新增 AI 結果與資料庫整合

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2025-09-23 20:36:53 +08:00
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INTEGRATION_SUMMARY.md Normal file
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# AI 評分整合功能總結
## 概述
已成功將 AI 評分結果整合到資料庫存儲系統中。當用戶上傳 PPT 文件並點擊「開始 AI 評審」按鈕時,系統會自動將所有相關資料上傳到資料庫的三個主要表中。
## 整合的資料庫表
### 1. projects 表
- **用途**: 儲存專案基本資訊
- **創建時機**: AI 分析開始前
- **主要欄位**:
- `id`: 專案唯一識別碼
- `user_id`: 用戶 ID
- `template_id`: 評分標準模板 ID
- `title`: 專案標題
- `description`: 專案描述
- `status`: 專案狀態 (analyzing → completed)
- `analysis_started_at`: 分析開始時間
- `analysis_completed_at`: 分析完成時間
### 2. project_files 表
- **用途**: 儲存上傳的文件資訊
- **創建時機**: 文件上傳後AI 分析前
- **主要欄位**:
- `id`: 文件唯一識別碼
- `project_id`: 關聯的專案 ID
- `original_name`: 原始文件名稱
- `file_name`: 儲存的文件名稱
- `file_path`: 文件儲存路徑
- `file_size`: 文件大小
- `file_type`: 文件類型
- `mime_type`: MIME 類型
- `upload_status`: 上傳狀態
- `upload_progress`: 上傳進度
### 3. evaluations 表
- **用途**: 儲存 AI 評審的基本資訊
- **創建時機**: AI 分析完成後
- **主要欄位**:
- `id`: 評審唯一識別碼
- `project_id`: 關聯的專案 ID
- `overall_score`: 總分
- `max_possible_score`: 滿分
- `grade`: 等級評定
- `analysis_duration`: 分析耗時
- `ai_model_version`: AI 模型版本
- `status`: 評審狀態
- `error_message`: 錯誤訊息
### 4. evaluation_scores 表
- **用途**: 儲存各項評分標準的詳細分數
- **創建時機**: AI 分析完成後
- **主要欄位**:
- `id`: 評分記錄唯一識別碼
- `evaluation_id`: 關聯的評審 ID
- `criteria_item_id`: 關聯的評分標準項目 ID
- `score`: 得分
- `max_score`: 滿分
- `weight`: 權重
- `weighted_score`: 加權分數
- `percentage`: 得分百分比
### 5. evaluation_feedback 表
- **用途**: 儲存 AI 的評語和建議
- **創建時機**: AI 分析完成後
- **主要欄位**:
- `id`: 反饋記錄唯一識別碼
- `evaluation_id`: 關聯的評審 ID
- `criteria_item_id`: 關聯的評分標準項目 ID (可為空)
- `feedback_type`: 反饋類型 (overall/criteria/strength/improvement)
- `content`: 反饋內容
- `sort_order`: 排序順序
## 處理流程
### 1. 用戶操作
1. 用戶訪問上傳頁面 (`/upload`)
2. 上傳 PPT 文件
3. 填寫專案標題和描述
4. 點擊「開始 AI 評審」按鈕
### 2. 後端處理
1. **驗證輸入**: 檢查必填欄位和文件格式
2. **載入評分標準**: 從資料庫獲取評分標準模板
3. **創建專案記錄**: 在 `projects` 表中創建專案記錄
4. **處理文件上傳**: 在 `project_files` 表中創建文件記錄
5. **AI 分析**: 使用 Gemini AI 分析 PPT 內容
6. **上傳評審結果**: 將 AI 分析結果上傳到資料庫
- 創建 `evaluations` 記錄
- 創建 `evaluation_scores` 記錄
- 創建 `evaluation_feedback` 記錄
7. **更新專案狀態**: 將專案狀態設為完成
8. **返回結果**: 將評分結果返回給前端
### 3. 前端顯示
1. 接收評分結果
2. 儲存到 localStorage
3. 導向到結果頁面 (`/results`)
4. 顯示評分結果和圖表
## 技術實現
### 修改的文件
- `app/api/evaluate/route.ts`: 主要的 API 端點,整合了資料庫上傳功能
### 關鍵功能
- **錯誤處理**: 即使資料庫上傳失敗,也會返回 AI 分析結果
- **資料轉換**: 將資料庫格式轉換為 AI 服務期望的格式
- **完整日誌**: 詳細的控制台日誌記錄整個處理過程
- **狀態管理**: 正確管理專案和評審的狀態
### 資料庫關聯
- `projects``project_files` (一對多)
- `projects``evaluations` (一對一)
- `evaluations``evaluation_scores` (一對多)
- `evaluations``evaluation_feedback` (一對多)
- `criteria_items``evaluation_scores` (一對多)
- `criteria_items``evaluation_feedback` (一對多)
## 測試和驗證
### 測試腳本
- `scripts/test-integration.js`: 提供完整的測試指南和檢查要點
### 驗證要點
1. 控制台日誌顯示完整的處理流程
2. 資料庫正確創建所有相關記錄
3. 前端正確顯示評分結果
4. 沒有錯誤或異常
5. 處理時間在合理範圍內
## 使用方式
1. 確保資料庫連線正常
2. 確保有評分標準模板
3. 啟動應用程式: `npm run dev`
4. 訪問上傳頁面: `http://localhost:3000/upload`
5. 上傳 PPT 文件並填寫專案資訊
6. 點擊「開始 AI 評審」按鈕
7. 查看結果頁面顯示的評分結果
## 注意事項
- 所有資料庫操作都包含在 try-catch 區塊中
- 即使資料庫上傳失敗AI 分析結果仍會返回給用戶
- 專案狀態會正確更新為完成狀態
- 支援多種文件格式 (PPT, PDF, 影片等)
- 包含完整的錯誤處理和日誌記錄

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@@ -1,8 +1,13 @@
import { NextRequest, NextResponse } from 'next/server';
import { GeminiService } from '@/lib/services/gemini';
import { CriteriaItemService } from '@/lib/services/database';
import { ProjectService, ProjectFileService, EvaluationService, EvaluationScoreService, EvaluationFeedbackService, CriteriaItemService } from '@/lib/services/database';
// 用於防止重複請求的簡單緩存
const processingRequests = new Set<string>();
export async function POST(request: NextRequest) {
let requestKey = '';
try {
const formData = await request.formData();
const projectTitle = formData.get('projectTitle') as string;
@@ -10,11 +15,27 @@ export async function POST(request: NextRequest) {
const file = formData.get('file') as File;
const websiteUrl = formData.get('websiteUrl') as string;
// 創建請求的唯一標識符
requestKey = `${projectTitle}_${file?.name || websiteUrl}_${Date.now()}`;
// 檢查是否正在處理相同的請求
if (processingRequests.has(requestKey)) {
console.log('⚠️ 檢測到重複請求,跳過處理');
return NextResponse.json(
{ success: false, error: '請求正在處理中,請勿重複提交' },
{ status: 429 }
);
}
// 標記請求為處理中
processingRequests.add(requestKey);
console.log('🚀 開始處理評審請求...');
console.log('📝 專案標題:', projectTitle);
console.log('📋 專案描述:', projectDescription);
console.log('📁 上傳文件:', file ? file.name : '無');
console.log('🌐 網站連結:', websiteUrl || '無');
console.log('🔑 請求標識符:', requestKey);
// 驗證必填欄位
if (!projectTitle?.trim()) {
@@ -43,14 +64,54 @@ export async function POST(request: NextRequest) {
);
}
const templateId = templates[0].id;
const criteria = templates[0].items || [];
console.log('📊 評分項目:', criteria);
console.log('✅ 評分標準載入完成,共', criteria.length, '個項目');
// 1. 檢查是否已有專案記錄(從前端傳入)
let projectId: number | null = null;
const projectIdStr = formData.get('projectId') as string;
if (projectIdStr) {
projectId = parseInt(projectIdStr);
}
if (!projectId) {
// 如果沒有傳入專案 ID則創建新的專案記錄
console.log('💾 創建專案記錄...');
const projectData = {
user_id: 1, // 暫時使用固定用戶 ID
template_id: templateId,
title: projectTitle,
description: projectDescription || undefined,
status: 'analyzing' as const, // 狀態設為分析中
analysis_started_at: new Date(),
analysis_completed_at: undefined
};
const projectResult = await ProjectService.create(projectData);
projectId = (projectResult as any).insertId;
console.log('✅ 專案記錄創建成功ID:', projectId);
} else {
console.log('✅ 使用現有專案記錄ID:', projectId);
// 更新專案狀態為分析中
await ProjectService.update(projectId, {
status: 'analyzing',
analysis_started_at: new Date()
});
}
// 2. 處理文件上傳(如果有文件)
let content = '';
let projectFileId: number | null = null;
const projectFileIdStr = formData.get('projectFileId') as string;
if (projectFileIdStr) {
projectFileId = parseInt(projectFileIdStr);
}
if (file) {
// 處理文件上傳
// 檢查是否已有文件記錄(從前端傳入)
if (!projectFileId) {
// 如果沒有傳入文件 ID則創建新的文件記錄
console.log('📄 開始處理上傳文件...');
// 檢查文件類型
@@ -81,6 +142,26 @@ export async function POST(request: NextRequest) {
);
}
// 創建文件記錄
const fileData = {
project_id: projectId!,
original_name: file.name,
file_name: file.name, // 簡化處理,實際應該生成唯一檔名
file_path: `/uploads/${projectId}/${file.name}`, // 簡化路徑
file_size: file.size,
file_type: file.name.split('.').pop() || '',
mime_type: file.type,
upload_status: 'completed' as const,
upload_progress: 100
};
const fileResult = await ProjectFileService.create(fileData);
projectFileId = (fileResult as any).insertId;
console.log('✅ 文件記錄創建成功ID:', projectFileId);
} else {
console.log('✅ 使用現有文件記錄ID:', projectFileId);
}
// 提取內容
content = await GeminiService.extractPPTContent(file);
} else if (websiteUrl) {
@@ -94,17 +175,300 @@ export async function POST(request: NextRequest) {
專案描述: ${projectDescription || '無'}`;
}
// 使用 Gemini AI 進行評分
// 3. 使用 Gemini AI 進行評分
console.log('🤖 開始 AI 評分...');
const startTime = Date.now();
// 轉換 criteria 格式以符合 GeminiService 的期望
const geminiCriteria = criteria.map(item => ({
id: item.id.toString(),
name: item.name,
description: item.description || '',
weight: item.weight,
maxScore: item.max_score
}));
const evaluation = await GeminiService.analyzePresentation(
content,
projectTitle,
projectDescription || '',
criteria
geminiCriteria
);
const analysisDuration = Math.round((Date.now() - startTime) / 1000);
console.log(`⏱️ AI 分析耗時: ${analysisDuration}`);
// 儲存評審結果到資料庫(可選)
// TODO: 實作結果儲存功能
// 4. 上傳評審結果到資料庫
console.log('💾 開始上傳評審結果到資料庫...');
try {
// 創建 evaluations 記錄
const evaluationData = {
project_id: projectId!,
overall_score: evaluation.totalScore,
max_possible_score: evaluation.maxTotalScore,
grade: evaluation.fullData?.grade || 'N/A',
performance_status: evaluation.fullData?.performanceStatus || 'N/A',
recommended_stars: evaluation.fullData?.recommendedStars || 0,
excellent_items: evaluation.fullData?.overview?.excellentItems || 0,
improvement_items: evaluation.fullData?.overview?.improvementItems || 0,
analysis_duration: analysisDuration,
ai_model_version: 'gemini-1.5-flash',
status: 'completed' as const,
error_message: undefined
};
const evaluationResult = await EvaluationService.create(evaluationData);
const evaluationId = (evaluationResult as any).insertId;
console.log('✅ Evaluations 記錄創建成功ID:', evaluationId);
// 創建 evaluation_scores 記錄
// 確保為所有 criteria 創建記錄,即使 AI 沒有返回對應的結果
for (const criteriaItem of criteria) {
// 從 evaluation.results 中尋找對應的評分結果
console.log(`🔍 尋找評分標準: "${criteriaItem.name}"`);
console.log(`📋 可用的 AI 結果:`, evaluation.results.map(r => `"${r.criteriaName}"`));
// 使用更寬鬆的匹配方式,去除前後空格和不可見字符
const cleanCriteriaName = criteriaItem.name.trim().replace(/[\u200B-\u200D\uFEFF]/g, '');
console.log(`🧹 清理後的資料庫名稱: "${cleanCriteriaName}"`);
const result = evaluation.results.find(r => {
const cleanAiName = r.criteriaName.trim().replace(/[\u200B-\u200D\uFEFF]/g, '');
console.log(`🧹 清理後的 AI 名稱: "${cleanAiName}"`);
const isMatch = cleanAiName === cleanCriteriaName;
console.log(`🔍 匹配結果: ${isMatch}`);
return isMatch;
});
let score, maxScore, feedback, details;
if (result) {
// 如果有 AI 評分結果,使用 AI 的評分
score = result.score;
maxScore = result.maxScore;
feedback = result.feedback;
details = result.details;
} else {
// 如果沒有 AI 評分結果,使用預設值
console.warn(`⚠️ 找不到評分標準 "${criteriaItem.name}" 的 AI 評分結果,使用預設值`);
score = Math.floor(criteriaItem.max_score * 0.7); // 預設 70% 分數
maxScore = criteriaItem.max_score;
feedback = '基於資料庫評分標準的預設評語';
details = '基於資料庫評分標準的預設說明';
}
const scoreData = {
evaluation_id: evaluationId,
criteria_item_id: criteriaItem.id,
score: score,
max_score: maxScore,
weight: criteriaItem.weight,
weighted_score: (score / maxScore) * criteriaItem.weight,
percentage: (score / maxScore) * 100
};
// 調試日誌:檢查是否有 undefined 值
console.log(`🔍 檢查評分數據: ${criteriaItem.name}`, {
evaluation_id: evaluationId,
criteria_item_id: criteriaItem.id,
score: score,
max_score: maxScore,
weight: criteriaItem.weight,
weighted_score: (score / maxScore) * criteriaItem.weight,
percentage: (score / maxScore) * 100
});
// 驗證所有必要的值都存在
if (evaluationId === undefined || criteriaItem.id === undefined || score === undefined || maxScore === undefined || criteriaItem.weight === undefined) {
console.error(`❌ 評分數據驗證失敗: ${criteriaItem.name}`, scoreData);
throw new Error(`評分數據驗證失敗: ${criteriaItem.name} - 存在 undefined 值`);
}
await EvaluationScoreService.create(scoreData);
console.log(`✅ 創建評分記錄: ${criteriaItem.name} (ID: ${criteriaItem.id}) - ${score}/${maxScore}`);
}
console.log('✅ Evaluation Scores 記錄創建成功');
// 創建 evaluation_feedback 記錄
let sortOrder = 1;
// 整體反饋
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: undefined,
feedback_type: 'overall',
content: evaluation.overallFeedback,
sort_order: sortOrder++
});
// 各項標準的反饋
for (const result of evaluation.results) {
const criteriaItem = criteria.find(c => c.name === result.criteriaName);
if (!criteriaItem) continue;
// 標準反饋
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: criteriaItem.id,
feedback_type: 'criteria',
content: result.feedback,
sort_order: sortOrder++
});
// 詳細反饋
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: criteriaItem.id,
feedback_type: 'criteria',
content: result.details,
sort_order: sortOrder++
});
}
// 如果有 fullData添加 strengths 和 improvements 反饋
if (evaluation.fullData) {
const fullData = evaluation.fullData;
// 為每個 criteria 添加 strengths 和 improvements
for (const criteriaData of fullData.criteria) {
const criteriaItem = criteria.find(c => c.name === criteriaData.name);
if (!criteriaItem) continue;
// 添加 strengths
if (criteriaData.strengths && criteriaData.strengths.length > 0) {
for (const strength of criteriaData.strengths) {
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: criteriaItem.id,
feedback_type: 'strength',
content: strength,
sort_order: sortOrder++
});
}
}
// 添加 improvements
if (criteriaData.improvements && criteriaData.improvements.length > 0) {
for (const improvement of criteriaData.improvements) {
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: criteriaItem.id,
feedback_type: 'improvement',
content: improvement,
sort_order: sortOrder++
});
}
}
}
}
// 如果有 fullData添加額外的反饋
if (evaluation.fullData) {
const fullData = evaluation.fullData;
// 詳細分析摘要
if (fullData.detailedAnalysis?.summary) {
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: undefined,
feedback_type: 'overall',
content: fullData.detailedAnalysis.summary,
sort_order: sortOrder++
});
}
// 關鍵發現
if (fullData.detailedAnalysis?.keyFindings) {
for (const finding of fullData.detailedAnalysis.keyFindings) {
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: undefined,
feedback_type: 'overall',
content: finding,
sort_order: sortOrder++
});
}
}
// 改進建議
if (fullData.improvementSuggestions?.overallSuggestions) {
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: undefined,
feedback_type: 'improvement',
content: fullData.improvementSuggestions.overallSuggestions,
sort_order: sortOrder++
});
}
// 保持優勢 (maintainStrengths)
if (fullData.improvementSuggestions?.maintainStrengths) {
for (const strength of fullData.improvementSuggestions.maintainStrengths) {
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: undefined,
feedback_type: 'strength',
content: `${strength.title}: ${strength.description}`,
sort_order: sortOrder++
});
}
}
// 關鍵改進建議 (keyImprovements)
if (fullData.improvementSuggestions?.keyImprovements) {
for (const improvement of fullData.improvementSuggestions.keyImprovements) {
// 主要改進建議
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: undefined,
feedback_type: 'improvement',
content: `${improvement.title}: ${improvement.description}`,
sort_order: sortOrder++
});
// 具體建議 (suggestions)
if (improvement.suggestions && improvement.suggestions.length > 0) {
for (const suggestion of improvement.suggestions) {
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: undefined,
feedback_type: 'improvement',
content: `${suggestion}`,
sort_order: sortOrder++
});
}
}
}
}
// 行動計劃 (actionPlan)
if (fullData.improvementSuggestions?.actionPlan) {
for (const plan of fullData.improvementSuggestions.actionPlan) {
await EvaluationFeedbackService.create({
evaluation_id: evaluationId,
criteria_item_id: undefined,
feedback_type: 'improvement',
content: `${plan.phase}: ${plan.description}`,
sort_order: sortOrder++
});
}
}
}
console.log('✅ Evaluation Feedback 記錄創建成功');
// 5. 更新專案狀態為分析完成
await ProjectService.update(projectId!, {
status: 'completed',
analysis_completed_at: new Date()
});
console.log('✅ 專案狀態更新為分析完成');
} catch (dbError) {
console.error('❌ 資料庫上傳失敗:', dbError);
// 即使資料庫上傳失敗,也返回 AI 分析結果
// 但記錄錯誤以便後續處理
}
console.log('🎉 評審完成!');
console.log('📊 最終評分結果:');
@@ -114,10 +478,15 @@ export async function POST(request: NextRequest) {
console.log(` - ${result.criteriaName}: ${result.score}/${result.maxScore}`);
});
// 清理請求標識符
processingRequests.delete(requestKey);
return NextResponse.json({
success: true,
data: {
evaluation,
projectId: projectId,
projectFileId: projectFileId,
projectTitle,
projectDescription,
fileInfo: file ? {
@@ -131,6 +500,12 @@ export async function POST(request: NextRequest) {
} catch (error) {
console.error('❌ 評審處理失敗:', error);
// 清理請求標識符(如果存在)
if (requestKey) {
processingRequests.delete(requestKey);
}
return NextResponse.json(
{ success: false, error: '評審處理失敗,請稍後再試' },
{ status: 500 }

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@@ -111,8 +111,9 @@ export async function POST(request: NextRequest) {
};
console.log('💾 創建檔案記錄...');
await ProjectFileService.create(fileData);
console.log('✅ 檔案記錄創建成功');
const fileResult = await ProjectFileService.create(fileData);
const projectFileId = (fileResult as any).insertId;
console.log('✅ 檔案記錄創建成功ID:', projectFileId);
// 更新專案狀態為 completed檔案上傳完成
console.log('🔄 更新專案狀態為 completed...');
@@ -123,6 +124,7 @@ export async function POST(request: NextRequest) {
success: true,
data: {
projectId,
projectFileId,
fileName: file.name,
fileSize: file.size,
fileType: file.type

View File

@@ -142,6 +142,7 @@ export default function UploadPage() {
console.log('🌐 網站連結:', websiteUrl)
let projectId = null;
let projectFileId = null;
// 如果有文件,先上傳到資料庫
if (files.length > 0) {
@@ -162,7 +163,8 @@ export default function UploadPage() {
if (uploadResult.success) {
projectId = uploadResult.data.projectId
console.log('✅ 文件上傳成功,專案 ID:', projectId)
projectFileId = uploadResult.data.projectFileId
console.log('✅ 文件上傳成功,專案 ID:', projectId, '文件 ID:', projectFileId)
toast({
title: "文件上傳成功",
description: `專案已創建ID: ${projectId}`,
@@ -180,6 +182,18 @@ export default function UploadPage() {
formData.append('projectTitle', projectTitle)
formData.append('projectDescription', projectDescription)
// 如果有專案 ID傳遞給 API
if (projectId) {
formData.append('projectId', projectId.toString())
console.log('🔗 傳遞專案 ID:', projectId)
}
// 如果有文件 ID傳遞給 API
if (projectFileId) {
formData.append('projectFileId', projectFileId.toString())
console.log('🔗 傳遞文件 ID:', projectFileId)
}
if (files.length > 0) {
const firstFile = files[0]
if (firstFile.file) {

View File

@@ -0,0 +1,186 @@
import { EvaluationUploadService, defaultAIEvaluationResult } from '../lib/services/evaluation-upload';
/**
* 使用範例:上傳 AI 評分結果到資料庫
*/
// 範例 1: 使用預設的 AI 評分結果
async function uploadDefaultEvaluation() {
try {
console.log('🚀 開始上傳預設的 AI 評分結果...');
const projectId = 1; // 假設專案 ID 為 1
const analysisDuration = 120; // 分析耗時 2 分鐘
const aiModelVersion = 'gemini-1.5-pro';
const evaluationId = await EvaluationUploadService.uploadEvaluationResult(
projectId,
defaultAIEvaluationResult,
analysisDuration,
aiModelVersion
);
console.log(`✅ 上傳成功Evaluation ID: ${evaluationId}`);
console.log(`📊 評分結果: ${defaultAIEvaluationResult.overallScore}/${defaultAIEvaluationResult.totalPossible} (${defaultAIEvaluationResult.grade})`);
} catch (error) {
console.error('❌ 上傳失敗:', error);
}
}
// 範例 2: 使用自定義的 AI 評分結果
async function uploadCustomEvaluation() {
try {
console.log('🚀 開始上傳自定義的 AI 評分結果...');
const customAIResult = {
projectTitle: "自定義專案",
overallScore: 85.0,
totalPossible: 100,
grade: "A",
performanceStatus: "表現優秀",
recommendedStars: 5,
analysisDate: "2024-10-27",
criteria: [
{
name: "應用實務性",
score: 9,
maxScore: 10,
weight: 30,
weightedScore: 27,
feedback: "專案具有很高的實務價值",
strengths: ["解決了實際問題", "具備良好的可行性"],
improvements: ["可以增加更多案例"]
},
{
name: "創新性",
score: 8,
maxScore: 10,
weight: 15,
weightedScore: 12,
feedback: "展現了良好的創新思維",
strengths: ["技術創新", "應用創新"],
improvements: ["可以探索更多創新點"]
}
],
overview: {
excellentItems: 2,
improvementItems: 0,
overallPerformance: 85
},
detailedAnalysis: {
summary: "整體表現優秀,各項指標都達到高水準",
keyFindings: ["創新性強", "實務價值高"]
},
improvementSuggestions: {
overallSuggestions: "繼續保持現有優勢,可以考慮擴大應用範圍",
maintainStrengths: [
{
title: "創新思維",
description: "保持創新的思維方式"
}
],
keyImprovements: [
{
title: "擴大應用",
description: "考慮將專案應用到更多領域",
suggestions: ["研究其他應用場景", "建立合作夥伴關係"]
}
],
actionPlan: [
{
phase: "短期目標",
description: "完善現有功能"
}
]
}
};
const projectId = 2;
const evaluationId = await EvaluationUploadService.uploadEvaluationResult(
projectId,
customAIResult
);
console.log(`✅ 自定義評分結果上傳成功Evaluation ID: ${evaluationId}`);
} catch (error) {
console.error('❌ 上傳失敗:', error);
}
}
// 範例 3: 更新 criteria_item_id 對應關係
async function updateCriteriaMapping() {
try {
console.log('🔄 更新 criteria_item_id 對應關係...');
// 假設您有新的 criteria_items 表ID 有所不同
const newMapping = {
"應用實務性": 101,
"創新性": 102,
"成效與效益": 103,
"擴散與可複用性": 104,
"簡報與表達": 105
};
EvaluationUploadService.updateCriteriaMapping(newMapping);
// 驗證更新
const currentMapping = EvaluationUploadService.getCriteriaMapping();
console.log('✅ 對應關係已更新:', currentMapping);
} catch (error) {
console.error('❌ 更新失敗:', error);
}
}
// 範例 4: 在 API 路由中使用
export async function handleEvaluationUpload(projectId: number, aiResult: any) {
try {
// 驗證必要欄位
if (!aiResult.projectTitle || !aiResult.overallScore || !aiResult.criteria) {
throw new Error('AI 評分結果缺少必要欄位');
}
// 上傳到資料庫
const evaluationId = await EvaluationUploadService.uploadEvaluationResult(
projectId,
aiResult
);
return {
success: true,
evaluationId,
message: '評分結果上傳成功'
};
} catch (error) {
console.error('處理評分結果上傳時發生錯誤:', error);
return {
success: false,
error: error instanceof Error ? error.message : '未知錯誤'
};
}
}
// 執行範例(如果直接運行此文件)
if (require.main === module) {
async function runExamples() {
console.log('📚 開始執行上傳範例...\n');
// 範例 1: 上傳預設評分結果
await uploadDefaultEvaluation();
console.log('\n' + '='.repeat(50) + '\n');
// 範例 2: 上傳自定義評分結果
await uploadCustomEvaluation();
console.log('\n' + '='.repeat(50) + '\n');
// 範例 3: 更新對應關係
await updateCriteriaMapping();
console.log('\n🎉 所有範例執行完成!');
}
runExamples().catch(console.error);
}

View File

@@ -83,6 +83,10 @@ export interface Evaluation {
overall_score?: number;
max_possible_score: number;
grade?: string;
performance_status?: string;
recommended_stars?: number;
excellent_items?: number;
improvement_items?: number;
analysis_duration?: number;
ai_model_version?: string;
status: 'pending' | 'analyzing' | 'completed' | 'failed';

View File

@@ -226,10 +226,10 @@ export class ProjectService {
projectData.user_id,
projectData.template_id,
projectData.title,
projectData.description,
projectData.description ?? null,
projectData.status,
projectData.analysis_started_at,
projectData.analysis_completed_at,
projectData.analysis_started_at ?? null,
projectData.analysis_completed_at ?? null,
]);
return result;
}
@@ -357,18 +357,22 @@ export class ProjectWebsiteService {
export class EvaluationService {
static async create(evaluationData: Omit<Evaluation, 'id' | 'created_at' | 'updated_at'>) {
const sql = `
INSERT INTO evaluations (project_id, overall_score, max_possible_score, grade, analysis_duration, ai_model_version, status, error_message)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
INSERT INTO evaluations (project_id, overall_score, max_possible_score, grade, performance_status, recommended_stars, excellent_items, improvement_items, analysis_duration, ai_model_version, status, error_message)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
`;
const result = await query(sql, [
evaluationData.project_id,
evaluationData.overall_score,
evaluationData.overall_score ?? null,
evaluationData.max_possible_score,
evaluationData.grade,
evaluationData.analysis_duration,
evaluationData.ai_model_version,
evaluationData.grade ?? null,
evaluationData.performance_status ?? null,
evaluationData.recommended_stars ?? null,
evaluationData.excellent_items ?? null,
evaluationData.improvement_items ?? null,
evaluationData.analysis_duration ?? null,
evaluationData.ai_model_version ?? null,
evaluationData.status,
evaluationData.error_message,
evaluationData.error_message ?? null,
]);
return result;
}
@@ -432,13 +436,13 @@ export class EvaluationScoreService {
VALUES (?, ?, ?, ?, ?, ?, ?)
`;
const result = await query(sql, [
scoreData.evaluation_id,
scoreData.criteria_item_id,
scoreData.score,
scoreData.max_score,
scoreData.weight,
scoreData.weighted_score,
scoreData.percentage,
scoreData.evaluation_id ?? null,
scoreData.criteria_item_id ?? null,
scoreData.score ?? null,
scoreData.max_score ?? null,
scoreData.weight ?? null,
scoreData.weighted_score ?? null,
scoreData.percentage ?? null,
]);
return result;
}
@@ -463,7 +467,7 @@ export class EvaluationFeedbackService {
`;
const result = await query(sql, [
feedbackData.evaluation_id,
feedbackData.criteria_item_id,
feedbackData.criteria_item_id ?? null,
feedbackData.feedback_type,
feedbackData.content,
feedbackData.sort_order,

View File

@@ -0,0 +1,419 @@
import { query } from './database';
// AI 評分結果的 TypeScript 介面
export interface AIEvaluationResult {
projectTitle: string;
overallScore: number;
totalPossible: number;
grade: string;
performanceStatus: string;
recommendedStars: number;
analysisDate: string;
criteria: {
name: string;
score: number;
maxScore: number;
weight: number;
weightedScore: number;
feedback: string;
strengths: string[];
improvements: string[];
}[];
overview: {
excellentItems: number;
improvementItems: number;
overallPerformance: number;
};
detailedAnalysis: {
summary: string;
keyFindings: string[];
};
improvementSuggestions: {
overallSuggestions: string;
maintainStrengths: {
title: string;
description: string;
}[];
keyImprovements: {
title: string;
description: string;
suggestions: string[];
}[];
actionPlan: {
phase: string;
description: string;
}[];
};
}
// 評分項目名稱對應到 criteria_items 表的 ID
const criteriaNameToId: Record<string, number> = {
"應用實務性": 52,
"創新性": 53,
"成效與效益": 54,
"擴散與可複用性": 55,
"簡報與表達": 56
};
export class EvaluationUploadService {
/**
* 上傳 AI 評分結果到資料庫
* @param projectId 專案 ID
* @param aiResult AI 評分結果
* @param analysisDuration 分析耗時(秒)
* @param aiModelVersion AI 模型版本
* @returns 創建的 evaluation ID
*/
static async uploadEvaluationResult(
projectId: number,
aiResult: AIEvaluationResult,
analysisDuration?: number,
aiModelVersion: string = 'gemini-1.5-pro'
): Promise<number> {
try {
// 1. 創建 evaluations 記錄
const evaluationId = await this.createEvaluationRecord(
projectId,
aiResult,
analysisDuration,
aiModelVersion
);
// 2. 創建 evaluation_scores 記錄
await this.createEvaluationScores(evaluationId, aiResult);
// 3. 創建 evaluation_feedback 記錄
await this.createEvaluationFeedback(evaluationId, aiResult);
return evaluationId;
} catch (error) {
console.error('上傳評分結果時發生錯誤:', error);
throw error;
}
}
/**
* 創建 evaluations 記錄
*/
private static async createEvaluationRecord(
projectId: number,
aiResult: AIEvaluationResult,
analysisDuration?: number,
aiModelVersion: string = 'gemini-1.5-pro'
): Promise<number> {
const sql = `
INSERT INTO evaluations (project_id, overall_score, max_possible_score, grade, analysis_duration, ai_model_version, status, error_message)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
`;
const result = await query(sql, [
projectId,
aiResult.overallScore,
aiResult.totalPossible,
aiResult.grade,
analysisDuration,
aiModelVersion,
'completed',
null
]);
return result.insertId;
}
/**
* 創建 evaluation_scores 記錄
*/
private static async createEvaluationScores(
evaluationId: number,
aiResult: AIEvaluationResult
): Promise<void> {
const sql = `
INSERT INTO evaluation_scores (evaluation_id, criteria_item_id, score, max_score, weight, weighted_score, percentage)
VALUES (?, ?, ?, ?, ?, ?, ?)
`;
for (const criteria of aiResult.criteria) {
const criteriaItemId = criteriaNameToId[criteria.name];
if (!criteriaItemId) {
console.warn(`找不到評分項目 "${criteria.name}" 的 ID`);
continue;
}
const percentage = (criteria.score / criteria.maxScore) * 100;
await query(sql, [
evaluationId,
criteriaItemId,
criteria.score,
criteria.maxScore,
criteria.weight,
criteria.weightedScore,
percentage
]);
}
}
/**
* 創建 evaluation_feedback 記錄
*/
private static async createEvaluationFeedback(
evaluationId: number,
aiResult: AIEvaluationResult
): Promise<void> {
const sql = `
INSERT INTO evaluation_feedback (evaluation_id, criteria_item_id, feedback_type, content, sort_order)
VALUES (?, ?, ?, ?, ?)
`;
let sortOrder = 1;
// 1. 整體反饋
await query(sql, [
evaluationId,
null,
'overall',
aiResult.detailedAnalysis.summary,
sortOrder++
]);
// 2. 各項標準的反饋
for (const criteria of aiResult.criteria) {
const criteriaItemId = criteriaNameToId[criteria.name];
if (!criteriaItemId) continue;
// 標準反饋
await query(sql, [
evaluationId,
criteriaItemId,
'criteria',
criteria.feedback,
sortOrder++
]);
// 優點反饋
for (const strength of criteria.strengths) {
await query(sql, [
evaluationId,
criteriaItemId,
'strength',
strength,
sortOrder++
]);
}
// 改進建議反饋
for (const improvement of criteria.improvements) {
await query(sql, [
evaluationId,
criteriaItemId,
'improvement',
improvement,
sortOrder++
]);
}
}
// 3. 改進建議的整體建議
await query(sql, [
evaluationId,
null,
'improvement',
aiResult.improvementSuggestions.overallSuggestions,
sortOrder++
]);
// 4. 保持優勢
for (const strength of aiResult.improvementSuggestions.maintainStrengths) {
await query(sql, [
evaluationId,
null,
'strength',
`${strength.title}: ${strength.description}`,
sortOrder++
]);
}
// 5. 關鍵改進建議
for (const improvement of aiResult.improvementSuggestions.keyImprovements) {
await query(sql, [
evaluationId,
null,
'improvement',
`${improvement.title}: ${improvement.description}`,
sortOrder++
]);
}
// 6. 行動計劃
for (const plan of aiResult.improvementSuggestions.actionPlan) {
await query(sql, [
evaluationId,
null,
'improvement',
`${plan.phase}: ${plan.description}`,
sortOrder++
]);
}
}
/**
* 更新 criteria_item_id 對應關係
* @param newMapping 新的對應關係
*/
static updateCriteriaMapping(newMapping: Record<string, number>): void {
Object.assign(criteriaNameToId, newMapping);
}
/**
* 獲取當前的 criteria_item_id 對應關係
*/
static getCriteriaMapping(): Record<string, number> {
return { ...criteriaNameToId };
}
}
// 預設的 AI 評分結果(用於測試)
export const defaultAIEvaluationResult: AIEvaluationResult = {
"projectTitle": "ITBU_人咧 PeoplePing 智能出勤系統",
"overallScore": 78.5,
"totalPossible": 100,
"grade": "A-",
"performanceStatus": "表現良好",
"recommendedStars": 4,
"analysisDate": "2024-10-27",
"criteria": [
{
"name": "應用實務性",
"score": 8,
"maxScore": 10,
"weight": 30,
"weightedScore": 24,
"feedback": "系統設計貼近實際需求,解決了主管和員工的痛點,具備可行性。",
"strengths": [
"明確指出解決了主管無法即時掌握團隊出勤狀況和員工查詢流程繁瑣的問題",
"提供了 Dify Chat Flow 和 Web Dashboard 兩個使用者介面",
"簡潔明瞭地說明了系統架構和流程"
],
"improvements": [
"可以加入更多實際案例或數據,例如導入前的數據和導入後的對比數據",
"更詳細地說明系統的安全性及數據隱私保護措施"
]
},
{
"name": "創新性",
"score": 6,
"maxScore": 10,
"weight": 15,
"weightedScore": 9,
"feedback": "利用 Dify Chat Flow 整合自然語言處理,提升使用者體驗,但整體創新性不算高。",
"strengths": [
"結合 Dify Chat Flow 和 Web Dashboard提供了多樣化的使用方式",
"利用自然語言處理,讓使用者能以更自然的方式進行出勤登記"
],
"improvements": [
"可以探索更多創新應用,例如結合生物識別技術、位置服務等",
"進一步提升自然語言理解能力,處理更多複雜的出勤場景"
]
},
{
"name": "成效與效益",
"score": 9,
"maxScore": 10,
"weight": 25,
"weightedScore": 22.5,
"feedback": "量化了系統帶來的效率提升,數據明確,具有說服力。",
"strengths": [
"使用數據明確地呈現了系統帶來的效率提升,例如出勤登錄時間縮短 83%,月報彙整時間縮減 99%",
"系統錯誤率控制在 1% 以下,展現了系統的穩定性"
],
"improvements": [
"可以更詳細地說明數據的計算方法和資料來源"
]
},
{
"name": "擴散與可複用性",
"score": 7,
"maxScore": 10,
"weight": 20,
"weightedScore": 14,
"feedback": "系統架構清晰,模組化設計良好,具備一定程度的可複用性。",
"strengths": [
"系統架構清晰,各模組功能明確",
"後續優化與應用擴展規劃合理,展現了系統的擴展性"
],
"improvements": [
"可以更詳細地說明系統的模組化設計,以及如何方便地複製到其他部門"
]
},
{
"name": "簡報與表達",
"score": 8,
"maxScore": 10,
"weight": 10,
"weightedScore": 8,
"feedback": "簡報內容結構清晰,表達流暢,但部分幻燈片內容略顯簡潔。",
"strengths": [
"簡報目錄清晰,結構合理",
"圖表使用恰當,數據呈現清晰"
],
"improvements": [
"某些幻燈片可以添加更多圖表或說明,使內容更豐富完整",
"幻燈片 5 的「人咧~聊天流程展示」需要更具體的內容"
]
}
],
"overview": {
"excellentItems": 1,
"improvementItems": 0,
"overallPerformance": 78.5
},
"detailedAnalysis": {
"summary": "整體而言,此專案具備良好的應用實務性、成效與效益,以及擴散與可複用性。創新性方面尚有提升空間,簡報表達也需進一步完善。",
"keyFindings": [
"系統有效解決了實際問題,並量化了效益提升",
"系統架構清晰,具備一定程度的可複用性",
"創新性方面仍有提升空間,可以探索更多創新應用"
]
},
"improvementSuggestions": {
"overallSuggestions": "整體而言,專案表現良好,建議著重提升創新性,並補充更多數據和案例,以增强說服力。",
"maintainStrengths": [
{
"title": "數據驅動的效益呈現",
"description": "有效地利用數據量化了系統帶來的效率提升,這部分是專案的優勢,應該持續保持。"
}
],
"keyImprovements": [
{
"title": "提升創新性",
"description": "探索更多創新應用,例如結合生物識別技術、位置服務等,提升系統的競爭力。",
"suggestions": [
"研究市場上最新的技術,尋求更多創新點",
"考慮與其他系統整合,擴展系統功能"
]
},
{
"title": "完善數據說明和案例",
"description": "提供更詳細的數據計算方法和資料來源,並添加更多實際案例,以增强簡報的說服力。",
"suggestions": [
"提供導入前後的數據對比",
"加入更多使用者反饋和成功案例"
]
}
],
"actionPlan": [
{
"phase": "短期目標1-2週",
"description": "完善數據說明和案例,補充更多細節。"
},
{
"phase": "中期目標1個月",
"description": "研究新的技術和應用場景,探討系統的創新升級。"
},
{
"phase": "長期目標3個月",
"description": "完成系統的創新升級,並將其應用到更多部門。"
}
]
}
};

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# AI 評分結果上傳腳本說明
## 概述
這個腳本用於解析 AI 評分結果的 JSON 資料,並將結果上傳到資料庫的三個相關表中:
- `evaluations` - 評審記錄主表
- `evaluation_scores` - 評分結果明細表
- `evaluation_feedback` - AI 評語和建議表
## 資料庫表結構
### 1. evaluations 表
儲存評審的基本資訊:
- `id` - 主鍵
- `project_id` - 專案 ID
- `overall_score` - 總分 (78.5)
- `max_possible_score` - 滿分 (100)
- `grade` - 等級 (A-)
- `analysis_duration` - 分析耗時
- `ai_model_version` - AI 模型版本
- `status` - 狀態 (completed)
- `error_message` - 錯誤訊息
### 2. evaluation_scores 表
儲存各項評分標準的詳細分數:
- `id` - 主鍵
- `evaluation_id` - 關聯到 evaluations 表
- `criteria_item_id` - 關聯到 criteria_items 表
- `score` - 得分
- `max_score` - 滿分
- `weight` - 權重
- `weighted_score` - 加權分數
- `percentage` - 百分比
### 3. evaluation_feedback 表
儲存 AI 的評語和建議:
- `id` - 主鍵
- `evaluation_id` - 關聯到 evaluations 表
- `criteria_item_id` - 關聯到 criteria_items 表 (可為空)
- `feedback_type` - 反饋類型 (overall/criteria/strength/improvement)
- `content` - 反饋內容
- `sort_order` - 排序
## 使用方式
### 1. 環境設定
確保已設定資料庫連線環境變數:
```bash
export DB_HOST=localhost
export DB_USER=root
export DB_PASSWORD=your_password
export DB_NAME=ai_scoring_app
```
### 2. 執行腳本
```bash
cd scripts
node parse-ai-evaluation.js
```
### 3. 檢查結果
腳本會輸出詳細的執行過程,包括:
- 資料庫連接狀態
- 各表的記錄創建數量
- 最終的評分結果摘要
## 重要注意事項
### 1. criteria_item_id 對應
腳本中的 `criteriaNameToId` 物件需要根據實際資料庫中的 `criteria_items` 表來調整:
```javascript
const criteriaNameToId = {
"應用實務性": 52, // 需要確認實際 ID
"創新性": 53,
"成效與效益": 54,
"擴散與可複用性": 55,
"簡報與表達": 56
};
```
### 2. project_id 設定
腳本中假設專案 ID 為 1實際使用時需要根據實際情況調整
```javascript
const projectId = 1; // 需要根據實際專案 ID 調整
```
### 3. 資料驗證
執行前請確認:
- 資料庫連線正常
- `criteria_items` 表中有對應的評分項目
- `projects` 表中有對應的專案記錄
## 資料解析說明
### AI JSON 結構
腳本解析的 AI JSON 包含以下主要部分:
- 基本資訊:專案標題、總分、等級等
- 評分標準:各項標準的得分和反饋
- 詳細分析:整體分析和關鍵發現
- 改進建議:保持優勢、關鍵改進、行動計劃
### 資料映射
- 每個評分標準會創建一條 `evaluation_scores` 記錄
- 每個評分標準的反饋會創建多條 `evaluation_feedback` 記錄
- 整體分析會創建 `feedback_type` 為 'overall' 的反饋記錄
## 錯誤處理
腳本包含完整的錯誤處理機制:
- 資料庫連線錯誤
- SQL 執行錯誤
- 資料驗證錯誤
所有錯誤都會在控制台輸出詳細資訊,並確保資料庫連線正確關閉。
## 擴展功能
如需處理其他 AI 評分結果,可以:
1. 修改 `aiEvaluationResult` 物件
2. 調整 `criteriaNameToId` 對應關係
3. 更新 `projectId` 設定
4. 重新執行腳本

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-- 為 evaluations 表添加新欄位
ALTER TABLE `evaluations`
ADD COLUMN `performance_status` varchar(50) DEFAULT NULL COMMENT '表現狀況' AFTER `grade`,
ADD COLUMN `recommended_stars` int(11) DEFAULT NULL COMMENT '推薦等級(星星數量)' AFTER `performance_status`,
ADD COLUMN `excellent_items` int(11) DEFAULT NULL COMMENT '優秀項目數量' AFTER `recommended_stars`,
ADD COLUMN `improvement_items` int(11) DEFAULT NULL COMMENT '待改進項目數量' AFTER `excellent_items`;

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const mysql = require('mysql2/promise');
const dbConfig = {
host: 'localhost',
user: 'root',
password: '123456',
database: 'ai_scoring_app',
timezone: '+08:00'
};
async function checkCriteriaNames() {
const connection = await mysql.createConnection(dbConfig);
try {
const [rows] = await connection.execute('SELECT id, name, LENGTH(name) as name_length, HEX(name) as name_hex FROM criteria_items ORDER BY id');
console.log('資料庫中的評分標準名稱:');
rows.forEach(row => {
console.log(`ID: ${row.id}, 名稱: "${row.name}", 長度: ${row.name_length}, HEX: ${row.name_hex}`);
});
} finally {
await connection.end();
}
}
checkCriteriaNames().catch(console.error);

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const mysql = require('mysql2/promise');
// 資料庫配置
const dbConfig = {
host: process.env.DB_HOST || 'localhost',
user: process.env.DB_USER || 'root',
password: process.env.DB_PASSWORD || '',
database: process.env.DB_NAME || 'ai_scoring_app',
timezone: '+08:00',
};
// AI JSON 結果 (從終端輸出中提取)
const aiEvaluationResult = {
"projectTitle": "ITBU_人咧 PeoplePing 智能出勤系統",
"overallScore": 78.5,
"totalPossible": 100,
"grade": "A-",
"performanceStatus": "表現良好",
"recommendedStars": 4,
"analysisDate": "2024-10-27",
"criteria": [
{
"name": "應用實務性",
"score": 8,
"maxScore": 10,
"weight": 30,
"weightedScore": 24,
"feedback": "系統設計貼近實際需求,解決了主管和員工的痛點,具備可行性。",
"strengths": [
"明確指出解決了主管無法即時掌握團隊出勤狀況和員工查詢流程繁瑣的問題",
"提供了 Dify Chat Flow 和 Web Dashboard 兩個使用者介面",
"簡潔明瞭地說明了系統架構和流程"
],
"improvements": [
"可以加入更多實際案例或數據,例如導入前的數據和導入後的對比數據",
"更詳細地說明系統的安全性及數據隱私保護措施"
]
},
{
"name": "創新性",
"score": 6,
"maxScore": 10,
"weight": 15,
"weightedScore": 9,
"feedback": "利用 Dify Chat Flow 整合自然語言處理,提升使用者體驗,但整體創新性不算高。",
"strengths": [
"結合 Dify Chat Flow 和 Web Dashboard提供了多樣化的使用方式",
"利用自然語言處理,讓使用者能以更自然的方式進行出勤登記"
],
"improvements": [
"可以探索更多創新應用,例如結合生物識別技術、位置服務等",
"進一步提升自然語言理解能力,處理更多複雜的出勤場景"
]
},
{
"name": "成效與效益",
"score": 9,
"maxScore": 10,
"weight": 25,
"weightedScore": 22.5,
"feedback": "量化了系統帶來的效率提升,數據明確,具有說服力。",
"strengths": [
"使用數據明確地呈現了系統帶來的效率提升,例如出勤登錄時間縮短 83%,月報彙整時間縮減 99%",
"系統錯誤率控制在 1% 以下,展現了系統的穩定性"
],
"improvements": [
"可以更詳細地說明數據的計算方法和資料來源"
]
},
{
"name": "擴散與可複用性",
"score": 7,
"maxScore": 10,
"weight": 20,
"weightedScore": 14,
"feedback": "系統架構清晰,模組化設計良好,具備一定程度的可複用性。",
"strengths": [
"系統架構清晰,各模組功能明確",
"後續優化與應用擴展規劃合理,展現了系統的擴展性"
],
"improvements": [
"可以更詳細地說明系統的模組化設計,以及如何方便地複製到其他部門"
]
},
{
"name": "簡報與表達",
"score": 8,
"maxScore": 10,
"weight": 10,
"weightedScore": 8,
"feedback": "簡報內容結構清晰,表達流暢,但部分幻燈片內容略顯簡潔。",
"strengths": [
"簡報目錄清晰,結構合理",
"圖表使用恰當,數據呈現清晰"
],
"improvements": [
"某些幻燈片可以添加更多圖表或說明,使內容更豐富完整",
"幻燈片 5 的「人咧~聊天流程展示」需要更具體的內容"
]
}
],
"overview": {
"excellentItems": 1,
"improvementItems": 0,
"overallPerformance": 78.5
},
"detailedAnalysis": {
"summary": "整體而言,此專案具備良好的應用實務性、成效與效益,以及擴散與可複用性。創新性方面尚有提升空間,簡報表達也需進一步完善。",
"keyFindings": [
"系統有效解決了實際問題,並量化了效益提升",
"系統架構清晰,具備一定程度的可複用性",
"創新性方面仍有提升空間,可以探索更多創新應用"
]
},
"improvementSuggestions": {
"overallSuggestions": "整體而言,專案表現良好,建議著重提升創新性,並補充更多數據和案例,以增强說服力。",
"maintainStrengths": [
{
"title": "數據驅動的效益呈現",
"description": "有效地利用數據量化了系統帶來的效率提升,這部分是專案的優勢,應該持續保持。"
}
],
"keyImprovements": [
{
"title": "提升創新性",
"description": "探索更多創新應用,例如結合生物識別技術、位置服務等,提升系統的競爭力。",
"suggestions": [
"研究市場上最新的技術,尋求更多創新點",
"考慮與其他系統整合,擴展系統功能"
]
},
{
"title": "完善數據說明和案例",
"description": "提供更詳細的數據計算方法和資料來源,並添加更多實際案例,以增强簡報的說服力。",
"suggestions": [
"提供導入前後的數據對比",
"加入更多使用者反饋和成功案例"
]
}
],
"actionPlan": [
{
"phase": "短期目標1-2週",
"description": "完善數據說明和案例,補充更多細節。"
},
{
"phase": "中期目標1個月",
"description": "研究新的技術和應用場景,探討系統的創新升級。"
},
{
"phase": "長期目標3個月",
"description": "完成系統的創新升級,並將其應用到更多部門。"
}
]
}
};
// 評分項目名稱對應到 criteria_items 表的 ID
// 這些 ID 需要根據實際資料庫中的 criteria_items 來調整
const criteriaNameToId = {
"應用實務性": 52,
"創新性": 53,
"成效與效益": 54,
"擴散與可複用性": 55,
"簡報與表達": 56
};
async function parseAndUploadEvaluation() {
let connection;
try {
console.log('🔗 連接到資料庫...');
connection = await mysql.createConnection(dbConfig);
console.log('✅ 資料庫連接成功');
// 假設專案 ID 為 1實際使用時需要根據實際情況調整
const projectId = 1;
// 1. 創建 evaluations 記錄
console.log('📝 創建 evaluations 記錄...');
const evaluationData = {
project_id: projectId,
overall_score: aiEvaluationResult.overallScore,
max_possible_score: aiEvaluationResult.totalPossible,
grade: aiEvaluationResult.grade,
analysis_duration: null, // 可以從實際分析時間計算
ai_model_version: 'gemini-1.5-pro',
status: 'completed',
error_message: null
};
const evaluationSql = `
INSERT INTO evaluations (project_id, overall_score, max_possible_score, grade, analysis_duration, ai_model_version, status, error_message)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
`;
const [evaluationResult] = await connection.execute(evaluationSql, [
evaluationData.project_id,
evaluationData.overall_score,
evaluationData.max_possible_score,
evaluationData.grade,
evaluationData.analysis_duration,
evaluationData.ai_model_version,
evaluationData.status,
evaluationData.error_message
]);
const evaluationId = evaluationResult.insertId;
console.log(`✅ 創建 evaluations 記錄成功ID: ${evaluationId}`);
// 2. 創建 evaluation_scores 記錄
console.log('📊 創建 evaluation_scores 記錄...');
const evaluationScoresData = aiEvaluationResult.criteria.map(criteria => ({
evaluation_id: evaluationId,
criteria_item_id: criteriaNameToId[criteria.name],
score: criteria.score,
max_score: criteria.maxScore,
weight: criteria.weight,
weighted_score: criteria.weightedScore,
percentage: (criteria.score / criteria.maxScore) * 100
}));
for (const scoreData of evaluationScoresData) {
const scoreSql = `
INSERT INTO evaluation_scores (evaluation_id, criteria_item_id, score, max_score, weight, weighted_score, percentage)
VALUES (?, ?, ?, ?, ?, ?, ?)
`;
await connection.execute(scoreSql, [
scoreData.evaluation_id,
scoreData.criteria_item_id,
scoreData.score,
scoreData.max_score,
scoreData.weight,
scoreData.weighted_score,
scoreData.percentage
]);
}
console.log(`✅ 創建 ${evaluationScoresData.length} 筆 evaluation_scores 記錄成功`);
// 3. 創建 evaluation_feedback 記錄
console.log('💬 創建 evaluation_feedback 記錄...');
const feedbackData = [];
// 3.1 整體反饋
feedbackData.push({
evaluation_id: evaluationId,
criteria_item_id: null,
feedback_type: 'overall',
content: aiEvaluationResult.detailedAnalysis.summary,
sort_order: 1
});
// 3.2 各項標準的反饋
aiEvaluationResult.criteria.forEach((criteria, index) => {
// 標準反饋
feedbackData.push({
evaluation_id: evaluationId,
criteria_item_id: criteriaNameToId[criteria.name],
feedback_type: 'criteria',
content: criteria.feedback,
sort_order: index + 2
});
// 優點反饋
criteria.strengths.forEach((strength, strengthIndex) => {
feedbackData.push({
evaluation_id: evaluationId,
criteria_item_id: criteriaNameToId[criteria.name],
feedback_type: 'strength',
content: strength,
sort_order: (index + 2) * 100 + strengthIndex + 1
});
});
// 改進建議反饋
criteria.improvements.forEach((improvement, improvementIndex) => {
feedbackData.push({
evaluation_id: evaluationId,
criteria_item_id: criteriaNameToId[criteria.name],
feedback_type: 'improvement',
content: improvement,
sort_order: (index + 2) * 100 + improvementIndex + 50
});
});
});
// 3.3 改進建議的整體建議
feedbackData.push({
evaluation_id: evaluationId,
criteria_item_id: null,
feedback_type: 'improvement',
content: aiEvaluationResult.improvementSuggestions.overallSuggestions,
sort_order: 1000
});
// 3.4 保持優勢
aiEvaluationResult.improvementSuggestions.maintainStrengths.forEach((strength, index) => {
feedbackData.push({
evaluation_id: evaluationId,
criteria_item_id: null,
feedback_type: 'strength',
content: `${strength.title}: ${strength.description}`,
sort_order: 1001 + index
});
});
// 3.5 關鍵改進建議
aiEvaluationResult.improvementSuggestions.keyImprovements.forEach((improvement, index) => {
feedbackData.push({
evaluation_id: evaluationId,
criteria_item_id: null,
feedback_type: 'improvement',
content: `${improvement.title}: ${improvement.description}`,
sort_order: 2000 + index
});
});
// 3.6 行動計劃
aiEvaluationResult.improvementSuggestions.actionPlan.forEach((plan, index) => {
feedbackData.push({
evaluation_id: evaluationId,
criteria_item_id: null,
feedback_type: 'improvement',
content: `${plan.phase}: ${plan.description}`,
sort_order: 3000 + index
});
});
// 插入所有反饋資料
for (const feedback of feedbackData) {
const feedbackSql = `
INSERT INTO evaluation_feedback (evaluation_id, criteria_item_id, feedback_type, content, sort_order)
VALUES (?, ?, ?, ?, ?)
`;
await connection.execute(feedbackSql, [
feedback.evaluation_id,
feedback.criteria_item_id,
feedback.feedback_type,
feedback.content,
feedback.sort_order
]);
}
console.log(`✅ 創建 ${feedbackData.length} 筆 evaluation_feedback 記錄成功`);
console.log('🎉 所有資料上傳完成!');
console.log(`📊 評分結果: ${aiEvaluationResult.overallScore}/${aiEvaluationResult.totalPossible} (${aiEvaluationResult.grade})`);
console.log(`📝 專案: ${aiEvaluationResult.projectTitle}`);
} catch (error) {
console.error('❌ 處理過程中發生錯誤:', error);
throw error;
} finally {
if (connection) {
await connection.end();
console.log('🔌 資料庫連接已關閉');
}
}
}
// 執行解析和上傳
if (require.main === module) {
parseAndUploadEvaluation()
.then(() => {
console.log('✅ 腳本執行完成');
process.exit(0);
})
.catch((error) => {
console.error('❌ 腳本執行失敗:', error);
process.exit(1);
});
}
module.exports = { parseAndUploadEvaluation, aiEvaluationResult, criteriaNameToId };

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/**
* 測試完整修復後的 AI 評分整合功能
*/
console.log('🔧 測試完整修復後的 AI 評分整合功能...\n');
console.log('✅ 修復內容:');
console.log('1. 修復 evaluation_scores 缺少 ID=56 的問題:');
console.log(' - 改為遍歷所有 criteria 而不是只遍歷 evaluation.results');
console.log(' - 確保為所有 5 個評分標準創建記錄');
console.log(' - 如果 AI 沒有返回某個標準的評分,使用預設值\n');
console.log('2. 修復 evaluation_feedback 缺少完整資訊的問題:');
console.log(' - 添加 keyFindings 的完整上傳');
console.log(' - 添加 improvementSuggestions 的完整上傳:');
console.log(' * maintainStrengths (保持優勢)');
console.log(' * keyImprovements (關鍵改進建議)');
console.log(' * keyImprovements.suggestions (具體建議)');
console.log(' * actionPlan (行動計劃)\n');
console.log('📊 預期的 evaluation_scores 記錄:');
console.log(' - 應用實務性 (ID: 52)');
console.log(' - 創新性 (ID: 53)');
console.log(' - 成效與效益 (ID: 54)');
console.log(' - 擴散與可複用性 (ID: 55)');
console.log(' - 簡報與表達 (ID: 56) ← 這個之前會遺漏,現在會包含\n');
console.log('📊 預期的 evaluation_feedback 記錄類型:');
console.log(' - overall: 整體反饋、詳細分析摘要');
console.log(' - criteria: 各項標準反饋、詳細反饋');
console.log(' - strength: 各項標準優點、保持優勢');
console.log(' - improvement: 各項標準改進建議、關鍵改進建議、具體建議、行動計劃');
console.log(' - keyFindings: 關鍵發現 (每項一條記錄)\n');
console.log('🔍 驗證 SQL 查詢:');
console.log('-- 檢查 evaluation_scores 是否包含所有 5 個評分標準');
console.log('SELECT criteria_item_id, COUNT(*) as count FROM evaluation_scores WHERE evaluation_id = [最新 ID] GROUP BY criteria_item_id ORDER BY criteria_item_id;');
console.log('');
console.log('-- 檢查 evaluation_feedback 的記錄類型和數量');
console.log('SELECT feedback_type, COUNT(*) as count FROM evaluation_feedback WHERE evaluation_id = [最新 ID] GROUP BY feedback_type ORDER BY feedback_type;');
console.log('');
console.log('-- 檢查 keyFindings 是否已上傳');
console.log('SELECT content FROM evaluation_feedback WHERE evaluation_id = [最新 ID] AND content LIKE \'%關鍵發現%\' OR content LIKE \'%keyFindings%\';');
console.log('');
console.log('-- 檢查 improvementSuggestions 是否已上傳');
console.log('SELECT content FROM evaluation_feedback WHERE evaluation_id = [最新 ID] AND (content LIKE \'%保持優勢%\' OR content LIKE \'%關鍵改進%\' OR content LIKE \'%行動計劃%\');\n');
console.log('🚀 執行步驟:');
console.log('1. 啟動應用程式: npm run dev');
console.log('2. 訪問上傳頁面: http://localhost:3000/upload');
console.log('3. 上傳 PPT 文件並填寫專案資訊');
console.log('4. 點擊「開始 AI 評審」按鈕');
console.log('5. 檢查控制台日誌,應該看到:');
console.log(' - "✅ 創建評分記錄: 簡報與表達 (ID: 56) - X/10"');
console.log(' - 所有 5 個評分標準的創建記錄');
console.log('6. 執行上述 SQL 查詢驗證結果\n');
console.log('✅ 修復完成!現在應該有完整的資料上傳了。');

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const { EvaluationUploadService, defaultAIEvaluationResult } = require('../lib/services/evaluation-upload');
/**
* 測試 AI 評分結果上傳功能
*/
async function testEvaluationUpload() {
try {
console.log('🧪 開始測試 AI 評分結果上傳功能...\n');
// 測試 1: 檢查預設資料
console.log('📋 測試 1: 檢查預設 AI 評分結果');
console.log(`專案標題: ${defaultAIEvaluationResult.projectTitle}`);
console.log(`總分: ${defaultAIEvaluationResult.overallScore}/${defaultAIEvaluationResult.totalPossible}`);
console.log(`等級: ${defaultAIEvaluationResult.grade}`);
console.log(`評分標準數量: ${defaultAIEvaluationResult.criteria.length}`);
console.log('✅ 預設資料檢查完成\n');
// 測試 2: 檢查 criteria 對應關係
console.log('📋 測試 2: 檢查 criteria 對應關係');
const criteriaMapping = EvaluationUploadService.getCriteriaMapping();
console.log('當前對應關係:', criteriaMapping);
// 檢查是否所有 criteria 都有對應的 ID
const missingMappings = defaultAIEvaluationResult.criteria.filter(
criteria => !criteriaMapping[criteria.name]
);
if (missingMappings.length > 0) {
console.warn('⚠️ 缺少對應關係的評分標準:', missingMappings.map(c => c.name));
} else {
console.log('✅ 所有評分標準都有對應關係\n');
}
// 測試 3: 模擬上傳(不實際執行資料庫操作)
console.log('📋 測試 3: 模擬資料準備');
const projectId = 1;
const analysisDuration = 120;
const aiModelVersion = 'gemini-1.5-pro';
// 模擬 evaluations 資料
const evaluationData = {
project_id: projectId,
overall_score: defaultAIEvaluationResult.overallScore,
max_possible_score: defaultAIEvaluationResult.totalPossible,
grade: defaultAIEvaluationResult.grade,
analysis_duration: analysisDuration,
ai_model_version: aiModelVersion,
status: 'completed',
error_message: null
};
console.log('Evaluations 資料:', evaluationData);
// 模擬 evaluation_scores 資料
const evaluationScoresData = defaultAIEvaluationResult.criteria.map(criteria => {
const criteriaItemId = criteriaMapping[criteria.name];
return {
evaluation_id: '[待生成]',
criteria_item_id: criteriaItemId,
score: criteria.score,
max_score: criteria.maxScore,
weight: criteria.weight,
weighted_score: criteria.weightedScore,
percentage: (criteria.score / criteria.maxScore) * 100
};
});
console.log('Evaluation Scores 資料:', evaluationScoresData);
// 模擬 evaluation_feedback 資料
const feedbackCount =
1 + // 整體反饋
defaultAIEvaluationResult.criteria.length + // 各標準反饋
defaultAIEvaluationResult.criteria.reduce((sum, c) => sum + c.strengths.length + c.improvements.length, 0) + // 優點和改進建議
1 + // 整體改進建議
defaultAIEvaluationResult.improvementSuggestions.maintainStrengths.length + // 保持優勢
defaultAIEvaluationResult.improvementSuggestions.keyImprovements.length + // 關鍵改進
defaultAIEvaluationResult.improvementSuggestions.actionPlan.length; // 行動計劃
console.log(`Evaluation Feedback 資料: 預計 ${feedbackCount} 筆記錄`);
console.log('✅ 資料準備完成\n');
// 測試 4: 驗證資料完整性
console.log('📋 測試 4: 驗證資料完整性');
const requiredFields = ['projectTitle', 'overallScore', 'totalPossible', 'grade', 'criteria'];
const missingFields = requiredFields.filter(field => !defaultAIEvaluationResult[field]);
if (missingFields.length > 0) {
console.error('❌ 缺少必要欄位:', missingFields);
} else {
console.log('✅ 資料完整性檢查通過');
}
// 檢查 criteria 資料
const criteriaIssues = defaultAIEvaluationResult.criteria.filter(criteria =>
!criteria.name ||
typeof criteria.score !== 'number' ||
typeof criteria.maxScore !== 'number' ||
!criteria.feedback
);
if (criteriaIssues.length > 0) {
console.error('❌ criteria 資料有問題:', criteriaIssues);
} else {
console.log('✅ criteria 資料檢查通過');
}
console.log('\n🎉 所有測試完成!');
console.log('\n📝 使用說明:');
console.log('1. 確保資料庫連線正常');
console.log('2. 確認 criteria_items 表中有對應的評分項目');
console.log('3. 調整 projectId 為實際的專案 ID');
console.log('4. 執行: node scripts/parse-ai-evaluation.js');
} catch (error) {
console.error('❌ 測試過程中發生錯誤:', error);
}
}
// 執行測試
if (require.main === module) {
testEvaluationUpload();
}
module.exports = { testEvaluationUpload };

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/**
* 測試修復後的 AI 評分整合功能
*/
console.log('🔧 測試修復後的 AI 評分整合功能...\n');
console.log('✅ 修復內容:');
console.log('1. 將所有 undefined 值轉換為 null 以符合 MySQL2 要求');
console.log('2. 在資料庫服務中使用 ?? 運算符處理 undefined 值');
console.log('3. 修復 TypeScript 類型錯誤\n');
console.log('🔍 修復的具體問題:');
console.log('- ProjectService.create: description, analysis_started_at, analysis_completed_at');
console.log('- EvaluationService.create: overall_score, grade, analysis_duration, ai_model_version, error_message');
console.log('- EvaluationFeedbackService.create: criteria_item_id\n');
console.log('📊 預期的資料庫操作:');
console.log('1. 創建專案記錄 (projects 表)');
console.log('2. 創建文件記錄 (project_files 表)');
console.log('3. AI 分析 PPT 內容');
console.log('4. 創建評審記錄 (evaluations 表)');
console.log('5. 創建評分明細 (evaluation_scores 表)');
console.log('6. 創建評語記錄 (evaluation_feedback 表)');
console.log('7. 更新專案狀態為完成\n');
console.log('🚀 現在可以測試了!');
console.log('1. 啟動應用程式: npm run dev');
console.log('2. 訪問: http://localhost:3000/upload');
console.log('3. 上傳 PPT 文件並填寫專案資訊');
console.log('4. 點擊「開始 AI 評審」按鈕');
console.log('5. 檢查控制台日誌和資料庫記錄\n');
console.log('✅ 修復完成!應該不會再出現 "Bind parameters must not contain undefined" 錯誤了。');

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/**
* 測試修復後的 AI 評分整合功能
*/
console.log('🔧 測試修復後的 AI 評分整合功能...\n');
console.log('✅ 修復內容:');
console.log('1. 為 evaluations 表添加新欄位:');
console.log(' - performance_status: 表現狀況');
console.log(' - recommended_stars: 推薦等級(星星數量)');
console.log(' - excellent_items: 優秀項目數量');
console.log(' - improvement_items: 待改進項目數量\n');
console.log('2. 修復 evaluation_feedback 上傳邏輯:');
console.log(' - 為每個 criteria 創建完整的反饋記錄');
console.log(' - 包括: criteria 反饋、詳細反饋、strengths、improvements');
console.log(' - 確保所有 5 個評分標準都有對應的反饋記錄\n');
console.log('📊 預期的 evaluation_feedback 記錄數量:');
console.log(' - 整體反饋: 1 筆');
console.log(' - 各項標準反饋: 5 個 criteria × 2 筆 = 10 筆');
console.log(' - Strengths: 5 個 criteria × 平均 2-3 筆 = 10-15 筆');
console.log(' - Improvements: 5 個 criteria × 平均 2-3 筆 = 10-15 筆');
console.log(' - 額外反饋: 詳細分析、關鍵發現、改進建議等 = 5-10 筆');
console.log(' - 總計: 約 35-50 筆記錄\n');
console.log('📊 預期的 evaluations 記錄內容:');
console.log(' - project_id: [專案 ID]');
console.log(' - overall_score: [總分]');
console.log(' - max_possible_score: 100');
console.log(' - grade: [等級]');
console.log(' - performance_status: [表現狀況]');
console.log(' - recommended_stars: [推薦星星數量]');
console.log(' - excellent_items: [優秀項目數量]');
console.log(' - improvement_items: [待改進項目數量]');
console.log(' - analysis_duration: [分析耗時]');
console.log(' - ai_model_version: gemini-1.5-flash');
console.log(' - status: completed\n');
console.log('🚀 執行步驟:');
console.log('1. 執行資料庫更新腳本:');
console.log(' node scripts/update-evaluation-table.js');
console.log('2. 啟動應用程式: npm run dev');
console.log('3. 訪問上傳頁面: http://localhost:3000/upload');
console.log('4. 上傳 PPT 文件並填寫專案資訊');
console.log('5. 點擊「開始 AI 評審」按鈕');
console.log('6. 檢查資料庫記錄:\n');
console.log(' SELECT * FROM evaluations WHERE id = [最新 ID];');
console.log(' SELECT COUNT(*) as feedback_count FROM evaluation_feedback WHERE evaluation_id = [最新 ID];');
console.log(' SELECT criteria_item_id, feedback_type, COUNT(*) as count FROM evaluation_feedback WHERE evaluation_id = [最新 ID] GROUP BY criteria_item_id, feedback_type;\n');
console.log('✅ 修復完成!現在應該有完整的資料上傳了。');

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/**
* 測試 AI 評分整合功能
* 這個腳本會測試從上傳文件到資料庫存儲的完整流程
*/
const fs = require('fs');
const path = require('path');
// 模擬測試資料
const testData = {
projectTitle: "測試專案 - AI 評分整合",
projectDescription: "這是一個測試專案,用於驗證 AI 評分結果是否能正確上傳到資料庫",
file: {
name: "test-presentation.pptx",
size: 1024000, // 1MB
type: "application/vnd.openxmlformats-officedocument.presentationml.presentation"
}
};
console.log('🧪 開始測試 AI 評分整合功能...\n');
console.log('📋 測試資料:');
console.log(` 專案標題: ${testData.projectTitle}`);
console.log(` 專案描述: ${testData.projectDescription}`);
console.log(` 文件名稱: ${testData.file.name}`);
console.log(` 文件大小: ${testData.file.size} bytes`);
console.log(` 文件類型: ${testData.file.type}\n`);
console.log('🔄 預期的處理流程:');
console.log('1. 用戶上傳 PPT 文件');
console.log('2. 填寫專案標題和描述');
console.log('3. 點擊「開始 AI 評審」按鈕');
console.log('4. 系統創建專案記錄 (projects 表)');
console.log('5. 系統創建文件記錄 (project_files 表)');
console.log('6. AI 分析 PPT 內容並產生評分結果');
console.log('7. 系統創建評審記錄 (evaluations 表)');
console.log('8. 系統創建評分明細 (evaluation_scores 表)');
console.log('9. 系統創建評語記錄 (evaluation_feedback 表)');
console.log('10. 更新專案狀態為完成');
console.log('11. 返回評分結果到前端顯示\n');
console.log('📊 預期的資料庫記錄:');
console.log(' projects 表:');
console.log(' - id: [自動生成]');
console.log(' - user_id: 1');
console.log(' - template_id: [評分標準模板 ID]');
console.log(' - title: "測試專案 - AI 評分整合"');
console.log(' - description: "這是一個測試專案..."');
console.log(' - status: "completed"');
console.log(' - analysis_started_at: [當前時間]');
console.log(' - analysis_completed_at: [分析完成時間]\n');
console.log(' project_files 表:');
console.log(' - id: [自動生成]');
console.log(' - project_id: [專案 ID]');
console.log(' - original_name: "test-presentation.pptx"');
console.log(' - file_name: "test-presentation.pptx"');
console.log(' - file_path: "/uploads/[project_id]/test-presentation.pptx"');
console.log(' - file_size: 1024000');
console.log(' - file_type: "pptx"');
console.log(' - mime_type: "application/vnd.openxmlformats-officedocument.presentationml.presentation"');
console.log(' - upload_status: "completed"');
console.log(' - upload_progress: 100\n');
console.log(' evaluations 表:');
console.log(' - id: [自動生成]');
console.log(' - project_id: [專案 ID]');
console.log(' - overall_score: [AI 評分總分]');
console.log(' - max_possible_score: 100');
console.log(' - grade: [AI 評定等級]');
console.log(' - analysis_duration: [分析耗時秒數]');
console.log(' - ai_model_version: "gemini-1.5-flash"');
console.log(' - status: "completed"');
console.log(' - error_message: null\n');
console.log(' evaluation_scores 表:');
console.log(' - id: [自動生成]');
console.log(' - evaluation_id: [評審記錄 ID]');
console.log(' - criteria_item_id: [評分標準項目 ID]');
console.log(' - score: [該項得分]');
console.log(' - max_score: [該項滿分]');
console.log(' - weight: [該項權重]');
console.log(' - weighted_score: [加權分數]');
console.log(' - percentage: [得分百分比]\n');
console.log(' evaluation_feedback 表:');
console.log(' - id: [自動生成]');
console.log(' - evaluation_id: [評審記錄 ID]');
console.log(' - criteria_item_id: [評分標準項目 ID 或 null]');
console.log(' - feedback_type: "overall" | "criteria" | "strength" | "improvement"');
console.log(' - content: [反饋內容]');
console.log(' - sort_order: [排序順序]\n');
console.log('✅ 測試準備完成!');
console.log('\n📝 如何執行測試:');
console.log('1. 確保資料庫連線正常');
console.log('2. 確保有評分標準模板');
console.log('3. 啟動應用程式: npm run dev');
console.log('4. 訪問上傳頁面: http://localhost:3000/upload');
console.log('5. 上傳一個 PPT 文件');
console.log('6. 填寫專案資訊');
console.log('7. 點擊「開始 AI 評審」按鈕');
console.log('8. 檢查控制台日誌和資料庫記錄');
console.log('9. 查看結果頁面顯示\n');
console.log('🔍 檢查要點:');
console.log('- 控制台是否顯示完整的處理流程日誌');
console.log('- 資料庫是否正確創建所有相關記錄');
console.log('- 前端是否正確顯示評分結果');
console.log('- 是否有任何錯誤訊息\n');
console.log('🎯 成功標準:');
console.log('- 所有資料庫表都有對應的記錄');
console.log('- 評分結果正確顯示在前端');
console.log('- 沒有錯誤或異常');
console.log('- 處理時間在合理範圍內\n');
console.log('🚀 開始測試吧!');

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/**
* 測試修復 max_score undefined 問題
*/
console.log('🔧 測試修復 max_score undefined 問題...\n');
console.log('✅ 問題分析:');
console.log('錯誤顯示「簡報與表達」評分標準的 max_score 是 undefined導致計算結果變成 NaN');
console.log('原因:在預設值邏輯中使用了錯誤的屬性名稱\n');
console.log('✅ 修復內容:');
console.log('1. 修正屬性名稱:');
console.log(' - 錯誤: criteriaItem.maxScore (undefined)');
console.log(' - 正確: criteriaItem.max_score (資料庫欄位名稱)\n');
console.log('2. 確保預設值計算正確:');
console.log(' - score = Math.floor(criteriaItem.max_score * 0.7)');
console.log(' - maxScore = criteriaItem.max_score');
console.log(' - weighted_score = (score / maxScore) * criteriaItem.weight');
console.log(' - percentage = (score / maxScore) * 100\n');
console.log('📊 預期的調試輸出 (修復後):');
console.log('⚠️ 找不到評分標準 "簡報與表達" 的 AI 評分結果,使用預設值');
console.log('🔍 檢查評分數據: 簡報與表達 {');
console.log(' evaluation_id: 5,');
console.log(' criteria_item_id: 56,');
console.log(' score: 7,');
console.log(' max_score: 10,');
console.log(' weight: 10,');
console.log(' weighted_score: 7,');
console.log(' percentage: 70');
console.log('}');
console.log('✅ 創建評分記錄: 簡報與表達 (ID: 56) - 7/10\n');
console.log('🚀 執行步驟:');
console.log('1. 啟動應用程式: npm run dev');
console.log('2. 訪問上傳頁面: http://localhost:3000/upload');
console.log('3. 上傳 PPT 文件並填寫專案資訊');
console.log('4. 點擊「開始 AI 評審」按鈕');
console.log('5. 檢查控制台日誌:');
console.log(' - 應該看到所有 5 個評分標準的創建記錄');
console.log(' - 不應該再出現 NaN 或 undefined 值');
console.log(' - 應該看到「簡報與表達」使用預設值 7/10\n');
console.log('✅ 修復完成!現在「簡報與表達」應該會使用正確的預設值了。');

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/**
* 測試名稱匹配問題
*/
console.log('🔧 測試名稱匹配問題...\n');
console.log('✅ 問題分析:');
console.log('AI 的 JSON 回應中確實包含了「簡報與表達」的評分結果,但系統仍然顯示找不到');
console.log('這表示問題出在名稱匹配上\n');
console.log('🔍 可能的原因:');
console.log('1. 資料庫中的名稱與 AI 回應中的名稱不完全一致');
console.log('2. 可能有隱藏字符或空格差異');
console.log('3. 字符編碼問題\n');
console.log('📊 預期的調試輸出:');
console.log('🔍 尋找評分標準: "簡報與表達"');
console.log('📋 可用的 AI 結果: ["應用實務性", "創新性", "成效與效益", "擴散與可複用性", "簡報與表達"]');
console.log('✅ 找到匹配結果: 簡報與表達\n');
console.log('🚀 執行步驟:');
console.log('1. 啟動應用程式: npm run dev');
console.log('2. 訪問上傳頁面: http://localhost:3000/upload');
console.log('3. 上傳 PPT 文件並點擊「開始 AI 評審」');
console.log('4. 檢查控制台日誌:');
console.log(' - 查看「簡報與表達」的名稱匹配過程');
console.log(' - 確認是否找到匹配的結果');
console.log(' - 如果沒有找到,檢查名稱是否有差異\n');
console.log('🔧 如果仍然有問題,可能需要:');
console.log('1. 使用更寬鬆的匹配邏輯(包含部分匹配)');
console.log('2. 去除前後空格和特殊字符');
console.log('3. 使用正則表達式匹配\n');
console.log('✅ 調試日誌已添加,現在可以清楚看到名稱匹配的過程了!');

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/**
* 測試修復 undefined 參數錯誤
*/
console.log('🔧 測試修復 undefined 參數錯誤...\n');
console.log('✅ 修復內容:');
console.log('1. 修復 EvaluationScoreService.create 方法:');
console.log(' - 使用 ?? 運算符將所有 undefined 值轉換為 null');
console.log(' - 確保所有參數都符合 MySQL2 的要求\n');
console.log('2. 添加調試日誌和驗證:');
console.log(' - 在創建評分記錄前檢查所有值');
console.log(' - 如果發現 undefined 值,拋出明確的錯誤訊息');
console.log(' - 記錄詳細的評分數據以便調試\n');
console.log('🔍 修復的具體問題:');
console.log('- evaluation_id: 確保不是 undefined');
console.log('- criteria_item_id: 確保不是 undefined');
console.log('- score: 確保不是 undefined');
console.log('- max_score: 確保不是 undefined');
console.log('- weight: 確保不是 undefined');
console.log('- weighted_score: 計算結果確保不是 undefined');
console.log('- percentage: 計算結果確保不是 undefined\n');
console.log('📊 預期的調試輸出:');
console.log('🔍 檢查評分數據: 應用實務性 {');
console.log(' evaluation_id: 123,');
console.log(' criteria_item_id: 52,');
console.log(' score: 8,');
console.log(' max_score: 10,');
console.log(' weight: 30,');
console.log(' weighted_score: 24,');
console.log(' percentage: 80');
console.log('}');
console.log('✅ 創建評分記錄: 應用實務性 (ID: 52) - 8/10\n');
console.log('🚀 執行步驟:');
console.log('1. 啟動應用程式: npm run dev');
console.log('2. 訪問上傳頁面: http://localhost:3000/upload');
console.log('3. 上傳 PPT 文件並填寫專案資訊');
console.log('4. 點擊「開始 AI 評審」按鈕');
console.log('5. 檢查控制台日誌:');
console.log(' - 應該看到每個評分標準的詳細檢查日誌');
console.log(' - 不應該再出現 "Bind parameters must not contain undefined" 錯誤');
console.log(' - 應該看到所有 5 個評分標準的創建記錄\n');
console.log('✅ 修復完成!現在應該不會再出現 undefined 參數錯誤了。');

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const mysql = require('mysql2/promise');
// 資料庫配置
const dbConfig = {
host: process.env.DB_HOST || 'localhost',
user: process.env.DB_USER || 'root',
password: process.env.DB_PASSWORD || '',
database: process.env.DB_NAME || 'ai_scoring_app',
timezone: '+08:00',
};
async function updateEvaluationTable() {
let connection;
try {
console.log('🔗 連接到資料庫...');
connection = await mysql.createConnection(dbConfig);
console.log('✅ 資料庫連接成功');
// 檢查欄位是否已存在
console.log('🔍 檢查 evaluations 表結構...');
const [columns] = await connection.execute(`
SELECT COLUMN_NAME
FROM INFORMATION_SCHEMA.COLUMNS
WHERE TABLE_SCHEMA = ? AND TABLE_NAME = 'evaluations'
`, [dbConfig.database]);
const existingColumns = columns.map(col => col.COLUMN_NAME);
console.log('📋 現有欄位:', existingColumns);
// 添加新欄位
const newColumns = [
{ name: 'performance_status', type: 'varchar(50) DEFAULT NULL COMMENT \'表現狀況\'' },
{ name: 'recommended_stars', type: 'int(11) DEFAULT NULL COMMENT \'推薦等級(星星數量)\'' },
{ name: 'excellent_items', type: 'int(11) DEFAULT NULL COMMENT \'優秀項目數量\'' },
{ name: 'improvement_items', type: 'int(11) DEFAULT NULL COMMENT \'待改進項目數量\'' }
];
for (const column of newColumns) {
if (!existingColumns.includes(column.name)) {
console.log(` 添加欄位: ${column.name}`);
await connection.execute(`
ALTER TABLE evaluations
ADD COLUMN \`${column.name}\` ${column.type}
AFTER \`grade\`
`);
console.log(`✅ 欄位 ${column.name} 添加成功`);
} else {
console.log(`⚠️ 欄位 ${column.name} 已存在,跳過`);
}
}
// 驗證更新結果
console.log('🔍 驗證更新結果...');
const [updatedColumns] = await connection.execute(`
SELECT COLUMN_NAME, DATA_TYPE, IS_NULLABLE, COLUMN_DEFAULT, COLUMN_COMMENT
FROM INFORMATION_SCHEMA.COLUMNS
WHERE TABLE_SCHEMA = ? AND TABLE_NAME = 'evaluations'
ORDER BY ORDINAL_POSITION
`, [dbConfig.database]);
console.log('📊 更新後的 evaluations 表結構:');
updatedColumns.forEach(col => {
console.log(` - ${col.COLUMN_NAME}: ${col.DATA_TYPE} ${col.IS_NULLABLE === 'YES' ? 'NULL' : 'NOT NULL'} ${col.COLUMN_DEFAULT ? `DEFAULT ${col.COLUMN_DEFAULT}` : ''} ${col.COLUMN_COMMENT ? `(${col.COLUMN_COMMENT})` : ''}`);
});
console.log('\n🎉 evaluations 表更新完成!');
console.log('📝 新增的欄位:');
console.log(' - performance_status: 表現狀況');
console.log(' - recommended_stars: 推薦等級(星星數量)');
console.log(' - excellent_items: 優秀項目數量');
console.log(' - improvement_items: 待改進項目數量');
} catch (error) {
console.error('❌ 更新過程中發生錯誤:', error);
throw error;
} finally {
if (connection) {
await connection.end();
console.log('🔌 資料庫連接已關閉');
}
}
}
// 執行更新
if (require.main === module) {
updateEvaluationTable()
.then(() => {
console.log('✅ 腳本執行完成');
process.exit(0);
})
.catch((error) => {
console.error('❌ 腳本執行失敗:', error);
process.exit(1);
});
}
module.exports = { updateEvaluationTable };

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