feat: 整合 AI 智能 quizOptions 到 due API
✨ 新增功能 - 每張詞卡自動生成 3 個混淆選項 (quizOptions) - AI 驅動的智能混淆選項生成系統 - 基於詞性和難度等級的選項匹配 🧠 AI 生成邏輯 - 使用 Gemini AI 生成語義相關但明確不同的選項 - 根據 CEFR 等級和詞性調整選項難度 - JSON 格式回應解析和錯誤處理 🚀 性能優化 - 記憶體快取機制 (1小時過期) - 資料庫持久化儲存生成的選項 - 智能降級機制：AI失敗時使用固定選項 📊 測試確認 - API 回應包含完整的 quizOptions 陣列 - 支援異步批量生成多張詞卡選項 - 前端可直接使用於詞彙選擇測驗 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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@ -3,19 +3,23 @@ using DramaLing.Api.Models.Entities;
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using DramaLing.Api.Repositories;
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using DramaLing.Api.Controllers;
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using DramaLing.Api.Utils;
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using DramaLing.Api.Services;
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namespace DramaLing.Api.Services.Review;
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public class ReviewService : IReviewService
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{
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private readonly IFlashcardReviewRepository _reviewRepository;
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private readonly IOptionsVocabularyService _optionsService;
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private readonly ILogger<ReviewService> _logger;
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public ReviewService(
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IFlashcardReviewRepository reviewRepository,
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IOptionsVocabularyService optionsService,
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ILogger<ReviewService> logger)
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{
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_reviewRepository = reviewRepository;
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_optionsService = optionsService;
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_logger = logger;
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}
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@ -26,8 +30,17 @@ public class ReviewService : IReviewService
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var dueFlashcards = await _reviewRepository.GetDueFlashcardsAsync(userId, query);
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var (todayDue, overdue, totalReviews) = await _reviewRepository.GetReviewStatsAsync(userId);
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// 轉換為符合前端期望的格式
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var flashcardData = dueFlashcards.Select(item => new
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// 為每張詞卡生成 quizOptions
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var flashcardDataTasks = dueFlashcards.Select(async item =>
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{
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// 生成混淆選項
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var generatedQuizOptions = await _optionsService.GenerateDistractorsAsync(
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item.Flashcard.Word,
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CEFRHelper.ToString(item.Flashcard.DifficultyLevelNumeric),
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item.Flashcard.PartOfSpeech ?? "noun",
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3);
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return new
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{
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// 基本詞卡信息 (匹配 api_seeds.json 格式)
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id = item.Flashcard.Id.ToString(),
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@ -51,6 +64,9 @@ public class ReviewService : IReviewService
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// 同義詞（暫時空陣列，未來可擴展）
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synonyms = new string[] { },
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// 測驗選項 (AI 生成的混淆選項)
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quizOptions = generatedQuizOptions,
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// 複習相關信息 (新增)
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reviewInfo = item.Review != null ? new
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{
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@ -75,12 +91,16 @@ public class ReviewService : IReviewService
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isOverdue = false,
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daysSinceLastReview = 0
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}
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}).ToList();
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};
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});
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// 等待所有異步任務完成
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var flashcardData = await Task.WhenAll(flashcardDataTasks);
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var response = new
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{
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flashcards = flashcardData,
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count = flashcardData.Count,
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count = flashcardData.Length,
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metadata = new
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{
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todayDue = todayDue,
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@ -2,10 +2,12 @@ using DramaLing.Api.Data;
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using DramaLing.Api.Models.Configuration;
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using DramaLing.Api.Models.Entities;
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using DramaLing.Api.Services.Monitoring;
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using DramaLing.Api.Services.AI.Gemini;
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using Microsoft.EntityFrameworkCore;
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using Microsoft.Extensions.Caching.Memory;
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using Microsoft.Extensions.Options;
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using System.Diagnostics;
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using System.Text.Json;
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namespace DramaLing.Api.Services;
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@ -20,19 +22,22 @@ public class OptionsVocabularyService : IOptionsVocabularyService
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private readonly ILogger<OptionsVocabularyService> _logger;
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private readonly OptionsVocabularyOptions _options;
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private readonly OptionsVocabularyMetrics _metrics;
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private readonly IGeminiClient _geminiClient;
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public OptionsVocabularyService(
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DramaLingDbContext context,
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IMemoryCache cache,
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ILogger<OptionsVocabularyService> logger,
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IOptions<OptionsVocabularyOptions> options,
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OptionsVocabularyMetrics metrics)
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OptionsVocabularyMetrics metrics,
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IGeminiClient geminiClient)
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{
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_context = context;
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_cache = cache;
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_logger = logger;
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_options = options.Value;
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_metrics = metrics;
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_geminiClient = geminiClient;
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}
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/// <summary>
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@ -66,71 +71,73 @@ public class OptionsVocabularyService : IOptionsVocabularyService
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// 記錄請求指標
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_metrics.RecordGenerationRequest(cefrLevel, partOfSpeech, count);
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_logger.LogInformation("Generating {Count} distractors for word '{Word}' (CEFR: {CEFR}, PartOfSpeech: {PartOfSpeech}) - Using fixed options",
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_logger.LogInformation("Generating {Count} distractors for word '{Word}' (CEFR: {CEFR}, PartOfSpeech: {PartOfSpeech})",
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count, targetWord, cefrLevel, partOfSpeech);
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// 暫時使用固定選項，跳過複雜的詞彙篩選機制
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var fixedDistractors = new List<OptionsVocabulary>
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{
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new OptionsVocabulary
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{
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Id = Guid.NewGuid(),
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Word = "apple",
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CEFRLevel = cefrLevel,
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PartOfSpeech = partOfSpeech,
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IsActive = true,
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CreatedAt = DateTime.UtcNow,
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UpdatedAt = DateTime.UtcNow
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},
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new OptionsVocabulary
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{
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Id = Guid.NewGuid(),
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Word = "orange",
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CEFRLevel = cefrLevel,
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PartOfSpeech = partOfSpeech,
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IsActive = true,
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CreatedAt = DateTime.UtcNow,
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UpdatedAt = DateTime.UtcNow
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},
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new OptionsVocabulary
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{
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Id = Guid.NewGuid(),
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Word = "banana",
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CEFRLevel = cefrLevel,
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PartOfSpeech = partOfSpeech,
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IsActive = true,
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CreatedAt = DateTime.UtcNow,
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UpdatedAt = DateTime.UtcNow
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}
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};
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// 1. 首先檢查資料庫中是否已有該詞彙的混淆選項
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var cacheKey = $"quiz_options_{targetWord.ToLowerInvariant()}_{cefrLevel}_{partOfSpeech}";
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// 計算字數長度
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foreach (var distractor in fixedDistractors)
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if (_cache.TryGetValue(cacheKey, out List<OptionsVocabulary>? cachedOptions) && cachedOptions != null)
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{
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distractor.CalculateWordLength();
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_logger.LogInformation("Using cached distractors for '{Word}': {Distractors}",
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targetWord, string.Join(", ", cachedOptions.Select(d => d.Word)));
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return cachedOptions.Take(count).ToList();
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}
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// 排除目標詞彙本身（如果匹配）
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var selectedDistractors = fixedDistractors
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.Where(v => !string.Equals(v.Word, targetWord, StringComparison.OrdinalIgnoreCase))
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// 2. 檢查資料庫中是否有現有選項
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var existingOptions = await _context.OptionsVocabularies
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.Where(ov => ov.CEFRLevel == cefrLevel &&
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ov.PartOfSpeech == partOfSpeech &&
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ov.IsActive &&
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!string.Equals(ov.Word, targetWord, StringComparison.OrdinalIgnoreCase))
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.Take(count * 2) // 取更多選項以供隨機選擇
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.ToListAsync();
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if (existingOptions.Count >= count)
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{
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var selectedExisting = existingOptions
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.OrderBy(x => Guid.NewGuid()) // 隨機排序
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.Take(count)
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.ToList();
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_logger.LogInformation("Successfully generated {Count} fixed distractors for '{Word}': {Distractors}",
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selectedDistractors.Count, targetWord,
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string.Join(", ", selectedDistractors.Select(d => d.Word)));
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// 快取結果
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_cache.Set(cacheKey, selectedExisting, TimeSpan.FromHours(1));
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_logger.LogInformation("Using existing distractors for '{Word}': {Distractors}",
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targetWord, string.Join(", ", selectedExisting.Select(d => d.Word)));
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return selectedExisting;
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}
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// 3. 使用 AI 生成新的混淆選項
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var aiGeneratedOptions = await GenerateOptionsWithAI(targetWord, cefrLevel, partOfSpeech, count);
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// 4. 保存新生成的選項到資料庫
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if (aiGeneratedOptions.Any())
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{
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await _context.OptionsVocabularies.AddRangeAsync(aiGeneratedOptions);
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await _context.SaveChangesAsync();
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// 快取結果
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_cache.Set(cacheKey, aiGeneratedOptions, TimeSpan.FromHours(1));
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}
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_logger.LogInformation("Successfully generated {Count} AI distractors for '{Word}': {Distractors}",
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aiGeneratedOptions.Count, targetWord,
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string.Join(", ", aiGeneratedOptions.Select(d => d.Word)));
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// 記錄生成完成指標
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stopwatch.Stop();
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_metrics.RecordGenerationDuration(stopwatch.Elapsed, selectedDistractors.Count);
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_metrics.RecordGenerationDuration(stopwatch.Elapsed, aiGeneratedOptions.Count);
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return selectedDistractors;
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return aiGeneratedOptions;
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}
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catch (Exception ex)
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{
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_logger.LogError(ex, "Error generating distractors for word '{Word}'", targetWord);
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_metrics.RecordError("generation_failed", "GenerateDistractorsWithDetailsAsync");
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return new List<OptionsVocabulary>();
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// 降級到固定選項
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return GetFallbackDistractors(targetWord, cefrLevel, partOfSpeech, count);
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}
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}
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@ -204,4 +211,120 @@ public class OptionsVocabularyService : IOptionsVocabularyService
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return allowed;
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}
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/// <summary>
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/// 使用 AI 生成混淆選項
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/// </summary>
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private async Task<List<OptionsVocabulary>> GenerateOptionsWithAI(
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string targetWord,
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string cefrLevel,
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string partOfSpeech,
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int count)
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{
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try
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{
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var prompt = $@"Generate {count} vocabulary words that would be good wrong answers for a multiple choice quiz about the word ""{targetWord}"".
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Requirements:
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- CEFR level: {cefrLevel}
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- Part of speech: {partOfSpeech}
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- The words should be plausible but clearly different from ""{targetWord}""
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- Avoid obviously wrong answers
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- Make the words challenging but fair for language learners
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Please respond with ONLY a JSON array of strings, like: [""word1"", ""word2"", ""word3""]";
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var response = await _geminiClient.CallGeminiAPIAsync(prompt);
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// 解析 AI 回應
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var cleanedResponse = ExtractJsonFromResponse(response);
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var generatedWords = JsonSerializer.Deserialize<string[]>(cleanedResponse);
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if (generatedWords == null || generatedWords.Length == 0)
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{
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_logger.LogWarning("AI returned empty or invalid response for word '{Word}'", targetWord);
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return GetFallbackDistractors(targetWord, cefrLevel, partOfSpeech, count);
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}
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// 轉換為 OptionsVocabulary 實體
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var options = generatedWords.Take(count).Select(word => new OptionsVocabulary
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{
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Id = Guid.NewGuid(),
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Word = word.Trim(),
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CEFRLevel = cefrLevel,
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PartOfSpeech = partOfSpeech,
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IsActive = true,
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CreatedAt = DateTime.UtcNow,
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UpdatedAt = DateTime.UtcNow
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}).ToList();
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// 計算字數長度
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foreach (var option in options)
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{
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option.CalculateWordLength();
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}
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return options;
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}
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catch (Exception ex)
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{
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_logger.LogError(ex, "AI generation failed for word '{Word}', falling back to fixed options", targetWord);
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return GetFallbackDistractors(targetWord, cefrLevel, partOfSpeech, count);
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}
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}
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/// <summary>
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/// 降級固定選項（當 AI 生成失敗時使用）
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/// </summary>
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private List<OptionsVocabulary> GetFallbackDistractors(
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string targetWord,
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string cefrLevel,
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string partOfSpeech,
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int count)
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{
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// 根據詞性提供不同的固定選項
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var fallbackWords = partOfSpeech.ToLower() switch
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{
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"verb" => new[] { "create", "destroy", "change", "develop", "improve", "reduce" },
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"noun" => new[] { "example", "result", "problem", "method", "system", "process" },
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"adjective" => new[] { "important", "different", "special", "general", "common", "simple" },
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"adverb" => new[] { "quickly", "carefully", "easily", "slowly", "clearly", "directly" },
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_ => new[] { "option", "choice", "answer", "question", "test", "study" }
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};
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return fallbackWords
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.Where(word => !string.Equals(word, targetWord, StringComparison.OrdinalIgnoreCase))
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.Take(count)
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.Select(word => new OptionsVocabulary
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{
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Id = Guid.NewGuid(),
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Word = word,
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CEFRLevel = cefrLevel,
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PartOfSpeech = partOfSpeech,
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IsActive = true,
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CreatedAt = DateTime.UtcNow,
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UpdatedAt = DateTime.UtcNow
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})
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.ToList();
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}
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/// <summary>
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/// 從 AI 回應中提取 JSON 內容
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/// </summary>
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private string ExtractJsonFromResponse(string response)
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{
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// 移除可能的 markdown 代碼塊標記
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var cleaned = response.Replace("```json", "").Replace("```", "").Trim();
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// 找到第一個 [ 和最後一個 ]
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var startIndex = cleaned.IndexOf('[');
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var endIndex = cleaned.LastIndexOf(']');
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if (startIndex >= 0 && endIndex >= 0 && endIndex > startIndex)
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{
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return cleaned.Substring(startIndex, endIndex - startIndex + 1);
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}
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return cleaned;
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}
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}
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