def callback():
data = request.json
eventType = request.headers.get('X-Github-Event')
if eventType == 'create':
# seseorang sedang membuat branch baru di remote repo
if data['ref_type'] == 'branch':
refMaster = data['master_branch']
refName = data['ref']
actor = data['sender']['login']
refLink = data['repository']['html_url']
message = actor + " telah membuat branch baru namanya " + refName + " dari branch " + refMaster + " : " + refLink + "/tree/" + refName
line_bot_api.push_message(app.config["roomId"],
TextSendMessage(text=message))
elif eventType == 'pull_request':
# seseorang sedang melakukan pull request
if data['action'] == 'opened':
link = data['pull_request']['html_url']
headRepo = data['pull_request']['head']['ref']
baseRepo = data['pull_request']['base']['ref']
actor = data['sender']['login']
message = "si " + actor + " udah bikin pull request dari " + headRepo + " ke " + baseRepo + ", tolong di review ya, ini link nya " + link
line_bot_api.push_message(app.config["roomId"],
TextSendMessage(text=message))
elif eventType == 'repository':
if data['action'] == 'unarchived':
repoName = data['repository']['name']
repoLink = data['repository']['html_url']
message = "Alhamdulillah ya repository " + repoName + " udah aktif lagi, yuk kita berkontribusi lagi. cek linknya di + " + repoLink
line_bot_api.push_message(app.config["roomId"],
TextSendMessage(text=message))
elif data['action'] == 'archived':
repoName = data['repository']['name']
repoLink = data['repository']['html_url']
message = "ALERT\nRepository " + repoName + " telah diarchive, tapi masih bisa diakses kok.\n makasih ya udah bersama-sama berkontribusi di repo tersebut. cek linknya di " + repoLink
line_bot_api.push_message(app.config["roomId"],
TextSendMessage(text=message))
elif eventType == 'pull_request_review':
if data['action'] == 'submitted':
repoName = data['repository']['name']
prName = data['pull_request']['title']
prReviewLink = data['review']['html_url']
message = "Ada review tuh buat Pull Request + " + prName + " di Repository " + repoName + ", yang bersangkutan jangan lupa cek ya di " + prReviewLink
line_bot_api.push_message(app.config["roomId"],
TextSendMessage(text=message))
else:
print(eventType + " belum ada handlernya ih")
return "OK", 200
def replyText(event):
if event.source.user_id == "Uf4a596a6eb65eabf52c003ffe325a21d":
try:
img_url = google_search(event.message.text)
print(img_url)
line_bot_api.reply_message(
event.reply_token,
ImageSendMessage(original_content_url=img_url,
preview_image_url=img_url))
except:
#hello_text = echo(event.message.text)
line_bot_api.push_message('Uf4a596a6eb65eabf52c003ffe325a21d',
TextSendMessage(text='沒找到'))
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 timed_job():
msg = connectDB.showAds()
print(msg)
line_bot_api.push_message("Uf4a596a6eb65eabf52c003ffe325a21d",
TextSendMessage(text=str(msg)))
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)))