Introduction:
Prior today at
Google I/O, the Hangouts Chat group (counting yours really) conveyed an
included chat on the bot structure for Hangouts Chat (talk video here [~40 mins]).
On the off chance that you missed it a while back, Google propelled the new
Hangouts Chat application for G Suite clients (yet not purchaser Gmail clients
as of now). This cutting edge coordinated effort stage has a few key highlights
not accessible in "exemplary Hangouts," including the capacity to
make talk rooms, search, and the capacity to connect records from Google Drive.
Anyway for engineers, the greatest new element is a bot structure and API
enabling designers to make bots that interface with clients inside
"spaces," i.e., talk rooms or direct messages (DMs).
Before beginning
with bots, how about we audit average API use where Python
Training in Bangalore your application must be approved for information
get to, i.e., OAuth2. When consent is in all actuality, your application calls
the API, the API benefits the solicitation and reacts back with the ideal
outcomes, as showed here:
Bot engineering
is very extraordinary. With bots, perceive that solicitations originate from
clients in talk rooms or DMs. Clients direct messages towards a bot, at that
point Hangouts Chat transfers those solicitations to the bot. The bot plays out
all the vital handling (conceivably calling different APIs and
administrations), examines the reaction, and returns it to Chat, which thus,
shows the outcomes to clients. Here's the condensed bot work process:
A key take away
from this discourse is that regularly in your applications, you call APIs. For
bots, Hangouts Chat calls you. Hence, the administration is incredibly adaptable
for designers: you can make bots utilizing
basically any language (not simply Python), utilizing your pile of
decision, and facilitated on any open or private cloud. The main prerequisite
is that as long as Hangouts Chat would http be able to POST to your bot, you're
ready.
Moreover, on the
off chance that you believe there's something missing in the outline since you
don't see OAuth2 nor API calls, you'd likewise be right. Search for both in a
future post where I center around offbeat reactions from Hangouts Chat bots. Python Training will give a vast
knowledge about this topic.
Types and Bot Preparing:
So what does the
payload resemble when your bot gets a call from Hangouts Chat? The primary
thing your bot needs to do is to decide the kind of occasion got. It would then
be able to process the solicitation dependent on that occasion type, lastly,
return a fitting JSON payload back to Hangouts Chat to render inside the space.
There are presently four occasion types in Hangouts Chat:
·
ADDED_TO_SPACE
·
REMOVED_FROM_SPACE
·
MESSAGE
·
CARD_CLICKED
The main pair is
for when a bot is added to or expelled from a space. In the principal case, the
bot would almost certainly send an invite message like, "A debt of
gratitude is in order for adding me to this room," and maybe give a few
guidelines on the most proficient method to speak with the bot. At the point
when a bot is expelled from a space, it can never again speak with talk room
members, so there's no reaction message sent for this situation; the probably
activity here is log that the bot was expelled from the space.
The third
message type is likely the most widely recognized situation, where a bot has
been added to a room, and now a human client is sending it a solicitation. The
other regular sort would be the last one. Instead of a message, this occasion
happens when clients click on a UI card component. The bot's activity here is
to summon the "callback" related with the card component clicked.
Various things can occur here: the bot can restore an instant message (or
nothing by any means), a UI card can be refreshed, or another card can be
returned.
All of what we
depicted above is acknowledged in the pseudocode underneath (regardless of
whether you execute in Python or some other upheld language) and accommodating
in setting you up to audit the official documentation:
def
process_event(req, rsp):
occasion =
json.loads(req['body']) # occasion got
in the event
that event['type'] == 'REMOVED_FROM_SPACE':
# no reaction as
bot expelled from room
return
elif
event['type'] == 'ADDED_TO_SPACE':
# bot added to
room; send welcome message
msg = {'text':
'A debt of gratitude is in order for adding me to this room!'}
elif
event['type'] == 'MESSAGE':
# message got
during typical activities
msg = respond_to_message(event['message']['text'])
elif
event['type'] == 'CARD_CLICKED':
# result from
client click on card UI
activity =
event['action']
msg =
respond_to_click( action['actionMethodName'], action['parameters'])
else:
return
rsp. Send(json.dumps(msg))
Notwithstanding
usage language, regardless you have to make the fundamental changes to keep
running on the facilitating stage you pick. Our model uses Google App Engine
(GAE) for facilitating; underneath you'll see the undeniable similitudes between
our real bot application and this pseudocode. For more details refer to Python Training in Bangalore.
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