807 lines
19 KiB
Markdown
807 lines
19 KiB
Markdown
# AI生成功能後端API規格
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## 📋 **文件資訊**
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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 (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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---
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## 🎯 **API概述**
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### **核心功能**
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AI生成功能後端API提供智能英文句子分析服務，包含語法檢查、詞彙分析、翻譯和慣用語識別，為前端提供完整的學習數據支援。
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### **主要特色**
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- 🤖 **AI驅動分析** - 使用先進AI模型進行語言分析
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- 🎯 **個人化標記** - 基於用戶CEFR等級的詞彙分類
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- 📊 **多維度數據** - 提供詞彙、語法、翻譯、慣用語分析
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- ⚡ **高性能處理** - 支援快速響應和批次處理
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---
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## 🛠 **技術架構**
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### **架構組成**
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```yaml
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API Gateway:
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- 路由管理
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- 認證驗證
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- 流量控制
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- 錯誤處理
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AI Analysis Service:
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- 語法分析引擎
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- 詞彙分析引擎
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- 翻譯服務
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- 慣用語識別
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Database Layer:
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- 詞彙資料庫
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- 用戶數據
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- 分析結果緩存
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- 使用記錄
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External Services:
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- AI模型服務
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- 詞典API
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- 翻譯API
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```
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### **技術棧要求**
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```yaml
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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 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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---
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## 📡 **API端點規格**
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### **API-001: 句子智能分析**
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#### **端點資訊**
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```http
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POST /api/ai/analyze-sentence
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Content-Type: application/json
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Authorization: Bearer {token}
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```
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#### **請求格式**
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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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"analysisMode": "full",
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"options": {
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"includeGrammarCheck": true,
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"includeVocabularyAnalysis": true,
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"includeTranslation": true,
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"includeIdiomDetection": true,
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"includeExamples": true
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}
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}
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```
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#### **請求參數說明**
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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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| 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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#### **成功回應格式**
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```json
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{
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"success": true,
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"processingTime": 2.34,
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"data": {
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"analysisId": "uuid-string",
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"originalText": "She just join the team, so let's cut her some slack until she get used to the workflow.",
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"grammarCorrection": {
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"hasErrors": true,
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"correctedText": "She just joined the team, so let's cut her some slack until she gets used to the workflow.",
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"corrections": [
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{
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"position": { "start": 9, "end": 13 },
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"error": "join",
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"correction": "joined",
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"type": "時態錯誤",
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"explanation": "第三人稱單數過去式應使用 'joined'",
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"severity": "high"
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},
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{
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"position": { "start": 79, "end": 82 },
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"error": "get",
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"correction": "gets",
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"type": "時態錯誤",
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"explanation": "第三人稱單數現在式應使用 'gets'",
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"severity": "high"
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}
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]
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},
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"sentenceMeaning": "她剛加入團隊，所以讓我們對她寬容一點，直到她習慣工作流程。",
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"vocabularyAnalysis": {
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"she": {
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"word": "she",
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"translation": "她",
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"definition": "female person pronoun",
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"partOfSpeech": "pronoun",
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"pronunciation": "/ʃiː/",
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"difficultyLevel": "A1",
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"frequency": "very_high",
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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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},
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"just": {
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"word": "just",
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"translation": "剛剛；僅僅",
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"definition": "recently; only",
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"partOfSpeech": "adverb",
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"pronunciation": "/dʒʌst/",
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"difficultyLevel": "A2",
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"frequency": "high",
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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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}
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},
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"idioms": [
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{
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"idiom": "cut someone some slack",
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"translation": "對某人寬容一點",
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"definition": "to be more lenient or forgiving with someone",
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"pronunciation": "/kʌt ˈsʌmwʌn səm slæk/",
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"difficultyLevel": "B2",
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"frequency": "medium",
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"synonyms": [
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"give someone a break",
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"go easy on someone",
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"let someone off the hook"
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],
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"example": "Cut him some slack, he's new here.",
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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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"metadata": {
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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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}
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}
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}
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```
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#### **錯誤回應格式**
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```json
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{
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"success": false,
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"error": {
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"code": "INVALID_INPUT",
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"message": "輸入文本超過最大長度限制",
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"details": {
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"maxLength": 300,
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"actualLength": 350
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}
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},
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"timestamp": "2025-01-25T10:30:00Z",
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"requestId": "uuid-string"
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}
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```
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---
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## 🔧 **數據模型規格**
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### **VocabularyAnalysis 模型**
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```typescript
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interface VocabularyAnalysis {
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word: string // 詞彙本身
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translation: string // 中文翻譯
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definition: string // 英文定義
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partOfSpeech: string // 詞性
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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
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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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### **GrammarCorrection 模型**
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```typescript
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interface GrammarCorrection {
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hasErrors: boolean
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correctedText: string
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corrections: GrammarError[]
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}
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interface GrammarError {
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position: { start: number; end: number }
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error: string
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correction: string
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type: string
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explanation: string
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severity: "low" | "medium" | "high"
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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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type FrequencyLevel = "very_high" | "high" | "medium" | "low" | "very_low"
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type AnalysisMode = "basic" | "full"
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```
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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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```yaml
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認證方式: Bearer Token (JWT)
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Token位置: Authorization Header
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Token格式: "Bearer {jwt_token}"
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過期時間: 24小時
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刷新機制: Refresh Token
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```
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### **權限等級**
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```yaml
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Guest用戶:
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- 每日5次免費分析
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- 基礎分析功能
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- 無歷史記錄
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Premium用戶:
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- 無限制分析
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- 完整分析功能
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- 歷史記錄保存
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- 批次分析
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```
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---
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## ⚡ **性能要求**
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### **響應時間目標**
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```yaml
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基礎分析: < 2秒
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完整分析: < 5秒
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批次分析: < 10秒 (10句)
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錯誤回應: < 500ms
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```
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### **吞吐量要求**
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```yaml
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並發請求: 100 req/sec
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每日請求: 100,000 requests
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峰值處理: 200 req/sec
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```
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### **資源限制**
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```yaml
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輸入文本: 最大300字符
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輸出大小: 最大5MB
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內存使用: 最大500MB per request
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超時設定: 30秒
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```
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---
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## 📊 **監控與日誌**
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### **關鍵指標**
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```yaml
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性能指標:
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- 請求響應時間
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- API成功率
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- AI服務響應時間
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- 資料庫查詢時間
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業務指標:
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- 每日分析次數
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- 用戶活躍度
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- 錯誤類型分布
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- 詞彙覆蓋率
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```
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### **日誌格式**
|
||
```json
|
||
{
|
||
"timestamp": "2025-01-25T10:30:00Z",
|
||
"level": "INFO",
|
||
"requestId": "uuid-string",
|
||
"userId": "user-id",
|
||
"endpoint": "/api/ai/analyze-sentence",
|
||
"method": "POST",
|
||
"statusCode": 200,
|
||
"responseTime": 2340,
|
||
"inputLength": 89,
|
||
"analysisMode": "full",
|
||
"aiModel": "gemini-1.5-flash",
|
||
"processingSteps": {
|
||
"grammarCheck": 450,
|
||
"vocabularyAnalysis": 1200,
|
||
"translation": 690
|
||
}
|
||
}
|
||
```
|
||
|
||
---
|
||
|
||
## 🔄 **錯誤處理**
|
||
|
||
### **錯誤碼定義**
|
||
```yaml
|
||
4000: INVALID_INPUT - 輸入格式錯誤
|
||
4001: TEXT_TOO_LONG - 文本超過長度限制
|
||
4002: INVALID_CEFR_LEVEL - 無效的CEFR等級
|
||
4003: UNSUPPORTED_LANGUAGE - 不支援的語言
|
||
|
||
4010: AUTHENTICATION_FAILED - 認證失敗
|
||
4011: TOKEN_EXPIRED - Token已過期
|
||
4012: INSUFFICIENT_PERMISSIONS - 權限不足
|
||
|
||
4290: RATE_LIMIT_EXCEEDED - 超過使用限制
|
||
4291: QUOTA_EXCEEDED - 超過配額
|
||
|
||
5000: AI_SERVICE_ERROR - AI服務錯誤
|
||
5001: DATABASE_ERROR - 資料庫錯誤
|
||
5002: EXTERNAL_API_ERROR - 外部API錯誤
|
||
5003: PROCESSING_TIMEOUT - 處理超時
|
||
```
|
||
|
||
### **錯誤回應範例**
|
||
```json
|
||
{
|
||
"success": false,
|
||
"error": {
|
||
"code": "RATE_LIMIT_EXCEEDED",
|
||
"message": "已超過每日使用限制",
|
||
"details": {
|
||
"limit": 5,
|
||
"used": 5,
|
||
"resetTime": "2025-01-26T00:00:00Z"
|
||
},
|
||
"suggestions": [
|
||
"升級到Premium帳戶以獲得無限使用",
|
||
"明天重新嘗試"
|
||
]
|
||
},
|
||
"timestamp": "2025-01-25T10:30:00Z",
|
||
"requestId": "uuid-string"
|
||
}
|
||
```
|
||
|
||
---
|
||
|
||
## 🧪 **測試規格**
|
||
|
||
### **API測試案例**
|
||
|
||
#### **TC-001: 正常分析流程**
|
||
```yaml
|
||
測試目的: 驗證完整分析功能
|
||
輸入數據:
|
||
inputText: "She just join the team, so let's cut her some slack until she get used to the workflow."
|
||
analysisMode: "full"
|
||
|
||
預期結果:
|
||
statusCode: 200
|
||
grammarCorrection.hasErrors: true
|
||
grammarCorrection.corrections.length: 2
|
||
vocabularyAnalysis keys: 16 (不含慣用語)
|
||
idioms.length: 1
|
||
```
|
||
|
||
#### **TC-002: 輸入驗證測試**
|
||
```yaml
|
||
測試目的: 驗證輸入驗證機制
|
||
測試案例:
|
||
- 空字串輸入
|
||
- 超長文本 (>300字符)
|
||
- 無效CEFR等級
|
||
- 純數字輸入
|
||
- 特殊字符輸入
|
||
|
||
預期結果: 400錯誤與相應錯誤訊息
|
||
```
|
||
|
||
#### **TC-003: 認證測試**
|
||
```yaml
|
||
測試目的: 驗證API認證機制
|
||
測試案例:
|
||
- 無Token訪問
|
||
- 無效Token
|
||
- 過期Token
|
||
- 權限不足
|
||
|
||
預期結果: 401/403錯誤
|
||
```
|
||
|
||
### **性能測試**
|
||
```yaml
|
||
負載測試:
|
||
- 100 concurrent users
|
||
- 1000 requests in 10 minutes
|
||
- 目標: 95% requests < 5 seconds
|
||
|
||
壓力測試:
|
||
- 200 concurrent users
|
||
- 持續20分鐘
|
||
- 目標: API仍然響應
|
||
|
||
容量測試:
|
||
- 模擬10,000 daily users
|
||
- 24小時持續測試
|
||
- 目標: 系統穩定運行
|
||
```
|
||
|
||
---
|
||
|
||
## 🚀 **部署規格**
|
||
|
||
### **環境配置**
|
||
```yaml
|
||
Development:
|
||
database: PostgreSQL 15
|
||
cache: Redis 7
|
||
ai_service: Google Gemini API
|
||
replicas: 1
|
||
resources:
|
||
cpu: 0.5 cores
|
||
memory: 1GB
|
||
|
||
Staging:
|
||
database: PostgreSQL 15 (replica)
|
||
cache: Redis 7 (cluster)
|
||
ai_service: Google Gemini API
|
||
replicas: 2
|
||
resources:
|
||
cpu: 1 core
|
||
memory: 2GB
|
||
|
||
Production:
|
||
database: PostgreSQL 15 (HA cluster)
|
||
cache: Redis 7 (cluster)
|
||
ai_service: Google Gemini API
|
||
replicas: 5
|
||
resources:
|
||
cpu: 2 cores
|
||
memory: 4GB
|
||
```
|
||
|
||
### **Docker配置**
|
||
```dockerfile
|
||
FROM mcr.microsoft.com/dotnet/aspnet:8.0 AS base
|
||
WORKDIR /app
|
||
EXPOSE 80
|
||
EXPOSE 443
|
||
|
||
FROM mcr.microsoft.com/dotnet/sdk:8.0 AS build
|
||
WORKDIR /src
|
||
COPY ["DramaLing.AI.Api/DramaLing.AI.Api.csproj", "DramaLing.AI.Api/"]
|
||
RUN dotnet restore "DramaLing.AI.Api/DramaLing.AI.Api.csproj"
|
||
COPY . .
|
||
WORKDIR "/src/DramaLing.AI.Api"
|
||
RUN dotnet build "DramaLing.AI.Api.csproj" -c Release -o /app/build
|
||
|
||
FROM build AS publish
|
||
RUN dotnet publish "DramaLing.AI.Api.csproj" -c Release -o /app/publish
|
||
|
||
FROM base AS final
|
||
WORKDIR /app
|
||
COPY --from=publish /app/publish .
|
||
ENTRYPOINT ["dotnet", "DramaLing.AI.Api.dll"]
|
||
```
|
||
|
||
---
|
||
|
||
## 📈 **擴展計劃**
|
||
|
||
### **短期擴展 (1-3個月)**
|
||
```yaml
|
||
功能擴展:
|
||
- 批次分析API
|
||
- 文本難度評估
|
||
- 個人化詞彙推薦
|
||
- 學習進度追蹤
|
||
|
||
技術改進:
|
||
- GraphQL支援
|
||
- WebSocket即時分析
|
||
- 分析結果緩存優化
|
||
- AI模型版本管理
|
||
```
|
||
|
||
### **中期擴展 (3-6個月)**
|
||
```yaml
|
||
多語言支援:
|
||
- 法語分析
|
||
- 德語分析
|
||
- 西班牙語分析
|
||
|
||
進階功能:
|
||
- 語音分析集成
|
||
- 圖片文字識別
|
||
- 視頻字幕分析
|
||
- 個人化AI調優
|
||
```
|
||
|
||
### **長期擴展 (6-12個月)**
|
||
```yaml
|
||
AI升級:
|
||
- 自訂AI模型訓練
|
||
- 多模態學習分析
|
||
- 即時語言學習建議
|
||
- 預測性學習路徑
|
||
|
||
企業功能:
|
||
- 團隊管理API
|
||
- 批量用戶管理
|
||
- 詳細分析報告
|
||
- 自訂詞彙庫
|
||
```
|
||
|
||
---
|
||
|
||
## 🔐 **安全規格**
|
||
|
||
### **數據安全**
|
||
```yaml
|
||
傳輸安全:
|
||
- TLS 1.3加密
|
||
- API密鑰輪換
|
||
- 請求簽名驗證
|
||
|
||
數據保護:
|
||
- 個人數據加密存儲
|
||
- 敏感信息遮罩
|
||
- 數據保留政策
|
||
- GDPR合規
|
||
```
|
||
|
||
### **API安全**
|
||
```yaml
|
||
防護措施:
|
||
- 速率限制
|
||
- IP白名單
|
||
- 異常檢測
|
||
- 自動封鎖機制
|
||
|
||
審計日誌:
|
||
- 完整請求記錄
|
||
- 敏感操作追蹤
|
||
- 異常行為警報
|
||
- 合規性報告
|
||
```
|
||
|
||
---
|
||
|
||
## 📋 **API文檔規範**
|
||
|
||
### **OpenAPI規格**
|
||
- 使用OpenAPI 3.0規範
|
||
- 提供互動式API文檔
|
||
- 自動生成客戶端SDK
|
||
- 版本化API文檔
|
||
|
||
### **文檔內容**
|
||
- 詳細的端點說明
|
||
- 請求/回應範例
|
||
- 錯誤碼說明
|
||
- 最佳實踐指南
|
||
|
||
---
|
||
|
||
**文件版本**: v1.1 (更新AI模型和模型定義)
|
||
**API版本**: v1
|
||
**最後更新**: 2025-01-25
|
||
**下次審查**: 2025-02-25
|
||
|
||
**更新記錄**:
|
||
- v1.1: 修正AI模型名稱為Gemini 1.5 Flash
|
||
- v1.1: 移除VocabularyAnalysis中tags欄位
|
||
- v1.1: 新增IdiomDto和ApiErrorResponse模型定義
|
||
- v1.1: 移除userLevel參數（簡化API）
|
||
- v1.1: 統一回應格式範例
|
||
- v1.1: 新增完整的AI Prompt設計規格和版本管理
|
||
- v1.1: 同步更新後端DTO模型實現（移除Tags、IsIdiom、UserLevel欄位）
|
||
- v1.1: 移除statistics計算邏輯（前端自行處理統計） |