Update app.py

app.py

@@ -10,6 +10,10 @@ from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_community.vectorstores import FAISS
 from PIL import Image
 from dotenv import load_dotenv
+import warnings
+
+# 忽略警告
+warnings.filterwarnings("ignore")
 load_dotenv()  # 自動尋找並載入 .env 檔案中的變數
 
 # ==========================================
@@ -34,27 +38,33 @@ def init_rag_system():
 
     print("⏳ 正在初始化系統...")
     
-    # --- A. 讀取 CSV (用於篩選與對照) ---
+    # --- A. 讀取 CSV ---
     try:
-        global_df = pd.read_csv('restaurants.csv')
-        global_df['RAG_Content'] = global_df['RAG_Content'].fillna("")
-        global_df['Category'] = global_df['Category'].fillna("其他")
-        
-        global_mood_df = pd.read_csv('mood_food_guide.csv')
+        # 嘗試讀取 restaurants.csv (請確保檔案存在)
+        if os.path.exists('restaurants.csv'):
+            global_df = pd.read_csv('restaurants.csv')
+            global_df['RAG_Content'] = global_df['RAG_Content'].fillna("")
+            global_df['Category'] = global_df['Category'].fillna("其他")
+        else:
+            print("⚠️ 找不到 restaurants.csv，將使用空的 DataFrame")
+            global_df = pd.DataFrame(columns=['Name', 'Category', 'Address', 'URL', 'Visual_prompt', 'RAG_Content'])
+
+        # 嘗試讀取 mood_food_guide.csv (若無則建立預設)
+        if os.path.exists('mood_food_guide.csv'):
+            global_mood_df = pd.read_csv('mood_food_guide.csv')
+        else:
+            global_mood_df = pd.DataFrame(columns=['分數', '推薦料理類別', '原因'])
+            
         print(f"✅ CSV 資料讀取成功 (餐廳: {len(global_df)} 筆)")
     except Exception as e:
         print(f"❌ CSV 讀取失敗: {e}")
         return
 
-    # --- B. 讀取預先建立好的 FAISS 索引 ---
-    # 這裡不再重新建立，而是直接讀取 "faiss_index" 資料夾
+    # --- B. 讀取 FAISS 索引 ---
     if os.path.exists("faiss_index"):
         try:
             print("⏳ 正在載入 FAISS 向量資料庫...")
             embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
-            
-            # allow_dangerous_deserialization=True 是必要的，因為我們讀取 pickle 檔
-            # 由於這是我們自己建立的檔案，所以是安全的
             vectorstore = FAISS.load_local(
                 "faiss_index", 
                 embeddings, 
@@ -64,9 +74,10 @@ def init_rag_system():
             print("✅ FAISS 資料庫載入完成！")
         except Exception as e:
             print(f"❌ FAISS 載入失敗: {e}")
+            global_retriever = None
     else:
-        print("⚠️ 警告：找不到 'faiss_index' 資料夾，RAG 功能將無法使用。")
-        print("請先執行 build_index.py 並上傳資料夾。")
+        print("⚠️ 警告：找不到 'faiss_index' 資料夾，RAG 功能將受限。")
+        global_retriever = None
 
     rag_initialized = True
 
@@ -80,13 +91,22 @@ custom_css = """
 .vertical-radio label { width: 100% !important; margin: 0 !important; display: flex !important; }
 """
 
-img_path_1 = "images/image_0.png"
-img_path_2 = "images/image_1.png"
+# 設定圖片路徑
+img_paths = {
+    "q1": "images/image_0.png",
+    "q2": "images/image_1.png",
+    "q3": "images/image_3.png",
+    "q4": "images/image_4.png",
+    "q5": "images/image_5.png"
+}
 
 if not os.path.exists("images"): os.makedirs("images")
-if not os.path.exists(img_path_1): Image.new('RGB', (400, 300), color='gray').save(img_path_1)
-if not os.path.exists(img_path_2): Image.new('RGB', (400, 300), color='lightblue').save(img_path_2)
+# 自動產生缺失的圖片（僅作為佔位符）
+for key, path in img_paths.items():
+    if not os.path.exists(path):
+        Image.new('RGB', (400, 300), color='#E0E0E0').save(path)
 
+# --- 選項設定 (您可以修改這裡的選項內容) ---
 q1_options_map = {
     "不​要​再​問白癡​問題​了​我​只​想​吃飯​": "現實主義者 (只想吃飯)",
     "去​過隱​居​生活": "隱士 (嚮往平靜)",
@@ -101,6 +121,30 @@ q2_options_map = {
     "領域​展開:​無量​空處​": "領域展開 (思緒混亂或想放空)"
 }
 
+# [新增] Q3 選項 - 旅遊
+q3_options_map = {
+    "日本 (秋葉原/古都巡禮)": "哈日族 (喜歡精緻美食)",
+    "歐洲 (充滿歷史與浪漫)": "浪漫派 (喜歡氣氛佳)",
+    "熱帶海島 (放空度假)": "享樂主義 (喜歡海鮮或冷飲)",
+    "南極 (挑戰極限)": "冒險家 (喜歡新奇食物)"
+}
+
+# [新增] Q4 選項 - 社交
+q4_options_map = {
+    "那個看起來最受歡迎的核心人物": "外向者 (喜歡熱鬧聚餐)",
+    "角落安靜滑手機的人": "內向者 (喜歡安靜獨食)",
+    "正在專心吃東西的人": "吃貨 (食物比人重要)",
+    "看起來跟我一樣尷尬的人": "隨和者 (好相處)"
+}
+
+# [新增] Q5 選項 - 追劇
+q5_options_map = {
+    "絕命毒師 (Breaking Bad)": "重口味/劇情控",
+    "六人行 (Friends)": "輕鬆美式/早午餐",
+    "鬼滅之刃": "熱血動漫迷",
+    "甄嬛傳": "宮廷/精緻料理"
+}
+
 # ==========================================
 # 3. 核心功能
 # ==========================================
@@ -114,17 +158,20 @@ def get_restaurant_data(mood_score_str, food_choice):
     except:
         score = 3
     
-    mood_info = global_mood_df[global_mood_df['分數'] == score]
-    if not mood_info.empty:
-        rec_categories = mood_info.iloc[0]['推薦料理類別']
-        mood_reason = mood_info.iloc[0]['原因']
-    else:
-        rec_categories = ""
-        mood_reason = "隨意探索"
+    # 嘗試從 mood_food_guide 獲取建議，若無則預設
+    rec_categories = ""
+    mood_reason = "隨意探索"
+    
+    if global_mood_df is not None and not global_mood_df.empty:
+        mood_info = global_mood_df[global_mood_df['分數'] == score]
+        if not mood_info.empty:
+            rec_categories = mood_info.iloc[0]['推薦料理類別']
+            mood_reason = mood_info.iloc[0]['原因']
 
     candidates = global_df.copy()
     
     if rec_categories:
+        # 簡單篩選類別
         candidates = candidates[candidates['Category'].apply(lambda x: str(x) in str(rec_categories) or str(rec_categories) in str(x))]
         
     food_keyword = "飯" if food_choice == "吃飯" else "麵" if food_choice == "吃麵" else ""
@@ -148,10 +195,21 @@ def generate_content_with_groq(restaurant_name, restaurant_detail, user_diary, m
     
     client = OpenAI(api_key=GROQ_API_KEY, base_url="https://api.groq.com/openai/v1")
     
-    system_prompt = "你是一個幽默、懂吃且善解人意的 AI 朋友。請根據使用者的日記、心情以及「心情美食指南」來推薦餐廳。"
+    system_prompt = "你是一個幽默、懂吃且善解人意的 AI 朋友。請根據使用者的日記、心情以及「五題心理測驗結果」來推薦餐廳。"
+    
+    # 組合測驗結果字串
+    quiz_summary = f"""
+    1. 直覺/人設: {quiz_result.get('q1', '未知')}
+    2. 魔法/口味: {quiz_result.get('q2', '未知')}
+    3. 旅遊/嚮往: {quiz_result.get('q3', '未知')}
+    4. 社交/個性: {quiz_result.get('q4', '未知')}
+    5. 追劇/喜好: {quiz_result.get('q5', '未知')}
+    """
+
     user_msg = f"""
     【狀態】心情分數：{mood_score}，日記：{user_diary}
-    【測驗結果】人設：{quiz_result.get('q1', '未知')}，魔法：{quiz_result.get('q2', '未知')}
+    【心理測驗全結果】
+    {quiz_summary}
     
     【心情美食指南建議】
     因為分數是 {mood_score}，建議吃這類食物的原因是：「{mood_guide_reason}」。
@@ -162,9 +220,9 @@ def generate_content_with_groq(restaurant_name, restaurant_detail, user_diary, m
     
     任務：
     請用繁體中文寫一段溫暖有趣的回覆：
-    1. 先回應他的日記與測驗人設。
-    2. 引用「心情美食指南」的原因，告訴他為什麼現在適合吃這家餐廳（例如：「就像指南說的，現在你需要一點多巴胺...」）。
-    3. 介紹這家餐廳的特色。
+    1. 綜合分析他的測驗結果（例如：提到他想去哪裡玩、或是想看什麼劇的關聯性）。
+    2. 結合日記內容與心情給予安慰或鼓勵。
+    3. 推薦上述餐廳，說明為什麼這家店適合「現在的他」。
     (只需要回覆文字內容)
     """
     try:
@@ -193,18 +251,20 @@ def mood_agent_logic(score_input, food_input, diary_input, quiz_state):
         yield "資料庫讀取錯誤", None, ""
         return
 
-    name = restaurant['Name']
-    address = restaurant['Address']
-    url = restaurant['URL']
+    name = str(restaurant['Name'])
+    address = str(restaurant.get('Address', '未知地址'))
+    url = str(restaurant.get('URL', f'https://www.google.com/maps/search/?api=1&query={urllib.parse.quote(name)}'))
     img_prompt = restaurant.get('Visual_prompt') 
     note = "(隨機推薦)" if is_random else ""
 
-    # RAG 檢索 (直接用 global_retriever)
+    # RAG 檢索
     rag_info = str(restaurant.get('RAG_Content', ''))
     if global_retriever:
-        docs = global_retriever.invoke(name)
-        if docs:
-            rag_info = "\n".join([d.page_content for d in docs])
+        try:
+            docs = global_retriever.invoke(name)
+            if docs:
+                rag_info = "\n".join([d.page_content for d in docs])
+        except: pass
 
     ai_text = generate_content_with_groq(name, rag_info, diary_input, score_input, quiz_state, mood_reason)
     
@@ -218,15 +278,32 @@ def mood_agent_logic(score_input, food_input, diary_input, quiz_state):
 # ==========================================
 # 4. 介面互動邏輯
 # ==========================================
-# (這部分與之前相同，略)
+
 def handle_q1_change(selected_label, current_state):
     if not selected_label: return current_state, gr.Button(interactive=False)
-    current_state["q1"] = q1_options_map[selected_label]
+    current_state["q1"] = q1_options_map.get(selected_label, selected_label)
     return current_state, gr.Button(interactive=True, variant="primary")
 
 def handle_q2_change(selected_label, current_state):
     if not selected_label: return current_state, gr.Button(interactive=False)
-    current_state["q2"] = q2_options_map[selected_label]
+    current_state["q2"] = q2_options_map.get(selected_label, selected_label)
+    return current_state, gr.Button(interactive=True, variant="primary")
+
+# [新增] Q3, Q4, Q5 的處理函式
+def handle_q3_change(selected_label, current_state):
+    if not selected_label: return current_state, gr.Button(interactive=False)
+    current_state["q3"] = q3_options_map.get(selected_label, selected_label)
+    return current_state, gr.Button(interactive=True, variant="primary")
+
+def handle_q4_change(selected_label, current_state):
+    if not selected_label: return current_state, gr.Button(interactive=False)
+    current_state["q4"] = q4_options_map.get(selected_label, selected_label)
+    return current_state, gr.Button(interactive=True, variant="primary")
+
+def handle_q5_change(selected_label, current_state):
+    if not selected_label: return current_state, gr.Button(interactive=False)
+    current_state["q5"] = q5_options_map.get(selected_label, selected_label)
+    # 最後一題，按鈕文字改為完成
     return current_state, gr.Button(interactive=True, variant="primary", value="完成測驗 (前往點餐) ➔")
 
 # ==========================================
@@ -236,12 +313,13 @@ with gr.Blocks(title="AI 心情食堂") as demo:
     gr.HTML(f"<style>{custom_css}</style>")
     quiz_state = gr.State(value={})
 
+    # 使用 Tabs 隱藏導覽列，透過按鈕切換
     with gr.Tabs(elem_id="hidden_tabs") as tabs:
         # Tab 0: Q1
         with gr.TabItem("Q1", id=0):
             with gr.Column():
-                gr.Markdown("### 🔮 第一題：直覺測試")
-                gr.Image(value=img_path_1, type="filepath", label="請觀察圖片", height=300)
+                gr.Markdown("### 🔮 Q1：直覺測試")
+                gr.Image(value=img_paths["q1"], type="filepath", label="請觀察圖片", height=300)
                 gr.Markdown("**問題：請觀察上方圖片，如果是你，你會怎麼做？**")
                 radio_q1 = gr.Radio(choices=list(q1_options_map.keys()), label="請選擇", elem_classes="vertical-radio")
                 btn_q1_next = gr.Button("下一頁 ➔", interactive=False)
@@ -249,16 +327,44 @@ with gr.Blocks(title="AI 心情食堂") as demo:
         # Tab 1: Q2
         with gr.TabItem("Q2", id=1):
             with gr.Column():
-                gr.Markdown("### 🔮 第二題：魔法適性")
-                gr.Image(value=img_path_2, type="filepath", label="請觀察圖片", height=300)
+                gr.Markdown("### 🔮 Q2：魔法適性")
+                gr.Image(value=img_paths["q2"], type="filepath", label="請觀察圖片", height=300)
                 gr.Markdown("**問題：身為魔導士的你，會選擇哪一個法術？**")
                 radio_q2 = gr.Radio(choices=list(q2_options_map.keys()), label="請選擇", elem_classes="vertical-radio")
-                btn_q2_finish = gr.Button("完成測驗 ➔", interactive=False)
+                btn_q2_next = gr.Button("下一頁 ➔", interactive=False)
 
-        # Tab 2: Main
-        with gr.TabItem("Main", id=2):
+        # Tab 2: Q3 (新增)
+        with gr.TabItem("Q3", id=2):
+            with gr.Column():
+                gr.Markdown("### ✈️ Q3：旅遊嚮往")
+                gr.Image(value=img_paths["q3"], type="filepath", label="機場圖片", height=300)
+                gr.Markdown("**問題：不考慮其他因素，假你在桃機你最想去哪裡玩？**")
+                radio_q3 = gr.Radio(choices=list(q3_options_map.keys()), label="請選擇目的地", elem_classes="vertical-radio")
+                btn_q3_next = gr.Button("下一頁 ➔", interactive=False)
+
+        # Tab 3: Q4 (新增)
+        with gr.TabItem("Q4", id=3):
+            with gr.Column():
+                gr.Markdown("### 🤝 Q4：社交直覺")
+                gr.Image(value=img_paths["q4"], type="filepath", label="聚會圖片", height=300)
+                gr.Markdown("**問題：你是小大一，班上還不熟，現在你正參加你們班上的認識彼此的活動。下列哪一個人是你會選擇搭話的人？**")
+                radio_q4 = gr.Radio(choices=list(q4_options_map.keys()), label="請選擇對象", elem_classes="vertical-radio")
+                btn_q4_next = gr.Button("下一頁 ➔", interactive=False)
+
+        # Tab 4: Q5 (新增)
+        with gr.TabItem("Q5", id=4):
+            with gr.Column():
+                gr.Markdown("### 📺 Q5：追劇時光")
+                gr.Image(value=img_paths["q5"], type="filepath", label="劇照/電視圖片", height=300)
+                gr.Markdown("**問題：假設失憶了忘記以下所列的劇的劇情，而你現在閒了下來剛好想看劇，你會想看哪一部？**")
+                radio_q5 = gr.Radio(choices=list(q5_options_map.keys()), label="請選擇劇集", elem_classes="vertical-radio")
+                btn_q5_finish = gr.Button("完成測驗 ➔", interactive=False)
+
+        # Tab 5: Main (ID 改為 5)
+        with gr.TabItem("Main", id=5):
             with gr.Column():
                 gr.Markdown(f"## 🍱 呷飽沒？？！")
+                gr.Markdown("測驗完成！AI 已根據你的選擇分析出最適合你的用餐氛圍。")
                 with gr.Row():
                     with gr.Column(scale=1):
                         score_input = gr.Radio(["1 (心情差)", "2 (不太好)", "3 (普通)", "4 (不錯)", "5 (超棒)"], label="1. 心情分數", value="3 (普通)")
@@ -270,11 +376,28 @@ with gr.Blocks(title="AI 心情食堂") as demo:
                         image_output = gr.Image(label="AI 推薦美食圖", type="pil", width=400)
                         map_output = gr.HTML(label="地圖導航")
 
+    # --- Event Binding ---
+    # Q1 -> Q2
     radio_q1.change(fn=handle_q1_change, inputs=[radio_q1, quiz_state], outputs=[quiz_state, btn_q1_next])
     btn_q1_next.click(fn=lambda: gr.Tabs(selected=1), outputs=tabs)
-    radio_q2.change(fn=handle_q2_change, inputs=[radio_q2, quiz_state], outputs=[quiz_state, btn_q2_finish])
-    btn_q2_finish.click(fn=lambda: gr.Tabs(selected=2), outputs=tabs)
+    
+    # Q2 -> Q3
+    radio_q2.change(fn=handle_q2_change, inputs=[radio_q2, quiz_state], outputs=[quiz_state, btn_q2_next])
+    btn_q2_next.click(fn=lambda: gr.Tabs(selected=2), outputs=tabs)
+
+    # Q3 -> Q4
+    radio_q3.change(fn=handle_q3_change, inputs=[radio_q3, quiz_state], outputs=[quiz_state, btn_q3_next])
+    btn_q3_next.click(fn=lambda: gr.Tabs(selected=3), outputs=tabs)
+
+    # Q4 -> Q5
+    radio_q4.change(fn=handle_q4_change, inputs=[radio_q4, quiz_state], outputs=[quiz_state, btn_q4_next])
+    btn_q4_next.click(fn=lambda: gr.Tabs(selected=4), outputs=tabs)
+
+    # Q5 -> Main
+    radio_q5.change(fn=handle_q5_change, inputs=[radio_q5, quiz_state], outputs=[quiz_state, btn_q5_finish])
+    btn_q5_finish.click(fn=lambda: gr.Tabs(selected=5), outputs=tabs)
 
+    # Main Agent Submit
     submit_btn.click(
         fn=mood_agent_logic,
         inputs=[score_input, food_input, diary_input, quiz_state],