import { randomBytes } from "node:crypto" import { createFlowchartRequestSchema, type CreateFlowchartResponse, type FlowchartCurrent, type FlowchartDetail, type FlowchartList, type FlowchartListItem, type FlowchartStatistics, type FlowchartSubmission, } from "@oj2/contract" import { and, asc, count, desc, eq, inArray, isNull, sql, type SQL } from "drizzle-orm" import { Hono } from "hono" import { requireAuth, requireTeacher, type AppEnv } from "../auth/middleware" import { config } from "../config" import { db, schema } from "../db" import { failure, success } from "../http" import { flowchartQueue } from "../queue" import { getBooleanOption } from "../services/options" import { consumeToken } from "../services/throttling" import { buildWordFrequencies } from "../services/word-frequency" import { todayStart } from "../time" import { isAdminRole, matchedUsers, objectValue, queryInteger, rounded, stripClassPrefix, } from "./helpers" export const flowchartRoutes = new Hono() // AI 评分单独一个限流桶,与代码提交的 `throttling:user:` 分开计数 function flowchartThrottleKey(userId: number) { return `flowchart:${userId}` } function canView(user: import("../auth/session").AuthUser, row: { userId: number }, problem: { createdById: number }) { return row.userId === user.id || isAdminRole(user) || problem.createdById === user.id } function flowchartData( flowchart: typeof schema.flowchartSubmission.$inferSelect, username: string, ) { return { id: flowchart.id, username, problemId: flowchart.problemId, mermaidCode: flowchart.mermaidCode, flowchartData: objectValue(flowchart.flowchartData), status: flowchart.status, createTime: flowchart.createTime, aiScore: flowchart.aiScore, aiGrade: flowchart.aiGrade, aiFeedback: flowchart.aiFeedback, aiSuggestions: flowchart.aiSuggestions, aiCriteriaDetails: objectValue(flowchart.aiCriteriaDetails), aiProvider: flowchart.aiProvider, aiModel: flowchart.aiModel, processingTime: flowchart.processingTime, evaluationTime: flowchart.evaluationTime, } satisfies FlowchartSubmission } flowchartRoutes.post("/flowcharts", requireAuth, async (c) => { const parsed = createFlowchartRequestSchema.safeParse(await c.req.json().catch(() => null)) if (!parsed.success || JSON.stringify(parsed.data?.flowchartData ?? {}).length > 500 * 1024) { return failure(c, 400, "invalid-request", parsed.error?.issues[0]?.message ?? "Flowchart data is too large") } const [problem] = await db.select({ id: schema.problem.id, allow: schema.problem.allowFlowchart }).from(schema.problem) .where(eq(schema.problem.id, parsed.data.problemId)).limit(1) if (!problem) return failure(c, 404, "problem-not-found", "Problem does not exist") if (!problem.allow) return failure(c, 400, "flowchart-not-allowed", "This problem does not allow flowchart submission") // 限流:每次提交都会触发一次外部 AI 调用,是和判题沙箱同级的有限资源。 // 身份前缀单独开一个桶,**不能**直接用 user id —— 那是代码提交在用的桶, // 共用的话学生在机房连着交几次代码,流程图这边就会莫名其妙交不上去。 const throttle = await consumeToken("user", flowchartThrottleKey(c.get("user")!.id)) if (!throttle.allowed) { return failure(c, 429, "too-many-submissions", `Please wait ${Math.floor(throttle.wait)} seconds`) } const id = randomBytes(16).toString("hex") await db.insert(schema.flowchartSubmission).values({ id, userId: c.get("user")!.id, problemId: problem.id, mermaidCode: parsed.data.mermaidCode, flowchartData: parsed.data.flowchartData, status: 0, createTime: new Date().toISOString(), aiScore: null, aiGrade: null, aiFeedback: null, aiSuggestions: null, aiCriteriaDetails: {}, aiProvider: "deepseek", aiModel: config.aiModel, processingTime: null, evaluationTime: null, }) try { await flowchartQueue.add("evaluate", { submissionId: id }, { jobId: id }) } catch (error) { await db.update(schema.flowchartSubmission).set({ status: 3 }).where(eq(schema.flowchartSubmission.id, id)) return failure(c, 502, "queue-unavailable", "Evaluation queue is unavailable") } return success(c, { submissionId: id, status: "pending" } satisfies CreateFlowchartResponse, 201) }) /** * 题号 / 用户名筛选一律先解析成 `flowchart_submission` 自己的列,不靠 join 之后比 * `problem._id` / `user.username`。同一套做法见 submission.ts 的 * problemFilter / usernameFilter,这里是两个好处: * * - 列表的 count 因此**一个 join 都不用挂**。挂了就回不到最小索引上的 index-only * scan,而这张表每行带 3KB 的 flowchart_data + 1.2KB 的 mermaid_code,堆页密度低, * 回表比 submission 那边贵。 * - 筛条件落在驱动表上,规划器能走 flowchart_user_time_idx / flowchart_problem_time_idx, * 不必顺着时间索引倒扫再逐行 join 过滤。 * * 查无此题 / 此人时留**恒假**条件 —— 少推一个 filter 就成了「不筛」, * 「查无此班」会变成「全站」。 */ async function flowchartProblemFilter(displayId: string) { const problems = await db .select({ id: schema.problem.id }) .from(schema.problem) .where(and( sql`lower(${schema.problem.displayId}) = lower(${displayId})`, // 流程图题都是公开题(快照里那 12 道 contest_id 全为空), // 比赛题的 _id 撞号是常态,不该被筛进来 isNull(schema.problem.contestId), )) return problems.length ? inArray(schema.flowchartSubmission.problemId, problems.map((row) => row.id)) : sql`false` } async function flowchartUserFilter(username: string) { const ids = (await matchedUsers(username)).map((row) => row.id) return ids.length ? inArray(schema.flowchartSubmission.userId, ids) : sql`false` } /** * 列表只取这几列。原来是 `select({ flowchart: 整行, problem: 整行 })`,把 * mermaid_code、flowchart_data、ai_feedback、ai_suggestions、ai_criteria_details * 和**整张题目表**(description / 标准答案 / 标准流程图…)一起拉回来,而响应一个 * 都用不到:生产快照实测流程图行均 4.9KB(p90 6.9KB)、题目行均 2.2KB,默认 10 行 * 一页白拉 ~70KB,limit=250 时 1.7MB。 * * 对齐 submission.ts 的 submissionListColumns —— 那边同样是手写白名单, * 刻意不取 code / info。 */ const flowchartListColumns = { flowchart: { id: schema.flowchartSubmission.id, // showLink 判定要,序列化本身用不到 userId: schema.flowchartSubmission.userId, status: schema.flowchartSubmission.status, createTime: schema.flowchartSubmission.createTime, aiScore: schema.flowchartSubmission.aiScore, aiGrade: schema.flowchartSubmission.aiGrade, aiProvider: schema.flowchartSubmission.aiProvider, aiModel: schema.flowchartSubmission.aiModel, processingTime: schema.flowchartSubmission.processingTime, evaluationTime: schema.flowchartSubmission.evaluationTime, }, username: schema.user.username, problem: { displayId: schema.problem.displayId, title: schema.problem.title, // 同上,canView 要 createdById: schema.problem.createdById, }, } flowchartRoutes.get("/flowcharts", requireAuth, async (c) => { const user = c.get("user")! const limit = queryInteger(c.req.query("limit"), 10, { min: 1, max: 250 }) const offset = queryInteger(c.req.query("offset"), 0, { min: 0 }) const displayId = c.req.query("problemId")?.trim() const username = c.req.query("username")?.trim() const grade = c.req.query("grade") // 与代码提交列表同一套口径(submission.ts 的 GET /submissions):关掉 // submission_list_show_all 时非管理员看不到列表。流程图这边一直漏了这道门, // 学生把语言切成「流程图」、用户名随便填一个字就能翻出全班的 AI 评分。 if (!(await getBooleanOption("submission_list_show_all", true)) && !isAdminRole(user)) { return success(c, { results: [], total: 0 } satisfies FlowchartList) } // 「只看自己」盖过用户名;普通学生不填用户名时也只看自己 const onlyMyself = c.req.query("myself") === "1" || (!username && user.adminType === "Regular User") const filters: Array = [] filters.push(...await Promise.all([ displayId ? flowchartProblemFilter(displayId) : undefined, !onlyMyself && username ? flowchartUserFilter(username) : undefined, ])) if (onlyMyself) filters.push(eq(schema.flowchartSubmission.userId, user.id)) if (c.req.query("today") === "1") filters.push(sql`${schema.flowchartSubmission.createTime} >= ${todayStart()}`) if (["S", "A", "B", "C"].includes(grade ?? "")) filters.push(eq(schema.flowchartSubmission.aiGrade, grade!)) const where = and(...filters) const [totalRows, rows] = await Promise.all([ // 筛条件已经全落在 flowchart_submission 自己的列上,count 不挂任何 join db.select({ value: count() }).from(schema.flowchartSubmission).where(where), db.select(flowchartListColumns) .from(schema.flowchartSubmission) .innerJoin(schema.user, eq(schema.flowchartSubmission.userId, schema.user.id)) .innerJoin(schema.problem, eq(schema.flowchartSubmission.problemId, schema.problem.id)) .where(where) .orderBy(desc(schema.flowchartSubmission.createTime)).limit(limit).offset(offset), ]) return success(c, { results: rows.map(({ flowchart, username, problem }) => ({ id: flowchart.id, username, problem: problem.displayId, problemTitle: problem.title, status: flowchart.status, createTime: flowchart.createTime, aiScore: flowchart.aiScore, aiGrade: flowchart.aiGrade, aiProvider: flowchart.aiProvider, aiModel: flowchart.aiModel, processingTime: flowchart.processingTime, evaluationTime: flowchart.evaluationTime, showLink: canView(user, flowchart, problem), } satisfies FlowchartListItem)), total: totalRows[0]?.value ?? 0, } satisfies FlowchartList) }) const FLOWCHART_COMPLETED = 2 /** * 词云取的提交条数上限,同时也是分词的文本条数上限。 * * 数值统计(总数、均分、等级分布、各项平均分、完成人数)按整个时间窗**精确**计算, * 但那几项现在全是 SQL 聚合,代价不随窗口里的行数走。**不能采样** —— 采了之后老师 * 看到的完成率和均分就是错的,而且从界面上看不出来。 * * 会随数据量线性变重的只剩词云:每条 feedback / suggestions / comment 都要走一遍 * jieba,而前端的「全部时段」是不带 start 的(FlowchartStatisticsPanel.vue 那个 * `duration === "all"`),攒一学年就得把所有评语重新 cut 一遍。词云是辅助性的, * 看的是高频问题,取最近这些条足够。 * * 这里**同时**卡了两道:SQL 侧 `order by create_time desc limit N` 只取最近 N 条提交, * JS 侧 pushText 再卡 N 条文本。生产快照实测一条提交出 5.97 段文本(几项 comment + * feedback + suggestions,最少的一条也有 1 段),所以先到的一直是文本那道闸——3000 段 * 在 500 条出头就满了,行数那道只是兜底:真遇到一批评语全空的提交,词云少看几条, * 可以接受。原来只有 JS 那道,行早就整批拉回内存了。 */ const WORDCLOUD_TEXT_LIMIT = 3000 flowchartRoutes.get("/flowcharts/statistics", requireTeacher, async (c) => { const end = c.req.query("end")?.trim() if (!end) return failure(c, 400, "invalid-request", "end is required") const start = c.req.query("start")?.trim() const filters: Array = [ eq(schema.flowchartSubmission.status, FLOWCHART_COMPLETED), sql`${schema.flowchartSubmission.createTime} <= ${end}`, ] if (start) filters.push(sql`${schema.flowchartSubmission.createTime} >= ${start}`) const displayId = c.req.query("problemId")?.trim() if (displayId) { const [problem] = await db .select({ id: schema.problem.id }) .from(schema.problem) .where(and( sql`lower(${schema.problem.displayId}) = lower(${displayId})`, isNull(schema.problem.contestId), eq(schema.problem.visible, true), )) .limit(1) if (!problem) return failure(c, 404, "problem-not-found", "Problem does not exist") filters.push(eq(schema.flowchartSubmission.problemId, problem.id)) } const username = c.req.query("username")?.trim() // 用户名先解析成账号,再拿 user_id 去筛 —— 理由同代码提交的统计接口 // (submission.ts 的 GET /submissions/statistics),顺带让下面这几条一个 join 都不用挂 const matched = username ? await matchedUsers(username) : [] if (username) { const ids = matched.map((row) => row.id) // 一个账号都没匹配上时得留个恒假条件,否则「查无此班」变成「全站统计」 filters.push(ids.length ? inArray(schema.flowchartSubmission.userId, ids) : sql`false`) } const where = and(...filters) // 花名册:只有指定了用户名才谈得上「班级人数」,不指定时分母无意义。 // 未禁用的普通用户才进分母,教师和管理员不算 const roster = username ? matched.filter((row) => !row.isDisabled && row.adminType === "Regular User") : [] /** * 五条查询,每条的代价都和窗口里的行数脱钩(词云那条卡了 limit)。 * * 原来是**一条**不带 limit 的 `select(username, score, grade, criteria, feedback, * suggestions) order by create_time desc`,把整个时间窗的行拉进内存再用 JS 算 —— * 词云的 3000 条上限是在 JS 里截的,行早就全回来了。备份实测每行的 AI 文本约 366B * (criteria 255 + suggestions 64 + feedback 47),现在 2134 条无感,5 万条就是一次 * 点击 18MB,而老师是开着面板反复切时段、切班的。 */ const [[totals], gradeRows, criteriaRows, textRows, submittedRows] = await Promise.all([ db .select({ total: count(), /** * 均分拆成 sum / count 两项,不直接用 `avg()`:分母是**有分数的条数**而不是 * 总条数(对齐 Django 的 Avg(),它跳过 NULL),拆开之后这个口径在代码里是 * 写明的,也省掉 avg() 在空集上回 NULL 还要兜底。 */ scoreSum: sql`coalesce(sum(${schema.flowchartSubmission.aiScore}), 0)`.mapWith(Number), scoreCount: sql`count(${schema.flowchartSubmission.aiScore})::int`.mapWith(Number), // 完成人数。user_id 和 username 一一对应,按哪个 distinct 都一样, // 按 user_id 就不必 join user completedCount: sql`count(distinct ${schema.flowchartSubmission.userId})::int`.mapWith(Number), }) .from(schema.flowchartSubmission) .where(where), db .select({ grade: schema.flowchartSubmission.aiGrade, n: count() }) .from(schema.flowchartSubmission) .where(where) .groupBy(schema.flowchartSubmission.aiGrade), /** * 各项**平均分**。`ai_criteria_details` 是 `{ 项名: { score, max, comment } }`, * 用 jsonb_each 展开之后按项名分组。分数不是数字的项整项跳过,和原来 JS 那句 * `typeof detail.score !== "number"` 的 continue 一致。 * * **那道 `jsonb_typeof(...) = 'object'` 的闸不能省,而且要写在 jsonb_each 的参数里。** * 不能省:撞上标量(历史脏数据)jsonb_each 直接抛错,整个面板 500 —— * 拿 `'5'::jsonb` 和 `'[1,2]'::jsonb` 各插一行验过。 * * 写在哪儿则纯是规划器的脸色:挪进 where 当基表过滤条件时,53350 行的探针上 * 实测 180ms → 360ms,因为计划从「并行 Partial HashAggregate」换成了「串行 * GroupAggregate + 21 万行外部归并排序、落盘 26MB」。两种写法都正确,选快的那个。 * * 每项的**满分**不在这里取,见下面 criteriaMax 的注释:在这条 SQL 里按 * create_time 取「最新那条」要给 21 万行(4 项 × 5 万条)排序,同一个探针上 * 实测 254ms → 842ms,而满分本来就是几个常数。 */ db.execute<{ key: string; avg: number }>(sql` select e.key as key, avg((e.value->>'score')::double precision) as avg from ${schema.flowchartSubmission} cross join lateral jsonb_each( case when jsonb_typeof(${schema.flowchartSubmission.aiCriteriaDetails}) = 'object' then ${schema.flowchartSubmission.aiCriteriaDetails} else '{}'::jsonb end ) e where ${where} and jsonb_typeof(e.value->'score') = 'number' group by e.key `), // 词云的原料。只有这条要读大列,所以只有它按时间倒序取最近的 N 条 db .select({ criteria: schema.flowchartSubmission.aiCriteriaDetails, feedback: schema.flowchartSubmission.aiFeedback, suggestions: schema.flowchartSubmission.aiSuggestions, }) .from(schema.flowchartSubmission) .where(where) .orderBy(desc(schema.flowchartSubmission.createTime)) .limit(WORDCLOUD_TEXT_LIMIT), // 「谁没做」只在有花名册时算得出来,行数也就一个班 roster.length ? db .selectDistinct({ userId: schema.flowchartSubmission.userId }) .from(schema.flowchartSubmission) .where(where) : [], ]) if (!totals || totals.total === 0) { return success(c, { totalCount: 0, avgScore: 0, gradeDistribution: {}, criteriaAverages: {}, personCount: roster.length, completedCount: 0, wordFrequencies: [], // 一条提交都没有时,花名册上的人**全都**是「没做」—— 原来这里写死空数组, // 于是一节课刚开始、最该点名的时候,教师面板反而一个名字都不给 dataUnaccepted: roster.map((row) => ({ username: row.username, realName: stripClassPrefix(row.username, row.className), })), } satisfies FlowchartStatistics) } const gradeDistribution: Record = {} for (const row of gradeRows) { // 旧后端用 values_list("ai_grade") 分组,null 也会成为一个桶;这里保持同样的口径。 // null 和空串会分成两组,合并到同一个桶里 const grade = row.grade ?? "" gradeDistribution[grade] = (gradeDistribution[grade] ?? 0) + row.n } /** * 词云原料和每项满分都从同一批行里取 —— 这批行本来就要读(见下面的 textRows), * 白嫖一遍,不额外查库。 * * 满分的口径是「按 create_time 倒序,某项**第一次**出现时写的那个 max,不是数字就 * 退回 100」,和原来逐行遍历时那句 `if (bucket) ... else set(max)` 完全一致,只是 * 遍历范围从整个时间窗收成最近 WORDCLOUD_TEXT_LIMIT 条。满分是评分标准里的常数 * (完整性 30、逻辑正确性 40…),几万条里换一次都算多;真出现一项**只**在更早的 * 行里有过,它的平均分照常出(那是 SQL 全窗口算的),满分退回 100。 */ const criteriaMax = new Map() const texts: string[] = [] const pushText = (value: string) => { if (texts.length < WORDCLOUD_TEXT_LIMIT) texts.push(value) } for (const row of textRows) { for (const [key, value] of Object.entries(objectValue(row.criteria))) { const detail = objectValue(value) // 和上面那条聚合同一道闸:分数不是数字的项当没配过,满分和评语也都不收 if (typeof detail.score !== "number") continue if (!criteriaMax.has(key)) { criteriaMax.set(key, typeof detail.max === "number" ? detail.max : 100) } if (typeof detail.comment === "string" && detail.comment) pushText(detail.comment) } if (row.feedback) pushText(row.feedback) if (row.suggestions) pushText(row.suggestions) } const criteriaAverages: Record = {} for (const row of criteriaRows) { criteriaAverages[row.key] = { avg: rounded(row.avg, 1), max: criteriaMax.get(row.key) ?? 100 } } const submitted = new Set(submittedRows.map((row) => row.userId)) return success(c, { totalCount: totals.total, avgScore: totals.scoreCount ? rounded(totals.scoreSum / totals.scoreCount, 1) : 0, gradeDistribution, criteriaAverages, personCount: roster.length, completedCount: totals.completedCount, wordFrequencies: await buildWordFrequencies(texts), dataUnaccepted: roster .filter((row) => !submitted.has(row.id)) .map((row) => ({ username: row.username, realName: stripClassPrefix(row.username, row.className), })), } satisfies FlowchartStatistics) }) flowchartRoutes.get("/flowcharts/:id", requireAuth, async (c) => { const [row] = await db.select({ flowchart: schema.flowchartSubmission, username: schema.user.username, problem: schema.problem }) .from(schema.flowchartSubmission).innerJoin(schema.user, eq(schema.flowchartSubmission.userId, schema.user.id)) .innerJoin(schema.problem, eq(schema.flowchartSubmission.problemId, schema.problem.id)) .where(eq(schema.flowchartSubmission.id, c.req.param("id"))).limit(1) if (!row || !canView(c.get("user")!, row.flowchart, row.problem)) return failure(c, 404, "flowchart-not-found", "Submission does not exist") return success(c, flowchartData(row.flowchart, row.username)) }) flowchartRoutes.post("/flowcharts/:id/retry", requireAuth, async (c) => { const user = c.get("user")! const [row] = await db.select({ flowchart: schema.flowchartSubmission, problem: schema.problem }).from(schema.flowchartSubmission) .innerJoin(schema.problem, eq(schema.flowchartSubmission.problemId, schema.problem.id)) .where(eq(schema.flowchartSubmission.id, c.req.param("id"))).limit(1) if (!row || !canView(user, row.flowchart, row.problem)) return failure(c, 404, "flowchart-not-found", "Submission does not exist") if (![2, 3].includes(row.flowchart.status)) return failure(c, 409, "retry-not-allowed", "Submission is not in a state that allows retry") // canView 允许本人重试自己的提交,不限流的话学生可以反复点着刷 AI 调用。 // 教师放行:重新判题是他们的日常操作,成批点几十行是正常用法 if (!isAdminRole(user)) { const throttle = await consumeToken("user", flowchartThrottleKey(user.id)) if (!throttle.allowed) { return failure(c, 429, "too-many-submissions", `Please wait ${Math.floor(throttle.wait)} seconds`) } } await db.update(schema.flowchartSubmission).set({ status: 0, aiScore: null, aiGrade: null, aiFeedback: null, aiSuggestions: null, aiCriteriaDetails: {}, processingTime: null, evaluationTime: null, }).where(eq(schema.flowchartSubmission.id, row.flowchart.id)) try { // jobId 必须**正好三段**:bullmq 对含 `:` 的自定义 id 有一条兼容老的可重复 // 任务的校验(job.js 的 `split(':').length !== 3`),两段会直接抛 // `Custom Id cannot contain :`。原来写的是 `${id}:${时间戳}`,于是这个接口 // 从来没成功过 —— 而清空评分在入队之前,每点一次就把原来的分数永久清掉、 // 提交卡在 PENDING 且没有任何任务会来救它。 await flowchartQueue.add( "evaluate", { submissionId: row.flowchart.id }, { jobId: `${row.flowchart.id}:retry:${Date.now()}` }, ) } catch (error) { // 入队失败就落 FAILED,别把提交丢在 PENDING 上 —— 和 POST /flowcharts 同一处理 await db.update(schema.flowchartSubmission).set({ status: 3 }).where(eq(schema.flowchartSubmission.id, row.flowchart.id)) return failure(c, 502, "queue-unavailable", "Evaluation queue is unavailable") } return success(c, { submissionId: row.flowchart.id, status: "pending" } satisfies CreateFlowchartResponse) }) flowchartRoutes.get("/problems/:id/flowchart/current", requireAuth, async (c) => { const problemId = queryInteger(c.req.param("id"), 0, { min: 1 }) const rows = await db.select({ score: schema.flowchartSubmission.aiScore, grade: schema.flowchartSubmission.aiGrade }) .from(schema.flowchartSubmission).where(and(eq(schema.flowchartSubmission.userId, c.get("user")!.id), eq(schema.flowchartSubmission.problemId, problemId), eq(schema.flowchartSubmission.status, 2))) .orderBy(desc(schema.flowchartSubmission.createTime)) return success(c, { count: rows.length, score: rows[0]?.score ?? 0, grade: rows[0]?.grade ?? "" } satisfies FlowchartCurrent) }) flowchartRoutes.get("/problems/:id/flowchart/history", requireAuth, async (c) => { const problemId = queryInteger(c.req.param("id"), 0, { min: 1 }) const page = queryInteger(c.req.query("page"), 0, { min: 0 }) const rows = await db.select({ flowchart: schema.flowchartSubmission, username: schema.user.username }) .from(schema.flowchartSubmission).innerJoin(schema.user, eq(schema.flowchartSubmission.userId, schema.user.id)) .where(and(eq(schema.flowchartSubmission.userId, c.get("user")!.id), eq(schema.flowchartSubmission.problemId, problemId), eq(schema.flowchartSubmission.status, 2))) .orderBy(asc(schema.flowchartSubmission.createTime)) const selected = page === 0 ? rows.at(-1) : rows[page - 1] if (page > rows.length) return failure(c, 400, "page-out-of-range", "Page out of range") return success(c, { submission: selected ? flowchartData(selected.flowchart, selected.username) : null, count: rows.length } satisfies FlowchartDetail) })