Update app.py

app.py

@@ -4,54 +4,41 @@
 
 import os
 import subprocess
+import urllib.parse
+import time
+import pandas as pd
+from dotenv import load_dotenv
 
-# 強制設定 Playwright 瀏覽器存放於 user 目錄
+# --- 1. 環境變數 & Playwright 初始化 ---
+load_dotenv()
 os.environ["PLAYWRIGHT_BROWSERS_PATH"] = "/home/user/.cache/ms-playwright"
 
 try:
-    # 如果目錄不存在，才執行下載，節省啟動時間
     if not os.path.exists(os.environ["PLAYWRIGHT_BROWSERS_PATH"]):
-        print("正在為 Debian Trixie 環境安裝 Chromium...")
-        # 僅安裝 chromium 即可，依賴項由 packages.txt 處理
+        print("正在為環境安裝 Chromium...")
         subprocess.run(["python3", "-m", "playwright", "install", "chromium"], check=True)
 except Exception as e:
     print(f"Playwright 初始化提示: {e}")
 
-# --- 3. 匯入必要的模組 ---
+# --- 2. 匯入核心模組 ---
 import gradio as gr
 from playwright.sync_api import sync_playwright
-from dotenv import load_dotenv
-import pandas as pd
-import urllib.parse # 用於處理網址編碼
-import time  # ✅ 確保這行存在
 from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_community.vectorstores import FAISS
-from PIL import Image
 from openai import OpenAI
 
-# ✅ 這裡就是漏掉的地方，必須加入這行：
-from dotenv import load_dotenv
-
-# --- 匯入組員的模組 ---
-import emotion 
-# ---------------------------
-
-load_dotenv()
-
-# 自動安裝 Playwright 瀏覽器 (HF 環境必要步驟)
+# 假設這是您組員開發的模組
 try:
-    import playwright
+    import emotion 
 except ImportError:
-    subprocess.run(["pip", "install", "playwright"])
-    subprocess.run(["playwright", "install", "chromium"])
-
-from playwright.sync_api import sync_playwright
+    # 防止因缺少 emotion 模組而無法執行
+    print("警告：找不到 emotion 模組，請確保該檔案存在。")
 
 # ==========================================
-# 0. 環境變數 & 系統初始化
+# 0. 全域設定
 # ==========================================
 GROQ_API_KEY = os.getenv("GROQ_API_KEY")
-HF_TOKEN = os.getenv("HF_TOKEN")
+GOOGLE_MAPS_API_KEY = os.getenv("GOOGLE_MAPS_API_KEY") # 請確保 .env 中有此項
 
 global_df = None
 global_mood_df = None
@@ -60,96 +47,57 @@ rag_initialized = False
 
 def init_static_data():
     global global_mood_df
-    try:
-        global_mood_df = pd.read_csv('mood_food_guide.csv')
-    except:
-        global_mood_df = pd.DataFrame({
-            '分數': [1, 2, 3, 4, 5],
-            '推薦料理類別': ["療癒系", "暖胃", "隨意", "豐富", "大餐"],
-            '原因': ["心情低落需要甜食", "給疲憊的自己一點溫暖", "隨意探索", "享受美食的快樂", "慶祝美好的時刻"]
-        })
+    if global_mood_df is None:
+        try:
+            global_mood_df = pd.read_csv('mood_food_guide.csv')
+        except:
+            global_mood_df = pd.DataFrame({
+                '分數': [1, 2, 3, 4, 5],
+                '推薦料理類別': ["療癒系", "暖胃", "隨意", "豐富", "大餐"],
+                '原因': ["心情低落需要甜食", "給疲憊的自己一點溫暖", "隨意探索", "享受美食的快樂", "慶祝美好的時刻"]
+            })
 
 # ==========================================
-# 1. 優化後的動態同步功能
+# 1. Google Maps 爬蟲同步功能 (僅爬取基本資料)
 # ==========================================
 def sync_google_maps(url):
     global global_df, global_retriever, rag_initialized
     clean_url = url.strip() if url else ""
     if not clean_url or "http" not in clean_url.lower():
-        yield "❌ 請輸入有效的網址。", None
+        yield "❌ 請輸入有效的網址。"
         return
 
     try:
-        yield "🚀 [1/4] 啟動瀏覽器...", None
+        yield "🚀 [1/4] 啟動瀏覽器..."
         with sync_playwright() as p:
-            # 關閉 headless 偵測，模擬真實使用者
             browser = p.chromium.launch(headless=True)
-            context = browser.new_context(
-                viewport={'width': 1280, 'height': 900},
-                user_agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
-            )
-            page = context.new_page()
-            
-            yield "🌐 [2/4] 正在前往地圖頁面...", None
+            page = browser.new_page()
+            yield "🌐 [2/4] 連線中..."
             page.goto(clean_url, wait_until="domcontentloaded", timeout=60000)
+            yield "⏳ [3/4] 等待加載資料..."
+            time.sleep(10) 
+            yield "📄 [4/4] 解析餐廳資訊..."
             
-            # --- 關鍵：處理 Google 的 Cookie/隱私同意視窗 ---
-            try:
-                # 尋找「全部接受」或「我同意」按鈕
-                consent_btn = page.locator('button:has-text("Accept all"), button:has-text("全部接受"), button:has-text("我同意")')
-                if consent_btn.count() > 0:
-                    consent_btn.first.click()
-                    time.sleep(2)
-            except: pass
-
-            yield "⏳ [3/4] 等待列表內容載入...", None
-            time.sleep(5) # 給予足夠時間執行 JS
+            # 獲取標題與詳情
+            titles = page.locator('div.fontHeadlineSmall').all_inner_texts()
+            details = page.locator('div.fontBodyMedium').all_inner_texts()
             
-            # 執行自動捲動以觸發圖片載入
-            page.mouse.wheel(0, 3000)
-            time.sleep(2)
-
-            # 存下除錯截圖
-            page.screenshot(path="debug_screenshot.png")
-            
-            yield "📄 [4/4] 解析餐廳資訊...", "debug_screenshot.png"
-
-            # 使用更廣泛的選取器邏輯
-            results = page.evaluate("""() => {
-                const data = [];
-                // 尋找所有可能是清單項目的 div
-                const cards = document.querySelectorAll('div[role="article"], div.m67Hec, .U9S99c');
-                
-                cards.forEach(card => {
-                    const nameEl = card.querySelector('.fontHeadlineSmall, .q876ed, div[style*="font-size: 1.125rem"]');
-                    const addrEl = card.querySelector('.fontBodyMedium, .W4Efsd');
-                    const imgEl = card.querySelector('img[src^="http"]');
-                    
-                    if (nameEl && nameEl.innerText.trim()) {
-                        data.push({
-                            name: nameEl.innerText.trim(),
-                            addr: addrEl ? addrEl.innerText.trim() : "地址詳見地圖",
-                            img: imgEl ? imgEl.src : ""
-                        });
-                    }
-                });
-                return data;
-            }""")
-
             restaurant_list = []
-            for res in results:
-                restaurant_list.append({
-                    "Name": res['name'],
-                    "Address": res['addr'],
-                    "Image_URL": res['img'] if res['img'] else "https://images.unsplash.com/photo-1517248135467-4c7edcad34c4?w=500",
-                    "RAG_Content": f"餐廳：{res['name']}，地址：{res['addr']}",
-                    "URL": f"https://www.google.com/search?q={urllib.parse.quote(res['name'])}"
-                })
-
+            for i, name in enumerate(titles):
+                name = name.strip()
+                if name:
+                    # 擷取地址或評價資訊
+                    addr = details[i].strip() if i < len(details) else ""
+                    restaurant_list.append({
+                        "Name": name,
+                        "Address": addr,
+                        "RAG_Content": f"餐廳：{name}，資訊：{addr}",
+                        "URL": f"https://www.google.com/search?q={urllib.parse.quote(name)}"
+                    })
             browser.close()
 
             if not restaurant_list:
-                yield "⚠️ 仍找不到餐廳。請查看下方的「除錯截圖」確認頁面內容。", "debug_screenshot.png"
+                yield "⚠️ 找不到餐廳。請確認連結已設為「共用」且為列表格式。"
                 return
 
             global_df = pd.DataFrame(restaurant_list)
@@ -157,20 +105,18 @@ def sync_google_maps(url):
             vectorstore = FAISS.from_texts(global_df['RAG_Content'].tolist(), embeddings, metadatas=global_df.to_dict('records'))
             global_retriever = vectorstore.as_retriever(search_kwargs={"k": 3})
             rag_initialized = True
-            yield f"✅ 同步成功！抓到 {len(restaurant_list)} 間餐廳。", "debug_screenshot.png"
-
+            yield f"✅ 同步成功！共有 {len(restaurant_list)} 間餐廳。"
     except Exception as e:
-        yield f"❌ 系統錯誤：{str(e)}", None
+        yield f"❌ 系統錯誤：{str(e)}"
 
 # ==========================================
-# 2. 核心推薦邏輯 (確保 fallback 機制)
+# 2. 推薦邏輯與 Embed API 生成
 # ==========================================
 def get_restaurant_data(mood_score_str, food_choice):
     init_static_data()
     if global_df is None or global_df.empty: 
         return None, True, "資料庫未載入", "尚未同步地圖資料", ""
     
-    # 取得目前資料庫中所有餐廳的名稱清單，方便回報給使用者
     all_restaurant_names = "、".join(global_df['Name'].tolist())
     
     try: score = int(str(mood_score_str).split(' ')[0])
@@ -184,73 +130,73 @@ def get_restaurant_data(mood_score_str, food_choice):
     
     is_match = True
     if food_keyword:
-        # 過濾包含關鍵字的餐廳
         filtered = candidates[candidates['Name'].str.contains(food_keyword) | candidates['RAG_Content'].str.contains(food_keyword)]
         if not filtered.empty:
             candidates = filtered
         else:
-            # ❗ 關鍵修改：如果找不到符合的，標記為「未命中」並使用全部資料隨機抽樣
             is_match = False
     
-    # 從候選（或全部）中隨機挑選一間
     result = candidates.sample(1).iloc[0]
     return result, is_match, "個人清單", mood_reason, all_restaurant_names
 
-# (其餘 generate_content_with_groq, mood_agent_logic 與橋接邏輯保持不變...)
-def generate_content_with_groq(restaurant_name, restaurant_detail, user_diary, mood_score, mood_guide_reason, debug_mode=False):
+def generate_content_with_groq(restaurant_name, restaurant_detail, user_diary, mood_score, mood_guide_reason):
     if not GROQ_API_KEY: return "⚠️ 請設定 GROQ_API_KEY"
     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..."
-    user_msg = f"【狀態】心情分數：{mood_score}\n【日記】{user_diary}\n【建議原因】{mood_guide_reason}\n【餐廳】{restaurant_name}\n資料：{restaurant_detail}"
+    system_prompt = "你是一個幽默、懂吃且善解人意的 AI 朋友，會根據對方的心情推薦合適的餐廳。請用溫暖且具備食記風格的口吻來描述。"
+    user_msg = f"【狀態】心情分數：{mood_score}\n【日記】{user_diary}\n【建議原因】{mood_guide_reason}\n【推薦餐廳】{restaurant_name}\n餐廳資料：{restaurant_detail}"
     try:
         response = client.chat.completions.create(model="llama-3.3-70b-versatile", messages=[{"role": "system", "content": system_prompt}, {"role": "user", "content": user_msg}])
         return response.choices[0].message.content
     except Exception as e: return f"Groq Error: {str(e)}"
 
-def generate_image_huggingface(prompt):
-    if not HF_TOKEN: return None
-    try:
-        hf_client = InferenceClient(token=HF_TOKEN)
-        return hf_client.text_to_image(prompt=prompt, model="stabilityai/stable-diffusion-xl-base-1.0")
-    except: return None
-
 def mood_agent_logic(score_input, food_input, diary_input, debug_mode):
     if not rag_initialized:
-        yield "⚠️ 請先同步地圖清單！", None, ""
+        yield "⚠️ 請先點擊上方按鈕同步地圖清單！", "", ""
         return
 
-    # 取得推薦餐廳資料
-    restaurant, is_match, rec_categories, mood_reason, all_names = get_restaurant_data(score_input, food_input)
+    restaurant, is_match, _, mood_reason, all_names = get_restaurant_data(score_input, food_input)
     
     prefix = ""
-    status_hint = ""
     if not is_match and food_input != "隨便":
-        prefix = f"> 💡 **溫馨提示**：您的清單目前只有：**{all_names}**，沒找到符合『{food_input}』的店。我先幫您從現有名單挑一間！\n\n"
-        status_hint = f"\n(注意：清單中無 '{food_input}'，請幽默解釋為何先推薦這間。)"
+        prefix = f"> 💡 **溫馨提示**：清單中暫無『{food_input}』，已從名單「{all_names}」中挑選最適合您今日心情的一間！\n\n"
 
     name = restaurant['Name']
+    addr = restaurant.get('Address', '')
     url = restaurant.get('URL', '#')
-    # 直接抓取剛才爬到的圖片 URL
-    img_url = restaurant.get('Image_URL') 
-    rag_info = str(restaurant.get('RAG_Content', '')) + status_hint
+    rag_info = str(restaurant.get('RAG_Content', ''))
     
-    # 生成 AI 文字評論
+    # 產生 AI 文案
     ai_text = generate_content_with_groq(name, rag_info, diary_input, score_input, mood_reason)
+    final_markdown = f"{prefix}### 🍽️ 今日推薦：{name}\n\n{ai_text}"
     
-    final_response = f"{prefix}### 🍽️ 推薦：{name}\n\n{ai_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">🗺️ 導航</a></div>'
+    # --- 關鍵：使用 Google Maps Embed API 替代圖片 ---
+    # query 參數包含 名稱 與 地址 以提高準確度
+    query_str = urllib.parse.quote(f"{name} {addr}")
+    if GOOGLE_MAPS_API_KEY:
+        embed_html = f"""
+        <div style="border-radius:15px; overflow:hidden; border:1px solid #ddd;">
+            <iframe
+              width="100%"
+              height="350"
+              frameborder="0" style="border:0"
+              src="https://www.google.com/maps/embed/v1/place?key={GOOGLE_MAPS_API_KEY}&q={query_str}"
+              allowfullscreen>
+            </iframe>
+        </div>
+        """
+    else:
+        embed_html = "<p style='color:red;'>⚠️ 尚未設定 GOOGLE_MAPS_API_KEY，無法顯示地圖預覽。</p>"
+
+    nav_button = f'<div style="text-align:center; margin-top:10px;"><a href="{url}" target="_blank" style="background:#4CAF50;color:white;padding:10px 20px;border-radius:25px;text-decoration:none;font-weight:bold;">📍 前往 Google Maps 導航</a></div>'
     
-    # 第二個回傳值改為 img_url，Gradio 的 gr.Image 會自動處理網址
-    yield final_response, img_url, map_html
+    yield final_markdown, embed_html, nav_button
 
 # ==========================================
-# 3. 橋接邏輯 (保留原本情緒辨識部分)
+# 3. 橋接情緒辨識邏輯 (保持原有功能)
 # ==========================================
 def _score_to_radio_value(score):
     mapping = {1: "1 (心情差)", 2: "2 (不太好)", 3: "3 (普通)", 4: "4 (不錯)", 5: "5 (超棒)"}
-    try: score = int(score)
-    except: score = 3
-    return mapping.get(score, "3 (普通)")
+    return mapping.get(int(score), "3 (普通)")
 
 def bridge_start_click(st):
     res = emotion.on_restart(st)
@@ -282,66 +228,57 @@ def bridge_predict_upload(img, st):
     return out_result, score_update, tabs_update, out_st
 
 # ==========================================
-# 4. Gradio 介面建構
+# 4. Gradio 介面
 # ==========================================
-combined_css = emotion.css 
-
-with gr.Blocks(title="AI 心情食堂", css=combined_css) as demo:
+with gr.Blocks(title="AI 心情食堂", css=getattr(emotion, 'css', '')) as demo:
     st_state = gr.State(emotion.AppState())
 
     with gr.Tabs() as tabs:
         # Tab 1: 情緒辨識
-        with gr.TabItem("😊 情緒辨識 (Step 1)", id=0):
-            with gr.Column(elem_id="app_container"):
-                gr.Markdown("### 第一步：測測你的心情能量")
+        with gr.TabItem("😊 第一步：測測心情", id=0):
+            with gr.Column():
+                gr.Markdown("### 📸 透過鏡頭或照片辨識您的當下情緒")
                 with gr.Row():
-                    btn_start = gr.Button("📸 開啟攝影機辨識", variant="primary")
-                    btn_stop  = gr.Button("⏹️ 停止", variant="secondary", visible=False)
+                    btn_start = gr.Button("開啟攝影機", variant="primary")
+                    btn_stop  = gr.Button("停止", variant="secondary", visible=False)
                 cam = gr.Image(sources=["webcam"], streaming=True, type="numpy", label="攝影機畫面", visible=False)
-                result_markdown = gr.Markdown(emotion._hint_html("請按「開啟攝影機辨識」或下方上傳照片。"))
-                gr.Markdown("---")
-                upload_img = gr.Image(sources=["upload"], type="numpy", label="上傳照片")
+                result_markdown = gr.Markdown("請按上方按鈕開始辨識")
+                upload_img = gr.Image(sources=["upload"], type="numpy", label="或是上傳照片辨識")
 
         # Tab 2: 主功能區
-        with gr.TabItem("🍽️ AI 心情食堂 (Step 2)", id=1):
+        with gr.TabItem("🍽️ 第二步：心情食堂推薦", id=1):
             with gr.Column():
-                gr.Markdown("## 🍱 同步口袋名單\n請貼上你的 Google Maps「已儲存地點」分享連結（需設為共用）。")
+                gr.Markdown("### 🔗 同步 Google Maps 分享清單")
                 with gr.Row():
-                    map_url = gr.Textbox(label="Google Maps 分享連結", placeholder="https://goo.gl/maps/...")
-                    sync_btn = gr.Button("🔄 同步我的清單", variant="secondary")
-                    with gr.Row():
-                        map_url = gr.Textbox(label="Google Maps 分享連結", placeholder="https://goo.gl/maps/...")
-                        sync_btn = gr.Button("🔄 同步我的清單", variant="secondary")
-                    debug_view = gr.Image(label="爬蟲即時畫面 (除錯用)", type="filepath", height=300)
-
-                sync_msg = gr.Markdown("ℹ️ 尚未同步資料庫")
+                    map_url = gr.Textbox(label="清單連結", placeholder="https://maps.app.goo.gl/...")
+                    sync_btn = gr.Button("🔄 同步我的口袋名單", variant="secondary")
+                sync_msg = gr.Markdown("ℹ️ 尚未載入資料庫")
                 
-                gr.Markdown("---")
+                gr.Divider()
                 
                 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", 
+                            label="心情分數 (辨識後自動填寫)", 
                             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="寫下今天的心情...")
-                        debug_mode_btn = gr.Checkbox(label="🔧 開啟除錯模式", value=False)
-                        submit_btn = gr.Button("🍱 推薦今天的驚喜", variant="primary")
+                        food_input = gr.Radio(["吃飯", "吃麵", "隨便"], label="想吃什麼？", value="隨便")
+                        diary_input = gr.Textbox(lines=3, label="心情日記 (選填)", placeholder="寫下現在的想法...")
+                        submit_btn = gr.Button("🍱 推薦今日驚喜", variant="primary")
                     
                     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)
-                        map_output = gr.HTML(label="地圖導航")
+                        agent_output = gr.Markdown(label="AI 推薦語")
+                        map_embed_output = gr.HTML(label="地圖實景預覽") 
+                        map_nav_output = gr.HTML()
 
     # 事件綁定
-    sync_btn.click(fn=sync_google_maps, inputs=[map_url], outputs=[sync_msg, debug_view])
+    sync_btn.click(fn=sync_google_maps, inputs=[map_url], outputs=[sync_msg])
     btn_start.click(fn=bridge_start_click, inputs=[st_state], outputs=[result_markdown, cam, btn_stop, btn_start, st_state])
     btn_stop.click(fn=bridge_stop_click, inputs=[st_state], outputs=[result_markdown, cam, btn_stop, btn_start, st_state])
     cam.stream(fn=bridge_predict_frame, inputs=[cam, st_state], outputs=[cam, result_markdown, st_state, btn_stop, btn_start, score_input, tabs])
     upload_img.change(fn=bridge_predict_upload, inputs=[upload_img, st_state], outputs=[result_markdown, score_input, tabs, st_state])
-    submit_btn.click(fn=mood_agent_logic, inputs=[score_input, food_input, diary_input, debug_mode_btn], outputs=[agent_output, image_output, map_output])
+    submit_btn.click(fn=mood_agent_logic, inputs=[score_input, food_input, diary_input, gr.Checkbox(value=False, visible=False)], outputs=[agent_output, map_embed_output, map_nav_output])
 
 if __name__ == "__main__":
-    demo.launch(ssr_mode=False)
+    demo.launch()