很少看到棕色的鸽子欸！

浙江怎么又要来台风了
而且为何是周末来 不是工作日来的台风就不是好台风😡

近日皮革
不小心把滨的小票扔了 愤怒（）

大后排cy!

从不断尝试到找到方向：我的秋招经历分享

本人计算机相关专业硕士，秋招同时尝试了互联网大厂、量化和国企几个方向，也都拿到了一些机会。
这篇不太想写成“标准秋招攻略”，更多还是想讲讲我自己这几年怎么一步一步试出来的。现在回头看，我最想分享的一点其实很简单：多去尝试，先找到自己舒服、也愿意长期过下去的生活方式，再去想到底该选什么工作。

一、我和量化的开始，其实挺偶然的

本科确定推免结果之后，我就开始找实习了。最开始其实还是想找互联网，当时对量化基本没什么概念。后来有一天在BOSS直聘上刷到一个量化实习，看到一天1500元左右的薪资，我一下就被吸引了。说得很现实一点，当时第一反应就是：这个钱好像够我攒毕业旅行经费了。
于是我开始认真去了解这个行业，补金融市场、统计、机器学习，也去看量化研究员到底每天在做什么。结果准备着准备着，我反而对这件事越来越上头。
我很喜欢量化的一点，是很多问题没有标准答案。你会不停地提出一个想法、找数据验证、发现不对、再改，再继续做。它既需要写代码，也需要做研究，还要真正去理解市场。这个过程我自己非常享受。
所以后来虽然起点只是“想赚点毕业旅行的钱”，但量化反而成了我研究生阶段投入精力最多的事情。研究生三年，我大部分时间都在做量化相关的学习和研究，也越来越确定：对投资的研究和钻研，对我来说确实可以是一件做很久、甚至做一辈子的事情。
我真心觉得，如果工作和自己的兴趣刚好能重合，是一件很幸运的事。至少对我来说，做自己真的感兴趣的东西，很多时候不会觉得是在“熬工作”，反而会很愿意一直往下钻。

二、暑期实习：十几次面试、7轮面试没拿到offer，也没什么

到了研究生后期，我也一直在尝试互联网方向。其实我是从3月份才开始正式投暑期互联网大厂实习的，现在回头看，这个时间已经有点晚了，而且当时准备得也不算充分。
那几个月我参加了十几次面试。最夸张的是BAT里的某一家，好几个个岗位前前后后面了7次，结果最后还是没拿到offer。这个事情当时确实挺打击人的，因为已经走到那么后面了，你会觉得“应该差不多了吧”，最后还是没过。
我一直到6月底才真正拿到一份暑期实习offer。后来我没有为了所谓的“暑期转正”再强行去补一段互联网暑期实习，而是直接参加互联网这边的秋招。
但最后秋招走完之后，我最大的感受反而是：有没有一段当年的互联网暑期实习，对最终结果没有想象中那么决定性。至少在我自己的经历里，只要之前有一两段比较solid的实习，真的做出过东西，面试的时候能把问题、方案、结果讲清楚，一样是有用的。
所以如果暑期没有找到特别理想的实习，我觉得真的没必要太焦虑。与其为了“简历上必须再多一段”到处补经历，不如把手里的事情做扎实一点。最好能有一两段比较垂直、产出也比较明确的工作，这种经历到秋招时其实更经得住追问。

三、我为什么一直愿意多试几个方向

我研究生阶段做过的事情其实挺杂的：在MSRA和Apple做过大模型相关工作，也在某百亿量化机构做过量化研究。看起来方向跨度挺大，但我自己并不觉得这是在“绕路”。
因为很多工作，你不真的进去做一段时间，很难只靠想象判断自己喜不喜欢。互联网、大模型、量化、国企，每个方向外面都有一套很成熟的叙事，但最后真正重要的还是：你每天具体在干什么，这种节奏你能不能接受，这种生活是不是你想要的。
所以我的秋招也没有只盯一个方向。我同时投了互联网大厂、量化，以及电网、运营商、银行这些国企方向。拿到不同选择以后，再去比较，反而更容易想清楚自己到底在意什么。
我现在比较认同的一种思路是：先别急着给自己贴标签。学生阶段能试就多试一点，试过之后再筛。你最后选的不一定是别人眼里“最好”的那个，但最好是你自己愿意长期过的那种生活。

四、国企方向：我自己的几个观察

国企这部分我主要投了电网、运营商和银行。下面只讲计算机方向，而且更多是我这一轮秋招里的个人体感，不一定适用于所有省份和所有年份。

1. 电网：户口 ≥ 学历 > 国奖、实习、论文等
   电网的计算机岗位其实非常少，大体可以分成地市供电公司里的信息通信/数字化岗位，以及省公司的直属单位。和互联网不同，这里面很多时候不是单纯看技术能力，而是会综合看户口、学历背景、学校层次以及其他经历。
   如果只说计算机方向，我自己的体感大概就是：户口因素 ≥ 学历 > 国奖、实习、论文等。提前批的门槛尤其高，很多地方基本要“双9”背景才比较容易进筛选范围。
   竞争也比很多人想象得夸张。某省甚至出现过150个左右清北计算机硕博一起参加提前批面试的情况。所以如果目标是省公司或者热门直属单位，我觉得一定要先看清楚岗位数量和竞争池，再评估自己的背景，不要只因为“电网稳定”就觉得它一定比互联网好进。
2. 运营商：笔试真的很重要
   运营商的计算机岗位相对多一些，但笔试非常重要。我的建议是，如果确定要投，最好提前1～2个月开始系统复习行测，不要等网申开了才临时抱佛脚。而且要想清楚一点，不同省份的运营商岗位具体做什么，差距非常大。一定要了解清楚，不要贸然做决定
3. 银行：计算机HC这几年确实在缩
   银行这边我一个很明显的感受就是，计算机HC在断崖式减少，特别是省级单位。有些省份省分行的信息科技岗位，可能只招0～1个计算机专业学生。这里我说的是省级单位，我自己没有投市级单位。
   所以如果把银行当成重要目标，第一是要早点看具体HC，不要只看机构名气；第二还是笔试。银行笔试的重要程度一点不低，我会建议至少提前3个月准备行测，尽量把基础题型先练到比较稳定。数量关系、言语理解、判断推理、资料分析这些都要提前做熟。运营商整体流程比较标准化，笔试成绩经常直接决定你后面有没有机会，所以这一块投入时间的性价比很高。

五、最后：别太早替自己决定人生

如果让我回头给刚开始找实习、找工作的自己一句建议，我大概会说：别太急着确定“我以后一定要干什么”。
我最开始只是因为在BOSS直聘上看到1500一天，才偶然去了解量化；后来因为真的喜欢，研究生几年反而把大量精力都放在了这件事上。互联网暑期实习一度让我很焦虑，连续面试很多次、7轮没拿到offer也很沮丧，但最后回头看，它也没有决定我的秋招结果。
很多当下觉得特别大的事情，拉长一点看其实都只是一次尝试。多试几个方向、多做一些真正有产出的事情，也多想想自己到底喜欢什么样的生活。等这些问题慢慢有答案之后，再去择业，我觉得会比一开始就追着“最热门”“最稳定”或者“最赚钱”跑舒服很多。

和十二年的闺蜜爆了，交情果然不能用时间长度来衡量。她总是在公开场合做一些让我眼前一黑的事，然后解释说我没有恶意是我想多了。如果是初中的时候，也就相信她了。但是二十岁的成年人了，不可能不知道什么场合该说什么话吧。
至于她带我认识的小团体成员，也不指望融入他们了。凡事还是要靠自己。

每个人都有闪光点
就像我也羡慕鱼老师读过很多书，会写文章！🥺

很有可能 所以基本没喝奶茶了

印象中如果在思源湖边留意一下 可能会看到白色里面掺杂一点棕色的（）

本帖用于统一记录和分享我收集到的在读或曾在读 JTU，且毕业于或从业于计算机相关专业或行业的学长学姐、师兄师姐分享的内容。

欢迎大家踊跃投稿或在帖子下直接分享。我这里支持匿名或署名，保护隐私。

我创建的校友群目前也已约 250+ 成员，欢迎校友加入，尤其是已毕业的师兄师姐、学长学姐。有意向者私聊我即可。

本帖将作为我唯一的分享和汇总处，因为微信群的内容保障实在难以恭维。

门里一些你或许会感兴趣的内容：
2023 年找工作个人 memo
说说计算机系本科生如何找实习
再开一个秋招记录贴
xjtu 计算机保研经验分享
距离秋招半年，该怎么准备呢
困顿且挣扎——我的 2025 秋招旅程
来自学长的毕设相关建议【计算机】
结束了本科最后一门考试后，你有什么想法？
Microsoft 人生体验随笔

If you like to befriend a friendly gate-friend, one way is to leave your blog here (by editing this post as long as you have reached trust level 1(青铜 (Bronze))). Below is some bootstrapping blogs aggregated from previous posts. You should put your blog's URL in angle brackets(< >) following the samples.

URL	Title	Your Handle @xjtu.app	Anything Else？
https://npu.moe	瓜大萌	Err(:nullptr)	瓜大人萌萌哒学习交流平台
https://axi404.top/	Axi404	@Forever	你好，我是阿汐，欢迎。
https://ilovebread.buzz/	主治医师李大华	@Lorange	何地才是樂土，讓競爭做指數
https://ciallo.cv/	JuniorTree	@Soyo34325	Ciallo~
https://bocheng.me/	Bocheng Zou	@uebian
https://bertsin.pages.dev/	Bertsin	@芙蓉湖第一树莓果	神秘小天地！

分享一些计算机专业的课程资料（课程作业，课程实验，部分往年题等），包括：计算机网络专题实验、编译器专题实验、嵌入式智能系统、软件定义网络、RUST语言程序设计、数据库系统、操作系统原理、软件工程、数字逻辑电路、形式语言与编译。

确实
在测试能否把用户名手动改成这个（）
可以改 但貌似也不会显示🤣

管理员辛苦了

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 (`$x^2$`). - **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.

07-04

昨天进的实验室，然后办了入校！云栖校区比我预期中的要小的很多很多，比起大学更像是一个小的研究所，来的第一天就有点绝望啊，因为周围真的好偏！感觉完全没啥玩的，下午入校找到工位之后就开始搬砖了，因为之前在线上的时候跟过一部分，周围比较好的是KFC和麦当劳都有！麦金卡续起来

今天到看房，和中介约好的，看的第一间房真的是惨不忍睹，原本是和实验室的同门合租，但是我发现那个房子有间屋子没有窗户，楼下是垃圾回收站，味道很大！但是短租真的超级难找，原本找到的一个梦中情房是上下楼的，下面是电视，然后上面是睡人的，但是人家不肯租，只能11个月签合同，后来找到个类似于酒店的那种公寓式的，价格贵了点，地方小了点，卫生还需要自己打扫一下，我想着要不要请一个阿姨来帮忙打扫一下，类似京东家居这种？

下午还到宜家！师兄说他来杭州1年了还不知道宜家在哪里！买了枕头、床单、空调被等等，感觉好幸福，正好还在住酒店，就把新买的床单借用酒店的洗衣机洗了一下，再烘干

已修复。我之前用Firefox没遇到过这个bug，用Chromium可以复现。

当前grid模式是为了更好地展示多张图片。目前当上传多张图片，或者多张图片连在一块时，会自动插入在两头插入

[grid mode ="tile"]
[ /grid]

，从而通过tile/slide展示多张图片。如果需要连续的布局，可以修改为[grid mode="off"]。

看来可以添加对mode="2x2"，mode="axb"这种允许用户自定义的参数的解析。（已实现）

已添加Quote/Copy Quote的功能。

这个只是和Discourse的行为不一样，我觉得当前的行为也能接受。

目前试验了一下，emoji-picker里自定义部分的图片都能正常加载。

目前登录.app或.men中的任一域名，登录状态都会被同步到另一个域名，所有功能全部相同，只是网络流量不过/过CDN的区别。
为了防止在不同的域名间切换，我們可能觉得有趣的内容 中的absolute URL已被手动改成了relative URL.

make post wiki 是个好功能，不过它依赖于：

• post revisions management，方便看到谁改了什么，以及回滚
• trust level system，当前把Discourse的等级迁移过来了，但是自动升级的机制比较复杂，还涉及到post read numbers / read time / login days 等的统计
• collaborative edit：类似于云文档多人同时协作编辑，可以用yjs. 否则如果两个人同时修改，容易产生冲突。

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

今天和朋友回高中看老师了
皮革记录

下载了一本关于Borgia家族历史的书（The Borgias: the hidden history） 主要是想看文艺复兴时期的权谋斗争（bushi）
没找到中文版于是只能看英文的 现在还停留在第一代Alonso Borgia的故事
这本书比较好的一点是它会有很详细的背景信息介绍 方便我理解

打算开始看《红猪》
《呼兰河传》看完了 接下来可能会看《生死场》 但目前还没开始
今天早上把《他改变了中国》剩下的一小部分读完了

今天开始看Rodrigo Borgia的故事 估计要看很久（）

高中的时候我们语文老师也推荐我们看这部电影，北野武老师真的好幽默 😆

抚顺战犯管理所旧址
看过好几次《末代皇帝》电影 也读过《我的前半生》和《溥杰自传》 一直都很想去这里看看
和电影里的场景看起来很像 好评

今天一直在下雨 尤其是下午考完后 遇上晚高峰还打不到车 对交大的杀意又一次达到顶峰

今天看了好久的鹅腿阿姨（变质鸭腿阿姨）的新闻
感觉好难以置信 之前好几年那么多人吃到发绿的鸭腿也都被糊弄过去了 但是在国贸那边居然没过一周就被举报了

前天晚上梦到查这学期考试的科目的成绩 被吓醒了
昨晚过了好久才睡着
应该是因为压力太大了 期末周坏 交大该杀

原先设置了spoiler的内容在这里似乎无法点开看到具体内容？望修复🥹
updt：抱歉我误会了！这个问题不存在

但是我刚刚发现同一个帖子有多个spoiler 内容不能同时显示 点开一个其他的就会隐藏？

以及 不知道本站是否支持选中其他发言的部分内容进行引用回复的功能（）

Issue tracking

进度栏，这个还真不太好实现，当前的远远没有Discourse完美

发现贴表情的时候 pig2的动图只能显示🐖的图案 但自己发帖可以正常显示

reactions: pig2 gif are not animated
the url hould be </uploads/image/a5/52/a552de2017382634e9bb9c81e663be3a8c3e4cca7a07c0a683cc44788464e62b.avif>
shows as an static pig emoji,
which is unlike wave_gif which the url is kept

群聊的文字配色或许可以优化一下… dark模式下别人发的文字有点难以辨认 light时自己发的文字看不清

improve basic topic moderation functionality
should allow mod and admin to edit any topic title, delete topic, close topic,

allow configure max number of posts in topic, auto close topic after reach this limit

https://meta.discourse.org/t/discourse-moderation-guide-part-2-managing-users/406265
https://meta.discourse.org/t/discourse-moderation-guide-part-3-managing-content/406266

new user cannot access the general chat, which should be available to all users. and also allow users to mute channels/chats.

use IndexedDB to cache content to prevent return-to-home-page lag

composer: Ctrl+X/C when nothing seletect should cut/copy whole line

reply-to and replied-by indicator in post

超出屏幕范围和图片无法上传问题已修复

换新ui了好怪，之前的一些图图也消失了

不过倒是蛮稳定了

最近在玩胶卷，在想 搭一个胶片的小app用于同好交流整理自己拍过的卷、ai调色、重构图、及一些胶片知识（？交流的部分可以类似于discourse
其实是我想学一下调色并且感觉自己的构图不够好，调色还需要积累构图也许未来会买点便宜的黑白卷多扫街练习！
并且我希望可以整合目前胶片爱好者所缺少的一些助手，比如我拍半格但扫描是两张扫在一起的需要手动裁成两张。比如拍胶卷最好的观看方式是按拍摄顺序排成一行因为有时间流逝的感觉。比如胶片后期调色有一定门槛，如果可以优化设置为一键调色会更方便。比如胶卷保存最好可以每卷都加一个地址、时间、拍摄的相关参数（ISO/快门速度/光圈大小等等）、这卷胶片的扫描机器以及每张的备注可以记录每张胶片背后的故事（每一次让我按下快门一定是有原因的）

我现在还只是一个想法，但似乎真的缺少针对胶片爱好者的圈子。大部分的讨论都在xhs，有一些这些零零散散的信息。是否有必要？会有多少用户？

反正我需要做一个网站交作业，做个demo正好。

玉米人是今年数院研一新生，最近几天涉及到自己制定培养方案的问题，比较迷茫。想在此咨询門友学长学姐们一些问题。🥺尤其是路过的数院与电信学部的学长学姐。🥹 当然也欢迎广大門友畅所欲言！（这是一个讨论帖）

一些比较宽泛的问题

1. 研究生是否应该选尽可能水的课（考核方式尽可能是“考察”），无论其是否与自己方向相关？

2. 今天在系统上，我注意到，有些课和本科期间专业课比较像（授课老师、大纲都差不多）。对于这种已经学过的、难度一般的、考核为考试的课，是否值得选？

3. 研究生期间的奖学金评比标准和本科差不多吗？还是智育和德育（论文、竞赛、社会实践等等）的加权吗？如果是加权的话，大致比例和下图一样吗？

4. 想拿学业奖学金的话，是否还需要卷绩点（我听说研究生阶段的成绩为优、良、中、合格、不合格）？在评定奖学金的时候，如果没有科研成果，是不是整个科研部分的得分就是 0？这是否意味着，如果没有小成果，就无法拿奖学金？😰（听说导师在研二下之前好像只允许投A会，不让投其他较水的会/刊）

想问数院学长学姐

下面是我准备圈定的培养计划之本院课程池子。
请问其中有哪些是课水分高的好课呢？其中有事多分低的烂课吗？请问其中有您上过的课吗？考核方式具体是什么呢？
如果您愿意告知，玉米人会不胜感激！🥰

课程名称	课程类型	学分	学时	学期/考核方式
非线性分析	必修课	3	64	秋季（考试）
凸分析与优化理论	必修课	3	48	春季（考试）
黎曼几何	必修课	3	64	春季（考试）
---	---	---	---	---
Stochastic Differential Equation with Application	选修课	2	32	秋季（考试）
Modern functional analysis	选修课	2	32	秋季（考试）
机器学习	选修课	2	32	秋上（考试）
计算方法	选修课	3	84	秋季（考试）
反散射简介	选修课	2	32	秋季（考查）
深度学习与人工智能	选修课	2	32	秋下（考查）
机器学习的数学理论及前沿进展选讲（AI进阶）	选修课	2	32	秋下（考查）
人工智能辅助科研写作的实践与应用（AI进阶）	选修课	1	16	秋上（考查）
运筹学方法	选修课	2	32	春上（考试）
文本分析与图像处理	选修课	2	40	春上（考试）
随机过程	选修课	2	32	春季（考试）
矩阵分析与矩阵计算	选修课	2	32	春上（考试）
大数据分析与处理方法	选修课	2	40	春上（考查）
机器学习的编程设计	选修课	2	32	春季（考查）
非参数统计推断	选修课	2	32	春季（考查）
生成式人工智能（AI实践）	选修课	2	32	春下（考查）

想问电信学部学长学姐

下面是我准备圈定的培养计划之跨院AI前沿课程池子。
请问其中有哪些是课水分高的好课呢？其中有事多分低的烂课吗？请问其中有您上过的课吗？考核方式具体是什么呢？
如果您愿意告知，玉米人会不胜感激！🥰

课程名称	课程类型	学分	学时	学期/考核方式
对抗性机器学习与人工智能安全（AI进阶）	选修课	2	32	秋下（考试）
大数据与深度学习及其应用（AI进阶）	选修课	2	32	春上（考试）
Artificial Intelligent Generative Content (AIGC) and image processing（AI进阶）	选修课	1	16	春上（考查）
大模型技术原理及应用（AI进阶）	选修课	2	32	春下（考查）
强化学习及其前沿（AI进阶）	选修课	2	32	春下（考查）

快读完了 感觉吉卜力的电影版更好看（虽然我平时一般原著和电影都是选择原著的）
原著的文笔个人感觉一般 然后吉卜力的电影版改编后情节更加流畅 而且有一些更优美的细节

想放点读书划线的内容 但都在电子书上懒得导出（）

在看菊次郎的夏天 里面的天使风铃的翅膀形状给我的第一反应竟是浙大求是鹰 瞬间出戏

今天看完了 很推荐这部电影（尤其是配乐很好听）

开始二刷安娜卡列宁娜 虽然不知道要看多久 在阅读包法利夫人之后二刷可能会有更深的感受🤔

接下来会外出旅游and皮革 可惜成绩还没出完 不安desu

旧的discourse论坛是没了吗 哀悼😭
这几天去辽宁游玩 皮革快乐（除了有次吃锅包肉被香菜偷袭）
去了西塔 堪比一只皮革的朝圣 看着满街的韩料真的很快乐 西塔韩百也很好逛 有在hk逛超市的感觉（虽然东西没那么多但也不少了）

西安这一周以来天天35°C+，即使中间有个晚上下了暴雨
没带伞的我在实验室被堵到4点钟

今天早上起来看到是高温红色预警，下午又来了暴雨大风黄色预警

东南沿海最近都在讨论台风
不知道门友所在地的天气如何？

西安市区依旧高于往年均值6°C左右

来自sjtu 但真诚地认为交大该杀
（目前主要是在这里发闲言碎语了 而且人少了几乎是单机模式）

爱来自刚从xjtu毕业的fudan新生😋

挑着看看指定的精华帖。这部分还是比danxi好的

rt。想问问这个上面XJTU和SJTU的uu们都有吗？
祝愉快！

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

昨晚本来想找浮士德的纸质书进行一个二刷的尝试 但发现了高一时购买的法国文明史 遂开始阅读 虽然目前还没走出中世纪的内容🤣
今天也在继续阅读包法利夫人 但还是会时不时想起牛虻的结局 真的太痛了😭

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！