def handle_unfollow_event(event):
# 取出消息內User的資料
# get_profile 取得用戶個資
user_profile = line_bot_api.get_profile(event.source.user_id)
print(event)
# 將用戶資訊存在檔案內
# save file by python
with open("./unfollow_user.txt", "a") as myfile:
myfile.write(json.dumps(vars(user_profile), sort_keys=True))
myfile.write('\r\n')
def handle_follow(event):
if isinstance(event.source, SourceUser):
profile = line_bot_api.get_profile(event.source.user_id)
response = login(event.source.user_id)
if (response):
print(profile)
else:
print("login failed")
url = 'https://i.imgur.com/vi9vaYc.jpg'
app.logger.info("url=" + url)
bubble_string = flexObj.profile
message = FlexSendMessage(alt_text="關於作者",
contents=json.loads(bubble_string))
line_bot_api.reply_message(event.reply_token, message)
def handle_join(event):
profile=line_bot_api.get_profile(event.source.user_id)
opening_text = f"👋👋👋👋 {profile.display_name} 您好\n\
為了您有更好的系統體驗, 是否傳送您目前的居住位置呢 \
"
line_bot_api.reply_message(
event.reply_token,
TextSendMessage(text=opening_text,
quick_reply=QuickReply(items=[
QuickReplyButton(action=MessageAction(label="否, 下次再傳送", text="否, 下次再傳送")),
QuickReplyButton(action=LocationAction(label="是的, 我很願意有更好的體驗"))
],
)
)
)
def reply_text_and_get_user_profile(event):
# 取出消息內User的資料
profile = line_bot_api.get_profile(event.source.user_id)
# 將用戶資訊存在檔案內
with open("./users.txt", "a") as myfile:
myfile.write(json.dumps(vars(profile), sort_keys=True))
myfile.write('\r\n')
# 將菜單綁定在用戶身上
linkRichMenuId = secretFileContentJson.get("rich_menu_id")
linkResult = line_bot_api.link_rich_menu_to_user(event.source.user_id,
linkRichMenuId)
# 對新關注用戶傳送文字訊息
Follow1_message = json.load(
open("../Json_message/Follow1", 'r', encoding="utf-8"))
Follow2_message = json.load(
open("../Json_message/Follow2", 'r', encoding="utf-8"))
Follow1_demo = TextSendMessage.new_from_json_dict(Follow1_message)
Follow2_demo = TextSendMessage.new_from_json_dict(Follow2_message)
line_bot_api.push_message(event.source.user_id, Follow1_demo)
line_bot_api.push_message(event.source.user_id, Follow2_demo)
def default_reply(event):
name = line_bot_api.get_profile(event.source.user_id).display_name
line_bot_api.reply_message(event.reply_token,
TextSendMessage(text=f"Hello {name}!"))
def handle_message(event):
profile = line_bot_api.get_profile(event.source.user_id) # 使用者資訊
msg = str(event.message.text).upper().strip() # 使用者輸入的內容
utterance = luis(msg) # Luis 自然語言處理語句
uid = profile.user_id # 發訊者ID
Timestamp = calendar.timegm(time.gmtime())
Name = profile.display_name
Pic = profile.picture_url
dict = {
"Name": Name,
"Picture": Pic,
"UserID": uid,
"Msg": msg,
'Timestamp': Timestamp
}
# 透過回傳至kafka dict可再後端進行分析/調整模型
main_api(dict)
# 針對圖文選單所觸發文字進行回復 動作或是文字訊息
if re.match('威士忌推薦', msg):
line_bot_api.push_message(uid, quickReplyTextSendMessage)
elif re.match('調酒推薦', msg):
line_bot_api.push_message(uid, cocktailTextSendMessage)
# 文字觸發 推播 Liff 嵌入式網頁 #未來展望：取得jquery +評論+liff.profile資訊+更多功能
elif re.match('酒吧地圖', msg):
buttons_template = ButtonsTemplate(
title='親愛的使用者',
text='請點選下表連結到酒吧',
actions=[
uid,
URIAction(label="將為您提供酒吧地圖",
uri="https://liff.line.me/1654667223-V7pklmP5")
])
template_message = TemplateSendMessage(alt_text='將為您提供酒吧地圖',
template=buttons_template)
line_bot_api.reply_message(event.reply_token, template_message)
elif re.match('尋找酒友', msg):
buttons_template = ButtonsTemplate(
title='親愛的使用者',
text='請點選下表連結到聊天室',
actions=[
uid,
URIAction(label="將為您提供酒友聊天室",
uri="https://liff.line.me/1654667223-3aR1lyPv")
])
template_message = TemplateSendMessage(alt_text='將為您提供酒友聊天室',
template=buttons_template)
line_bot_api.reply_message(event.reply_token, template_message)
elif re.match('關鍵字查詢', msg):
line_bot_api.push_message(uid, TextSendMessage("請再輸入任意風味或酒名關鍵字"))
elif re.match('熱門排行', msg):
line_bot_api.push_message(uid, TextSendMessage("將為您提供熱門排行前五名"))
Pop_message = json.load(
open("./app/Json_message/popular", 'r', encoding="utf-8"))
Pop_demo = FlexSendMessage.new_from_json_dict(Pop_message)
line_bot_api.push_message(uid, Pop_demo)
elif re.match('好酒貪杯', msg):
IOT_message = json.load(
open("./app/Json_message/Drink", 'r', encoding="utf-8"))
IOT_demo = TemplateSendMessage.new_from_json_dict(IOT_message)
line_bot_api.push_message(uid, IOT_demo)
elif re.match('倒酒動作', msg):
line_bot_api.push_message(uid, TextSendMessage("正在進行倒酒動作"))
elif re.match('取消動作', msg):
line_bot_api.push_message(uid, TextSendMessage("已為您取消動作"))
elif re.match('資策會_EB102_愛心組', msg):
line_bot_api.push_message(uid,
TextSendMessage("https://ibar3.webnode.tw/"))
# 針對調酒風味re.match 文字訊息 作出reply
elif re.match("風味：圓熟", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦圓熟調酒......"))
Mellow_message = json.load(
open("./cocktail_flavor/Mellow", 'r', encoding="utf-8"))
Mellow_demo = FlexSendMessage.new_from_json_dict(Mellow_message)
line_bot_api.push_message(uid, Mellow_demo)
elif re.match("風味：經典", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦經典調酒......"))
Classic_message = json.load(
open("./cocktail_flavor/Classic", 'r', encoding="utf-8"))
Classic_demo = FlexSendMessage.new_from_json_dict(Classic_message)
line_bot_api.push_message(uid, Classic_demo)
elif re.match("風味：獨創", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦獨創調酒......"))
Original_message = json.load(
open("./cocktail_flavor/Original", 'r', encoding="utf-8"))
Original_demo = FlexSendMessage.new_from_json_dict(Original_message)
line_bot_api.push_message(uid, Original_demo)
elif re.match("風味：草藥", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦草藥味調酒......"))
herbal_message = json.load(
open("./cocktail_flavor/herbal", 'r', encoding="utf-8"))
herbal_demo = FlexSendMessage.new_from_json_dict(herbal_message)
line_bot_api.push_message(uid, herbal_demo)
elif re.match("風味：甜", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦甜味調酒......"))
Sweet_message = json.load(
open("./cocktail_flavor/Sweet", 'r', encoding="utf-8"))
Sweet_demo = FlexSendMessage.new_from_json_dict(Sweet_message)
line_bot_api.push_message(uid, Sweet_demo)
elif re.match("風味：酸", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦酸味調酒......"))
Sour_message = json.load(
open("./cocktail_flavor/Sour", 'r', encoding="utf-8"))
Sour_demo = FlexSendMessage.new_from_json_dict(Sour_message)
line_bot_api.push_message(uid, Sour_demo)
elif re.match("風味：苦甜", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦苦甜味調酒......"))
Bittersweet_message = json.load(
open("./cocktail_flavor/Bittersweet", 'r', encoding="utf-8"))
Bittersweet_demo = FlexSendMessage.new_from_json_dict(
Bittersweet_message)
line_bot_api.push_message(uid, Bittersweet_demo)
elif re.match("風味：細緻", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦細緻味調酒......"))
light_message = json.load(
open("./cocktail_flavor/light", 'r', encoding="utf-8"))
light_demo = FlexSendMessage.new_from_json_dict(light_message)
line_bot_api.push_message(uid, light_demo)
elif re.match("風味：和諧", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦和諧味調酒......"))
Balanced_message = json.load(
open("./cocktail_flavor/Balanced", 'r', encoding="utf-8"))
Balanced_demo = FlexSendMessage.new_from_json_dict(Balanced_message)
line_bot_api.push_message(uid, Balanced_demo)
elif re.match("風味：柑橘", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦柑橘味調酒......"))
Orange_message = json.load(
open("./cocktail_flavor/Orange", 'r', encoding="utf-8"))
Orange_demo = FlexSendMessage.new_from_json_dict(Orange_message)
line_bot_api.push_message(uid, Orange_demo)
elif re.match("風味：水果香", msg):
# line_bot_api.push_message(uid, TextSendMessage("將為您推薦果香味調酒......"))
Fruity_message = json.load(
open("./cocktail_flavor/Fruity", 'r', encoding="utf-8"))
Fruity_demo = FlexSendMessage.new_from_json_dict(Fruity_message)
line_bot_api.push_message(uid, Fruity_demo)
# 關鍵字搜尋，先進行酒名關鍵字查詢、再進行風味tag搜尋之後才進行OLAMI模組回復使用者
# 先透過關鍵字名稱找尋有無相關data 若無再利用標籤查詢data 再沒有則利用olami查詢是否有相關AI數據庫資訊
else:
try:
data = name_api(msg)
flexSendMessage1 = FlexSendMessage.new_from_json_dict(data)
line_bot_api.push_message(uid, TextSendMessage("請稍等…將為您進行搜尋"))
line_bot_api.push_message(uid, flexSendMessage1)
except IndexError:
data2 = tag_api(utterance)
if not len(data2['contents']['contents']) == 0:
flexSendMessage2 = FlexSendMessage.new_from_json_dict(data2)
line_bot_api.push_message(uid, TextSendMessage("請稍等…將為您進行搜尋"))
line_bot_api.push_message(uid, flexSendMessage2)
else:
line_bot_api.reply_message(
event.reply_token,
TextSendMessage(text=Olami().nli(event.message.text)))
def handle_text_message(event):
text = event.message.text
if text == '我的labelr檔案':
if isinstance(event.source, SourceUser):
profile = line_bot_api.get_profile(event.source.user_id)
response = login(event.source.user_id)
if (response):
print(profile)
totalFinished = sum(list(response.values()))
bubble = BubbleContainer(
direction='ltr',
hero=ImageComponent(url=profile.picture_url,
size='full',
aspect_ratio='1:1',
aspect_mode='cover'),
body=BoxComponent(
layout='vertical',
contents=[
# title
TextComponent(text=profile.display_name,
weight='bold',
size='xl',
align="center"),
# info
BoxComponent(
layout='vertical',
margin='lg',
spacing='sm',
contents=[
BoxComponent(
layout='baseline',
spacing='sm',
contents=[
TextComponent(
text='總共完成{}項任務'.format(
totalFinished),
align="center",
color='#aaaaaa',
weight='bold',
size='md',
flex=1),
],
),
BoxComponent(
layout='baseline',
spacing='sm',
contents=[
TextComponent(text='分類任務',
align="center",
color='#aaaaaa',
size='sm',
flex=3),
TextComponent(text=str(
response['CLAS']),
wrap=True,
align="center",
color='#666666',
size='sm',
flex=3)
],
),
BoxComponent(
layout='baseline',
spacing='sm',
contents=[
TextComponent(text='NER任務',
align="center",
color='#aaaaaa',
size='sm',
flex=3),
TextComponent(
text=str(response['NER']),
align="center",
wrap=True,
color='#666666',
size='sm',
flex=3,
),
],
),
],
)
],
),
footer=BoxComponent(
layout='vertical',
spacing='sm',
contents=[
ButtonComponent(
style='primary',
height='sm',
action=URIAction(
label='我的Labelr檔案',
uri=
"https://line-label.herokuapp.com/Profile")
)
]),
)
message = FlexSendMessage(alt_text="我的Labelr檔案", contents=bubble)
line_bot_api.reply_message(event.reply_token, message)
else:
line_bot_api.reply_message(
event.reply_token, TextSendMessage(text="目前無法顯示使用者資訊，請稍後再嘗試"))
elif text == '任務清單':
response = get_all_tasks()
if (response):
carousels = []
for task in response:
if (task['taskType'] == 'classification'):
carousels.append(
CarouselColumn(
thumbnail_image_url=
'https://i.imgur.com/vphbdKm.jpg',
title=task['taskTitle'],
text="委託人: {}".format(task['taskOwnerName']),
actions=[
PostbackAction(
label='開始任務',
data='action=startTask&taskId={}'.format(
task['taskId']))
]))
image_carousel_template = CarouselTemplate(columns=carousels)
template_message = TemplateSendMessage(
alt_text='所有任務', template=image_carousel_template)
line_bot_api.reply_message(event.reply_token, template_message)
else:
send_error_message(event)
elif text == '關於作者':
url = 'https://i.imgur.com/vi9vaYc.jpg'
app.logger.info("url=" + url)
bubble_string = flexObj.profile
message = FlexSendMessage(alt_text="關於作者",
contents=json.loads(bubble_string))
line_bot_api.reply_message(event.reply_token, message)
elif text == 'insight_followers':
today = datetime.date.today().strftime("%Y%m%d")
response = line_bot_api.get_insight_followers(today)
if response.status == 'ready':
messages = [
TextSendMessage(text='followers: ' + str(response.followers)),
TextSendMessage(text='targetedReaches: ' +
str(response.targeted_reaches)),
TextSendMessage(text='blocks: ' + str(response.blocks)),
]
else:
messages = [TextSendMessage(text='status: ' + response.status)]
line_bot_api.reply_message(event.reply_token, messages)
elif text == 'insight_demographic':
response = line_bot_api.get_insight_demographic()
if response.available:
messages = [
"{gender}: {percentage}".format(gender=it.gender,
percentage=it.percentage)
for it in response.genders
]
else:
messages = [TextSendMessage(text='available: false')]
line_bot_api.reply_message(event.reply_token, messages)
else:
line_bot_api.reply_message(event.reply_token,
TextSendMessage(text=event.message.text))