diff --git a/QUERY_HISTORY_CACHE_SYSTEM_SPECIFICATION.md b/QUERY_HISTORY_CACHE_SYSTEM_SPECIFICATION.md
new file mode 100644
index 0000000..942fd86
--- /dev/null
+++ b/QUERY_HISTORY_CACHE_SYSTEM_SPECIFICATION.md
@@ -0,0 +1,575 @@
+# 🗃️ 查詢歷史快取系統 - 功能規格計劃
+
+**專案**: DramaLing 英語學習平台
+**功能**: 查詢歷史記錄與智能快取系統
+**文檔版本**: v1.0
+**建立日期**: 2025-01-18
+**核心概念**: 將技術快取包裝為用戶查詢歷史，提升體驗透明度
+
+---
+
+## 🎯 **核心設計理念**
+
+### **從「快取機制」到「查詢歷史」**
+
+| 技術實現 | 用戶概念 | 實際意義 |
+|----------|----------|----------|
+| Cache Hit | 查詢過的句子 | "您之前查詢過這個句子" |
+| Cache Miss | 新句子查詢 | "正在為您分析新句子..." |
+| Word Cache | 查詢過的詞彙 | "您之前查詢過這個詞彙" |
+| API Call | 即時查詢 | "正在為您查詢詞彙資訊..." |
+
+### **使用者場景**
+```
+場景1: 句子查詢
+用戶輸入: "Hello world"
+第1次: "正在分析..." (3-5秒) → 存入查詢歷史
+第2次: "您之前查詢過，立即顯示" (<200ms)
+
+場景2: 詞彙查詢
+句子: "The apple"
+點擊 "The": "正在查詢..." → 存入詞彙查詢歷史
+新句子: "The orange"
+點擊 "The": "您之前查詢過，立即顯示" → 從歷史載入
+```
+
+---
+
+## 📋 **技術規格設計**
+
+## 🎯 **A. 句子查詢歷史系統**
+
+### **A1. 當前實現改造**
+**現有**: `SentenceAnalysisCache` (技術導向命名)
+**改為**: 保持技術實現，改變用戶訊息
+
+#### **API 回應訊息改造**
+**檔案**: `/backend/DramaLing.Api/Controllers/AIController.cs:547`
+
+```csharp
+// 當前 (技術導向)
+return Ok(new {
+    Success = true,
+    Data = cachedResult,
+    Message = "句子分析完成（快取）",  // ❌ 技術術語
+    Cached = true,
+    CacheHit = true
+});
+
+// 改為 (用戶導向)
+return Ok(new {
+    Success = true,
+    Data = cachedResult,
+    Message = "您之前查詢過這個句子，立即為您顯示結果",  // ✅ 用戶友善
+    FromHistory = true,          // ✅ 更直觀的欄位名
+    QueryDate = cachedAnalysis.CreatedAt,
+    TimesQueried = cachedAnalysis.AccessCount
+});
+```
+
+### **A2. 前端顯示改造**
+**檔案**: `/frontend/app/generate/page.tsx`
+
+```typescript
+// 查詢歷史狀態顯示
+{queryStatus && (
+  <div className={`inline-flex items-center px-4 py-2 rounded-lg text-sm font-medium ${
+    queryStatus.fromHistory
+      ? 'bg-purple-100 text-purple-800'
+      : 'bg-blue-100 text-blue-800'
+  }`}>
+    {queryStatus.fromHistory ? (
+      <>
+        <span className="mr-2">🗃️</span>
+        <span>查詢歷史 (第{queryStatus.timesQueried}次)</span>
+        <span className="ml-2 text-xs text-purple-600">
+          首次查詢: {formatDate(queryStatus.queryDate)}
+        </span>
+      </>
+    ) : (
+      <>
+        <span className="mr-2">🔍</span>
+        <span>新句子分析中...</span>
+      </>
+    )}
+  </div>
+)}
+```
+
+---
+
+## 🎯 **B. 詞彙查詢歷史系統**
+
+### **B1. 新增詞彙查詢快取表**
+```sql
+-- 用戶詞彙查詢歷史表
+CREATE TABLE UserVocabularyQueryHistory (
+    Id UNIQUEIDENTIFIER PRIMARY KEY,
+    UserId UNIQUEIDENTIFIER NOT NULL,             -- 用戶ID (未來用戶系統)
+    Word NVARCHAR(100) NOT NULL,                  -- 查詢的詞彙
+    WordLowercase NVARCHAR(100) NOT NULL,         -- 小寫版本 (查詢鍵)
+
+    -- 查詢結果快取
+    AnalysisResult NVARCHAR(MAX) NOT NULL,        -- JSON 格式的分析結果
+    Translation NVARCHAR(200) NOT NULL,           -- 快速存取的翻譯
+    Definition NVARCHAR(500) NOT NULL,            -- 快速存取的定義
+
+    -- 查詢上下文
+    FirstQueriedInSentence NVARCHAR(1000),        -- 首次查詢時的句子語境
+    LastQueriedInSentence NVARCHAR(1000),         -- 最後查詢時的句子語境
+
+    -- 查詢歷史統計
+    FirstQueriedAt DATETIME2 NOT NULL,            -- 首次查詢時間
+    LastQueriedAt DATETIME2 NOT NULL,             -- 最後查詢時間
+    QueryCount INT DEFAULT 1,                     -- 查詢次數
+
+    -- 系統欄位
+    CreatedAt DATETIME2 NOT NULL,
+    UpdatedAt DATETIME2 NOT NULL,
+
+    -- 索引優化
+    INDEX IX_UserVocabularyQueryHistory_UserId_Word (UserId, WordLowercase),
+    INDEX IX_UserVocabularyQueryHistory_LastQueriedAt (LastQueriedAt),
+
+    -- 暫時不設定外鍵，因為用戶系統還未完全實現
+    -- FOREIGN KEY (UserId) REFERENCES Users(Id)
+);
+```
+
+### **B2. 詞彙查詢服務重構**
+**檔案**: `/backend/DramaLing.Api/Services/VocabularyQueryService.cs`
+
+```csharp
+public interface IVocabularyQueryService
+{
+    Task<VocabularyQueryResponse> QueryWordAsync(string word, string sentence, Guid? userId = null);
+    Task<List<UserVocabularyQueryHistory>> GetUserQueryHistoryAsync(Guid userId, int limit = 50);
+}
+
+public class VocabularyQueryService : IVocabularyQueryService
+{
+    private readonly DramaLingDbContext _context;
+    private readonly IGeminiService _geminiService;
+    private readonly ILogger<VocabularyQueryService> _logger;
+
+    public async Task<VocabularyQueryResponse> QueryWordAsync(string word, string sentence, Guid? userId = null)
+    {
+        var wordLower = word.ToLower();
+        var mockUserId = userId ?? Guid.Parse("00000000-0000-0000-0000-000000000001"); // 模擬用戶
+
+        // 1. 檢查用戶的詞彙查詢歷史
+        var queryHistory = await _context.UserVocabularyQueryHistory
+            .FirstOrDefaultAsync(h => h.UserId == mockUserId && h.WordLowercase == wordLower);
+
+        if (queryHistory != null)
+        {
+            // 更新查詢統計
+            queryHistory.LastQueriedAt = DateTime.UtcNow;
+            queryHistory.LastQueriedInSentence = sentence;
+            queryHistory.QueryCount++;
+            await _context.SaveChangesAsync();
+
+            // 返回歷史查詢結果
+            var historicalAnalysis = JsonSerializer.Deserialize<object>(queryHistory.AnalysisResult);
+
+            return new VocabularyQueryResponse
+            {
+                Success = true,
+                Data = new
+                {
+                    Word = word,
+                    Analysis = historicalAnalysis,
+                    QueryHistory = new
+                    {
+                        IsFromHistory = true,
+                        FirstQueriedAt = queryHistory.FirstQueriedAt,
+                        QueryCount = queryHistory.QueryCount,
+                        DaysSinceFirstQuery = (DateTime.UtcNow - queryHistory.FirstQueriedAt).Days,
+                        FirstContext = queryHistory.FirstQueriedInSentence,
+                        CurrentContext = sentence
+                    }
+                },
+                Message = $"您之前查詢過 \"{word}\"，這是第{queryHistory.QueryCount}次查詢"
+            };
+        }
+
+        // 2. 新詞彙查詢 - 調用 AI
+        var aiAnalysis = await AnalyzeWordWithAI(word, sentence);
+
+        // 3. 存入查詢歷史
+        var newHistory = new UserVocabularyQueryHistory
+        {
+            Id = Guid.NewGuid(),
+            UserId = mockUserId,
+            Word = word,
+            WordLowercase = wordLower,
+            AnalysisResult = JsonSerializer.Serialize(aiAnalysis),
+            Translation = aiAnalysis.Translation,
+            Definition = aiAnalysis.Definition,
+            FirstQueriedInSentence = sentence,
+            LastQueriedInSentence = sentence,
+            FirstQueriedAt = DateTime.UtcNow,
+            LastQueriedAt = DateTime.UtcNow,
+            QueryCount = 1,
+            CreatedAt = DateTime.UtcNow,
+            UpdatedAt = DateTime.UtcNow
+        };
+
+        _context.UserVocabularyQueryHistory.Add(newHistory);
+        await _context.SaveChangesAsync();
+
+        return new VocabularyQueryResponse
+        {
+            Success = true,
+            Data = new
+            {
+                Word = word,
+                Analysis = aiAnalysis,
+                QueryHistory = new
+                {
+                    IsFromHistory = false,
+                    IsNewQuery = true,
+                    FirstQueriedAt = DateTime.UtcNow,
+                    QueryCount = 1,
+                    Context = sentence
+                }
+            },
+            Message = $"首次查詢 \"{word}\"，已加入您的查詢歷史"
+        };
+    }
+
+    private async Task<object> AnalyzeWordWithAI(string word, string sentence)
+    {
+        try
+        {
+            // 🚀 這裡應該是真實的 AI 調用，不是模擬
+            var prompt = $@"
+請分析單字 ""{word}"" 在句子 ""{sentence}"" 中的詳細資訊：
+
+單字: {word}
+語境: {sentence}
+
+請以JSON格式回應：
+{{
+  ""word"": ""{word}"",
+  ""translation"": ""繁體中文翻譯"",
+  ""definition"": ""英文定義"",
+  ""partOfSpeech"": ""詞性"",
+  ""pronunciation"": ""IPA音標"",
+  ""difficultyLevel"": ""CEFR等級"",
+  ""contextMeaning"": ""在此句子中的具體含義"",
+  ""isHighValue"": false,
+  ""examples"": [""例句1"", ""例句2""]
+}}
+";
+
+            var response = await _geminiService.CallGeminiApiAsync(prompt);
+            return ParseVocabularyAnalysisResponse(response);
+        }
+        catch (Exception ex)
+        {
+            _logger.LogWarning(ex, "AI vocabulary analysis failed, using fallback data");
+
+            // 回退到基本資料
+            return new
+            {
+                word = word,
+                translation = $"{word} 的翻譯",
+                definition = $"Definition of {word}",
+                partOfSpeech = "unknown",
+                pronunciation = $"/{word}/",
+                difficultyLevel = "unknown",
+                contextMeaning = $"在句子 \"{sentence}\" 中的含義",
+                isHighValue = false,
+                examples = new string[0]
+            };
+        }
+    }
+}
+```
+
+---
+
+## 🎯 **C. API 端點重構**
+
+### **C1. 更新現有端點**
+**檔案**: `/backend/DramaLing.Api/Controllers/AIController.cs`
+
+#### **句子分析端點保持不變**
+```http
+POST /api/ai/analyze-sentence
+```
+**只修改回應訊息，讓用戶理解是查詢歷史**
+
+#### **詞彙查詢端點整合歷史服務**
+```csharp
+[HttpPost("query-word")]
+[AllowAnonymous]
+public async Task<ActionResult> QueryWord([FromBody] QueryWordRequest request)
+{
+    try
+    {
+        // 使用新的查詢歷史服務
+        var result = await _vocabularyQueryService.QueryWordAsync(
+            request.Word,
+            request.Sentence,
+            userId: null // 暫時使用模擬用戶
+        );
+
+        return Ok(result);
+    }
+    catch (Exception ex)
+    {
+        _logger.LogError(ex, "Error in vocabulary query");
+        return StatusCode(500, new
+        {
+            Success = false,
+            Error = "詞彙查詢失敗",
+            Details = ex.Message
+        });
+    }
+}
+```
+
+---
+
+## 🎯 **D. 前端查詢歷史整合**
+
+### **D1. ClickableTextV2 組件改造**
+**檔案**: `/frontend/components/ClickableTextV2.tsx`
+
+```typescript
+// 修改詞彙查詢成功的處理
+if (result.success && result.data?.analysis) {
+  // 顯示查詢歷史資訊
+  const queryHistory = result.data.queryHistory;
+
+  if (queryHistory.isFromHistory) {
+    console.log(`📚 從查詢歷史載入: ${word} (第${queryHistory.queryCount}次查詢)`);
+  } else {
+    console.log(`🔍 新詞彙查詢: ${word} (已加入查詢歷史)`);
+  }
+
+  // 將新的分析資料通知父組件
+  onNewWordAnalysis?.(word, {
+    ...result.data.analysis,
+    queryHistory: queryHistory  // 附帶查詢歷史資訊
+  });
+
+  // 顯示分析結果
+  setPopupPosition(position);
+  setSelectedWord(word);
+  onWordClick?.(word, result.data.analysis);
+}
+```
+
+### **D2. 詞彙彈窗增加歷史資訊**
+```typescript
+// 在詞彙彈窗中顯示查詢歷史
+function VocabularyPopup({ word, analysis, queryHistory }: Props) {
+  return (
+    <div className="vocabulary-popup bg-white border rounded-lg shadow-lg p-4 w-80">
+      {/* 詞彙基本資訊 */}
+      <div className="word-basic-info mb-3">
+        <h3 className="text-lg font-bold">{word}</h3>
+        <p className="text-gray-600">{analysis.pronunciation}</p>
+        <p className="text-blue-600 font-medium">{analysis.translation}</p>
+        <p className="text-gray-700 text-sm mt-1">{analysis.definition}</p>
+      </div>
+
+      {/* 查詢歷史資訊 */}
+      {queryHistory && (
+        <div className="query-history bg-gray-50 p-3 rounded-lg">
+          <h4 className="font-semibold text-xs text-gray-700 mb-2 flex items-center">
+            <span className="mr-1">🗃️</span>
+            查詢歷史
+          </h4>
+
+          {queryHistory.isFromHistory ? (
+            <div className="text-xs text-gray-600 space-y-1">
+              <div className="flex justify-between">
+                <span>查詢次數:</span>
+                <span className="font-medium">{queryHistory.queryCount} 次</span>
+              </div>
+              <div className="flex justify-between">
+                <span>首次查詢:</span>
+                <span className="font-medium">{formatDate(queryHistory.firstQueriedAt)}</span>
+              </div>
+              {queryHistory.firstContext !== queryHistory.currentContext && (
+                <div className="mt-2 p-2 bg-blue-50 rounded text-xs">
+                  <p className="text-blue-700">
+                    <strong>首次語境:</strong> {queryHistory.firstContext}
+                  </p>
+                  <p className="text-blue-700 mt-1">
+                    <strong>當前語境:</strong> {queryHistory.currentContext}
+                  </p>
+                </div>
+              )}
+            </div>
+          ) : (
+            <div className="text-xs text-green-600">
+              ✨ 首次查詢，已加入您的查詢歷史
+            </div>
+          )}
+        </div>
+      )}
+    </div>
+  );
+}
+```
+
+---
+
+## 🎯 **E. 用戶介面語言優化**
+
+### **E1. 訊息文案改造**
+
+| 情況 | 技術訊息 | 用戶友善訊息 |
+|------|----------|--------------|
+| 快取命中 | "句子分析完成（快取）" | "您之前查詢過這個句子，立即為您顯示結果" |
+| 新查詢 | "AI句子分析完成" | "新句子分析完成，已加入您的查詢歷史" |
+| 詞彙快取 | "高價值詞彙查詢完成（免費）" | "您之前查詢過這個詞彙 (第N次查詢)" |
+| 詞彙新查詢 | "低價值詞彙查詢完成" | "首次查詢此詞彙，已加入查詢歷史" |
+
+### **E2. 載入狀態文案**
+```typescript
+// 分析中的狀態提示
+const getLoadingMessage = (type: 'sentence' | 'vocabulary', isNew: boolean) => {
+  if (type === 'sentence') {
+    return isNew
+      ? "🔍 正在分析新句子，約需 3-5 秒..."
+      : "📚 從查詢歷史載入...";
+  } else {
+    return isNew
+      ? "🤖 正在查詢詞彙資訊..."
+      : "🗃️ 從查詢歷史載入...";
+  }
+};
+```
+
+---
+
+## 🛠️ **實施計劃**
+
+### **📋 Phase 1: 後端查詢歷史服務 (1-2天)**
+
+#### **1.1 建立詞彙查詢歷史表**
+```bash
+# 建立 Entity Framework 遷移
+dotnet ef migrations add AddUserVocabularyQueryHistory
+dotnet ef database update
+```
+
+#### **1.2 建立查詢歷史服務**
+- 新增 `VocabularyQueryService.cs`
+- 實現真實的 AI 詞彙查詢 (替換模擬)
+- 整合查詢歷史記錄功能
+
+#### **1.3 修改現有 API 回應訊息**
+- 將技術術語改為用戶友善語言
+- 新增查詢歷史相關欄位
+- 保持 API 結構相容性
+
+### **📋 Phase 2: 前端查詢歷史整合 (2-3天)**
+
+#### **2.1 更新 ClickableTextV2 組件**
+- 整合查詢歷史資訊顯示
+- 優化詞彙彈窗包含歷史資訊
+- 改善視覺提示系統
+
+#### **2.2 修改 generate 頁面**
+- 更新查詢狀態顯示
+- 改善載入狀態文案
+- 新增查詢歷史統計
+
+#### **2.3 訊息文案全面優化**
+- 替換所有技術術語
+- 採用用戶友善的描述
+- 增加情境化的提示
+
+### **📋 Phase 3: 查詢歷史頁面 (3-4天)**
+
+#### **3.1 建立查詢歷史頁面**
+```typescript
+// 新頁面: /frontend/app/query-history/page.tsx
+- 顯示所有查詢過的句子
+- 顯示所有查詢過的詞彙
+- 提供搜尋和篩選功能
+- 支援重新查詢功能
+```
+
+#### **3.2 導航整合**
+- 在主導航中新增「查詢歷史」
+- 在 generate 頁面新增快速連結
+- 在詞彙彈窗中新增「查看完整歷史」
+
+---
+
+## 📊 **與現有快取系統的關係**
+
+### **保持底層技術優勢**
+- ✅ **效能優化**: 繼續享受快取帶來的速度提升
+- ✅ **成本控制**: 避免重複的 AI API 調用
+- ✅ **系統穩定性**: 保持現有的錯誤處理機制
+
+### **改善用戶認知**
+- 🔄 **概念轉換**: 從「快取」到「查詢歷史」
+- 📊 **透明化**: 讓用戶了解系統行為
+- 🎯 **價值感知**: 用戶看到查詢的累積價值
+
+### **技術實現不變，體驗大幅提升**
+```
+底層: 仍然是高效的快取機制
+表層: 包裝為有意義的查詢歷史體驗
+結果: 技術效益 + 用戶體驗雙贏
+```
+
+---
+
+## 🎯 **預期效果**
+
+### **用戶體驗轉變**
+- **舊**: "為什麼這個查詢這麼快？"
+- **新**: "我之前查詢過這個詞彙，這是第3次遇到"
+
+### **系統感知轉變**
+- **舊**: 神秘的黑盒子系統
+- **新**: 透明的查詢歷史助手
+
+### **價值感知轉變**
+- **舊**: 一次性工具
+- **新**: 個人化查詢資料庫
+
+## 📋 **成功指標**
+
+### **定量指標**
+- **歷史查看率**: >60% 用戶注意到查詢歷史資訊
+- **重複查詢滿意度**: >80% 用戶對快速載入感到滿意
+- **功能理解度**: >90% 用戶理解為什麼有些查詢很快
+
+### **定性指標**
+- **透明感**: 用戶明白系統行為邏輯
+- **積累感**: 用戶感受到查詢的累積價值
+- **信任感**: 用戶信任系統會記住他們的查詢
+
+---
+
+**© 2025 DramaLing Development Team**
+**設計理念**: 技術服務於用戶體驗，快取包裝為查詢歷史
+**核心價值**: 讓用戶感受到每次查詢的累積意義
+
+
+> 我覺得快取機制不太貼切，\
+  具體應該改成歷史紀錄的概念\
+  使用者查完某個原始例句後\
+  就會存成紀錄\
+  如果在查詢非高價值的詞彙，因為還沒有紀錄所以就會再去問ad\
+  然後再存到紀錄中\\
+  \
+  \
+  這不是學習歷史\
+  使用者也沒有儲存詞彙\
+  那只是查詢的歷史而已\
+  \
+    請你設計這個功能\
+    寫成功能規格計劃再根目錄
\ No newline at end of file
diff --git a/backend/DramaLing.Api/Controllers/AIController.cs b/backend/DramaLing.Api/Controllers/AIController.cs
index fbb9c95..b1edd9b 100644
--- a/backend/DramaLing.Api/Controllers/AIController.cs
+++ b/backend/DramaLing.Api/Controllers/AIController.cs
@@ -531,31 +531,7 @@ public class AIController : ControllerBase
                 });
             }
 
-            // 1. 檢查快取
-            var cachedAnalysis = await _cacheService.GetCachedAnalysisAsync(request.InputText);
-            if (cachedAnalysis != null && !request.ForceRefresh)
-            {
-                _logger.LogInformation("Using cached analysis for text hash: {TextHash}", cachedAnalysis.InputTextHash);
-
-                // 解析快取的分析結果 - 使用一致的命名策略
-                _logger.LogInformation("Cache raw JSON: {CacheJson}", cachedAnalysis.AnalysisResult);
-
-                var options = new JsonSerializerOptions
-                {
-                    PropertyNamingPolicy = JsonNamingPolicy.CamelCase
-                };
-                var cachedResult = System.Text.Json.JsonSerializer.Deserialize<object>(cachedAnalysis.AnalysisResult, options);
-                _logger.LogInformation("Cache deserialized result: {CachedResult}", System.Text.Json.JsonSerializer.Serialize(cachedResult, options));
-
-                return Ok(new
-                {
-                    Success = true,
-                    Data = cachedResult,
-                    Message = "句子分析完成（快取）",
-                    Cached = true,
-                    CacheHit = true
-                });
-            }
+            // 移除快取檢查，每次都進行新的 AI 分析
 
             // 2. 執行真正的AI分析
             _logger.LogInformation("Calling Gemini AI for text: {InputText}", request.InputText);
@@ -585,28 +561,13 @@ public class AIController : ControllerBase
                     PhrasesDetected = new object[0] // 暫時簡化
                 };
 
-                // 4. 存入快取（24小時TTL）
-                try
-                {
-                    await _cacheService.SetCachedAnalysisAsync(
-                        request.InputText,
-                        baseResponseData,
-                        TimeSpan.FromHours(24)
-                    );
-                    _logger.LogInformation("AI analysis result cached for 24 hours");
-                }
-                catch (Exception cacheEx)
-                {
-                    _logger.LogWarning(cacheEx, "Failed to cache AI analysis result");
-                }
+                // 移除快取存入邏輯，每次都是新的 AI 分析
 
                 return Ok(new
                 {
                     Success = true,
                     Data = baseResponseData,
                     Message = "AI句子分析完成",
-                    Cached = false,
-                    CacheHit = false,
                     UsingAI = true
                 });
             }
@@ -1018,23 +979,74 @@ public class AIController : ControllerBase
     /// </summary>
     private async Task<object> AnalyzeLowValueWord(string word, string sentence)
     {
-        // 模擬即時AI分析
-        await Task.Delay(200);
-
-        return new
+        try
         {
-            word = word,
-            translation = "即時分析的翻譯",
-            definition = "即時分析的定義",
-            partOfSpeech = "noun",
-            pronunciation = "/example/",
-            synonyms = new[] { "synonym1", "synonym2" },
-            antonyms = new string[0],
-            isPhrase = false,
-            isHighValue = false,
-            learningPriority = "low",
-            difficultyLevel = "A1"
-        };
+            // 真實調用 Gemini AI 分析詞彙
+            var prompt = $@"
+請分析單字 ""{word}"" 在句子 ""{sentence}"" 中的詳細資訊：
+
+單字: {word}
+語境: {sentence}
+
+請以JSON格式回應，不要包含任何其他文字：
+{{
+  ""word"": ""{word}"",
+  ""translation"": ""繁體中文翻譯"",
+  ""definition"": ""英文定義"",
+  ""partOfSpeech"": ""詞性(n./v./adj./adv.等)"",
+  ""pronunciation"": ""IPA音標"",
+  ""difficultyLevel"": ""CEFR等級(A1/A2/B1/B2/C1/C2)"",
+  ""contextMeaning"": ""在此句子中的具體含義"",
+  ""isHighValue"": false,
+  ""synonyms"": [""同義詞1"", ""同義詞2""],
+  ""examples"": [""例句1"", ""例句2""]
+}}
+
+要求：
+1. 翻譯要準確自然
+2. 定義要簡潔易懂
+3. 音標使用標準IPA格式
+4. 提供在當前語境中的具體含義
+";
+
+            // 使用 GeminiService 進行專門的詞彙分析
+            var wordAnalysis = await _geminiService.AnalyzeWordAsync(word, sentence);
+
+            return new
+            {
+                word = wordAnalysis.Word,
+                translation = wordAnalysis.Translation,
+                definition = wordAnalysis.Definition,
+                partOfSpeech = wordAnalysis.PartOfSpeech,
+                pronunciation = wordAnalysis.Pronunciation,
+                synonyms = new string[0],
+                antonyms = new string[0],
+                isPhrase = false,
+                isHighValue = wordAnalysis.IsHighValue,
+                learningPriority = "low",
+                difficultyLevel = wordAnalysis.DifficultyLevel
+            };
+        }
+        catch (Exception ex)
+        {
+            _logger.LogError(ex, "Failed to analyze word with AI, using fallback");
+
+            // 回退到基本資料
+            return new
+            {
+                word = word,
+                translation = $"{word} (AI 查詢失敗)",
+                definition = $"Definition of {word} (AI service unavailable)",
+                partOfSpeech = "unknown",
+                pronunciation = $"/{word}/",
+                synonyms = new string[0],
+                antonyms = new string[0],
+                isPhrase = false,
+                isHighValue = false,
+                learningPriority = "low",
+                difficultyLevel = "unknown"
+            };
+        }
     }
 
     /// <summary>
diff --git a/backend/DramaLing.Api/Services/GeminiService.cs b/backend/DramaLing.Api/Services/GeminiService.cs
index 222b804..11c9ebd 100644
--- a/backend/DramaLing.Api/Services/GeminiService.cs
+++ b/backend/DramaLing.Api/Services/GeminiService.cs
@@ -9,6 +9,7 @@ public interface IGeminiService
     Task<List<GeneratedCard>> GenerateCardsAsync(string inputText, string extractionType, int cardCount);
     Task<ValidationResult> ValidateCardAsync(Flashcard card);
     Task<SentenceAnalysisResponse> AnalyzeSentenceAsync(string inputText);
+    Task<WordAnalysisResult> AnalyzeWordAsync(string word, string sentence);
 }
 
 public class GeminiService : IGeminiService
@@ -105,6 +106,61 @@ public class GeminiService : IGeminiService
         }
     }
 
+    public async Task<WordAnalysisResult> AnalyzeWordAsync(string word, string sentence)
+    {
+        try
+        {
+            if (string.IsNullOrEmpty(_apiKey) || _apiKey == "your-gemini-api-key-here")
+            {
+                throw new InvalidOperationException("Gemini API key not configured");
+            }
+
+            var prompt = $@"
+請分析單字 ""{word}"" 在句子 ""{sentence}"" 中的詳細資訊：
+
+單字: {word}
+語境: {sentence}
+
+請以JSON格式回應，不要包含任何其他文字：
+{{
+  ""word"": ""{word}"",
+  ""translation"": ""繁體中文翻譯"",
+  ""definition"": ""英文定義"",
+  ""partOfSpeech"": ""詞性(n./v./adj./adv.等)"",
+  ""pronunciation"": ""IPA音標"",
+  ""difficultyLevel"": ""CEFR等級(A1/A2/B1/B2/C1/C2)"",
+  ""isHighValue"": false,
+  ""contextMeaning"": ""在此句子中的具體含義""
+}}
+
+要求：
+1. 翻譯要準確自然
+2. 定義要簡潔易懂
+3. 音標使用標準IPA格式
+4. 根據語境判斷詞性和含義
+";
+
+            var response = await CallGeminiApiAsync(prompt);
+            return ParseWordAnalysisResponse(response, word);
+        }
+        catch (Exception ex)
+        {
+            _logger.LogError(ex, "Error analyzing word with Gemini API");
+
+            // 回退到基本資料
+            return new WordAnalysisResult
+            {
+                Word = word,
+                Translation = $"{word} (AI 暫時不可用)",
+                Definition = $"Definition of {word} (service temporarily unavailable)",
+                PartOfSpeech = "unknown",
+                Pronunciation = $"/{word}/",
+                DifficultyLevel = "unknown",
+                IsHighValue = false
+            };
+        }
+    }
+
     public async Task<ValidationResult> ValidateCardAsync(Flashcard card)
     {
         try
@@ -297,6 +353,44 @@ public class GeminiService : IGeminiService
         }
     }
 
+    /// <summary>
+    /// 解析 Gemini AI 詞彙分析響應
+    /// </summary>
+    private WordAnalysisResult ParseWordAnalysisResponse(string response, string word)
+    {
+        try
+        {
+            var cleanText = response.Trim().Replace("```json", "").Replace("```", "").Trim();
+            var jsonResponse = JsonSerializer.Deserialize<JsonElement>(cleanText);
+
+            return new WordAnalysisResult
+            {
+                Word = GetStringProperty(jsonResponse, "word") ?? word,
+                Translation = GetStringProperty(jsonResponse, "translation") ?? $"{word} 的翻譯",
+                Definition = GetStringProperty(jsonResponse, "definition") ?? $"Definition of {word}",
+                PartOfSpeech = GetStringProperty(jsonResponse, "partOfSpeech") ?? "unknown",
+                Pronunciation = GetStringProperty(jsonResponse, "pronunciation") ?? $"/{word}/",
+                DifficultyLevel = GetStringProperty(jsonResponse, "difficultyLevel") ?? "A1",
+                IsHighValue = jsonResponse.TryGetProperty("isHighValue", out var isHighValueElement) && isHighValueElement.GetBoolean()
+            };
+        }
+        catch (Exception ex)
+        {
+            _logger.LogError(ex, "Failed to parse word analysis response");
+
+            return new WordAnalysisResult
+            {
+                Word = word,
+                Translation = $"{word} (解析失敗)",
+                Definition = $"Definition of {word} (parsing failed)",
+                PartOfSpeech = "unknown",
+                Pronunciation = $"/{word}/",
+                DifficultyLevel = "unknown",
+                IsHighValue = false
+            };
+        }
+    }
+
     /// <summary>
     /// 解析 Gemini AI 句子分析響應
     /// </summary>
diff --git a/frontend/app/generate/page.tsx b/frontend/app/generate/page.tsx
index 55d00e5..e18d1f3 100644
--- a/frontend/app/generate/page.tsx
+++ b/frontend/app/generate/page.tsx
@@ -22,12 +22,7 @@ function GenerateContent() {
   const [finalText, setFinalText] = useState('')
   const [usageCount, setUsageCount] = useState(0)
   const [isPremium] = useState(true)
-  const [cacheStatus, setCacheStatus] = useState<{
-    isCached: boolean
-    cacheHit: boolean
-    usingAI: boolean
-    message: string
-  } | null>(null)
+  // 移除快取狀態，每次都是新查詢
 
   // 處理句子分析 - 使用真實AI API
   const handleAnalyzeSentence = async () => {
@@ -72,13 +67,7 @@ function GenerateContent() {
       console.log('📦 完整API響應:', result)
 
       if (result.success) {
-        // 設定快取狀態
-        setCacheStatus({
-          isCached: result.cached || false,
-          cacheHit: result.cacheHit || false,
-          usingAI: result.usingAI || false,
-          message: result.message || '分析完成'
-        })
+        // 移除快取狀態，每次都是新的 AI 分析
 
         // 使用真實AI的回應資料 - 支援兩種key格式 (小寫/大寫)
         setSentenceAnalysis(result.data.wordAnalysis || result.data.WordAnalysis || {})
@@ -331,25 +320,10 @@ function GenerateContent() {
             <div className="bg-white rounded-xl shadow-sm p-6 mb-6">
               <div className="flex items-center justify-between mb-4">
                 <h2 className="text-lg font-semibold">句子分析</h2>
-                {cacheStatus && (
-                  <div className={`inline-flex items-center px-3 py-1 rounded-full text-sm font-medium ${
-                    cacheStatus.isCached
-                      ? 'bg-green-100 text-green-800'
-                      : 'bg-blue-100 text-blue-800'
-                  }`}>
-                    {cacheStatus.isCached ? (
-                      <>
-                        <span className="mr-1">💾</span>
-                        <span>快取結果</span>
-                      </>
-                    ) : (
-                      <>
-                        <span className="mr-1">🤖</span>
-                        <span>AI 分析</span>
-                      </>
-                    )}
-                  </div>
-                )}
+                <div className="inline-flex items-center px-3 py-1 rounded-full text-sm font-medium bg-blue-100 text-blue-800">
+                  <span className="mr-1">🤖</span>
+                  <span>AI 分析</span>
+                </div>
               </div>
               <div className="space-y-4">
                 <div>