Update app.py

app.py

@@ -10,8 +10,11 @@ from langchain_community.document_loaders import DataFrameLoader
 from langchain_text_splitters import RecursiveCharacterTextSplitter
 from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_community.vectorstores import FAISS
-from PIL import Image
+from PIL import Image, ImageFont, ImageDraw
 import warnings
+import cv2
+import numpy as np
+from deepface import DeepFace
 
 # 忽略 pandas 的一些警告
 warnings.filterwarnings("ignore")
@@ -25,7 +28,6 @@ HF_TOKEN = os.getenv("HF_TOKEN")
 # --- 1. 資料讀取 (主要資料庫 - 使用 restaurants.csv) ---
 df = pd.DataFrame()
 try:
-    # 修改：讀取 restaurants.csv
     df = pd.read_csv('restaurants.csv', engine='python')
     df.columns = df.columns.str.strip() # 清理欄位空白
 
@@ -54,26 +56,15 @@ try:
 except Exception as e:
     print(f"⚠️ 讀取 restaurants.csv 失敗: {e}")
 
-# --- 2. 資料讀取 (Prompt 資料庫 - 使用 restaurants.csv) ---
+# --- 2. 資料讀取 (Prompt 資料庫) ---
 df_prompts = pd.DataFrame()
-# 修改：您的 CSV 中 Prompt 欄位名稱為 Visual_prompt
 PROMPT_COL_NAME = 'Visual_prompt' 
 
 try:
-    # 直接使用已讀取的 df 來建立 Prompt 索引
     if not df.empty:
         df_prompts = df.copy()
-        
         if 'Name' in df_prompts.columns:
             df_prompts.set_index('Name', inplace=True)
-        else:
-            print(f"⚠️ Prompts 處理警告: 找不到 'Name' 欄位")
-
-        if PROMPT_COL_NAME not in df_prompts.columns:
-            print(f"⚠️ Prompts 處理警告: 找不到 '{PROMPT_COL_NAME}' 欄位")
-    else:
-        print("⚠️ 主資料庫為空，無法建立 Prompt 索引")
-
 except Exception as e:
     print(f"⚠️ 處理 Prompt 資料發生錯誤: {e}")
 
@@ -108,7 +99,7 @@ custom_css = """
     display: flex !important;
 }
 """
-
+# 若無圖片自動生成空白圖避免報錯
 img_path_1 = "images/image_0.png"
 img_path_2 = "images/image_1.png"
 if not os.path.exists("images"): os.makedirs("images")
@@ -132,11 +123,12 @@ q2_options_map = {
 }
 
 # ==========================================
-# 2. 核心功能函式
+# 2. 核心功能函式 (餐廳推薦邏輯)
 # ==========================================
 
 def get_restaurant_data(mood_score_str, food_choice):
     if df.empty: return None, True
+    # 定義分數與 Mood_Tags 的對應關係
     score_map = {
         "1 (心情差)": ["傷心/疲憊", "生氣/發洩"],
         "2 (不太好)": ["傷心/疲憊", "生氣/發洩"],
@@ -200,15 +192,19 @@ def generate_image_huggingface(prompt):
         return hf_client.text_to_image(prompt=prompt, model="stabilityai/stable-diffusion-xl-base-1.0")
     except: return None
 
-# --- 主邏輯 Agent (新增 debug_mode 參數) ---
+# --- 主邏輯 Agent ---
 def mood_agent_logic(score_input, food_input, diary_input, quiz_state, debug_mode):
+    # 確保 score_input 有值
+    if not score_input:
+        yield "⚠️ 請先選擇心情分數，或使用上方相機偵測！", None, ""
+        return
+
     restaurant, is_random = get_restaurant_data(score_input, food_input)
     if restaurant is None:
         yield "資料庫讀取錯誤或為空", None, ""
         return
 
     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)}'))
     note = "(隨機推薦)" if is_random else ""
 
@@ -220,56 +216,102 @@ def mood_agent_logic(score_input, food_input, diary_input, quiz_state, debug_mod
             if docs: rag_info = "\n".join([d.page_content for d in docs])
         except: pass
 
-    # 2. 準備圖片 Prompt (提前執行以便顯示除錯資訊)
-    img_prompt = f"Delicious food from {name}, cinematic lighting, 8k, photorealistic" # 預設值
-    prompt_source = "⚠️ 預設生成 (未找到 CSV 對應)"
+    # 2. 準備圖片 Prompt
+    img_prompt = f"Delicious food from {name}, cinematic lighting, 8k, photorealistic"
+    prompt_source = "⚠️ 預設生成"
 
     if not df_prompts.empty and PROMPT_COL_NAME in df_prompts.columns:
         if name in df_prompts.index:
             try:
                 csv_prompt = df_prompts.loc[name, PROMPT_COL_NAME]
                 if isinstance(csv_prompt, pd.Series): csv_prompt = csv_prompt.iloc[0]
-                
                 if pd.notna(csv_prompt) and str(csv_prompt).strip() != "":
                     img_prompt = str(csv_prompt)
-                    # 修改：更新來源顯示為 restaurants.csv
-                    prompt_source = "✅ CSV 檔案 (restaurants.csv)"
-                else:
-                    prompt_source = "⚠️ CSV 有此餐廳但 Prompt 空白"
-            except Exception as e:
-                prompt_source = f"❌ 讀取錯誤: {e}"
-        else:
-            prompt_source = "ℹ️ CSV 中無此餐廳"
+                    prompt_source = "✅ CSV 檔案"
+            except: pass
 
     # 3. 呼叫 LLM
     ai_text = generate_content_with_groq(name, rag_info, diary_input, score_input, quiz_state)
     
-    # 4. 組合回應 (包含除錯資訊)
+    # 4. 組合回應
     debug_text = ""
     if debug_mode:
-        debug_text = f"""
-        \n\n---
-        **🛠️ Prompt 除錯模式**
-        * **餐廳名稱**: `{name}`
-        * **Prompt 來源**: {prompt_source}
-        * **實際使用 Prompt**: 
-        ```
-        {img_prompt}
-        ```
-        """
+        debug_text = f"\n\n---\n**🛠️ Prompt 來源**: {prompt_source}\n**Prompt**: `{img_prompt}`"
     
     final_response = f"### 🍽️ 推薦：{name} {note}\n\n{ai_text}{debug_text}"
     map_html = f'<div style="text-align:center"><a href="{url}" target="_blank" style="background:#4CAF50;color:white;padding:8px 16px;border-radius:20px;text-decoration:none">🗺️ Google Map 導航</a></div>'
     
-    # 5. 先回傳文字
     yield final_response, None, map_html
-
-    # 6. 生成圖片
     image_output = generate_image_huggingface(img_prompt)
     yield final_response, image_output, map_html
 
 # ==========================================
-# 3. 頁面切換邏輯
+# 3. [新增] 情緒辨識整合模組
+# ==========================================
+
+# 定義中文字典 (繪圖用)
+emotion_text_obj = {
+    'angry': '生氣', 'disgust': '噁心', 'fear': '害怕',
+    'happy': '開心', 'sad': '難過', 'surprise': '驚訝', 'neutral': '正常'
+}
+
+# 繪圖函式
+def putText(img, x, y, text, size=50, color=(255, 255, 255)):
+    try:
+        fontpath = 'NotoSansTC-VariableFont_wght.ttf'
+        # 確保字型存在，若無則回傳原圖
+        if not os.path.exists(fontpath): return img
+        font = ImageFont.truetype(fontpath, size)
+        imgPil = Image.fromarray(img)
+        draw = ImageDraw.Draw(imgPil)
+        displayText = emotion_text_obj.get(text, text)
+        draw.text((x, y), displayText, fill=color, font=font)
+        return np.array(imgPil)
+    except:
+        return img
+
+# ★ 關鍵功能：偵測情緒並回傳「分數選項」
+def detect_emotion_and_map(frame):
+    if frame is None:
+        return frame, None
+    
+    detected_emotion = "neutral" # 預設
+    mapped_score = "3 (普通)"    # 預設
+
+    try:
+        # 1. 辨識情緒
+        analyze = DeepFace.analyze(frame, actions=['emotion'], enforce_detection=False)
+        if isinstance(analyze, list): analyze = analyze[0]
+        detected_emotion = analyze['dominant_emotion']
+        
+        # 2. 畫在圖片上
+        frame = putText(frame, 20, 40, detected_emotion)
+
+        # 3. 橋樑：將情緒轉換為餐廳系統的分數
+        # happy -> 5
+        # surprise -> 4
+        # neutral -> 3
+        # sad, fear -> 2
+        # angry, disgust -> 1
+        if detected_emotion == 'happy':
+            mapped_score = "5 (超棒)"
+        elif detected_emotion == 'surprise':
+            mapped_score = "4 (不錯)"
+        elif detected_emotion == 'neutral':
+            mapped_score = "3 (普通)"
+        elif detected_emotion in ['sad', 'fear']:
+            mapped_score = "2 (不太好)"
+        elif detected_emotion in ['angry', 'disgust']:
+            mapped_score = "1 (心情差)"
+
+    except Exception as e:
+        print(f"DeepFace Error: {e}")
+        pass
+    
+    return frame, mapped_score
+
+# ==========================================
+# 4. 頁面切換與 UI 邏輯
 # ==========================================
 
 def handle_q1_change(selected_label, current_state):
@@ -286,7 +328,7 @@ def go_to_page_2(): return gr.update(visible=False), gr.update(visible=True)
 def go_to_main_app(): return gr.update(visible=False), gr.update(visible=True)
 
 # ==========================================
-# 4. Gradio 介面建構
+# 5. Gradio 介面建構
 # ==========================================
 
 with gr.Blocks(title="AI 心情食堂") as demo:
@@ -312,19 +354,32 @@ with gr.Blocks(title="AI 心情食堂") as demo:
     # Page 3 (Main)
     with gr.Column(visible=False) as main_app_col:
         gr.Markdown(f"## 🍱 AI 心情食堂導航")
-        gr.Markdown("測驗結束！現在，告訴我你真正想吃什麼吧！")
+        gr.Markdown("測驗結束！讓 AI 看看你的臉色，幫你決定吃什麼！")
 
         with gr.Row():
+            # 左側：輸入區
             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)")
+                
+                # ★ 新增：情緒偵測區塊
+                gr.Markdown("### 📸 步驟 1：心情偵測 (選用)")
+                with gr.Group():
+                    webcam_input = gr.Image(sources=["webcam"], label="看著鏡頭", streaming=True)
+                    detect_btn = gr.Button("📸 偵測心情並自動填入 👇", variant="secondary")
+                
+                gr.Markdown("### 📝 步驟 2：確認與補充")
+                # score_input 會被 detect_btn 更新
+                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 (可手動修改)", 
+                    value="3 (普通)"
+                )
                 food_input = gr.Radio(["吃飯", "吃麵", "隨便"], label="2. 想吃什麼", value="隨便")
-                diary_input = gr.Textbox(lines=4, label="3. 心情日記", placeholder="寫下今天發生的事...")
+                diary_input = gr.Textbox(lines=3, label="3. 心情日記 (選填)", placeholder="例如：今天被老闆罵了，想吃點好料的...")
                 
-                # [新增] 除錯模式開關
                 debug_mode_btn = gr.Checkbox(label="🔧 顯示 Prompt 除錯資訊", value=False)
-                
-                submit_btn = gr.Button("送出給 Agent", variant="primary")
+                submit_btn = gr.Button("🚀 送出給 Agent", variant="primary")
 
+            # 右側：輸出區
             with gr.Column(scale=1):
                 agent_output = gr.Markdown(label="AI 回應")
                 image_output = gr.Image(label="AI 推薦美食圖", type="pil", width=400)
@@ -336,7 +391,13 @@ with gr.Blocks(title="AI 心情食堂") as demo:
     radio_q2.change(fn=handle_q2_change, inputs=[radio_q2, quiz_state], outputs=[quiz_state, btn_q2_finish])
     btn_q2_finish.click(fn=go_to_main_app, outputs=[page_2_col, main_app_col])
 
-    # [修改] 加入 debug_mode_btn 到 inputs
+    # ★ 新增事件：點擊偵測按鈕 -> 執行 DeepFace -> 更新 score_input
+    detect_btn.click(
+        fn=detect_emotion_and_map,
+        inputs=[webcam_input],
+        outputs=[webcam_input, score_input] # 同時更新圖片(畫字)和分數(Radio)
+    )
+
     submit_btn.click(
         fn=mood_agent_logic,
         inputs=[score_input, food_input, diary_input, quiz_state, debug_mode_btn],