114 lines
3.7 KiB
TypeScript
114 lines
3.7 KiB
TypeScript
/**
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* Quiz Grading API
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*
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* POST: Receives a text question + user answer, calls LLM for scoring and feedback.
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* Used for short-answer (text) questions that cannot be graded locally.
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*/
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import { NextRequest } from 'next/server';
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import { callLLM } from '@/lib/ai/llm';
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import { createLogger } from '@/lib/logger';
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import { apiError, apiSuccess } from '@/lib/server/api-response';
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import { resolveModelFromRequest } from '@/lib/server/resolve-model';
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const log = createLogger('Quiz Grade');
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interface GradeRequest {
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question: string;
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userAnswer: string;
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points: number;
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commentPrompt?: string;
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language?: string;
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}
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interface GradeResponse {
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score: number;
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comment: string;
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}
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export async function POST(req: NextRequest) {
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let questionSnippet: string | undefined;
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let resolvedPoints: number | undefined;
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try {
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const body = (await req.json()) as GradeRequest;
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const { question, userAnswer, points, commentPrompt, language } = body;
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questionSnippet = question?.substring(0, 60);
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resolvedPoints = points;
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if (!question || !userAnswer) {
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return apiError('MISSING_REQUIRED_FIELD', 400, 'question and userAnswer are required');
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}
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// Validate points is a positive finite number
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if (!points || !Number.isFinite(points) || points <= 0) {
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return apiError('INVALID_REQUEST', 400, 'points must be a positive number');
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}
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// Resolve model from request headers/body
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const { model: languageModel, thinkingConfig } = await resolveModelFromRequest(
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req,
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body,
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'quiz-grade',
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);
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const isZh = language === 'zh-CN';
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const systemPrompt = isZh
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? `你是一位专业的教育评估专家。请根据题目和学生答案进行评分并给出简短评语。
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必须以如下 JSON 格式回复（不要包含其他内容）：
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{"score": <0到${points}的整数>, "comment": "<一两句评语>"}`
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: `You are a professional educational assessor. Grade the student's answer and provide brief feedback.
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You must reply in the following JSON format only (no other content):
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{"score": <integer from 0 to ${points}>, "comment": "<one or two sentences of feedback>"}`;
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const userPrompt = isZh
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? `题目：${question}
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满分：${points}分
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${commentPrompt ? `评分要点：${commentPrompt}\n` : ''}学生答案：${userAnswer}`
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: `Question: ${question}
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Full marks: ${points} points
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${commentPrompt ? `Grading guidance: ${commentPrompt}\n` : ''}Student answer: ${userAnswer}`;
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const result = await callLLM(
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{
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model: languageModel,
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system: systemPrompt,
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prompt: userPrompt,
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},
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'quiz-grade',
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undefined,
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thinkingConfig,
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);
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// Parse the LLM response as JSON
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const text = result.text.trim();
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let gradeResult: GradeResponse;
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try {
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// Try to extract JSON from the response
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const jsonMatch = text.match(/\{[\s\S]*\}/);
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if (!jsonMatch) throw new Error('No JSON found');
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const parsed = JSON.parse(jsonMatch[0]);
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gradeResult = {
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score: Math.max(0, Math.min(points, Math.round(Number(parsed.score)))),
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comment: String(parsed.comment || ''),
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};
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} catch {
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// Fallback: give partial credit with a generic comment
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gradeResult = {
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score: Math.round(points * 0.5),
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comment: isZh
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? '已作答，请参考标准答案。'
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: 'Answer received. Please refer to the standard answer.',
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};
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}
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return apiSuccess({ ...gradeResult });
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} catch (error) {
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log.error(
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`Quiz grading failed [question="${questionSnippet ?? 'unknown'}...", points=${resolvedPoints ?? 'unknown'}]:`,
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error,
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);
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return apiError('INTERNAL_ERROR', 500, 'Failed to grade answer');
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}
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}
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