refactor: 后端从 Django 换成 Bun + SQLite
Django 多个 worker 内存占用 1-2 GB，换成 Bun 单进程后约 25 MB， 同时去掉 Postgres 和 Redis，只剩 Caddy + Bun 两个容器。 - server/：Hono + bun:sqlite + Bun 原生 WebSocket，接口与原 django-ninja 保持兼容；表结构、时间/UUID 存储格式、密码哈希与 Django 一致，旧数据可直接使用 - 评分加权、贝叶斯平滑、成绩册的计算结果与原实现逐位一致（复刻 Python round/sum） - scripts/：Postgres → SQLite 迁移、新建超管、提示词层级标注、重算分数 - 前端：Django Admin 去掉后，用户新建/修改改为页面内弹窗； 非超管的挑战公开按钮置灰 - 权限不足返回 JSON 403（原来是重定向到不存在的登录页） - docker-compose / Caddyfile / dev.sh / CLAUDE.md 更新，删除 AGENTS.md - 服务器切换步骤见 docs/migrate-to-bun.md Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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import { config } from "../config"
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export const SYSTEM_PROMPT = `你是一个网页生成助手。根据用户的需求描述，生成网页代码。
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规则：
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1. 使用一个 \`\`\`html 代码块返回所有代码
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2. HTML 代码只需要 body 内的内容，不需要完整的 HTML 文档结构
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3. CSS 样式写在 <style> 标签内，JavaScript 写在 <script> 标签内，都放在代码块里
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4. 用中文回复，先简要说明你做了什么，然后给出代码
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5. 在已有代码基础上修改时，返回完整的修改后代码，不要只返回片段
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6. 由于任何外部链接都被屏蔽，使用纯 HTML、CSS 和 JS 实现功能，不要依赖外部库
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输出格式示例（必须严格遵守，只用一个代码块）：
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好的，我为你创建了一个点击按钮变色的示例。
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\`\`\`html
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<style>
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button { padding: 8px 16px; }
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</style>
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<button id="btn">点击我</button>
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<script>
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document.getElementById('btn').onclick = function() {
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this.style.background = 'red';
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};
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</script>
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\`\`\``
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export const GUIDANCE_SYSTEM_PROMPT = `你是一个提示词写作教练，帮助学生写出清晰、具体的网页需求描述。
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判断标准——满足以下条件视为"够好"：
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- 有明确主题（例如：登录页、计时器、商品卡片列表）
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- 至少包含以下一项具体描述：颜色/布局/风格、交互行为（按钮点击、动画等）、页面内容（文字、数量、图标）
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判断为"不够好"的典型情况：
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- 目标太泛，如"做一个好看的页面"
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- 只有主题，完全没有任何视觉、交互或内容描述
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规则：
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1. 如果提示词不够好，用 1-2 个启发性问题引导学生补充细节，不要直接给出答案
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2. 如果提示词已经够好，以 [READY] 开头回复，简短夸奖学生并说明可以生成了
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3. 用中文回复，语气鼓励，简洁明了
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4. 使用 Markdown 语法高亮关键词，优先突出 **主题**、**视觉**、**交互**、**内容**、**可以生成** 等重点
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5. 如果回复以 [READY] 开头，[READY] 不要加粗，必须保持原始文本
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6. 不要生成任何代码`
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const DEFAULT_MODEL = "deepseek-v4-flash"
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const MODEL_ALIASES: Record<string, string> = {
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"deepseek-v4-flash-thinking": DEFAULT_MODEL,
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}
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const NON_THINKING_MODELS = new Set(["deepseek-v4-flash"])
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// 走火山方舟（ARK）接口的模型
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const ARK_MODELS = new Set(["doubao-seed-2-0-lite-260215"])
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export interface ChatMessage {
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role: "system" | "user" | "assistant"
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content: string
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}
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interface CompletionOptions {
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model?: string
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stream: boolean
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maxTokens?: number
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signal?: AbortSignal
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timeoutMs?: number
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}
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export const llmConfigured = () => !!config.llmApiKey
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function buildRequest(messages: ChatMessage[], opts: CompletionOptions) {
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const requested = opts.model || DEFAULT_MODEL
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const resolved = MODEL_ALIASES[requested] ?? requested
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const ark = ARK_MODELS.has(resolved)
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const body: Record<string, unknown> = {
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model: resolved,
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messages,
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stream: opts.stream,
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}
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if (opts.maxTokens) body.max_tokens = opts.maxTokens
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if (NON_THINKING_MODELS.has(resolved) && !(requested in MODEL_ALIASES)) {
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body.thinking = { type: "disabled" }
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}
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const apiKey = ark ? config.arkApiKey : config.llmApiKey
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if (!apiKey) throw new Error("未配置模型接口密钥")
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const baseUrl = (ark ? config.arkBaseUrl : config.llmBaseUrl).replace(/\/$/, "")
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const signals = [AbortSignal.timeout(opts.timeoutMs ?? 120_000)]
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if (opts.signal) signals.push(opts.signal)
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return fetch(`${baseUrl}/chat/completions`, {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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Authorization: `Bearer ${apiKey}`,
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},
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body: JSON.stringify(body),
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signal: AbortSignal.any(signals),
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})
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}
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async function ensureOk(res: Response) {
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if (res.ok) return
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const text = await res.text().catch(() => "")
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throw new Error(`Error code: ${res.status} - ${text.slice(0, 500)}`)
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}
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// 读取 OpenAI 兼容接口的 SSE 流，逐段产出文本
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async function* streamCompletion(
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messages: ChatMessage[],
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model?: string,
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signal?: AbortSignal,
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): AsyncGenerator<string> {
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const res = await buildRequest(messages, { model, stream: true, signal })
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await ensureOk(res)
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if (!res.body) return
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const decoder = new TextDecoder()
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let buffer = ""
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for await (const chunk of res.body) {
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buffer += decoder.decode(chunk, { stream: true })
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let idx: number
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while ((idx = buffer.indexOf("\n")) >= 0) {
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const line = buffer.slice(0, idx).trim()
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buffer = buffer.slice(idx + 1)
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if (!line.startsWith("data:")) continue
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const data = line.slice(5).trim()
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if (data === "[DONE]") return
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const json = JSON.parse(data)
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if (json.error) throw new Error(json.error.message ?? JSON.stringify(json.error))
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const content = json.choices?.[0]?.delta?.content
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if (content) yield content
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}
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}
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}
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export function streamChat(history: ChatMessage[], model?: string, signal?: AbortSignal) {
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return streamCompletion([{ role: "system", content: SYSTEM_PROMPT }, ...history], model, signal)
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}
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export function streamGuidance(history: ChatMessage[], signal?: AbortSignal) {
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return streamCompletion(
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[{ role: "system", content: GUIDANCE_SYSTEM_PROMPT }, ...history],
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undefined,
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signal,
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)
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}
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export async function complete(
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messages: ChatMessage[],
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opts: { model?: string; maxTokens?: number; timeoutMs?: number } = {},
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): Promise<string> {
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const res = await buildRequest(messages, {
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model: opts.model ?? config.llmModel,
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stream: false,
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maxTokens: opts.maxTokens,
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timeoutMs: opts.timeoutMs,
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})
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await ensureOk(res)
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const json: any = await res.json()
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return json.choices?.[0]?.message?.content ?? ""
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}
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export interface ExtractedCode {
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html: string | null
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css: string | null
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js: string | null
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}
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// 从 AI 回复中提取代码：支持单个 html 代码块（新）或分开的 html/css/js 代码块（旧）
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export function extractCode(text: string): ExtractedCode {
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const result: ExtractedCode = { html: null, css: null, js: null }
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const pattern = /```(html|css|js|javascript|typescript|ts|jsx|tsx)\s*\n([\s\S]*?)```/gi
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for (const [, rawLang, code] of text.matchAll(pattern)) {
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let lang = rawLang!.toLowerCase()
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if (["javascript", "typescript", "ts", "jsx", "tsx"].includes(lang)) lang = "js"
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const key = lang as keyof ExtractedCode
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if (key in result && result[key] === null) result[key] = code!.trim()
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}
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// 单个 HTML 代码块：把 <style>/<script> 的内容拆出来，并从 html 中去掉
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if (result.html && result.css === null && result.js === null) {
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let html = result.html
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const style = /<style[^>]*>([\s\S]*?)<\/style>/i.exec(html)
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if (style) {
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result.css = style[1]!.trim()
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html = html.replace(/<style[^>]*>[\s\S]*?<\/style>/gi, "")
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}
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const script = /<script[^>]*>([\s\S]*?)<\/script>/i.exec(html)
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if (script) {
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result.js = script[1]!.trim()
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html = html.replace(/<script[^>]*>[\s\S]*?<\/script>/gi, "")
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}
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result.html = html.trim()
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}
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return result
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}
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export function parseGuidanceResponse(full: string): [string, boolean] {
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if (full.startsWith("[READY]")) {
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return [full.slice("[READY]".length).replace(/^\n+/, ""), true]
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}
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return [full, false]
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}
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