo.ts](file:///f/murmur/src/lib/server/repo.ts). Do not write inline database queries in routes or page endpoints.

Code Separation

• Server-Only Code: Any logic placed under src/lib/server/** is excluded from browser bundles.
• Shared Types: Clientside modules cannot import server code. Shared structures must be defined in [types.ts](file:///f/murmur/src/lib/types.ts).

Styling & CSS (TailwindCSS v4)

• TailwindCSS v4 is integrated as a CSS-first design tool. There is no tailwind.config.js.
• Configurations, theme overrides, and custom fonts are managed in [layout.css](file:///f/murmur/src/routes/layout.css) using CSS variables.

---

2. Directory Routing Structure

The routing layer uses standard SvelteKit file-based routing under src/routes/:

• / : Landing page displaying latest topics.
• /c/[slug]/[id] : Topics filtered by category.
• /t/[slug]/[id] : Topic thread displaying posts and reply forms. Includes SSE streaming listeners.
• /new : Full-page composer workspace.
• /login : Authentication page (GitHub SSO & dev login).
• /admin/settings : Dashboard for administrators to configure site settings.
• /sitemap.xml : Dynamic sitemap generation for web crawlers.

---

3. Formatting Standards

Code styling is enforced using Prettier and ESLint:

• Indent: Tabs.
• Quotes: Single quotes (').
• Trailing Commas: None.
• Line Width: 100 characters.

Verify formatting using the formatting scripts before submitting changes:

pnpm lint      # Checks linting and formatting compliance
pnpm format    # Automatically formats files

🛠️ [Operations & Maintenance Scripts](file:///f/murmur/doc/scripts.md)

• Standalone operational scripts under scripts/ (import tools, reindexing, post rebaking, and embedding calculations).

Data Migrations & Operations Scripts

This document details the standalone command-line scripts located in the /scripts/ folder. These scripts are run using tsx (e.g. pnpm tsx scripts/rebake-posts.ts).

---

1. Data Imports & Exports

[import_discourse_csv.ts](file:///f/murmur/scripts/import_discourse_csv.ts)

Imports forum databases from a Discourse CSV export.

• Workflow: Parses user profiles, categories, topics, and posts.
• Parsing: Translates Discourse emojis, system formatting, and image layouts into Murmur equivalents.
• Rebaking: Automatically runs the HTML cooking function on all imported posts to populate the cooked column.

[import_post_revisions.ts](file:///f/murmur/scripts/import_post_revisions.ts)

Reads historical edit logs from a Discourse CSV export and populates the postRevisions table.

• Workflow: Converts Discourse YAML modifications into JSON and links them to their respective post IDs.
• Recalculation: Adjusts version and publicVersion sequences on affected posts.

---

2. Topic recommendations & Embeddings

[embed-posts.ts](file:///f/murmur/scripts/embed-posts.ts)

Generates vector float embeddings for search calculations.

• Workflow: Identifies posts that do not have embeddings in the post_embeddings table.
• Generation: Calls the configured LLM API (e.g. Ollama, OpenAI) to generate vector embeddings.
• Persistence: Writes vector embeddings to the database as binary buffers.

[generate-related-topics.ts](file:///f/murmur/scripts/generate-related-topics.ts)

Computes topic similarity recommendations.

• Workflow: Calculates vector distances between topic posts.
• Storage: Saves the top 50 matches for each topic as a JSON list in topic_recommendations.

---

3. Maintenance & Optimizations

[rebake-posts.ts](file:///f/murmur/scripts/rebake-posts.ts)

Re-processes post content using the Markdown compiler.

• Usage: Run this script after modifying markdown parser rules, BBCode preprocessors, or HTML sanitization options to update all compiled posts.

[rehash-compress-replace.ts](file:///f/murmur/scripts/rehash-compress-replace.ts)

Compresses and optimizes uploaded assets.

• Workflow: Compresses images on disk, updates their URLs, and updates file paths in raw and cooked post content.

[reindex.ts](file:///f/murmur/scripts/reindex.ts)

Rebuilds the virtual FTS5 search index.

• Workflow: Wipes search_index and indexes all posts in the database.
• CJK splitting: Uses Jieba to segment Chinese, Japanese, and Korean content.

---

⚡ Quick Start

1. Prerequisite Installations

Ensure you have Node.js 26+ and pnpm 11+ installed. If you plan to run the uploads proxy or semantic search, make sure cargo (Rust toolchain) and SQLite are available.

2. Development Setup

Clone the repository and install dependencies:

pnpm install

Configure your environment variables:

cp .env.example .env

Modify .env to define:

• DATABASE_URL: Path to your database file (defaults to local.db).
• ORIGIN: The server domain (e.g. http://localhost:5173).
• GITHUB_CLIENT_ID / GITHUB_CLIENT_SECRET: OAuth credentials.

Initialize and seed the database with mock categories, users, and topics:

pnpm db:push
pnpm db:seed

Start the Vite development server:

pnpm dev

Open /login and use the Dev Login button to authenticate as any user without configuring GitHub OAuth.

---

📁 Repository Layout

• src/routes/ - SvelteKit routing layer (pages, endpoints, SSE streams).
• src/lib/ - Shared code, UI components, and state modules.
• src/lib/server/ - Server-side modules (database pools, auth Oslo, markdown cooker, search caches).
• scripts/ - Standalone tools (data imports, re-indexing, embedding pre-calculations).
• uploads-proxy/ - Rust Axum asset cache proxy server.
• doc/ - System documentation markdown files.

我好像理解了为什么读博会抑郁，当然我没有去看过精卫所以不能说我的心理出现了疾病，但是这一次回家，我怀着对于科研没有底气的心面对着家里对自己学业有成走上人生巅峰的期待，我被其他亲戚以近乎造神的态度拿来和小孩对比来教育小孩，我在我希望可以塑造自己未来人生道路的年纪被家人开始赋予结婚生子的期待，我很痛苦我好像理解了为什么读博会抑郁，当然我没有去看过精卫所以不能说我的心理出现了疾病，但是这一次回家，我怀着对于科研没有底气的心面对着家里对自己学业有成走上人生巅峰的期待，我被其他亲戚以近乎造神的态度拿来和小孩对比来教育小孩，我在我希望可以塑造自己未来人生道路的年纪被家人开始赋予结婚生子的期待，我很痛苦

cite from 一个水源我爱看的日记楼，因为是日记楼就不放链接了。

但我终于对于读博可能带来的心理问题有了可以换位思考的同感，还是记一下。希望这位源友读博顺利

Are you in favour of replacing Discourse with new Sveltekit-based community app?

Background:
The current xjtu.men serves a new community app based on Sveltekit, a framework for rapidly developing robust, performant web applications using Svelte.

While Discourse is a mature and feature-rich community app, we often feel it is too heavy. The initial loading time can be quite long in bad network circumstances. The deployment and configuration are quite complex, because of too many features it offer and especially because of the plugin and theme component system.

Discourse is good if you are in a good network condition and you need so many features and customization, while what we need is a community app that just works. We can develop features we need relatively easily thanks to the Sveltekit framework we use, compared to the Ruby on Rails + Emebrjs framework Discourse uses.

读完了包法利夫人 感觉里面对人类情感和欲望的描写以及走向毁灭的过程非常真实 甚至很符合当今现实
今天开始二刷呼兰河传 第一次看是小学的时候 评价是它有些内容不太适合小学生看 里面有一些关于封建迷信的情节在我幼小的心灵中留下了不可磨灭的印象
因为喜欢《记忆中的玛妮》这部电影 所以还找到了原著（叫做 when Marnie was there） 也是今天开始阅读🥰
最近考完几天就这样开始沉迷文学 期末考请永远不要出分 或者不要给我带来惊吓啊啊啊

总算可以上门了
沉迷小说
昨天二刷了牛虻 一刷是因为保尔柯察金 二刷是因为基督山伯爵里面不经意的一句话涉及了牛虻的关键情节
结局给我的印象极其深刻 完全是恨海情天 强烈推荐！ 我到现在还无法使自己的精神恢复平静（好处是在想这个书 暂时没那么担心出分了）
为了避免剧透 就暂且不放具体的内容了

今天开始首次阅读包法利夫人 目前读到了第二部 对人物情感的描写也很精彩

今天到合肥IKEA玩，这里的感觉相对较小（甚至一楼还有McDonalds），但是人很多，有不少年青靓丽的美女，还见到个老外带她老婆和孩子逛。

餐厅不大，人不多，菜品不多，主打肉丸和烤串。没看到三文鱼冷盘沙拉。
物价好像比一年前涨了，肉串12一串，卖3串送饮料，不过一串确实比较大。
比较抽象的是卖冰淇淋的在一楼，卖主食的在二楼。

今年拿到了西湖大学某个神秘课题组的暑研名额，第一次有机会做线下实习
目前定下几个小小目标想要在这个暑假完成

• 去千岛湖骑车
• 自己租房，想要一个带厨房的公寓，想自己做饭吃
• 想买一把电吉他，组一辈子乐队

水一帖。

不知道门友对暑日和假期有什么印象，又有什么规划。成长在中国火炉的我，记忆里的夏日总是无尽灿烂的烈日倾盆而下，裹覆着大地和生灵万物。从江边袭来的氤氲水汽，锁住已经被粘腻汗水打湿的毛孔。身体的热量无处散发，积郁在胸腔和脑腔。热，真的很热，人像是蒸笼里的螃蟹，被炙烤、汽蒸着心神，被折磨、剥夺理智。

但我喜欢夏天。冬天太阴郁，春天和秋天太短暂。只有夏日有明媚的蔚蓝色天空。深沉的蓝色好像windows7的壁纸一样纯净。还有西瓜，夏季给人类的馈赠，没有比西瓜更好吃的水果，多汁清甜，但不酸不腻，只是我妈不允许我多吃，避免我拉肚子。

夏天还有一年中最长的假期。暑假里我有时间拜访舅舅，和表弟在老家漫山遍野地乱跑。折下树枝，然后去山另一边的小卖部买彩纸做风车；晚上睡在一起但比力气摔跤到半夜；拿把柴刀砍树，制作两把圣剑然后决斗... 种种行为大人们看来幼稚，但给我们无尽快乐。遗憾的是年龄渐长，两人没有了共同话题。我还是当年那般幼稚，但他已经长大成熟了。

暑假里还会和同学相约，每日一同沿江骑行，到区图书馆看书、游戏。家乡的河流真的非常、非常美丽，笔直宽阔的滨江路沿着江水延伸，沿江一侧是茂密的树林，另一侧是缓缓的山体和防滑坡墙，山脚的洋房，一所大学和区图书馆。我和同学在午后两点顶着四十度的高温骑车到图书馆，在图书馆看书、打游戏。我喜好阅读科幻文学，在图书馆里看完了刘慈欣所有的小说，长篇如三体、球闪，短篇如山、赡养上帝等（超新星纪元的各版本还是在网上才阅读完全）；因为没有电话卡，连不上网，我们只能玩平板上的单机游戏。桥梁建筑(poly bridge)成为我们的最爱，两个人交替提出改进意见，优化桥梁设计直到通关。我们至今仍然保持联系，但他在北京上学，所以平时无法见面。

人总是会美化经历，抛却记忆中的不快，塑造美好的回忆，但曾经的快乐的确真实。

日子总不会太好，也不会太差。我是贪婪的物种，即使未来会创造新的快乐回忆，但因为过去的快乐无法重现，我也分外怀念那些逝去的日子。

这个暑假，机械专业实习和重修结束后，我又要返回家乡了。这次我期待着家里肥美的狸花猫，想狠狠撸它；期待着能用攒的钱买一台无人机，在镜头里俯瞰我的家乡；期待着看完《计网自顶向下》后开始学习计组...

最后，祝福所有门友暑假快乐，度过一个难忘的快乐夏天！

在平板上用了一年
感觉已经被同化了，还挺好看的 😸

但是在手机这种小屏幕下面还是喜欢Google的Material Design

令人感慨，我自己也要准备就业了。本科致谢写的近乎‘博爱’，现在感觉已经失去了那种胸襟。
我知道有人港硕毕业后华为-百度实习，第二年春招才进某AI公司，似乎也并非完全不行。（太细节的我不晓得）
如果是我这种保守人士是会接，但上海12k确实有点拮据了，在杭州或许还过的下去。

买了spcx然后在15个交易日内卖出的将被禁止参与oai和anthropic IPO 👿

第一次看到了池鹭
其实也看到了夜鹭 但距离太远了拍不出来 还是夜鹭更加猥琐🤣
为什么无法发送图片😡

鹅肉饭好吃😋
最喜欢的鹅肉制品是扬州的盐水鹅和潮汕卤水鹅肉

上海把子肉(可能是复旦枫林校区)，18r：

根据不靠谱的沪币换算汇率18/1.25 = 其他地区的14.4r

西交康桥苑一楼14r把子肉：

碳水这一块 🫪

出口转内销了

约一周前我就看见这幅图了，但当时登不上門，就没发。今天再见还是绷不住。🤣

每过一两个月就觉得以前写的东西依托构使，恨不得狠狠 refactor 但是又没精力有没有懂的

如题，基本发消息看到就会回，如果同时在线基本都是秒回，有时候晚回也会道歉。回的时候也不是敷衍挺热情的，有时也会主动延长话题。约出来线下在食堂很随意地吃过一次饭。这样到底有没有戏？

也许从某个时间节点开始，就注定了在这个游戏里我没法获得一个GOOD END。

我的确不够努力，学习的方法也全是错的，但也真的就差一点运气。唯一一个非常想去且技术面通过的公司，最终倒在了hr面，之后的春招就再没有其他声响。

本来想趁着情绪还在多写一些东西，但困意已经上来了。

要致谢的还有很多：
在本科时候偶尔和我聊天的刘军老师，今天就我是否要考研的困惑和我聊了一个下午。
我的舍友，感谢他们没有在意我每一个熬夜看代码的每一个夜晚。
隔壁宿舍的朋友，我偶尔会去和他们吹吹比。
隔壁班的好朋友，虽然我们两个人像两条区一样。

我的父母，虽然他们的意见真的不怎么有用，但是大学四年的生活费几乎都是他们出的。
以及交大门，我在这里写了很多没什么用，但也许以后看到会很怀念的日记。

很遗憾这些当时都没有写入我的本科论文，虽然我的本科毕业论文也是一坨 💩。

怎样才能回到过去——除了时光机以外。

想起来大一时候组织的活动：写一封信留给毕业的自己。我一直不敢打开，生怕里面写的是诸如搞技术、进大厂、拿大包一类的话语——我一定让过去的自己失望了吧。

但抑制不住好奇，终于是打开了。
一种难以形容的感觉，原来过去的我早就原谅了自己。
不知道该说什么，但小珍珠已经下来了。
幸好旁边就是我的毛巾，不用让舍友听到我的哭声。

SplitArgs

• 把字符串根据空格/引号分割成多个 token
• 无引号 token 按照字面字符处理
• 单引号 token 仅 unescape '' -> '
• 双引号 token 按照 YAML 双引号字符串 unescape

FSM

Go 实现

这样用闭包按照我的理解应该不会有性能问题？可惜因为需要 unescape 无法做到 zero-allocation

const (
	splitArgsLookForToken int = iota
	splitArgsInToken
	splitArgsInSingleQuotes
	splitArgsInDoubleQuotes
	splitArgsSingleQuoteEscape
	splitArgsDoubleQuoteEscape
	splitArgsEndSuccess
	splitArgsEndFail
)

func SplitArgs(s string) (result []string, err error) {
	var sb strings.Builder
	var current rune
	var currentSize int
	var errMsg string
	peeked := false
	eoi := false
	idx := 0

	state := splitArgsLookForToken

	peek := func() {
		if peeked {
			return
		}
		peeked = true
		if idx >= len(s) {
			eoi = true
		} else {
			current, currentSize = utf8.DecodeRuneInString(s[idx:])
		}
	}

	peekHex := func(size int) error {
		if idx+size > len(s) {
			return errors.New("early EOI at index " + strconv.Itoa(idx))
		}

		r := rune(0)

		for i := range size {
			c := s[idx+i]
			var v rune
			switch {
			case c >= '0' && c <= '9':
				v = rune(c - '0')
			case c >= 'a' && c <= 'f':
				v = rune(c - 'a' + 10)
			case c >= 'A' && c <= 'F':
				v = rune(c - 'A' + 10)
			default:
				return errors.New("bad hex digit at index " + strconv.Itoa(idx+i))
			}
			r = (r << 4) | v
		}

		current = r
		currentSize = size
		return nil
	}

	// Must only be called after calling peek()
	pop := func() {
		idx += currentSize
		peeked = false
	}

	begin := func() {
		sb.Reset()
	}

	end := func() {
		result = append(result, sb.String())
	}

	// Must only be called after calling peek() and before calling pop()
	write := func() {
		sb.WriteRune(current)
	}

	for {
		switch state {
		case splitArgsEndFail:
			err = errors.New("SplitArgs: " + errMsg)
			fallthrough
		case splitArgsEndSuccess:
			return
		case splitArgsLookForToken:
			peek()
			if eoi {
				state = splitArgsEndSuccess
				continue
			}

			switch current {
			case '\t', '\n', '\v', '\f', '\r', ' ':
				pop()
				continue
			case '\'':
				pop()
				begin()
				state = splitArgsInSingleQuotes
				continue
			case '"':
				pop()
				begin()
				state = splitArgsInDoubleQuotes
				continue
			default:
				begin()
				state = splitArgsInToken
				continue
			}

		case splitArgsInToken:
			peek()

			if eoi {
				end()
				state = splitArgsEndSuccess
				continue
			}

			switch current {
			case '\t', '\n', '\v', '\f', '\r', ' ':
				pop()
				end()
				state = splitArgsLookForToken
				continue
			default:
				write()
				pop()
				continue
			}

		case splitArgsInSingleQuotes:
			peek()

			if eoi {
				errMsg = "early EOI at index " + strconv.Itoa(idx)
				state = splitArgsEndFail
				continue
			}

			switch current {
			case '\'':
				pop()
				state = splitArgsSingleQuoteEscape
				continue
			default:
				write()
				pop()
				continue
			}

		case splitArgsInDoubleQuotes:
			peek()

			if eoi {
				errMsg = "early EOI at index " + strconv.Itoa(idx)
				state = splitArgsEndFail
				continue
			}

			switch current {
			case '"':
				end()
				pop()
				state = splitArgsLookForToken
				continue
			case '\\':
				pop()
				state = splitArgsDoubleQuoteEscape
				continue
			default:
				write()
				pop()
				continue
			}

		case splitArgsSingleQuoteEscape:
			peek()

			if !eoi && current == '\'' {
				write()
				pop()
				state = splitArgsInSingleQuotes
				continue
			} else {
				end()
				state = splitArgsLookForToken
				continue
			}

		case splitArgsDoubleQuoteEscape:
			peek()

			if eoi {
				errMsg = "early EOI at index " + strconv.Itoa(idx)
				state = splitArgsEndFail
				continue
			}

			switch current {
			case '"', '\\', '/', ' ', '\x09':
				write()
				pop()
				state = splitArgsInDoubleQuotes
				continue
			case '0', 'a', 'b', 't', 'n', 'v', 'f', 'r', 'e', 'N', '_', 'L', 'P':
				switch current {
				case '0':
					current = '\x00'
				case 'a':
					current = '\a'
				case 'b':
					current = '\b'
				case 't':
					current = '\t'
				case 'n':
					current = '\n'
				case 'v':
					current = '\v'
				case 'f':
					current = '\f'
				case 'r':
					current = '\r'
				case 'e':
					current = '\x1b'
				case 'N':
					current = '\x85'
				case '_':
					current = '\xa0'
				case 'L':
					current = '\u2028'
				case 'P':
					current = '\u2029'
				}
				write()
				pop()
				state = splitArgsInDoubleQuotes
				continue
			case 'x', 'u', 'U':
				var size int
				switch current {
				case 'x':
					size = 2
				case 'u':
					size = 4
				case 'U':
					size = 8
				}
				pop()
				if err := peekHex(size); err != nil {
					errMsg = err.Error()
					state = splitArgsEndFail
					continue
				}

				write()
				pop()
				state = splitArgsInDoubleQuotes
				continue
			default:
				errMsg = "bad escape sequence at index " + strconv.Itoa(idx)
				state = splitArgsEndFail
				continue
			}

		default:
			errMsg = "internal error"
			state = splitArgsEndFail
			continue
		}
	}
}

感觉接口设计有点问题，似乎应该把 unescape 和 split 分开？ 🤔

才发现状态名写错了应该是 unescape

方法论

写这种复杂状态机之前，先用表格大致设计出状态和迁移会顺利很多

我第一次写 IP Prefix trie 的时候完全梦到哪写到哪，哪里有问题就多加一个分支，最后变得非常莫名其妙 😅

我觉得有意思的学习内容

以前我一直认为自己对知识的渴望是纯粹的，认知、建模是我所有的意义。应试的学习让我感到不屑，却又因这份借口而无需过多进行实践

现在看来，对学习进步的需求无非来自三种追求：

• 获得知识本身
• 优越感
• 逃避劣等的恐惧

也许大部份人都有这些追求，只是不同的人和学习的内容，三种占比不同吧

我曾经自以为的纯粹知识渴望，也不过很大程度是对劣等感的逃避，为了没有胆量承认的虚荣

然而也许内心并不纯粹，追求俗不可耐，这样的自己才是真实的，而非想象中某种完美的幻影

无论出发点如何，如果还有兴趣能让我感到幸福，那便足够了吧 🙂

我的毕业论文的致谢是抄的模板的，但我发现很多人都会在上面写上一些整活的话语来告慰这白驹过隙般的四年，我今晚也很有感想，所以决定在这里写一写，弥补遗憾。

我虽然小时候很快乐，但是更多是看鱼的猎奇心理，说实在我现在并不怀念。让我羡慕的只是当时对时间流逝的无感

你发了这张图片反而让现在的我很期待再去一次水族馆了，因为我觉得气氛很美，而且意义很有意思（看迷途之子导致的），这是小时候的我感受不到的

所以我们在当下的开心才是最有意义的吧

我觉得现在的我和小时候的我并不是同一个人。小时候容易的快乐，对于现在的我来说并不快乐。也许不该被以前的残影束缚，而是应该重视现在的自己？ 😇

感觉活着的意义似乎不是能够用逻辑有意识地分析的东西。它是一种潜意识的，不受主观控制的感受。有时候我觉得空虚到窒息，积极地活着似乎只是一种完全没理由的选择，好像这感受就像一种遗传性的集体垃圾回收机制，让处境更差的个体自我销毁？

从这个角度反过来看，也许变得更世俗，更 typical 一些，也许就能获得一些无意识的价值感吧 ？（何意味

可惜死的过程是很痛苦很令人恐惧的，胜过我活着的痛苦，否则确实是很令人羡慕的了

要是有什么方法能完全抹去我的存在（包括存在过的记录），也许我会接受吧

没关系的，我也喜欢说莫名其妙的话，起码我不会在意别人这样

能够和类似的人讨论能够共情的话题，也许这就是你站特别的地方之一吧

之前看到的小鸭子已经变得半大不小了 正在换毛

图1 川普鱼 😸

上一次去水族馆还是小时候，具体细节已经遗忘了，那时我还是健康的人

现在谈到水族馆我大概会想到迷途之子？

以前无忧无虑地在水族馆玩一天，任由时间消磨流逝掉，也不感到恐惧，这样的我大抵已经死掉了 🥲

是陆家嘴水族馆吗
我小时候经常去 但现在感觉太小了而且人太多 应该对我来说不好玩了

我先把你那句 "I am garbage" 放在一边——不是因为它不重要，而是因为我不太相信它是真的。等一下说为什么。

先说我读到了什么。你不是随手发了几句丧气话。你描述得特别清楚、特别诚实：从前的你在图书馆一天能啃很多页 Rust，读完还记得，会"古法编程"；现在一个问题甩给 AI，跑通就行，代码看都不看完。从前你有勇气去要两个女生的联系方式；现在让你心动的，一句话都不敢说，不心动的，又懒得多说，甚至要把聊天记录发来问我该怎么聊。你把这一切都看在眼里，而且为此难受。

这里有个你可能没留意的点：垃圾是不会为自己的退化感到痛的。你能这么精确地说出"我从前是什么样、现在丢了什么"，恰恰说明你心里那套标准、那个你想成为的人，一直都在。会痛，是因为你还在乎。这不是垃圾的状态，这是一个有价值的人暂时熄了火的状态——两者天差地别。

我想认真说一件正好戳中你的事，它同时关于编程和"没意义"。你怀念的那个图书馆里的自己，享受的其实不是"学会 Rust"这个结果，而是过程里的阻力：自己一行行啃、卡住、想通、记住。学习科学里管这叫 desirable difficulties（合意困难）——正是那些费劲的部分建立了真正的能力，也正是那份费劲，让事情有嚼头、有成就感。你把阻力外包给了 AI，省了力，可你把那份回报也一起外包掉了。代码能跑，但"我搞懂了"的那种满足感没了。难怪觉得空。

至于"活着有什么意义"，我不想给你鸡汤。我只想说：从前读 Rust 的你，并不是先想清楚了人生意义才扎进去的，意义是你扎进去之后顺带长出来的。意义基本是干出来的，不是想出来的，更不是躺着等来的。所以这个问题现在这么难答，很可能不是因为你得先找到答案，而是因为你把那些会自动产生意义的事停掉了。

还有一点我得说，但不会替你下诊断：你描述的这种状态——发不出力、对什么都提不起劲、连游戏和 YouTube 也只是打发而非真享受、对自己特别狠——是很多人在抑郁或长期 burnout 时都会有的感受。如果这些话戳中了你，那它更可能是一种会变的"状态"，而不是一句关于你是谁的判决。如果它已经持续了挺久，找个专业的人、或者一个你信得过的人聊聊，是真的会有用的；需要的话我也可以帮你想从哪里开始。

最后，别去做什么宏大的"重新做人"计划，那种计划一般第三天就崩。就挑一件很小的、有阻力的事，自己做完。比如下一段代码别问 AI，自己写，哪怕慢、哪怕丑；或者那个让你心动的人，就发一句真实的话，不为了"培养感情"这个 KPI，只是说一句真的话。重点不是结果，是重新尝到一点点"我自己动了"的感觉。一次就够，它松动局面的力气会超出你的想象。

你不是垃圾。你是一个把自己看得太清楚、暂时熄了火的人。火还在不在？你能把这些写得这么清楚、这么诚实，我觉得它还在。

nihongo no sky so blue

我现在已经失去激情了

曾经2次，我要过两个感性趣的女生的IM号

现在，好几年多了，我再也没干过这样的事。

让我感到crush的女生没有勇气说（一句）话。
感不到crush的女生我没有激情说（很多）话。 😅

甚至，我把聊天记录发给Claude，问她我该怎么聊？该怎样培养感情？

曾经，我在图书馆阅读Rust编程教程，一天看很多页，能看下去，看完还多都能记得的。在前ChatGPT时代时还古法编程。

如今，我动不动一个问题甩给Claude/ChatGPT/Gemini，写出来的代码也不全看，直接跑看能否实现想要的效果。

哎，时代

哎，退化。

唯有行尸般度日，逆来顺受，没有勇气说不。

唯有游戏、Youtube、闲逛度日，没有静心思考，将想法转化成实际的动力。

For a long time, I know I am a garbage.

我活得有什么意义？

学校里的戴胜
之前有次看夜鹭的时候也看到戴胜了 但是拍不到