refactor: 簡化API設計，移除statistics計算和userLevel參數
- 移除後端statistics計算邏輯，改由前端處理 - 移除userLevel參數，簡化API接口 - 清理DTO模型中的多餘欄位 (Tags, IsIdiom, UserLevel) - 更新AI模型名稱為gemini-1.5-flash - 新增完整的AI Prompt設計規格 - 建立AI驅動產品後端技術架構指南 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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AI生成功能後端API規格.md
232
AI生成功能後端API規格.md
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@ -5,7 +5,7 @@
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- **文件名稱**: AI生成功能後端API規格
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- **版本**: v1.0
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- **建立日期**: 2025-01-25
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- **最後更新**: 2025-01-25
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- **最後更新**: 2025-01-25 (修正API規格)
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- **負責團隊**: DramaLing後端開發團隊
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- **對應前端**: `/app/generate/page.tsx`
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@ -57,7 +57,7 @@ External Services:
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語言: C# / .NET 8
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框架: ASP.NET Core Web API
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資料庫: PostgreSQL + Redis (緩存)
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AI服務: Google Gemini API
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AI服務: Google Gemini 1.5 Flash API (包含結構化Prompt設計)
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部署: Docker + Kubernetes
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監控: Application Insights
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```
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@ -79,7 +79,6 @@ Authorization: Bearer {token}
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```json
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{
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"inputText": "She just join the team, so let's cut her some slack until she get used to the workflow.",
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"userLevel": "A2",
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"analysisMode": "full",
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"options": {
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"includeGrammarCheck": true,
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@ -95,7 +94,6 @@ Authorization: Bearer {token}
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| 參數 | 類型 | 必需 | 說明 |
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|------|------|------|------|
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| inputText | string | 是 | 待分析的英文句子 (最多300字) |
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| userLevel | string | 是 | 用戶CEFR等級 (A1-C2) |
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| analysisMode | string | 否 | 分析模式: "basic"\|"full" (預設: "full") |
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| options | object | 否 | 分析選項配置 |
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@ -142,7 +140,6 @@ Authorization: Bearer {token}
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"synonyms": ["her"],
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"example": "She is a teacher.",
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"exampleTranslation": "她是一名老師。",
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"tags": ["basic", "pronoun"]
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},
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"just": {
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"word": "just",
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@ -155,7 +152,6 @@ Authorization: Bearer {token}
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"synonyms": ["recently", "only", "merely"],
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"example": "I just arrived.",
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"exampleTranslation": "我剛到。",
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"tags": ["time", "adverb"]
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}
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},
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"idioms": [
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@ -175,20 +171,10 @@ Authorization: Bearer {token}
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"exampleTranslation": "對他寬容一點，他是新來的。"
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}
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],
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"statistics": {
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"totalWords": 16,
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"uniqueWords": 15,
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"simpleWords": 8,
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"moderateWords": 4,
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"difficultWords": 3,
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"idioms": 1,
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"averageDifficulty": "A2"
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},
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"metadata": {
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"analysisModel": "gemini-pro",
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"analysisVersion": "1.0",
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"analysisModel": "gemini-1.5-flash",
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"analysisVersion": "2.0",
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"processingDate": "2025-01-25T10:30:00Z",
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"userLevel": "A2"
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}
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}
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}
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@ -228,7 +214,6 @@ interface VocabularyAnalysis {
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synonyms: string[] // 同義詞
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example?: string // 例句
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exampleTranslation?: string // 例句翻譯
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tags: string[] // 標籤分類
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}
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```
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@ -250,6 +235,48 @@ interface GrammarError {
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}
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```
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### **IdiomDto 模型**
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```typescript
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interface IdiomDto {
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idiom: string // 慣用語本身
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translation: string // 中文翻譯
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definition: string // 英文定義
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pronunciation: string // 發音 (IPA)
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difficultyLevel: CEFRLevel // CEFR等級
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frequency: FrequencyLevel // 使用頻率
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synonyms: string[] // 同義詞或相似表達
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example?: string // 例句
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exampleTranslation?: string // 例句翻譯
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}
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```
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### **AnalysisMetadata 模型**
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```typescript
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interface AnalysisMetadata {
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analysisModel: string // AI模型名稱
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analysisVersion: string // 分析版本
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processingDate: string // 處理時間 (ISO 8601)
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}
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```
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### **ApiErrorResponse 模型**
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```typescript
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interface ApiErrorResponse {
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success: boolean // 固定為 false
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error: ApiError // 錯誤詳情
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timestamp: string // 錯誤時間 (ISO 8601)
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requestId: string // 請求ID
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}
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interface ApiError {
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code: string // 錯誤代碼
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message: string // 錯誤訊息
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details?: object // 錯誤詳情
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suggestions: string[] // 建議解決方案
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}
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```
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### **枚舉定義**
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```typescript
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type CEFRLevel = "A1" | "A2" | "B1" | "B2" | "C1" | "C2"
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@ -259,6 +286,151 @@ type AnalysisMode = "basic" | "full"
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---
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## 🤖 **AI Prompt設計規格**
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### **Prompt架構設計**
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#### **核心Prompt模板**
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```text
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You are an English learning assistant. Analyze this sentence for a learner and return ONLY a valid JSON response.
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**Input Sentence**: "{inputText}"
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**Required JSON Structure:**
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{
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"sentenceTranslation": "Traditional Chinese translation of the entire sentence",
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"hasGrammarErrors": true/false,
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"grammarCorrections": [
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{
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"original": "incorrect text",
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"corrected": "correct text",
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"type": "error type (tense/subject-verb/preposition/word-order)",
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"explanation": "brief explanation in Traditional Chinese"
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}
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],
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"vocabularyAnalysis": {
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"word1": {
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"word": "the word",
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"translation": "Traditional Chinese translation",
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"definition": "English definition",
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"partOfSpeech": "noun/verb/adjective/etc",
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"pronunciation": "/phonetic/",
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"difficultyLevel": "A1/A2/B1/B2/C1/C2",
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"frequency": "high/medium/low",
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"synonyms": ["synonym1", "synonym2"],
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"example": "example sentence",
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"exampleTranslation": "Traditional Chinese example translation"
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}
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},
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"idioms": [
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{
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"idiom": "idiomatic expression",
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"translation": "Traditional Chinese meaning",
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"definition": "English explanation",
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"pronunciation": "/phonetic notation/",
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"difficultyLevel": "A1/A2/B1/B2/C1/C2",
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"frequency": "high/medium/low",
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"synonyms": ["synonym1", "synonym2"],
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"example": "usage example",
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"exampleTranslation": "Traditional Chinese example"
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}
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]
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}
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```
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### **Prompt指導原則**
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#### **分析指導方針**
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```yaml
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語法檢查:
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- 檢測範圍: 時態錯誤、主謂一致、介詞使用、詞序問題
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- 修正原則: 提供自然且正確的英語表達
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- 解釋語言: 使用繁體中文（台灣標準）
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詞彙分析:
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- 包含範圍: 所有有意義的詞彙（排除冠詞 a, an, the）
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- CEFR標準: 準確分配A1-C2等級
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- 發音標記: 使用國際音標(IPA)
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- 例句品質: 提供實用且常見的例句
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慣用語識別:
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- 識別目標: 慣用語、片語動詞、固定搭配
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- 分類原則: 獨立於vocabularyAnalysis處理
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- 解釋詳度: 提供文化背景和使用場景
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翻譯品質:
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- 語言標準: 繁體中文（台灣用法）
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- 自然程度: 符合中文表達習慣
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- 準確性: 保持原文語義完整
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```
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### **Prompt優化策略**
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#### **結構化輸出控制**
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```text
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**IMPORTANT**: Return ONLY the JSON object, no additional text or explanation.
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**Quality Assurance:**
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1. Ensure all JSON keys are exactly as specified
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2. Use Traditional Chinese for all translations
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3. Assign accurate CEFR levels based on standard guidelines
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4. Separate idioms from regular vocabulary
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5. Provide practical examples that learners can use
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```
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#### **錯誤處理Prompt**
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```text
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**Error Handling Guidelines:**
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- If unable to analyze: Return basic structure with explanatory messages
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- If safety filtered: Provide alternative analysis approach
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- If ambiguous input: Make reasonable assumptions and proceed
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- Always return valid JSON regardless of input complexity
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```
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### **Prompt版本管理**
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#### **版本演進記錄**
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```yaml
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v1.0 (2025-01-20):
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- 基礎prompt結構
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- 簡單詞彙分析
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v1.5 (2025-01-22):
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- 新增慣用語識別
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- 優化語法檢查
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v2.0 (2025-01-25):
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- 結構化JSON輸出
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- 完整資料模型支援
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- 繁體中文本地化
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- 錯誤處理機制
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```
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#### **A/B測試配置**
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```csharp
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// Prompt變體測試
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public enum PromptVariant
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{
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Standard, // 標準prompt
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DetailedExamples, // 強調例句品質
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StrictGrammar, // 加強語法檢查
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CulturalContext // 增加文化背景
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}
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// 動態Prompt選擇
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private string GetPromptByVariant(PromptVariant variant, string inputText)
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{
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return variant switch
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{
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PromptVariant.Standard => BuildStandardPrompt(inputText),
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PromptVariant.DetailedExamples => BuildDetailedPrompt(inputText),
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_ => BuildStandardPrompt(inputText)
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};
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}
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```
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---
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## 🔒 **認證與授權**
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### **API認證**
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@ -343,7 +515,7 @@ Premium用戶:
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"responseTime": 2340,
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"inputLength": 89,
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"analysisMode": "full",
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"aiModel": "gpt-4",
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"aiModel": "gemini-1.5-flash",
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"processingSteps": {
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"grammarCheck": 450,
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"vocabularyAnalysis": 1200,
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@ -409,18 +581,14 @@ Premium用戶:
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測試目的: 驗證完整分析功能
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輸入數據:
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inputText: "She just join the team, so let's cut her some slack until she get used to the workflow."
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userLevel: "A2"
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analysisMode: "full"
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預期結果:
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statusCode: 200
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grammarCorrection.hasErrors: true
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grammarCorrection.corrections.length: 2
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vocabularyAnalysis keys: 17 (16個詞 + 1個慣用語)
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statistics.simpleWords: 8
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statistics.moderateWords: 4
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statistics.difficultWords: 3
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statistics.phrases: 1
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vocabularyAnalysis keys: 16 (不含慣用語)
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idioms.length: 1
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```
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#### **TC-002: 輸入驗證測試**
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@ -623,7 +791,17 @@ AI升級:
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---
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**文件版本**: v1.0
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**文件版本**: v1.1 (更新AI模型和模型定義)
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**API版本**: v1
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**最後更新**: 2025-01-25
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**下次審查**: 2025-02-25
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**更新記錄**:
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- v1.1: 修正AI模型名稱為Gemini 1.5 Flash
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- v1.1: 移除VocabularyAnalysis中tags欄位
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- v1.1: 新增IdiomDto和ApiErrorResponse模型定義
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- v1.1: 移除userLevel參數（簡化API）
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- v1.1: 統一回應格式範例
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- v1.1: 新增完整的AI Prompt設計規格和版本管理
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- v1.1: 同步更新後端DTO模型實現（移除Tags、IsIdiom、UserLevel欄位）
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- v1.1: 移除statistics計算邏輯（前端自行處理統計）
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@ -498,7 +498,6 @@ API通信: Fetch API
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```json
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{
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"inputText": "英文句子",
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"userLevel": "A2",
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"analysisMode": "full"
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}
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```
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@ -508,9 +507,12 @@ API通信: Fetch API
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{
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"success": true,
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"data": {
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"WordAnalysis": "詞彙分析對象",
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"SentenceMeaning": "句子翻譯",
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"GrammarCorrection": "語法修正資料"
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"vocabularyAnalysis": "詞彙分析字典對象",
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"sentenceMeaning": "句子翻譯字串",
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"grammarCorrection": "語法修正資料對象",
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"idioms": "慣用語陣列",
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"statistics": "統計資料對象",
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"metadata": "分析元資料對象"
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}
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}
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```
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@ -537,7 +539,7 @@ interface WordAnalysisRequired {
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partOfSpeech: string // 必需：詞性
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pronunciation: string // 必需：發音
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difficultyLevel: string // 必需：CEFR等級
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isIdiom: boolean // 必需：是否為慣用語
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frequency: string // 必需：使用頻率
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}
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```
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@ -727,7 +729,13 @@ interface WordAnalysisOptional {
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---
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**文件版本**: v1.0
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**文件版本**: v1.1 (配合後端API規格更新)
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**產品負責人**: DramaLing產品團隊
|
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**最後更新**: 2025-09-21
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**下次審查**: 2025-10-21
|
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**最後更新**: 2025-01-25
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**下次審查**: 2025-02-25
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**更新記錄**:
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- v1.1: 移除API請求中的userLevel參數要求
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- v1.1: 更新API回應格式為實際實現的格式
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- v1.1: 修正資料模型，移除isIdiom欄位，新增frequency欄位
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- v1.1: 保留前端個人化分類邏輯，改為從localStorage獲取用戶等級
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@ -53,7 +53,7 @@ public class AIController : ControllerBase
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// 直接執行 AI 分析，不使用快取
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var options = request.Options ?? new AnalysisOptions();
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var analysisData = await _geminiService.AnalyzeSentenceAsync(
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request.InputText, request.UserLevel, options);
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request.InputText, options);
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stopwatch.Stop();
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analysisData.Metadata.ProcessingDate = DateTime.UtcNow;
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@ -8,9 +8,6 @@ public class SentenceAnalysisRequest
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[StringLength(300, MinimumLength = 1, ErrorMessage = "輸入文本長度必須在1-300字符之間")]
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public string InputText { get; set; } = string.Empty;
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[Required]
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[RegularExpression("^(A1|A2|B1|B2|C1|C2)$", ErrorMessage = "無效的CEFR等級")]
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public string UserLevel { get; set; } = "A2";
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public string AnalysisMode { get; set; } = "full";
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@ -42,7 +39,6 @@ public class SentenceAnalysisData
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public string SentenceMeaning { get; set; } = string.Empty;
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public Dictionary<string, VocabularyAnalysisDto> VocabularyAnalysis { get; set; } = new();
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public List<IdiomDto> Idioms { get; set; } = new();
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public AnalysisStatistics Statistics { get; set; } = new();
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public AnalysisMetadata Metadata { get; set; } = new();
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}
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@ -77,12 +73,10 @@ public class VocabularyAnalysisDto
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public string PartOfSpeech { get; set; } = string.Empty;
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public string Pronunciation { get; set; } = string.Empty;
|
||||
public string DifficultyLevel { get; set; } = string.Empty;
|
||||
public bool IsIdiom { get; set; }
|
||||
public string Frequency { get; set; } = string.Empty;
|
||||
public List<string> Synonyms { get; set; } = new();
|
||||
public string? Example { get; set; }
|
||||
public string? ExampleTranslation { get; set; }
|
||||
public List<string> Tags { get; set; } = new();
|
||||
}
|
||||
|
||||
public class IdiomDto
|
||||
|
|
@ -98,23 +92,12 @@ public class IdiomDto
|
|||
public string? ExampleTranslation { get; set; }
|
||||
}
|
||||
|
||||
public class AnalysisStatistics
|
||||
{
|
||||
public int TotalWords { get; set; }
|
||||
public int UniqueWords { get; set; }
|
||||
public int SimpleWords { get; set; }
|
||||
public int ModerateWords { get; set; }
|
||||
public int DifficultWords { get; set; }
|
||||
public int Idioms { get; set; }
|
||||
public string AverageDifficulty { get; set; } = string.Empty;
|
||||
}
|
||||
|
||||
public class AnalysisMetadata
|
||||
{
|
||||
public string AnalysisModel { get; set; } = "gpt-4";
|
||||
public string AnalysisVersion { get; set; } = "1.0";
|
||||
public string AnalysisModel { get; set; } = "gemini-1.5-flash";
|
||||
public string AnalysisVersion { get; set; } = "2.0";
|
||||
public DateTime ProcessingDate { get; set; } = DateTime.UtcNow;
|
||||
public string UserLevel { get; set; } = string.Empty;
|
||||
}
|
||||
|
||||
public class ApiErrorResponse
|
||||
|
|
|
|||
|
|
@ -6,7 +6,7 @@ namespace DramaLing.Api.Services;
|
|||
|
||||
public interface IGeminiService
|
||||
{
|
||||
Task<SentenceAnalysisData> AnalyzeSentenceAsync(string inputText, string userLevel, AnalysisOptions options);
|
||||
Task<SentenceAnalysisData> AnalyzeSentenceAsync(string inputText, AnalysisOptions options);
|
||||
}
|
||||
|
||||
public class GeminiService : IGeminiService
|
||||
|
|
@ -31,20 +31,19 @@ public class GeminiService : IGeminiService
|
|||
_httpClient.DefaultRequestHeaders.Add("User-Agent", "DramaLing/1.0");
|
||||
}
|
||||
|
||||
public async Task<SentenceAnalysisData> AnalyzeSentenceAsync(string inputText, string userLevel, AnalysisOptions options)
|
||||
public async Task<SentenceAnalysisData> AnalyzeSentenceAsync(string inputText, AnalysisOptions options)
|
||||
{
|
||||
var startTime = DateTime.UtcNow;
|
||||
|
||||
try
|
||||
{
|
||||
_logger.LogInformation("Starting sentence analysis for text: {Text}, UserLevel: {UserLevel}",
|
||||
inputText.Substring(0, Math.Min(50, inputText.Length)), userLevel);
|
||||
_logger.LogInformation("Starting sentence analysis for text: {Text}",
|
||||
inputText.Substring(0, Math.Min(50, inputText.Length)));
|
||||
|
||||
// 符合產品需求規格的結構化 prompt
|
||||
var prompt = $@"You are an English learning assistant. Analyze this sentence for a {userLevel} CEFR level learner and return ONLY a valid JSON response.
|
||||
var prompt = $@"You are an English learning assistant. Analyze this sentence and return ONLY a valid JSON response.
|
||||
|
||||
**Input Sentence**: ""{inputText}""
|
||||
**Learner Level**: {userLevel}
|
||||
|
||||
**Required JSON Structure:**
|
||||
{{
|
||||
|
|
@ -113,7 +112,7 @@ public class GeminiService : IGeminiService
|
|||
}
|
||||
|
||||
// 直接使用 AI 的回應創建分析數據
|
||||
var analysisData = CreateAnalysisFromAIResponse(inputText, userLevel, aiResponse);
|
||||
var analysisData = CreateAnalysisFromAIResponse(inputText, aiResponse);
|
||||
|
||||
var processingTime = (DateTime.UtcNow - startTime).TotalSeconds;
|
||||
_logger.LogInformation("Sentence analysis completed in {ProcessingTime}s", processingTime);
|
||||
|
|
@ -127,7 +126,7 @@ public class GeminiService : IGeminiService
|
|||
}
|
||||
}
|
||||
|
||||
private SentenceAnalysisData CreateAnalysisFromAIResponse(string inputText, string userLevel, string aiResponse)
|
||||
private SentenceAnalysisData CreateAnalysisFromAIResponse(string inputText, string aiResponse)
|
||||
{
|
||||
_logger.LogInformation("Creating analysis from AI response: {ResponsePreview}...",
|
||||
aiResponse.Substring(0, Math.Min(100, aiResponse.Length)));
|
||||
|
|
@ -166,15 +165,12 @@ public class GeminiService : IGeminiService
|
|||
GrammarCorrection = ConvertGrammarCorrection(aiAnalysis),
|
||||
Metadata = new AnalysisMetadata
|
||||
{
|
||||
UserLevel = userLevel,
|
||||
ProcessingDate = DateTime.UtcNow,
|
||||
AnalysisModel = "gemini-1.5-flash",
|
||||
AnalysisVersion = "2.0"
|
||||
}
|
||||
};
|
||||
|
||||
// 計算統計
|
||||
analysisData.Statistics = CalculateStatistics(analysisData.VocabularyAnalysis, analysisData.Idioms, userLevel);
|
||||
|
||||
return analysisData;
|
||||
}
|
||||
|
|
@ -182,7 +178,7 @@ public class GeminiService : IGeminiService
|
|||
{
|
||||
_logger.LogError(ex, "Failed to parse AI response as JSON: {Response}", aiResponse);
|
||||
// 回退到舊的處理方式
|
||||
return CreateFallbackAnalysis(inputText, userLevel, aiResponse);
|
||||
return CreateFallbackAnalysis(inputText, aiResponse);
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -205,7 +201,6 @@ public class GeminiService : IGeminiService
|
|||
Synonyms = aiWord.Synonyms ?? new List<string>(),
|
||||
Example = aiWord.Example,
|
||||
ExampleTranslation = aiWord.ExampleTranslation,
|
||||
Tags = new List<string> { "ai-analyzed", "gemini" }
|
||||
};
|
||||
}
|
||||
|
||||
|
|
@ -260,7 +255,7 @@ public class GeminiService : IGeminiService
|
|||
};
|
||||
}
|
||||
|
||||
private SentenceAnalysisData CreateFallbackAnalysis(string inputText, string userLevel, string aiResponse)
|
||||
private SentenceAnalysisData CreateFallbackAnalysis(string inputText, string aiResponse)
|
||||
{
|
||||
_logger.LogWarning("Using fallback analysis due to JSON parsing failure");
|
||||
|
||||
|
|
@ -271,12 +266,10 @@ public class GeminiService : IGeminiService
|
|||
VocabularyAnalysis = CreateBasicVocabularyFromText(inputText, aiResponse),
|
||||
Metadata = new AnalysisMetadata
|
||||
{
|
||||
UserLevel = userLevel,
|
||||
ProcessingDate = DateTime.UtcNow,
|
||||
AnalysisModel = "gemini-1.5-flash-fallback",
|
||||
AnalysisVersion = "1.0"
|
||||
AnalysisVersion = "2.0"
|
||||
},
|
||||
Statistics = new AnalysisStatistics()
|
||||
};
|
||||
}
|
||||
|
||||
|
|
@ -303,7 +296,6 @@ public class GeminiService : IGeminiService
|
|||
Synonyms = new List<string>(),
|
||||
Example = null,
|
||||
ExampleTranslation = null,
|
||||
Tags = new List<string> { "fallback-analysis" }
|
||||
};
|
||||
}
|
||||
|
||||
|
|
@ -335,21 +327,6 @@ public class GeminiService : IGeminiService
|
|||
return "B2";
|
||||
}
|
||||
|
||||
private AnalysisStatistics CalculateStatistics(Dictionary<string, VocabularyAnalysisDto> vocabulary, List<IdiomDto> idioms, string userLevel)
|
||||
{
|
||||
var stats = new AnalysisStatistics
|
||||
{
|
||||
TotalWords = vocabulary.Count,
|
||||
UniqueWords = vocabulary.Count,
|
||||
SimpleWords = vocabulary.Count(kvp => kvp.Value.DifficultyLevel == "A1"),
|
||||
ModerateWords = vocabulary.Count(kvp => kvp.Value.DifficultyLevel == "A2"),
|
||||
DifficultWords = vocabulary.Count(kvp => !new[] { "A1", "A2" }.Contains(kvp.Value.DifficultyLevel)),
|
||||
Idioms = idioms.Count, // 基於實際 idioms 陣列計算
|
||||
AverageDifficulty = userLevel
|
||||
};
|
||||
|
||||
return stats;
|
||||
}
|
||||
|
||||
private async Task<string> CallGeminiAPI(string prompt)
|
||||
{
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
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Reference in New Issue