app.py

import os
import sqlite3
import requests
from google import 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

app = Flask(__name__)

# ================= 1. 從環境變數讀取金鑰（安全防護） =================
line_bot_api = LineBotApi(os.environ.get('LINE_CHANNEL_ACCESS_TOKEN'))
handler = WebhookHandler(os.environ.get('LINE_CHANNEL_SECRET'))
gemini_client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))

DB_PATH = os.path.join(os.path.dirname(__file__), "products.db")

STORE_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",
}

def query_product(name):
    """從 SQLite 查詢商品，回傳各店資料的 list；查無則回傳 None。"""
    try:
        conn = sqlite3.connect(DB_PATH)
        conn.row_factory = sqlite3.Row
        rows = conn.execute(
            "SELECT * FROM products WHERE name = ? ORDER BY store", (name,)
        ).fetchall()
        conn.close()
        if rows:
            return [dict(r) for r in rows]
    except Exception:
        pass
    return None

# ================= 2. 建立狀態儲存區 =================
user_states = {}

@app.route("/")
def health():
    return "OK"

@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'

# ================= 3. 處理使用者傳送照片的邏輯 (拍照精靈) =================
@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":
        line_bot_api.reply_message(
            event.reply_token,
            TextSendMessage(text="✨ 收到照片！精靈正在用魔法辨識這款產品，請稍候...")
        )
        
        try:
            message_content = line_bot_api.get_message_content(event.message.id)
            image_bytes = io.BytesIO(message_content.content)
            pil_image = Image.open(image_bytes)
            
            vision_prompt = """
            請辨識這張圖片中的保養品。
            如果是 CeraVe (適樂膚) 的產品，請直接回答：CeraVe適樂膚 長效潤澤修護霜 340g
            如果是 Avene (雅漾) 活泉水，請直接回答：Avene 雅漾舒護活泉水150ml
            如果都不是，請發揮你的專業，判斷它是什麼真實的品牌與品名，並「直接回答品牌與品名」。
            
            注意：非常重要！無論如何，你只能輸出「商品名稱」，絕對不要輸出任何其他廢話、標點符號、價格 or 商家資訊。
            """
            
            response = gemini_client.models.generate_content(
                model='gemini-2.5-flash',
                contents=[vision_prompt, pil_image]
            )
            product_name = response.text.strip()

            data_list = query_product(product_name)
            if not data_list:
                estimate_prompt = f"""
                請估算「{product_name}」這款產品在台灣屈臣氏、康是美、寶雅的合理售價。
                請務必「只回傳」一個標準的 JSON 陣列，不要有任何額外的說明文字。格式嚴格如下：
                [
                  {{"store": "屈臣氏", "name": "{product_name}", "price": "估計數字"}},
                  {{"store": "康是美", "name": "{product_name}", "price": "估計數字"}},
                  {{"store": "寶雅", "name": "{product_name}", "price": "估計數字"}}
                ]
                """
                est_response = gemini_client.models.generate_content(
                    model='gemini-2.5-flash',
                    contents=estimate_prompt
                )
                clean_text = est_response.text.replace("```json", "").replace("```", "").strip()
                data_list = json.loads(clean_text)
            
            bubbles = []
            for item in data_list:
                safe_store = item.get("store", "推薦藥妝店")
                safe_name = item.get("name", "未知名稱商品")
                safe_price = item.get("price", "請洽門市")
                safe_logo = item.get("logo", STORE_LOGOS.get(safe_store, "https://via.placeholder.com/600x300/eeeeee/999999?text=Store+Logo"))
                safe_discount = item.get("discount", "")
                
                search_query = urllib.parse.quote(f"{safe_store} {safe_name}")
                safe_link = item.get("link", f"https://www.google.com/search?q={search_query}")
                
                specs_box = {
                    "type": "box",
                    "layout": "vertical",
                    "spacing": "sm",
                    "margin": "lg",
                    "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": f"${safe_price}", "size": "md", "color": "#111111", "weight": "bold", "flex": 2}
                            ]
                        }
                    ]
                }

                if safe_discount:
                    specs_box["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},
                      specs_box
                    ]
                  },
                  "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
                }
            })
            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"❌ 哎呀！精靈遇到了一點問題。錯誤原因：\n{e}")
            )

# ================= 4. 處理使用者傳送位置的邏輯 (附近店家地圖) =================
@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")
    
    # 使用與 Hugging Face Secrets 完美對應的正確環境變數
    google_api_key = os.environ.get('GOOGLE_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

    # 計算距離的數學公式
    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)

    # 查詢「今天確切營業時間」的 Place Details 函式
    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"
            
            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 =================
@handler.add(MessageEvent, message=TextMessage)
def handle_message(event):
    user_id = event.source.user_id
    user_msg = event.message.text.strip()

    # 附近店家 - 步驟 1：選擇品牌
    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

    # 附近店家 - 步驟 2：要求定位
    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

    # 任何時候輸入「精靈顧問」或「重新開始」，皆重置該用戶的狀態
    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

    state = user_states.get(user_id)
    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")

    # 【步驟一】處理膚質選擇
    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！"))

    # 【步驟二】處理困擾選擇
    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！"))

    # 【步驟三】處理偏好選擇 -> 產生建議
    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。
                格式要求固定包括：精靈診斷、保養建議、推薦產品。
            """
            try:
                response = gemini_client.models.generate_content(
                    model='gemini-2.5-flash',
                    contents=prompt
                )
                ai_reply = response.text
                line_bot_api.push_message(user_id, TextSendMessage(text=ai_reply))
            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！"))

    # 處理純文字商品查詢
    elif current_step == "ASK_PHOTO_ITEM":
        text_prompt = f"請幫我查詢「{user_msg}」這款產品在台灣藥妝店的合理售價範圍與推薦購買商家。請簡單溫柔地回答，並條列出品名、價格、商家。"
        try:
            line_bot_api.reply_message(event.reply_token, TextSendMessage(text="✨ 收到文字！精靈正在幫您查詢這款產品，請稍候..."))
            response = gemini_client.models.generate_content(
                model='gemini-2.5-flash',
                contents=text_prompt
            )
            line_bot_api.push_message(user_id, TextSendMessage(text=f"🧚‍♀️ 查詢成功！\n\n{response.text}"))
        except Exception as e:
            line_bot_api.push_message(user_id, TextSendMessage(text=f"❌ 查詢失敗，錯誤原因：\n{e}"))
        del user_states[user_id]

if __name__ == "__main__":
    app.run(host='0.0.0.0', port=7860)