feat: implement QuestionBank CRUD with pagination and template query

- Add pagination support to findAll (page, limit query params) - Add findByTemplateId method to service - Add GET /by-template/:templateId endpoint to controller - Service already includes CRUD for QuestionBank and QuestionBankItem
2026-04-23 17:19:11 +08:00
commit 0a9588abb7
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+import { ChatOpenAI } from '@langchain/openai';
+import { SystemMessage, HumanMessage } from '@langchain/core/messages';
+import { RunnableConfig } from '@langchain/core/runnables';
+import { EvaluationState } from '../state';
+import { safeParseJson } from '../../../common/json-utils';
+
+/**
+ * Node responsible for generating assessment questions based on the knowledge base content.
+ */
+export const questionGeneratorNode = async (
+  state: EvaluationState,
+  config?: RunnableConfig,
+): Promise<Partial<EvaluationState>> => {
+  const { model, knowledgeBaseContent, targetCount } = (config?.configurable as any) || {};
+  const limitCount = targetCount || 5;
+
+  console.log('[GeneratorNode] Starting generation...', {
+    language: state.language,
+    hasModel: !!model,
+    contentLength: knowledgeBaseContent?.length,
+    keywords: state.keywords || [],
+    targetCount: limitCount,
+  });
+
+  if (!model || !knowledgeBaseContent) {
+    console.error('[GeneratorNode] Missing model or knowledgeBaseContent');
+    throw new Error(
+      'Missing model or knowledgeBaseContent in node configuration',
+    );
+  }
+
+  const isZh = state.language === 'zh';
+  const isJa = state.language === 'ja';
+
+  const style = state.style || 'technical';
+  const difficultyText = state.difficultyDistribution
+    ? JSON.stringify(state.difficultyDistribution)
+    : isZh
+      ? '随机分布'
+      : isJa
+        ? 'ランダム分布'
+        : 'Random distribution';
+  const keywords = state.keywords || [];
+  const hasKeywords = keywords.length > 0;
+  const keywordText = hasKeywords ? keywords.join(', ') : '';
+
+  const rulesZh = [
+    `**禁止重复**：绝对禁止生成与下方“禁止重复列表”中相似的题目。`,
+    `**深度挖掘**：如果之前的题目考查了核心定义，新题目必须考查具体的应用案例、对比分析或隐藏的细节。`,
+    hasKeywords
+      ? `**关键词权重**：必须围绕关键词 (${keywordText}) 展开，但要从关键词的不同侧面（如流程、限制、优缺点、具体参数等）进行挖掘。`
+      : null,
+    `**随机扰动**：即使对于相同的主题或关键词，也要尝试从不同的逻辑链条（如“因为...所以...” vs “如果没有...会怎样”）出发。`,
+  ]
+    .filter(Boolean)
+    .map((r, i) => `${i + 1}. ${r}`)
+    .join('\n');
+
+  const rulesJa = [
+    `**重複禁止**：下記の「作成済み問題リスト」と類似した内容は絶対に避けてください。`,
+    `**多角的アプローチ**：前回が定義だった場合は、今回は応用方法、制限事項、具体的な数値などに焦点を当ててください。`,
+    hasKeywords
+      ? `**キーワードの深掘り**：キーワード (${keywordText}) の異なる側面から出題してください。`
+      : null,
+  ]
+    .filter(Boolean)
+    .map((r, i) => `${i + 1}. ${r}`)
+    .join('\n');
+
+  const rulesEn = [
+    `**NO REPETITION**: Strictly avoid any conceptual overlap with the "Previous Questions" list below.`,
+    `**New Facets**: If previous questions were about definitions, focus on applications, edge cases, or specific details.`,
+    hasKeywords
+      ? `**Keyword Variety**: Center on (${keywordText}), but explore different aspects (process, pros/cons, requirements).`
+      : null,
+  ]
+    .filter(Boolean)
+    .map((r, i) => `${i + 1}. ${r}`)
+    .join('\n');
+
+  const existingQuestions = state.questions || [];
+  const existingQuestionsText = existingQuestions
+    .map((q, i) => `Q${i + 1}: ${q.questionText}`)
+    .join('\n');
+
+  const systemPromptZh = `你是一位专业的知识评估专家。请根据提供的知识库片段生成 1 个唯一的测试题目。
+
+### 强制性语言规则：
+**必须使用中文 (Simplified Chinese) 进行回复**。即使知识库内容是英文或其他语言，问题(question_text)和关键点(key_points)也必须使用中文。
+
+### 强制性多样性规则：
+${rulesZh}
+
+### 禁止重复列表（已出过）：
+${existingQuestionsText || '无'}
+
+### 任务：
+${hasKeywords ? `目标关键词：${keywordText}\n` : ''}出题风格：${style}
+难度：${difficultyText}
+
+请以 JSON 数组格式返回 1 个问题：
+[
+  {
+    "question_text": "...",
+    "key_points": ["点1", "点2"],
+    "difficulty": "...",
+    "dimension": "prompt/llm/ide/devPattern/workCapability",
+    "basis": "[n] 引用原文..."
+  }
+]`;
+// dimension取值：prompt=提示词, llm=LLM原理, ide=IDE协作, devPattern=开发范式, workCapability=工作能力
+
+  const systemPromptJa = `あなたは専門的なアセスメントエキスパートです。提供されたナレッジベースに基づいて、ユニークな問題を 1 つ作成してください。
+
+### 言語ルール（最重要）：
+**必ず日本語で作成してください**。提供されたナレッジベースが英語や中国語、その他の言語であっても、質問文(question_text)およびキーポイント(key_points)は必ず日本語で回答してください。中国語が混ざらないように厳格に注意してください。
+
+### 多様性ルール：
+${rulesJa}
+
+### 作成済み問題リスト：
+${existingQuestionsText || 'なし'}
+
+### 任務：
+${hasKeywords ? `目標キーワード：${keywordText}\n` : ''}出題スタイル：${style}
+難易度：${difficultyText}
+
+以下のJSON配列形式で問題を1つ返してください：
+[
+  {
+    "question_text": "...",
+    "key_points": ["ポイント1", "ポイント2"],
+    "difficulty": "...",
+    "dimension": "prompt/llm/ide/devPattern/workCapability",
+    "basis": "[n] 引用箇所..."
+  }
+ ]`;
+
+  const systemPromptEn = `You are an expert examiner. Generate 1 UNIQUE question based on the provided context.
+
+### Language Rule:
+**You MUST generate the question and key points in English.**
+
+### Diversity Rules:
+${rulesEn}
+
+### Previous Questions (DO NOT REPEAT):
+${existingQuestionsText || 'None'}
+
+Return 1 question as a JSON array with format:
+[
+  {
+    "question_text": "...",
+    "key_points": ["point1", "point2"],
+    "difficulty": "...",
+    "dimension": "prompt/llm/ide/devPattern/workCapability",
+    "basis": "[n] citation..."
+  }
+]`;
+
+// dimension values: prompt=prompt engineering, llm=LLM principles, ide=IDE collaboration, devPattern=development paradigm, workCapability=work capability
+
+  const systemPrompt = isZh
+    ? systemPromptZh
+    : isJa
+      ? systemPromptJa
+      : systemPromptEn;
+  const humanMsg = isZh
+    ? `请使用中文基于以下内容生成题目：\n\n${knowledgeBaseContent}`
+    : isJa
+      ? `以下の内容に基づいて、必ず日本語でアセスメント問題を作成してください：\n\n${knowledgeBaseContent}`
+      : `Generate evaluation question in English based on:\n\n${knowledgeBaseContent}`;
+
+  try {
+    const response = await model.invoke([
+      new SystemMessage(systemPrompt),
+      new HumanMessage(humanMsg),
+    ]);
+
+    try {
+      let newQuestions = safeParseJson<any>(response.content as string);
+      
+      if (!newQuestions) {
+        console.error('[GeneratorNode] Failed to parse JSON. Raw content:', response.content);
+        throw new Error('Invalid JSON format from AI');
+      }
+
+      // Handle both array and single object
+      if (!Array.isArray(newQuestions)) {
+        newQuestions = [newQuestions];
+      }
+
+      const dimensionMap: Record<string, string> = {
+        // 中文
+        '技术能力-提示词': 'prompt',
+        '提示词': 'prompt',
+        '技术能力-LLM': 'llm',
+        'LLM': 'llm',
+        'IDE协作能力': 'ide',
+        'IDE': 'ide',
+        'AI开发范式': 'devPattern',
+        '开发范式': 'devPattern',
+        '工作能力-安全': 'workCapability',
+        '工作能力': 'workCapability',
+        // 英文直接映射
+        'prompt': 'prompt',
+        'llm': 'llm',
+        'ide': 'ide',
+        'devPattern': 'devPattern',
+        'workCapability': 'workCapability',
+      };
+
+      const mappedNewQuestions = newQuestions.map((q: any) => {
+        let inferredDimension = 'workCapability';
+        const dimValue = q.dimension?.toString().toLowerCase().trim();
+        if (dimValue) {
+          inferredDimension = dimensionMap[dimValue] || 'workCapability';
+          console.log('[GeneratorNode] Dimension mapping:', { original: q.dimension, mapped: inferredDimension });
+        }
+        return {
+          id: (existingQuestions.length + 1).toString(),
+          questionText: q.question_text,
+          keyPoints: q.key_points,
+          difficulty: q.difficulty,
+          basis: q.basis,
+          dimension: inferredDimension,
+        };
+      });
+
+      const questionsToGenerate = Math.max(1, limitCount - existingQuestions.length);
+      const limitedNewQuestions = mappedNewQuestions.slice(0, questionsToGenerate);
+      
+      console.log('[GeneratorNode] Generated questions:', mappedNewQuestions.length, 'Limit:', questionsToGenerate);
+      
+      return {
+        questions: [...existingQuestions, ...limitedNewQuestions],
+      };
+    } catch (error) {
+      console.error('[GeneratorNode] Parse error:', error);
+      return { questions: existingQuestions };
+    }
+  } catch (invokeError) {
+    console.error('[GeneratorNode] Invoke error:', invokeError);
+    throw invokeError;
+  }
+};