import os import requests import google.generativeai as genai from flask import Flask, request, abort from linebot import LineBotApi, WebhookHandler from linebot.exceptions import InvalidSignatureError import io import json from PIL import Image from linebot.models import ( MessageEvent, TextMessage, TextSendMessage, QuickReply, QuickReplyButton, MessageAction, ImageMessage, FlexSendMessage, LocationMessage, LocationAction ) import urllib.parse import math from datetime import datetime, timezone, timedelta import re import threading from scraper import scrape_all_stores, discover_cosmed, discover_watsons, scrape_watsons_and_poya app = Flask(__name__) # ================= 1. 從環境變數讀取金鑰 ================= line_bot_api = LineBotApi(os.environ.get('LINE_CHANNEL_ACCESS_TOKEN')) handler = WebhookHandler(os.environ.get('LINE_CHANNEL_SECRET')) genai.configure(api_key=os.environ.get('GEMINI_API_KEY')) model = genai.GenerativeModel('gemini-2.5-flash') def _clean_91app_name(name: str) -> str: """ Strip 91APP category prefix (e.g. '醫美乳液–CeraVe…' → 'CeraVe…'). Pattern: Chinese-only tag + any non-CJK/non-alnum separator + English-led brand. Uses regex so it works regardless of which dash/separator character the site uses. """ m = re.match(r'^[一-鿿\s]+' # 純中文前綴（含空格） r'[^一-鿿A-Za-z0-9]+' # 任意分隔符（非中文、非英數） r'([A-Za-z].+)', # 英文品牌開頭的主體名稱 name) if m: return m.group(1).strip() return name def normalize_product_name(user_input: str): """ 用 Gemini 將模糊/錯字/簡稱輸入辨識為正確商品名稱。 回傳 (正確名稱, 是否已修正)，辨識失敗回傳 (None, False)。 """ prompt = ( f"使用者輸入了「{user_input}」，這是台灣藥妝/保養品的商品名稱。\n" "只做兩件事，不要改動其他任何內容：\n" "1. 補完品牌的中英文全名（如「雅漾」→「Avène 雅漾」、「高露潔」→「Colgate 高露潔」）\n" "2. 修正明顯錯字（如「貝德馬」→「貝德瑪」、「理膚寶睡」→「理膚寶水」）\n" "絕對不要補充、猜測或改變使用者沒有說的產品型號或容量。只輸出名稱，不要說明。\n" "若完全無法辨識 → 只輸出 UNKNOWN\n\n" "範例：\n" "「雅漾防曬」→「Avène 雅漾 防曬」\n" "「高露潔牙膏 150g」→「Colgate 高露潔 牙膏 150g」\n" "「naruko茶樹慕斯」→「NARÜKO 茶樹慕斯」\n" "「cerave長效修護霜」→「CeraVe 適樂膚 長效修護霜」\n" "「理膚寶水B5精華」→「La Roche-Posay 理膚寶水 B5精華」" ) try: resp = model.generate_content(prompt) result = resp.text.strip().strip("「」") if result == "UNKNOWN" or not result: return None, False corrected = result != user_input return result, corrected except Exception: return user_input, False def _send_confirm_dialog(user_id, feature, recognized, original_input, cosmed_result=None, reply_token=None): user_states[user_id] = { "step": "CONFIRM_PRODUCT", "feature": feature, "product_name": recognized, "original": original_input, "cosmed_result": cosmed_result, # 探索到的康是美結果，確認後直接複用 } confirm_qr = QuickReply(items=[ QuickReplyButton(action=MessageAction(label="✅ 對，就是這個", text="✅ 對，就是這個")), QuickReplyButton(action=MessageAction(label="❌ 不是，重新輸入", text="❌ 不是，重新輸入")), ]) msg = TextSendMessage(text=f"🔍 您是指「{recognized}」嗎？", quick_reply=confirm_qr) if reply_token: try: line_bot_api.reply_message(reply_token, msg) return except Exception: pass line_bot_api.push_message(user_id, msg) def _send_or_push(user_id, reply_token, msg): if reply_token: line_bot_api.reply_message(reply_token, msg) else: line_bot_api.push_message(user_id, msg) def _is_specific_keyword(keyword: str) -> bool: """特徵詞夠長（>3字）時不需探索，直接精確搜尋。""" zh_terms = re.findall(r'[一-鿿]{2,}', keyword) feature_terms = zh_terms[1:] if len(zh_terms) >= 2 else zh_terms return sum(len(t) for t in feature_terms) > 3 def _discover_and_confirm_bg(user_id, user_input, reply_token=None, force_discover=False): """ 二段式搜尋背景執行： 1. Gemini 僅展開品牌（不猜型號） 2. 若關鍵字模糊，優先用屈臣氏探索真實商品名稱（名稱乾淨，無分類前綴） 3. 屈臣氏找不到時，退回康是美探索（並清除分類前綴） 4. 顯示確認框 → 確認後 scrape_all_stores 三家全搜 force_discover=True：跳過 _is_specific_keyword 捷徑，強制走 discovery（照片流程用） """ try: # 步驟一：品牌展開 expanded, _ = normalize_product_name(user_input) keyword = expanded if expanded else user_input if not force_discover and _is_specific_keyword(keyword): _do_photo_query_bg(user_id, keyword, reply_token=reply_token) return # 步驟二：優先用屈臣氏探索（名稱乾淨，curl 快速路徑） watsons_result = discover_watsons(keyword) print(f"[discover] watsons_result={watsons_result!r}", flush=True) if watsons_result: exact_name = watsons_result["name"] print(f"[discover] keyword={keyword!r} → watsons={exact_name!r}", flush=True) # cosmed_result=None → 確認後三家全搜（不重複利用屈臣氏結果） _send_confirm_dialog(user_id, "photo", exact_name, user_input, cosmed_result=None, reply_token=reply_token) return # 步驟三：屈臣氏找不到，退回康是美探索 cosmed_result = discover_cosmed(keyword) if not cosmed_result: _do_photo_query_bg(user_id, keyword, reply_token=reply_token) return # 清除康是美分類前綴（如「醫美乳液–CeraVe…」→「CeraVe…」） raw_name = cosmed_result["name"] exact_name = _clean_91app_name(raw_name) print(f"[discover] cosmed raw={raw_name!r} → cleaned={exact_name!r}", flush=True) cosmed_result = {**cosmed_result, "name": exact_name} print(f"[discover] keyword={keyword!r} → cosmed={exact_name!r}", flush=True) _send_confirm_dialog(user_id, "photo", exact_name, user_input, cosmed_result=cosmed_result, reply_token=reply_token) except Exception as e: line_bot_api.push_message(user_id, TextSendMessage(text=f"❌ 精靈遇到問題：{e}")) def _do_photo_query(user_id, reply_token, product_name): # 把 reply_token 留給背景執行緒回傳結果（reply_message 免費無限次） threading.Thread(target=_do_photo_query_bg, args=(user_id, product_name), kwargs={"reply_token": reply_token}, daemon=True).start() def _display_price_results(user_id, data_list, product_name, reply_token=None): """將爬蟲結果渲染成 Flex 訊息並推送給用戶。""" try: default_logos = { "屈臣氏": "https://openhouse.osa.nycu.edu.tw/media/data/company_logos/3._%E5%B1%88%E8%87%A3%E6%B0%8Flogo.png", "康是美": "https://img.skmbuy.com.tw/App_Images/727/Brand/2022/1215/4b8e1829-8f30-46a9-b044-834c11fc884a.jpg", "寶雅": "https://color-matching.s3.ap-northeast-1.amazonaws.com/color-image/%E5%AF%B6%E9%9B%85%EF%BC%8C%E6%A8%99%E8%AA%8C.jpg", } bubbles = [] for item in data_list: safe_store = item.get("store", "推薦藥妝店") safe_name = item.get("name", product_name) raw_price = item.get("price", "請洽門市") safe_price_display = str(raw_price) if item.get("real") else f"NT${raw_price}" safe_logo = item.get("logo", default_logos.get(safe_store, "")) safe_discount = item.get("discount", "") original_price = item.get("original_price", "") raw_url = item.get("url") or item.get("link") or "" if raw_url.startswith(("https://", "http://")): safe_link = raw_url else: search_query = urllib.parse.quote(f"{safe_store} {safe_name}") safe_link = f"https://www.google.com/search?q={search_query}" specs_contents = [ {"type": "box", "layout": "horizontal", "contents": [ {"type": "text", "text": "販售商家", "size": "md", "color": "#8c8c8c", "flex": 1}, {"type": "text", "text": safe_store, "size": "md", "color": "#111111", "weight": "bold", "flex": 2}, ]}, {"type": "box", "layout": "horizontal", "contents": [ {"type": "text", "text": "商品售價", "size": "md", "color": "#8c8c8c", "flex": 1}, {"type": "text", "text": safe_price_display, "size": "md", "color": "#e8192c", "weight": "bold", "flex": 2}, ]}, ] if original_price: try: cur_val = int(str(raw_price).replace("NT$", "").replace(",", "")) ori_val = int(original_price.replace("NT$", "").replace(",", "")) pct = round(cur_val / ori_val * 10, 1) discount_tag = f"🔥 {pct}折｜省 NT${ori_val - cur_val}" except Exception: discount_tag = "" specs_contents.append({"type": "box", "layout": "horizontal", "contents": [ {"type": "text", "text": "原　　價", "size": "sm", "color": "#8c8c8c", "flex": 1}, {"type": "text", "text": original_price, "size": "sm", "color": "#aaaaaa", "decoration": "line-through", "flex": 2}, ]}) if discount_tag: specs_contents.append({"type": "box", "layout": "horizontal", "contents": [ {"type": "text", "text": "折扣優惠", "size": "sm", "color": "#8c8c8c", "flex": 1}, {"type": "text", "text": discount_tag, "size": "sm", "color": "#ff3b30", "weight": "bold", "flex": 2}, ]}) if safe_discount: specs_contents.append({"type": "box", "layout": "horizontal", "contents": [ {"type": "text", "text": "獨家優惠", "size": "md", "color": "#8c8c8c", "flex": 1}, {"type": "text", "text": safe_discount, "size": "md", "color": "#ff3b30", "weight": "bold", "flex": 2}, ]}) card = { "type": "bubble", "size": "mega", "hero": {"type": "image", "url": safe_logo, "size": "full", "aspectRatio": "2:1", "aspectMode": "fit", "backgroundColor": "#FFFFFF"}, "body": {"type": "box", "layout": "vertical", "contents": [ {"type": "text", "text": safe_name, "weight": "bold", "size": "xl", "wrap": True}, {"type": "box", "layout": "vertical", "spacing": "sm", "margin": "lg", "contents": specs_contents}, ]}, "footer": {"type": "box", "layout": "vertical", "contents": [ {"type": "button", "style": "primary", "color": "#000000", "height": "md", "action": {"type": "uri", "label": "前往商家購買", "uri": safe_link}}, ]}, } bubbles.append(card) flex_message = FlexSendMessage.new_from_json_dict({ "type": "flex", "alt_text": "🔍 藥妝精靈比價報告來囉！", "contents": {"type": "carousel", "contents": bubbles}, }) _ALL_STORES = ["屈臣氏", "康是美", "寶雅"] found_stores = {item["store"] for item in data_list} missing = [s for s in _ALL_STORES if s not in found_stores] msgs = [flex_message] if missing: msgs.append(TextSendMessage(text="🥺 " + "、".join(missing) + "目前沒有找到符合的商品")) if reply_token: try: line_bot_api.reply_message(reply_token, msgs) return except Exception: pass line_bot_api.push_message(user_id, msgs) except Exception as e: line_bot_api.push_message(user_id, TextSendMessage(text=f"❌ 哎呀！精靈遇到了一點問題。錯誤原因：\n{e}")) if user_id in user_states: del user_states[user_id] def _do_photo_query_bg(user_id, product_name, reply_token=None): def _push_or_reply(msg): if reply_token: try: line_bot_api.reply_message(reply_token, msg) return except Exception: pass line_bot_api.push_message(user_id, msg) try: if product_name in fake_database: data_list = fake_database[product_name] else: scraped = scrape_all_stores(product_name) if not scraped: _push_or_reply(TextSendMessage( text=f"🥺 三家藥妝店都找不到「{product_name}」的商品，請確認商品名稱或嘗試其他關鍵字。" )) if user_id in user_states: del user_states[user_id] return data_list = scraped _display_price_results(user_id, data_list, product_name, reply_token=reply_token) except Exception as e: line_bot_api.push_message(user_id, TextSendMessage(text=f"❌ 哎呀！精靈遇到了一點問題。錯誤原因：\n{e}")) if user_id in user_states: del user_states[user_id] def _do_review_query(user_id, reply_token, product_name): _send_or_push(user_id, reply_token, TextSendMessage(text=f"🔍 正在搜尋「{product_name}」的社群口碑，請稍候...")) threading.Thread(target=_do_review_query_bg, args=(user_id, product_name), daemon=True).start() def _do_review_query_bg(user_id, product_name): review_prompt = f""" 你是一個台灣保養品社群平台，請為「{product_name}」這款商品生成 3 則真實風格的用戶評價。 必須「只回傳」一個標準的 JSON 陣列，不要有任何額外說明文字。格式嚴格如下： [ {{"reviewer": "身份描述+英文名（如 小資女Sandy、上班族Cathy、學生妹Mia、熟齡女Vivian）", "skin_type": "膚質（乾性肌/油性肌/混合肌/敏感肌）", "rating": 評分數字（1-5）, "date": "日期（如 2025/03/15）", "review": "評價內容（50-80字，繁體中文，具體使用心得）", "helpful": 點讚數（0-50之間整數）, "pros": ["優點標籤（最多5字）", "優點標籤"], "cons": ["缺點標籤（最多5字）"]}}, {{"reviewer": "...", "skin_type": "...", "rating": ..., "date": "...", "review": "...", "helpful": ..., "pros": [...], "cons": [...]}}, {{"reviewer": "...", "skin_type": "...", "rating": ..., "date": "...", "review": "...", "helpful": ..., "pros": [...], "cons": [...]}} ] pros 最多 2 個，cons 最多 1 個，每個標籤不超過 6 個中文字。 """ try: review_resp = model.generate_content(review_prompt) clean = review_resp.text.replace("```json", "").replace("```", "").strip() reviews = json.loads(clean) star_map = {5: "⭐⭐⭐⭐⭐", 4: "⭐⭐⭐⭐", 3: "⭐⭐⭐", 2: "⭐⭐", 1: "⭐"} bubbles = [] for r in reviews: stars = star_map.get(int(r.get("rating", 5)), "⭐⭐⭐⭐⭐") pros = r.get("pros", []) cons = r.get("cons", []) tag_box_contents = [] for p in pros: tag_box_contents.append({"type": "text", "text": f"✅ {p}", "size": "xs", "color": "#27AE60"}) for c in cons: tag_box_contents.append({"type": "text", "text": f"⚠️ {c}", "size": "xs", "color": "#E67E22"}) body_contents = [ {"type": "text", "text": product_name, "size": "sm", "color": "#FF6B8A", "weight": "bold"}, {"type": "text", "text": r.get("review", ""), "size": "sm", "color": "#333333", "wrap": True, "margin": "md"}, ] if tag_box_contents: body_contents.append({"type": "box", "layout": "vertical", "margin": "md", "contents": tag_box_contents}) body_contents.append({"type": "box", "layout": "horizontal", "margin": "md", "contents": [{"type": "text", "text": f"👍 {r.get('helpful', 0)} 人覺得有幫助", "size": "xs", "color": "#8c8c8c"}]}) card = { "type": "bubble", "size": "mega", "header": { "type": "box", "layout": "vertical", "backgroundColor": "#FFF8E7", "paddingAll": "15px", "contents": [{"type": "box", "layout": "horizontal", "contents": [ {"type": "box", "layout": "vertical", "flex": 1, "contents": [{"type": "text", "text": "👤", "size": "xxl", "align": "center"}]}, {"type": "box", "layout": "vertical", "flex": 4, "contents": [ {"type": "text", "text": r.get("reviewer", "匿名"), "weight": "bold", "size": "md", "color": "#111111"}, {"type": "text", "text": r.get("skin_type", ""), "size": "xs", "color": "#8c8c8c"}, {"type": "text", "text": stars, "size": "sm", "margin": "xs"} ]}, {"type": "text", "text": r.get("date", ""), "size": "xs", "color": "#8c8c8c", "align": "end", "flex": 2} ]}] }, "body": {"type": "box", "layout": "vertical", "contents": body_contents} } bubbles.append(card) flex_msg = FlexSendMessage.new_from_json_dict({ "type": "flex", "alt_text": f"💬 {product_name} 的社群口碑", "contents": {"type": "carousel", "contents": bubbles} }) line_bot_api.push_message(user_id, flex_msg) avg_rating = sum(int(r.get("rating", 5)) for r in reviews) / len(reviews) summary_prompt = f""" 根據以下針對「{product_name}」的評論資料，生成一段精簡總結。 評論資料：{json.dumps(reviews, ensure_ascii=False)} 必須完全依照下列格式輸出，不要有其他文字： 🧴 {product_name} ⭐ 社群好評度：{avg_rating:.1f} / 5 👍 網友最常提到 1️⃣ （優點1） 2️⃣ （優點2） 3️⃣ （優點3） 👎 常見缺點 • （10-15字，描述具體膚質或情境限制，如「對油性肌或T字部位可能較悶厚」） • （10-15字，另一個具體使用限制，如「夏季高溫使用容易感覺黏膩」） 🧚‍♀️ 精靈總結 （1句話，15～25字，點出最適合族群與核心優勢，繁體中文） """ summary_resp = model.generate_content(summary_prompt) line_bot_api.push_message(user_id, TextSendMessage(text=summary_resp.text.strip())) except Exception as e: line_bot_api.push_message(user_id, TextSendMessage(text=f"❌ 口碑查詢失敗：{e}")) if user_id in user_states: del user_states[user_id] def _build_fav_card(index, fav): return { "type": "bubble", "size": "mega", "header": { "type": "box", "layout": "vertical", "backgroundColor": "#FFE8F0", "paddingAll": "12px", "contents": [{"type": "text", "text": f"❤️ 收藏 #{index+1}", "weight": "bold", "size": "sm", "color": "#FF6B8A"}] }, "body": { "type": "box", "layout": "vertical", "contents": [ {"type": "text", "text": fav["name"], "weight": "bold", "size": "lg", "wrap": True, "color": "#111111"}, {"type": "box", "layout": "vertical", "spacing": "sm", "margin": "lg", "contents": [ {"type": "box", "layout": "baseline", "spacing": "sm", "contents": [ {"type": "text", "text": "參考售價", "size": "sm", "color": "#8c8c8c", "flex": 3}, {"type": "text", "text": fav.get("price", "未知"), "size": "sm", "color": "#111111", "weight": "bold", "flex": 5} ]}, {"type": "box", "layout": "baseline", "spacing": "sm", "contents": [ {"type": "text", "text": "備註", "size": "sm", "color": "#8c8c8c", "flex": 3}, {"type": "text", "text": fav.get("note", "無"), "size": "sm", "color": "#111111", "flex": 5, "wrap": True} ]} ]} ] }, "footer": { "type": "box", "layout": "vertical", "spacing": "sm", "contents": [ {"type": "button", "style": "primary", "color": "#000000", "height": "sm", "action": {"type": "message", "label": "🛒 前往購物", "text": f"查詢購買:{fav['name']}"}}, {"type": "button", "style": "secondary", "height": "sm", "action": {"type": "message", "label": "🗑️ 刪除此收藏", "text": f"刪除收藏:{fav['name']}"}} ] } } def _do_favorite_save(user_id, reply_token, product_name): _send_or_push(user_id, reply_token, TextSendMessage(text=f"✨ 正在查詢「{product_name}」商品資訊...")) threading.Thread(target=_do_favorite_save_bg, args=(user_id, product_name), daemon=True).start() def _do_favorite_save_bg(user_id, product_name): try: price_resp = model.generate_content(f"請告訴我「{product_name}」在台灣藥妝店的大約售價，只回傳數字，不要貨幣符號或其他文字。") price_text = price_resp.text.strip().replace("$", "").replace("NT", "").replace(",", "").strip() price_display = f"${price_text}" except Exception: price_display = "未知" if user_id not in user_favorites: user_favorites[user_id] = [] already_exists = any(f["name"] == product_name for f in user_favorites[user_id]) if already_exists: line_bot_api.push_message(user_id, TextSendMessage(text=f"💝「{product_name}」已在您的收藏清單中囉！")) else: user_favorites[user_id].append({"name": product_name, "price": price_display, "note": "手動加入收藏"}) if user_id in user_states: del user_states[user_id] # 顯示更新後的收藏圖卡 favorites = user_favorites.get(user_id, []) add_qr = QuickReply(items=[QuickReplyButton(action=MessageAction(label="➕ 新增收藏", text="新增收藏"))]) if not already_exists and favorites: bubbles = [_build_fav_card(i, fav) for i, fav in enumerate(favorites)] flex_msg = FlexSendMessage.new_from_json_dict({ "type": "flex", "alt_text": "💝 您的收藏清單", "contents": {"type": "carousel", "contents": bubbles} }) line_bot_api.push_message(user_id, [flex_msg, TextSendMessage(text=f"✅ 已加入收藏！共有 {len(favorites)} 件商品", quick_reply=add_qr)]) # ================= 建立虛擬藥妝資料庫 ================= fake_database = { "CeraVe適樂膚 長效潤澤修護霜 340g": [ {"store": "屈臣氏", "name": "CeraVe適樂膚 長效潤澤修護霜 340g", "price": "619","link": "https://www.watsons.com.tw/cerave-cerave%E9%81%A9%E6%A8%82%E8%86%9A%E9%95%B7%E6%95%88%E6%BD%A4%E6%BE%A4%E4%BF%AE%E8%AD%B7%E9%9C%9C-340g/p/BP_153671","logo": "https://openhouse.osa.nycu.edu.tw/media/data/company_logos/3._%E5%B1%88%E8%87%A3%E6%B0%8Flogo.png"}, {"store": "康是美", "name": "CeraVe適樂膚 長效潤澤修護霜 340g", "price": "619", "link": "https://shop.cosmed.com.tw/SalePage/Index/6414249","logo": "https://img.skmbuy.com.tw/App_Images/727/Brand/2022/1215/4b8e1829-8f30-46a9-b044-834c11fc884a.jpg"}, {"store": "寶雅", "name": "CeraVe適樂膚 長效潤澤修護霜 340g", "price": "619","link": "https://www.poyabuy.com.tw/SalePage/Index/10104261","logo": "https://color-matching.s3.ap-northeast-1.amazonaws.com/color-image/%E5%AF%B6%E9%9B%85%EF%BC%8C%E6%A8%99%E8%AA%8C.jpg"} ], "Avene 雅漾舒護活泉水150ml": [ {"store": "屈臣氏", "name": "Avene 雅漾舒護活泉水150ml", "price": "299","discount": "🔥限時67折", "link": "https://www.watsons.com.tw/avene-%E9%9B%85%E6%BC%BE-%E9%9B%85%E6%BC%BE%E8%88%92%E8%AD%B7%E6%B4%BB%E6%B3%89%E6%B0%B4150ml/p/BP_291419","logo": "https://openhouse.osa.nycu.edu.tw/media/data/company_logos/3._%E5%B1%88%E8%87%A3%E6%B0%8Flogo.png"}, {"store": "康是美", "name": "Avene 雅漾舒護活泉水150ml", "price": "299","discount": "🔥限時67折", "link": "https://shop.cosmed.com.tw/SalePage/Index/5767522","logo": "https://img.skmbuy.com.tw/App_Images/727/Brand/2022/1215/4b8e1829-8f30-46a9-b044-834c11fc884a.jpg"}, {"store": "寶雅", "name": "Avene 雅漾舒護活泉水150ml", "price": "450", "link": "https://www.poyabuy.com.tw/SalePage/Index/9929185","logo": "https://color-matching.s3.ap-northeast-1.amazonaws.com/color-image/%E5%AF%B6%E9%9B%85%EF%BC%8C%E6%A8%99%E8%AA%8C.jpg"} ] } # ================= 2. 狀態儲存區 ================= user_states = {} user_favorites = {} # {user_id: [{"name": "...", "price": "...", "note": "..."}]} @app.route("/callback", methods=['POST']) def callback(): signature = request.headers['X-Line-Signature'] body = request.get_data(as_text=True) try: handler.handle(body, signature) except InvalidSignatureError: abort(400) return 'OK' def _handle_image_bg(user_id, image_data, reply_token=None): """背景執行：Gemini 視覺辨識 → normalize_product_name 精煉 → 確認對話框""" try: pil_image = Image.open(io.BytesIO(image_data)) vision_prompt = ( "你是台灣藥妝保養品辨識專家。請仔細觀察圖片中商品包裝上的文字與外觀，" "輸出一行完整精確的商品名稱，供台灣屈臣氏/康是美/寶雅的搜尋引擎使用。\n\n" "輸出規則（按順序）：\n" "1. 品牌英文原名 + 中文品牌名（如 La Roche-Posay 理膚寶水）\n" "2. 產品線名稱：優先使用台灣藥妝店通用的繁體中文名稱；\n" " 若包裝只有外文（法文/英文），請翻譯為台灣常用中文商品名\n" " （如 Eau Thermale→舒護活泉水、Cicaplast→全面修復霜）\n" "3. 產品型態（乳霜/乳液/精華液/洗髮乳/慕斯/牙膏 等，若中文名已含則不重複）\n" "4. 容量規格，從包裝讀取（如 100ml、454g、120g）\n\n" "只輸出一行，不要標點、說明或換行。\n" "範例：La Roche-Posay 理膚寶水 B5全效修復霜 100ml\n" "範例：Avène 雅漾 舒護活泉水 150ml\n" "範例：NARÜKO 茶樹淨痘卸妝潔顏慕斯 200ml\n" "範例：CeraVe 適樂膚 修護保濕乳霜 454g\n" "範例：Colgate 高露潔 全效清新薄荷牙膏 120g\n\n" "若圖片模糊或看不出是保養品/藥妝/日用品，只輸出：UNKNOWN" ) print(f"[photo] Gemini vision start", flush=True) response = model.generate_content([vision_prompt, pil_image]) vision_result = response.text.strip().strip("「」") print(f"[photo] Gemini vision done: {vision_result!r}", flush=True) if not vision_result or vision_result == "UNKNOWN": _rt_err = reply_token def _send_unknown(): msg = TextSendMessage(text="🔍 精靈無法從這張圖片辨識出商品，請換一張更清晰的照片，或直接輸入商品名稱。") if _rt_err: try: line_bot_api.reply_message(_rt_err, msg) return except Exception: pass line_bot_api.push_message(user_id, msg) _send_unknown() return # 視覺辨識結果再經 normalize_product_name 二次精煉 normalized, _ = normalize_product_name(vision_result) product_name = normalized if normalized else vision_result print(f"[photo] vision={vision_result!r} → normalized={product_name!r}", flush=True) # 走 discovery 找出店家真實商品名（如「修護保濕乳霜」→「長效潤澤修護霜」）再確認 _discover_and_confirm_bg(user_id, product_name, reply_token=reply_token, force_discover=True) except Exception as e: print(f"[photo] ERROR: {e}", flush=True) msg = TextSendMessage(text=f"❌ 哎呀！精靈遇到了一點問題。錯誤原因：\n{e}") if reply_token: try: line_bot_api.reply_message(reply_token, msg) return except Exception: pass line_bot_api.push_message(user_id, msg) # ================= 3. 拍照精靈 (圖片處理) ================= @handler.add(MessageEvent, message=ImageMessage) def handle_image(event): user_id = event.source.user_id state = user_states.get(user_id) if state and state.get("step") == "ASK_PHOTO_ITEM": # 把 reply_token 留給背景辨識完成後的確認框使用（reply_message 免費無限次） try: message_content = line_bot_api.get_message_content(event.message.id) image_data = message_content.content threading.Thread(target=_handle_image_bg, args=(user_id, image_data, event.reply_token), daemon=True).start() except Exception as e: line_bot_api.push_message( user_id, TextSendMessage(text=f"❌ 哎呀！精靈遇到了一點問題。錯誤原因：\n{e}") ) # ================= 4. 附近店家 (位置處理) ================= @handler.add(MessageEvent, message=LocationMessage) def handle_location(event): user_id = event.source.user_id user_lat = event.message.latitude user_lon = event.message.longitude state = user_states.get(user_id, {}) brand_preference = state.get("search_brand", "全都要") # ✅ 完美修正：正確的環境變數名稱 google_api_key = os.environ.get('Maps_API_KEY') if not google_api_key: line_bot_api.reply_message(event.reply_token, TextSendMessage(text="❌ 系統尚未設定 Google Maps API 金鑰。")) return def calculate_distance(lat1, lon1, lat2, lon2): R = 6371.0 lat1_rad, lon1_rad = math.radians(lat1), math.radians(lon1) lat2_rad, lon2_rad = math.radians(lat2), math.radians(lon2) dlon = lon2_rad - lon1_rad dlat = lat2_rad - lat1_rad a = math.sin(dlat / 2)**2 + math.cos(lat1_rad) * math.cos(lat2_rad) * math.sin(dlon / 2)**2 c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a)) return int(R * c * 1000) def get_exact_hours(place_id, api_key): url = f"https://maps.googleapis.com/maps/api/place/details/json?place_id={place_id}&fields=opening_hours&language=zh-TW&key={api_key}" try: res = requests.get(url).json() if 'result' in res and 'opening_hours' in res['result']: weekday_text = res['result']['opening_hours'].get('weekday_text', []) if weekday_text: tw_tz = timezone(timedelta(hours=8)) today_idx = datetime.now(tw_tz).weekday() today_str = weekday_text[today_idx] if ": " in today_str: return today_str.split(": ", 1)[1] except Exception: pass return "詳情請洽門市" brands_to_search = ["屈臣氏", "康是美", "寶雅"] if brand_preference == "全都要" else [brand_preference] search_radius = 3000 try: line_bot_api.reply_message(event.reply_token, TextSendMessage(text="🧚‍♀️ 精靈正在為您精準定位各品牌門市，請稍候...")) nearest_stores = [] for brand in brands_to_search: url = f"https://maps.googleapis.com/maps/api/place/textsearch/json?query={brand}&location={user_lat},{user_lon}&radius={search_radius}&language=zh-TW&key={google_api_key}" response = requests.get(url).json() if response['status'] == 'OK' and response.get('results'): brand_stores = [] for place in response['results']: store_lat = place['geometry']['location']['lat'] store_lon = place['geometry']['location']['lng'] distance = calculate_distance(user_lat, user_lon, store_lat, store_lon) photo_ref = "" if 'photos' in place and len(place['photos']) > 0: photo_ref = place['photos'][0]['photo_reference'] open_now = place.get('opening_hours', {}).get('open_now') if open_now is True: status_light = "🟢 營業中" elif open_now is False: status_light = "🔴 休息中" else: status_light = "🕒 營業狀態" brand_stores.append({ "place_id": place.get('place_id'), "name": place.get('name', '未知名稱'), "rating": place.get('rating', '無評分'), "lat": store_lat, "lon": store_lon, "distance": distance, "address": place.get('formatted_address', ''), "status_light": status_light, "photo_ref": photo_ref }) sorted_brand_stores = sorted(brand_stores, key=lambda x: x['distance']) if brand_preference == "全都要": if sorted_brand_stores: nearest_stores.append(sorted_brand_stores[0]) else: nearest_stores.extend(sorted_brand_stores[:3]) if not nearest_stores: line_bot_api.push_message(user_id, TextSendMessage(text="🥺 哎呀，精靈在您附近 3 公里內都找不到藥妝店呢...")) if user_id in user_states: del user_states[user_id] return nearest_stores = sorted(nearest_stores, key=lambda x: x['distance']) bubbles = [] for store in nearest_stores: exact_hours = get_exact_hours(store['place_id'], google_api_key) display_hours = f"{store['status_light']} ({exact_hours})" map_query = urllib.parse.quote(f"{store['name']} {store['address']}") map_url = f"https://www.google.com/maps/search/?api=1&query={map_query}" if store['photo_ref']: image_url = f"https://maps.googleapis.com/maps/api/place/photo?maxwidth=600&photo_reference={store['photo_ref']}&key={google_api_key}" else: image_url = "https://images.unsplash.com/photo-1576426863848-c21f53c60b19?q=80&w=600&auto=format&fit=crop" # ✅ 完美修正：排版乾淨、結構完全正確的規格表！ card = { "type": "bubble", "size": "mega", "hero": { "type": "image", "url": image_url, "size": "full", "aspectRatio": "16:9", "aspectMode": "cover" }, "body": { "type": "box", "layout": "vertical", "contents": [ {"type": "text", "text": store['name'], "weight": "bold", "size": "xl", "wrap": True, "color": "#111111"}, { "type": "box", "layout": "vertical", "spacing": "sm", "margin": "lg", "contents": [ { "type": "box", "layout": "baseline", "spacing": "sm", "contents": [ {"type": "text", "text": "目前距離", "size": "sm", "color": "#8c8c8c", "flex": 3}, {"type": "text", "text": f"{store['distance']} 公尺", "size": "sm", "color": "#111111", "weight": "bold", "flex": 5} ] }, { "type": "box", "layout": "baseline", "spacing": "sm", "contents": [ {"type": "text", "text": "營業時間", "size": "sm", "color": "#8c8c8c", "flex": 3}, {"type": "text", "text": display_hours, "size": "sm", "color": "#111111", "weight": "bold", "flex": 5, "wrap": True} ] }, { "type": "box", "layout": "baseline", "spacing": "sm", "contents": [ {"type": "text", "text": "店家評分", "size": "sm", "color": "#8c8c8c", "flex": 3}, {"type": "text", "text": f"⭐ {store['rating']}", "size": "sm", "color": "#fbbc04", "weight": "bold", "flex": 5} ] } ] } ] }, "footer": { "type": "box", "layout": "vertical", "contents": [ { "type": "button", "style": "primary", "color": "#000000", "height": "md", "action": { "type": "uri", "label": "開啟地圖導航", "uri": map_url } } ] } } bubbles.append(card) flex_message = FlexSendMessage.new_from_json_dict({ "type": "flex", "alt_text": "🔍 附近的藥妝店地圖出爐囉！", "contents": { "type": "carousel", "contents": bubbles } }) line_bot_api.push_message(user_id, flex_message) if user_id in user_states: del user_states[user_id] except Exception as e: line_bot_api.push_message(user_id, TextSendMessage(text=f"❌ 搜尋過程發生錯誤：{e}")) if user_id in user_states: del user_states[user_id] # ================= 5. 多輪對話核心邏輯 (文字對話) ================= @handler.add(MessageEvent, message=TextMessage) def handle_message(event): user_id = event.source.user_id user_msg = event.message.text.strip() if user_msg == "附近店家": user_states[user_id] = {"step": "ASK_BRAND"} brand_buttons = QuickReply(items=[ QuickReplyButton(action=MessageAction(label="屈臣氏", text="屈臣氏")), QuickReplyButton(action=MessageAction(label="康是美", text="康是美")), QuickReplyButton(action=MessageAction(label="寶雅", text="寶雅")), QuickReplyButton(action=MessageAction(label="全都要", text="全都要")) ]) line_bot_api.reply_message( event.reply_token, TextSendMessage(text="請問你想尋找哪一間藥妝店呢？", quick_reply=brand_buttons) ) return state = user_states.get(user_id) if state and state.get("step") == "ASK_BRAND": if user_msg in ["屈臣氏", "康是美", "寶雅", "全都要"]: state["search_brand"] = user_msg state["step"] = "ASK_LOCATION" location_button = QuickReply(items=[ QuickReplyButton(action=LocationAction(label="📍 點我分享位置")) ]) line_bot_api.reply_message( event.reply_token, TextSendMessage(text=f"沒問題！請分享您的位置，精靈來幫您找最近的【{user_msg}】！", quick_reply=location_button) ) else: line_bot_api.reply_message(event.reply_token, TextSendMessage(text="請點擊下方的按鈕選擇品牌喔！")) return if user_msg == "精靈顧問" or user_msg == "重新開始": user_states[user_id] = {"step": "ASK_SKIN"} skin_buttons = QuickReply(items=[ QuickReplyButton(action=MessageAction(label="乾性肌", text="乾性肌")), QuickReplyButton(action=MessageAction(label="油性肌", text="油性肌")), QuickReplyButton(action=MessageAction(label="混合肌", text="混合肌")), QuickReplyButton(action=MessageAction(label="敏感肌", text="敏感肌")) ]) line_bot_api.reply_message( event.reply_token, TextSendMessage(text="🧚‍♀️ 嗨！我是你的專屬精靈顧問。為了給你最精準的保養建議，先告訴我，你覺得自己偏向哪一種膚質呢？", quick_reply=skin_buttons) ) return if user_msg == "拍照精靈": user_states[user_id] = {"step": "ASK_PHOTO_ITEM"} line_bot_api.reply_message( event.reply_token, TextSendMessage(text="📷 歡迎開啟拍照精靈！\n您可以直接拍下商品照片傳給我，或是輸入「文字」來查詢商品售價喔！") ) return # ── 社群真實口碑 ── if user_msg == "社群真實口碑": user_states[user_id] = {"step": "ASK_REVIEW_PRODUCT"} line_bot_api.reply_message( event.reply_token, [ TextSendMessage(text="💬 歡迎使用社群真實口碑！"), TextSendMessage(text="請輸入您想查詢口碑的商品名稱，例如：「CeraVe 乳液」或「資生堂防曬」") ] ) return # ── 熱銷排行榜 ── if user_msg == "熱銷排行榜": user_states[user_id] = {"step": "ASK_RANKING_CATEGORY"} category_buttons = QuickReply(items=[ QuickReplyButton(action=MessageAction(label="💧 保濕", text="💧 保濕")), QuickReplyButton(action=MessageAction(label="✨ 美白", text="✨ 美白")), QuickReplyButton(action=MessageAction(label="🌿 修護", text="🌿 修護")), QuickReplyButton(action=MessageAction(label="🫧 痘痘粉刺", text="🫧 痘痘粉刺")), QuickReplyButton(action=MessageAction(label="☀️ 防曬", text="☀️ 防曬")), QuickReplyButton(action=MessageAction(label="😴 面膜", text="😴 面膜")), QuickReplyButton(action=MessageAction(label="🧴 乳液／乳霜", text="🧴 乳液／乳霜")), QuickReplyButton(action=MessageAction(label="🧼 洗面乳", text="🧼 洗面乳")), QuickReplyButton(action=MessageAction(label="💎 精華液", text="💎 精華液")), QuickReplyButton(action=MessageAction(label="🔍 其他類型", text="🔍 其他類型")), ]) line_bot_api.reply_message( event.reply_token, TextSendMessage(text="🏆 歡迎查看熱銷排行榜！\n請選擇您想查看的商品類別：", quick_reply=category_buttons) ) return # ── 收藏商品：查看清單 ── if user_msg in ["收藏商品", "購物車"]: favorites = user_favorites.get(user_id, []) add_qr = QuickReply(items=[QuickReplyButton(action=MessageAction(label="➕ 新增收藏", text="新增收藏"))]) if not favorites: line_bot_api.reply_message( event.reply_token, TextSendMessage(text="💝 您的收藏清單目前是空的！\n點擊下方按鈕新增您喜愛的商品吧～", quick_reply=add_qr) ) else: bubbles = [_build_fav_card(i, fav) for i, fav in enumerate(favorites)] flex_msg = FlexSendMessage.new_from_json_dict({ "type": "flex", "alt_text": "💝 您的收藏清單", "contents": {"type": "carousel", "contents": bubbles} }) line_bot_api.reply_message( event.reply_token, [flex_msg, TextSendMessage(text=f"共有 {len(favorites)} 件收藏商品", quick_reply=add_qr)] ) return # ── 收藏商品：新增 ── if user_msg == "新增收藏": user_states[user_id] = {"step": "ASK_FAVORITE_NAME"} line_bot_api.reply_message(event.reply_token, TextSendMessage(text="➕ 請輸入您想收藏的商品名稱：")) return # ── 收藏商品：刪除 ── if user_msg.startswith("刪除收藏:"): product_name = user_msg[5:] favs = user_favorites.get(user_id, []) user_favorites[user_id] = [f for f in favs if f["name"] != product_name] line_bot_api.reply_message(event.reply_token, TextSendMessage(text=f"🗑️ 已從收藏中刪除「{product_name}」")) return # ── 熱銷排行榜快速收藏 ── # ── 購物車「前往購物」→ 比價圖卡 ── if user_msg.startswith("查詢購買:"): buy_product = user_msg[5:] if buy_product: _do_photo_query(user_id, event.reply_token, buy_product) return if user_msg.startswith("快速收藏:"): parts = user_msg.split(":") p_name = parts[1] if len(parts) > 1 else "" p_price = parts[2] if len(parts) > 2 else "未知" if p_name: if user_id not in user_favorites: user_favorites[user_id] = [] if any(f["name"] == p_name for f in user_favorites[user_id]): line_bot_api.reply_message(event.reply_token, TextSendMessage(text=f"💝「{p_name}」已在收藏清單中囉！")) else: user_favorites[user_id].append({"name": p_name, "price": p_price, "note": "從熱銷排行榜加入"}) line_bot_api.reply_message(event.reply_token, TextSendMessage(text=f"🛒 已加入購物車！\n「{p_name}」")) return if not state: line_bot_api.reply_message( event.reply_token, TextSendMessage(text="請輸入「精靈顧問」來開啟膚況諮詢服務喔！") ) return current_step = state.get("step") if current_step == "ASK_SKIN": if user_msg in ["乾性肌", "油性肌", "混合肌", "敏感肌"]: state["skin_type"] = user_msg state["step"] = "ASK_ISSUE" issue_buttons = QuickReply(items=[ QuickReplyButton(action=MessageAction(label="嚴重脫皮", text="嚴重脫皮")), QuickReplyButton(action=MessageAction(label="暗沉無光", text="暗沉無光")), QuickReplyButton(action=MessageAction(label="痘痘粉刺", text="痘痘粉刺")), QuickReplyButton(action=MessageAction(label="泛紅乾癢", text="泛紅乾癢")) ]) line_bot_api.reply_message( event.reply_token, TextSendMessage(text=f"記錄下來了！你是 {user_msg}。那最近最讓你困擾的肌膚問題是什麼呢？", quick_reply=issue_buttons) ) else: line_bot_api.reply_message(event.reply_token, TextSendMessage(text="請選擇下方的膚質選項，或是輸入「重新開始」喔！")) elif current_step == "ASK_ISSUE": if user_msg in ["嚴重脫皮", "暗沉無光", "痘痘粉刺", "泛紅乾癢"]: state["issue"] = user_msg state["step"] = "ASK_PREFERENCE" pref_buttons = QuickReply(items=[ QuickReplyButton(action=MessageAction(label="偏好清爽凝露", text="偏好清爽凝露")), QuickReplyButton(action=MessageAction(label="偏好滋潤乳霜", text="偏好滋潤乳霜")), QuickReplyButton(action=MessageAction(label="都可以", text="都可以")) ]) line_bot_api.reply_message( event.reply_token, TextSendMessage(text=f"收到！針對 {user_msg} 的問題，你在挑選保養品時有特別偏好哪種質地嗎？", quick_reply=pref_buttons) ) else: line_bot_api.reply_message(event.reply_token, TextSendMessage(text="請選擇下方的肌膚問題選項，或是輸入「重新開始」喔！")) elif current_step == "ASK_PREFERENCE": if user_msg in ["偏好清爽凝露", "偏好滋潤乳霜", "都可以"]: skin_type = state["skin_type"] issue = state["issue"] preference = user_msg line_bot_api.reply_message( event.reply_token, TextSendMessage(text="🧚‍♀️ 精靈正在為您翻閱保養圖鑑，請稍候幾秒鐘...") ) prompt = f""" 你現在是一位「台灣藥妝店皮膚科精靈顧問🧚‍♀️」，擁有10年以上保養諮詢經驗。 使用者資料： * 膚質：{skin_type} * 困擾：{issue} * 偏好：{preference} 請根據以上資訊提供個人化保養建議。 【輸出規則】 1. 回覆控制在 180~250 字。 2. 語氣溫柔、親切，像專業美容顧問。 3. 使用繁體中文。 4. 不要使用表格。 5. 必須完全依照下列格式輸出： 🧚‍♀️ 哈囉親愛的！ 🩺 精靈診斷 （用1~2句話分析目前膚況，需根據使用者的膚質與困擾客製化） 💡 保養建議 • （具體建議1） • （具體建議2） • （具體建議3） 🛍️ 推薦產品 ① （完整品牌＋產品名稱） ⭐ （20字內推薦原因） ② （完整品牌＋產品名稱） ⭐ （20字內推薦原因） ③ （完整品牌＋產品名稱） ⭐ （20字內推薦原因） """ try: response = model.generate_content(prompt) line_bot_api.push_message(user_id, TextSendMessage(text=response.text)) except Exception as e: line_bot_api.push_message(user_id, TextSendMessage(text=f"❌ 精靈魔法發動失敗！錯誤原因：\n{e}")) del user_states[user_id] else: line_bot_api.reply_message(event.reply_token, TextSendMessage(text="請選擇下方的質地偏好選項，或是輸入「重新開始」喔！")) elif current_step == "ASK_PHOTO_ITEM": threading.Thread(target=_discover_and_confirm_bg, args=(user_id, user_msg, event.reply_token), daemon=True).start() # ── 社群真實口碑：收到商品名稱後產生評論 ── elif current_step == "ASK_REVIEW_PRODUCT": line_bot_api.reply_message(event.reply_token, TextSendMessage(text="🔍 精靈正在辨識商品，請稍候...")) product_name, corrected = normalize_product_name(user_msg) if product_name is None: line_bot_api.push_message(user_id, TextSendMessage( text=f"🔍 找不到「{user_msg}」的相關資訊耶～\n請輸入更完整的商品名稱或品牌，例如：「CeraVe 乳液」、「Bioderma 卸妝水」" )) return if corrected: _send_confirm_dialog(user_id, "review", product_name, user_msg) return _do_review_query(user_id, None, product_name) # ── 熱銷排行榜：收到「其他類型」後詢問自訂類別 ── elif current_step == "ASK_RANKING_CATEGORY" and user_msg == "🔍 其他類型": user_states[user_id] = {"step": "ASK_RANKING_CUSTOM"} line_bot_api.reply_message(event.reply_token, TextSendMessage(text="🔍 請告訴我您想找的保養品類型，例如：「去角質」、「眼霜」、「頸霜」、「身體乳」等～")) return # ── 熱銷排行榜：自訂類別 AI 生成排行 ── elif current_step == "ASK_RANKING_CUSTOM": custom_category = user_msg if user_id in user_states: del user_states[user_id] _rt_custom = event.reply_token def _ranking_custom_bg(_uid=user_id, _cat=custom_category, _rt=_rt_custom): try: ai_prompt = ( f"請列出台灣藥妝店最熱銷的「{_cat}」TOP 5 商品。" "請用以下 JSON 格式回傳，不要多餘說明：\n" '[{"name":"商品全名","brand":"品牌名稱","price":"數字不含$","tag":"emoji+3字特色","sales":"月售 X,XXX+"}]' ) ai_resp = model.generate_content(ai_prompt) import re, json as _json raw = ai_resp.text.strip() match = re.search(r'\[.*\]', raw, re.DOTALL) items_data = _json.loads(match.group()) if match else [] rank_list = [dict(item, rank=i+1) for i, item in enumerate(items_data[:5])] except Exception: rank_list = [{"rank": 1, "name": f"{_cat}相關商品", "brand": "綜合推薦", "price": "依品牌", "tag": "⭐ 精選推薦", "sales": "熱銷中"}] rank_colors = ["#FFD700", "#C0C0C0", "#CD7F32", "#4A90D9", "#7ED321"] rank_medals = ["🥇", "🥈", "🥉", "4️⃣", "5️⃣"] bubbles = [] for item in rank_list: idx = item["rank"] - 1 color = rank_colors[idx] if idx < 5 else "#8c8c8c" medal = rank_medals[idx] if idx < 5 else f"#{item['rank']}" card = { "type": "bubble", "size": "mega", "header": { "type": "box", "layout": "horizontal", "backgroundColor": color, "paddingAll": "20px", "contents": [ {"type": "text", "text": medal, "size": "xxl", "flex": 1, "align": "center", "gravity": "center"}, {"type": "box", "layout": "vertical", "flex": 4, "justifyContent": "center", "contents": [ {"type": "text", "text": f"排行第 {item['rank']} 名", "size": "xl", "color": "#FFFFFF", "weight": "bold", "align": "start"}, {"type": "text", "text": item["tag"], "size": "sm", "color": "#FFFFFF", "align": "start", "margin": "xs"} ]} ] }, "body": { "type": "box", "layout": "vertical", "paddingAll": "20px", "contents": [ {"type": "text", "text": item["name"], "weight": "bold", "size": "lg", "wrap": True, "color": "#111111"}, {"type": "text", "text": item["brand"], "size": "sm", "color": "#8c8c8c", "margin": "sm"}, {"type": "box", "layout": "vertical", "spacing": "sm", "margin": "lg", "contents": [ {"type": "box", "layout": "baseline", "spacing": "sm", "contents": [ {"type": "text", "text": "參考售價", "size": "sm", "color": "#8c8c8c", "flex": 3}, {"type": "text", "text": f"${item['price']}", "size": "sm", "color": "#111111", "weight": "bold", "flex": 5} ]}, {"type": "box", "layout": "baseline", "spacing": "sm", "contents": [ {"type": "text", "text": "銷售熱度", "size": "sm", "color": "#8c8c8c", "flex": 3}, {"type": "text", "text": item["sales"], "size": "sm", "color": "#FF6B00", "weight": "bold", "flex": 5} ]} ]} ] }, "footer": { "type": "box", "layout": "vertical", "contents": [{"type": "button", "style": "primary", "color": "#000000", "height": "sm", "action": {"type": "message", "label": "💝 加入購物車", "text": f"快速收藏:{item['name']}:${item['price']}"}}] } } bubbles.append(card) flex_msg = FlexSendMessage.new_from_json_dict({ "type": "flex", "alt_text": f"🏆 {_cat} 熱銷排行榜", "contents": {"type": "carousel", "contents": bubbles} }) try: line_bot_api.reply_message(_rt, flex_msg) except Exception: line_bot_api.push_message(_uid, flex_msg) threading.Thread(target=_ranking_custom_bg, daemon=True).start() return # ── 熱銷排行榜：收到類別後顯示榜單 ── elif current_step == "ASK_RANKING_CATEGORY": category = user_msg valid_categories = ["💧 保濕", "✨ 美白", "🌿 修護", "🫧 痘痘粉刺", "☀️ 防曬", "😴 面膜", "🧴 乳液／乳霜", "🧼 洗面乳", "💎 精華液"] if category not in valid_categories: line_bot_api.reply_message(event.reply_token, TextSendMessage(text="請點擊下方按鈕選擇類別喔！")) return rankings = { "💧 保濕": [ {"rank": 1, "name": "CeraVe 長效潤澤修護霜 340g", "brand": "CeraVe 適樂膚", "price": "619", "tag": "💧 神級保濕", "sales": "月售 5,000+"}, {"rank": 2, "name": "HADA LABO 極潤保濕乳液 140ml", "brand": "HADA LABO 肌研", "price": "396", "tag": "🎌 日系人氣", "sales": "月售 3,200+"}, {"rank": 3, "name": "Neutrogena 水活保濕精華 30ml", "brand": "Neutrogena 露得清", "price": "679", "tag": "🌊 輕透水感", "sales": "月售 2,800+"}, {"rank": 4, "name": "Avene 雅漾舒護活泉水 150ml", "brand": "Avene 雅漾", "price": "299", "tag": "🌿 敏肌首選", "sales": "月售 2,500+"}, {"rank": 5, "name": "Dr.Jart+ 積雪草修護霜 50ml", "brand": "Dr.Jart+", "price": "1500", "tag": "🔬 修護強效", "sales": "月售 1,800+"}, ], "✨ 美白": [ {"rank": 1, "name": "SK-II 青春露 230ml", "brand": "SK-II", "price": "3199", "tag": "✨ 頂級亮白", "sales": "月售 2,800+"}, {"rank": 2, "name": "高絲 雪肌精乳液 200ml", "brand": "Kose 高絲", "price": "1100", "tag": "🌸 和漢美白", "sales": "月售 2,200+"}, {"rank": 3, "name": "資生堂 ELIXIR 亮白精華 40ml", "brand": "資生堂 Shiseido", "price": "1580", "tag": "💫 緊緻亮白", "sales": "月售 1,900+"}, {"rank": 4, "name": "Dr.Wu 杏仁酸亮白精華 15ml", "brand": "Dr.Wu", "price": "850", "tag": "🍑 溫和換膚", "sales": "月售 1,600+"}, {"rank": 5, "name": "mediheal 維他命C亮白面膜 10片", "brand": "MEDIHEAL", "price": "419", "tag": "🍋 平價入門", "sales": "月售 1,400+"}, ], "🌿 修護": [ {"rank": 1, "name": "La Roche-Posay B5修護精華 30ml", "brand": "理膚寶水", "price": "820", "tag": "🌿 屏障修護", "sales": "月售 3,500+"}, {"rank": 2, "name": "Avene 雅漾舒護修護霜 50ml", "brand": "Avene 雅漾", "price": "580", "tag": "💙 敏肌救星", "sales": "月售 2,800+"}, {"rank": 3, "name": "CeraVe 修護保濕乳霜 340g", "brand": "CeraVe 適樂膚", "price": "619", "tag": "🔬 三重神經醯胺", "sales": "月售 2,500+"}, {"rank": 4, "name": "Dr.Jart+ 積雪草舒緩霜 15ml", "brand": "Dr.Jart+", "price": "580", "tag": "🌱 積雪草鎮靜", "sales": "月售 2,100+"}, {"rank": 5, "name": "Vaseline 凡士林深層修護乳 400ml", "brand": "Vaseline", "price": "199", "tag": "💰 超值必備", "sales": "月售 1,800+"}, ], "🫧 痘痘粉刺": [ {"rank": 1, "name": "Paula's Choice BHA 2% 水楊酸精華 30ml", "brand": "Paula's Choice", "price": "950", "tag": "🫧 深層疏通", "sales": "月售 3,200+"}, {"rank": 2, "name": "Dr.Wu 杏仁酸15%亮白更新精華 15ml", "brand": "Dr.Wu", "price": "480", "tag": "🍑 溫和去角質", "sales": "月售 2,600+"}, {"rank": 3, "name": "理膚寶水 Effaclar 調理精華 30ml", "brand": "La Roche-Posay", "price": "780", "tag": "🔬 皮科推薦", "sales": "月售 2,300+"}, {"rank": 4, "name": "Stridex 水楊酸棉片 55片", "brand": "Stridex", "price": "299", "tag": "✅ 方便快速", "sales": "月售 2,000+"}, {"rank": 5, "name": "COSRX 蝸牛修護精華 96ml", "brand": "COSRX", "price": "420", "tag": "🐌 修護痘印", "sales": "月售 1,700+"}, ], "☀️ 防曬": [ {"rank": 1, "name": "Biore 碧柔水感防曬乳 SPF50+ 50ml", "brand": "Biore 碧柔", "price": "299", "tag": "☀️ 超輕盈", "sales": "月售 6,000+"}, {"rank": 2, "name": "Anessa 金鑽高效防曬乳 60ml", "brand": "Anessa 安耐曬", "price": "780", "tag": "🏅 戶外神器", "sales": "月售 4,200+"}, {"rank": 3, "name": "SKIN1004 超鎮靜防曬精華 50ml", "brand": "SKIN1004", "price": "550", "tag": "🍃 溫和無感", "sales": "月售 3,500+"}, {"rank": 4, "name": "肌研極潤防曬乳 SPF50 50ml", "brand": "Rohto 樂敦", "price": "320", "tag": "💆 保濕防曬", "sales": "月售 2,900+"}, {"rank": 5, "name": "ISDIN 防曬乳 SPF50+ 100ml", "brand": "ISDIN", "price": "1200", "tag": "🌟 皮科推薦", "sales": "月售 1,500+"}, ], "😴 面膜": [ {"rank": 1, "name": "我的美麗日記 黑珍珠面膜 10片", "brand": "我的美麗日記", "price": "199", "tag": "🖤 經典熱銷", "sales": "月售 8,500+"}, {"rank": 2, "name": "MEDIHEAL NMF水庫保濕面膜 10片", "brand": "MEDIHEAL", "price": "250", "tag": "💦 韓系保濕", "sales": "月售 6,200+"}, {"rank": 3, "name": "森田藥粧 玻尿酸精華面膜 8片", "brand": "森田藥粧", "price": "149", "tag": "💧 高cp值", "sales": "月售 5,800+"}, {"rank": 4, "name": "SNP 燕窩保濕面膜 10片", "brand": "SNP", "price": "280", "tag": "🪹 燕窩滋養", "sales": "月售 4,500+"}, {"rank": 5, "name": "SK-II 青春敷面膜 6片", "brand": "SK-II", "price": "1180", "tag": "✨ 頂級保養", "sales": "月售 2,200+"}, ], "🧴 乳液／乳霜": [ {"rank": 1, "name": "CeraVe 長效潤澤修護霜 340g", "brand": "CeraVe 適樂膚", "price": "619", "tag": "🔬 醫美等級", "sales": "月售 5,000+"}, {"rank": 2, "name": "Neutrogena 深層修護身體乳 400ml", "brand": "Neutrogena 露得清", "price": "299", "tag": "🌊 輕透吸收", "sales": "月售 4,200+"}, {"rank": 3, "name": "NIVEA 深層修護乳液 400ml", "brand": "Nivea 妮維雅", "price": "169", "tag": "💰 超值日常", "sales": "月售 3,800+"}, {"rank": 4, "name": "Eucerin 優色林修護乳液 250ml", "brand": "Eucerin 優色林", "price": "499", "tag": "🏥 敏肌皮科", "sales": "月售 2,600+"}, {"rank": 5, "name": "資生堂 ELIXIR 彈潤活膚乳液 130ml", "brand": "資生堂 Shiseido", "price": "980", "tag": "🌸 彈潤緊緻", "sales": "月售 1,900+"}, ], "🧼 洗面乳": [ {"rank": 1, "name": "SENKA 洗顏專科柔膚泡沫 120g", "brand": "SENKA 洗顏專科", "price": "199", "tag": "🫧 綿密泡沫", "sales": "月售 7,000+"}, {"rank": 2, "name": "CeraVe 溫和泡沫洗面乳 236ml", "brand": "CeraVe 適樂膚", "price": "399", "tag": "🔬 醫美配方", "sales": "月售 5,500+"}, {"rank": 3, "name": "FANCL 無添加淨化洗顏粉 50g", "brand": "FANCL", "price": "580", "tag": "🌸 無添加溫和", "sales": "月售 4,200+"}, {"rank": 4, "name": "DHC 橄欖柔膚洗面皂 90g", "brand": "DHC", "price": "280", "tag": "🫒 橄欖滋潤", "sales": "月售 3,600+"}, {"rank": 5, "name": "理膚寶水 控油調理洗面乳 150ml", "brand": "La Roche-Posay", "price": "650", "tag": "🛢️ 控油清爽", "sales": "月售 2,800+"}, ], "💎 精華液": [ {"rank": 1, "name": "SK-II 青春露 230ml", "brand": "SK-II", "price": "3900", "tag": "💎 殿堂級精華", "sales": "月售 2,800+"}, {"rank": 2, "name": "Estée Lauder 小棕瓶精華 50ml", "brand": "Estée Lauder 雅詩蘭黛", "price": "2800", "tag": "🤎 修護經典", "sales": "月售 2,200+"}, {"rank": 3, "name": "La Roche-Posay B5修護精華 30ml", "brand": "La Roche-Posay", "price": "820", "tag": "🌿 屏障修護", "sales": "月售 2,000+"}, {"rank": 4, "name": "COSRX 蝸牛修護精華 96ml", "brand": "COSRX", "price": "420", "tag": "🐌 高效修護", "sales": "月售 1,800+"}, {"rank": 5, "name": "資生堂 ELIXIR 亮白精華 40ml", "brand": "資生堂 Shiseido", "price": "1580", "tag": "✨ 亮白緊緻", "sales": "月售 1,500+"}, ], } rank_list = rankings[category] rank_colors = ["#FFD700", "#C0C0C0", "#CD7F32", "#4A90D9", "#7ED321"] rank_medals = ["🥇", "🥈", "🥉", "4️⃣", "5️⃣"] bubbles = [] for item in rank_list: idx = item["rank"] - 1 color = rank_colors[idx] if idx < 5 else "#8c8c8c" medal = rank_medals[idx] if idx < 5 else f"#{item['rank']}" card = { "type": "bubble", "size": "mega", "header": { "type": "box", "layout": "horizontal", "backgroundColor": color, "paddingAll": "20px", "contents": [ {"type": "text", "text": medal, "size": "xxl", "flex": 1, "align": "center", "gravity": "center"}, {"type": "box", "layout": "vertical", "flex": 4, "justifyContent": "center", "contents": [ {"type": "text", "text": f"排行第 {item['rank']} 名", "size": "xl", "color": "#FFFFFF", "weight": "bold", "align": "start"}, {"type": "text", "text": item["tag"], "size": "sm", "color": "#FFFFFF", "align": "start", "margin": "xs"} ]} ] }, "body": { "type": "box", "layout": "vertical", "paddingAll": "20px", "contents": [ {"type": "text", "text": item["name"], "weight": "bold", "size": "lg", "wrap": True, "color": "#111111"}, {"type": "text", "text": item["brand"], "size": "sm", "color": "#8c8c8c", "margin": "sm"}, {"type": "box", "layout": "vertical", "spacing": "sm", "margin": "lg", "contents": [ {"type": "box", "layout": "baseline", "spacing": "sm", "contents": [ {"type": "text", "text": "參考售價", "size": "sm", "color": "#8c8c8c", "flex": 3}, {"type": "text", "text": f"${item['price']}", "size": "sm", "color": "#111111", "weight": "bold", "flex": 5} ]}, {"type": "box", "layout": "baseline", "spacing": "sm", "contents": [ {"type": "text", "text": "銷售熱度", "size": "sm", "color": "#8c8c8c", "flex": 3}, {"type": "text", "text": item["sales"], "size": "sm", "color": "#FF6B00", "weight": "bold", "flex": 5} ]} ]} ] }, "footer": { "type": "box", "layout": "vertical", "contents": [{"type": "button", "style": "primary", "color": "#000000", "height": "sm", "action": {"type": "message", "label": "💝 加入購物車", "text": f"快速收藏:{item['name']}:${item['price']}"}}] } } bubbles.append(card) flex_msg = FlexSendMessage.new_from_json_dict({ "type": "flex", "alt_text": f"🏆 {category} 熱銷排行榜", "contents": {"type": "carousel", "contents": bubbles} }) try: line_bot_api.reply_message(event.reply_token, flex_msg) except Exception: line_bot_api.push_message(user_id, flex_msg) if user_id in user_states: del user_states[user_id] # ── 收藏商品：輸入商品名稱後儲存 ── elif current_step == "ASK_FAVORITE_NAME": line_bot_api.reply_message(event.reply_token, TextSendMessage(text="🔍 精靈正在辨識商品，請稍候...")) product_name, corrected = normalize_product_name(user_msg) if product_name is None: line_bot_api.push_message(user_id, TextSendMessage( text=f"💝 找不到「{user_msg}」這個商品耶～\n請輸入更完整的商品名稱或品牌，例如：「FANCL 卸妝油」、「蘭蔻小黑瓶」" )) return if corrected: _send_confirm_dialog(user_id, "favorite", product_name, user_msg) return _do_favorite_save(user_id, None, product_name) # ── 商品確認對話 ── elif current_step == "CONFIRM_PRODUCT": feature = state.get("feature") product_name = state.get("product_name") step_map = {"photo": "ASK_PHOTO_ITEM", "review": "ASK_REVIEW_PRODUCT", "favorite": "ASK_FAVORITE_NAME"} retry_msg = { "photo": "請重新輸入商品名稱，精靈幫您查詢 📷", "review": "請重新輸入想查詢口碑的商品名稱 💬", "favorite": "請重新輸入想收藏的商品名稱 💝", } if user_msg == "✅ 對，就是這個": cosmed_result = state.get("cosmed_result") del user_states[user_id] if feature == "photo": if cosmed_result: # 有探索結果：康是美已有，只需搜屈臣氏＋寶雅 # reply_token 留給背景結果使用，不在這裡預先消耗 _rt = event.reply_token def _photo_with_cosmed_bg(uid, exact_name, cr, rt=_rt): search_name = _clean_91app_name(exact_name) other = scrape_watsons_and_poya(search_name) all_res = [] watsons = next((r for r in other if r["store"] == "屈臣氏"), None) poya = next((r for r in other if r["store"] == "寶雅"), None) if watsons: all_res.append(watsons) all_res.append(cr) if poya: all_res.append(poya) if all_res: _display_price_results(uid, all_res, exact_name, reply_token=rt) else: line_bot_api.push_message(uid, TextSendMessage( text=f"🥺 三家藥妝店都找不到「{exact_name}」，請嘗試其他關鍵字。" )) threading.Thread( target=_photo_with_cosmed_bg, args=(user_id, product_name, cosmed_result), daemon=True, ).start() else: _do_photo_query(user_id, event.reply_token, product_name) elif feature == "review": _do_review_query(user_id, event.reply_token, product_name) elif feature == "favorite": _do_favorite_save(user_id, event.reply_token, product_name) elif user_msg == "❌ 不是，重新輸入": user_states[user_id] = {"step": step_map[feature]} line_bot_api.reply_message(event.reply_token, TextSendMessage(text=retry_msg[feature])) else: confirm_qr = QuickReply(items=[ QuickReplyButton(action=MessageAction(label="✅ 對，就是這個", text="✅ 對，就是這個")), QuickReplyButton(action=MessageAction(label="❌ 不是，重新輸入", text="❌ 不是，重新輸入")), ]) line_bot_api.reply_message(event.reply_token, TextSendMessage( text=f"請點選下方按鈕確認～您是指「{product_name}」嗎？", quick_reply=confirm_qr )) if __name__ == "__main__": app.run(host='0.0.0.0', port=7860)