Showing posts with label App Engine. Show all posts
Showing posts with label App Engine. Show all posts

Wednesday, May 9, 2018

Creating Hangouts Chat bots with Python

NOTE: The code featured here is also available as a video + overview post as part of this developers series from Google.

Introduction

Earlier today at Google I/O, the Hangouts Chat team (including yours truly) delivered a featured talk on the bot framework for Hangouts Chat (talk video here [~40 mins]). If you missed it several months ago, Google launched the new Hangouts Chat application for G Suite customers (but not consumer Gmail users at this time). This next-generation collaboration platform has several key features not available in "classic Hangouts," including the ability to create chat rooms, search, and the ability to attach files from Google Drive. However for developers, the biggest new feature is a bot framework and API allowing developers to create bots that interact with users inside "spaces," i.e., chat rooms or direct messages (DMs).

Before getting started with bots, let's review typical API usage where your app must be authorized for data access, i.e., OAuth2. Once permission is granted, your app calls the API, the API services the request and responds back with the desired results, as illustrated here:

Bot architecture is quite different. With bots, recognize that requests come from users in chat rooms or DMs. Users direct messages towards a bot, then Hangouts Chat relays those requests to the bot. The bot performs all the necessary processing (possibly calling other APIs and services), collates the response, and returns it to Chat, which in turn, displays the results to users. Here's the summarized bot workflow:

A key takeaway from this discussion is that normally in your apps, you call APIs. For bots, Hangouts Chat calls you. For this reason, the service is extremely flexible for developers: you can create bots using pretty much any language (not just Python), using your stack of choice, and hosted on any public or private cloud. The only requirement is that as long as Hangouts Chat can HTTP POST to your bot, you're good to go.

Furthermore, if you think there's something missing in the diagram because you don't see OAuth2 nor API calls, you'd also be correct. Look for both in a future post where I focus on asynchronous responses from Hangouts Chat bots.

Event types & bot processing

So what does the payload look like when your bot receives a call from Hangouts Chat? The first thing your bot needs to do is to determine the type of event received. It can then process the request based on that event type, and finally, return an appropriate JSON payload back to Hangouts Chat to render within the space. There are currently four event types in Hangouts Chat:
  1. ADDED_TO_SPACE
  2. REMOVED_FROM_SPACE
  3. MESSAGE
  4. CARD_CLICKED
The first pair are for when a bot is added to or removed from a space. In the first case, the bot would likely send a welcome message like, "Thanks for adding me to this room," and perhaps give some instructions on how to communicate with the bot. When a bot is removed from a space, it can no longer communicate with chat room participants, so there's no response message sent in this case; the most likely action here would be to log that the bot was removed from the space.

The 3rd message type is likely the most common scenario, where a bot has been added to a room, and now a human user is sending it a request. The other common type would be the last one. Rather than a message, this event occurs when users click on a UI card element. The bot's job here is to invoke the "callback" associated with the card element clicked. A number of things can happen here: the bot can return a text message (or nothing at all), a UI card can be updated, or a new card can be returned.

All of what we described above is realized in the pseudocode below (whether you choose to implement in Python or any other supported language) and helpful in preparing you to review the official documentation:
def process_event(req, rsp):
    event = json.loads(req['body']) # event received
    if event['type'] == 'REMOVED_FROM_SPACE':
        # no response as bot removed from room
        return
    elif event['type'] == 'ADDED_TO_SPACE':
        # bot added to room; send welcome message
        msg = {'text': 'Thanks for adding me to this room!'}
    elif event['type'] == 'MESSAGE':
        # message received during normal operations
        msg = respond_to_message(event['message']['text'])
    elif event['type'] == 'CARD_CLICKED':
        # result from user-click on card UI
        action = event['action']
        msg = respond_to_click(
          action['actionMethodName'], action['parameters'])
    else:
        return
    rsp.send(json.dumps(msg))
Regardless of implementation language, you still need to make the necessary tweaks to run on the hosting platform you choose. Our example uses Google App Engine (GAE) for hosting; below you'll see the obvious similarities between our actual bot app and this pseudocode.

Polling chat room users for votes

For a basic voting bot, we need a vote counter, buttons for users to upvote or downvote, and perhaps some reset or "new vote" button. To implement it, we need to unpack the inbound JSON object, determine the event type, then process each event type with actions like this:
  1. ADDED_TO_SPACE — ignore.. we don't do anything unless asked by users
  2. REMOVED_FROM_SPACE — no action (bot removed)
  3. MESSAGE — start new vote
  4. CARD_CLICKED — process "upvote", "downvote", or "newvote" request
Here's a handler implementation for Python App Engine using its webapp2 micro framework:
class VoteBot(webapp2.RequestHandler):
    def post(self):
        event = json.loads(self.request.body)
        user = event['user']['displayName']
        if event['type'] == 'CARD_CLICKED':
            method = event['action']['actionMethodName']
            if method == 'newvote':
                body = create_message(user)
            else:
                delta = 1 if method == 'upvote' else -1
                vote_count = int(event['action']['parameters'][0]['value']) + delta
                body = create_message(user, vote_count, True)
        elif event['type'] == 'MESSAGE':
            body = create_message(user)
        else: # no response for ADDED_TO_SPACE or REMOVED_FROM_SPACE
            return
        self.response.headers['Content-Type'] = 'application/json'
        self.response.out.write(json.dumps(body)) 
If you've never written an app using webapp2, don't fret, as this example is easily portable to Flask or other web framework. Why didn't I write it with Flask to begin with? Couple of reasons: 1) the webapp2 framework comes native with App Engine... no need to go download/install it, and 2) because it's native, I don't need to deploy any other files other than bot.py and its app.yaml config file whereas with Flask, you're uploading another ~1300 files in addition this pair. (More on this towards the end of this post.)

Compare this real app to the pseudocode... similar, right? Our bot is a bit more complex in that it renders UI cards, so the create_message() function will need to do more than just return a plain text response. Instead, it must generate and return the JSON markup rendering the card in the Hangouts Chat UI:
def create_message(voter, vote_count=0, should_update=False):
    PARAMETERS = [{'key': 'count', 'value': str(vote_count)}]
    return {
        'actionResponse': {
            'type': 'UPDATE_MESSAGE' if should_update else 'NEW_MESSAGE'
        },
        'cards': [{
            'header': {'title': 'Last vote by %s!' % voter},
            'sections': [{
                'widgets': [{
                    'textParagraph': {'text': '%d votes!' % vote_count}
                }, {
                    'buttons': [{
                        'textButton': {
                            'text': '+1',
                            'onClick': {
                                'action': {
                                    'actionMethodName': 'upvote',
                                    'parameters': PARAMETERS,
                                }
                            }
                        }
                    }, {
                        'textButton': {
                            'text': '-1',
                            'onClick': {
                                'action': {
                                    'actionMethodName': 'downvote',
                                    'parameters': PARAMETERS,
                                }
                            }
                        }
                    }, {
                        'textButton': {
                            'text': 'NEW',
                            'onClick': {
                                'action': {
                                    'actionMethodName': 'newvote',
                                }
                            }
                        }
                    }]
                }]
            }]
        }]
    }

Finishing touches

The last thing App Engine needs is an app.yaml configuration file:
runtime: python27
api_version: 1
threadsafe: true

handlers:
- url: /.*
  script: bot.app
If you've deployed apps to GAE before, you know you need to create a project in the Google Cloud Developers Console. You also need to have a project for bots, however you can use the same project for both your use of the Hangouts Chat bot framework (link only works for G Suite customers) as well as hosting your App Engine-based bot.

Once you've deployed your bot to GAE, go to the Hangouts Chat API configuration tab, and add the HTTP endpoint for your App Engine-based bot to the Conenctions Settings section:

As you can see, there are several options here for where Hangouts Chat can post messages destined for bots: standard HTTPS bots like our App Engine example, Google Apps Script (a customized JavaScript-in-the-cloud platform with built-in G Suite integration [intro video]), or Google Cloud Pub/Sub. Pub/Sub is the message queue proxy for when your bot is hosted on-premise behind a firewall, requiring you to register a pull subscription to retrieve bot messages from Hangouts Chat.

Once you've published your bot, add the bot to a room or @mention it in a DM. Send it a message, and it returns an interactive vote card like what you see below. Cast some votes or create a new vote to test drive your new bot.

Conclusion

Congrats for creating your first Python bot! Below is the entire bot.py file for your convenience. (At this time, Python App Engine standard only supports Python 2, so if you want to run Python 3 instead, use the Python App Engine flexible environment.) Also don't forget the app.yaml configuration file above.
import json
import webapp2

def create_message(voter, vote_count=0, should_update=False):
    PARAMETERS = [{'key': 'count', 'value': str(vote_count)}]
    return {
        'actionResponse': {
            'type': 'UPDATE_MESSAGE' if should_update else 'NEW_MESSAGE'
        },
        'cards': [{
            'header': {'title': 'Last vote by %s!' % voter},
            'sections': [{
                'widgets': [{
                    'textParagraph': {'text': '%d votes!' % vote_count}
                }, {
                    'buttons': [{
                        'textButton': {
                            'text': '+1',
                            'onClick': {
                                'action': {
                                    'actionMethodName': 'upvote',
                                    'parameters': PARAMETERS,
                                }
                            }
                        }
                    }, {
                        'textButton': {
                            'text': '-1',
                            'onClick': {
                                'action': {
                                    'actionMethodName': 'downvote',
                                    'parameters': PARAMETERS,
                                }
                            }
                        }
                    }, {
                        'textButton': {
                            'text': 'NEW',
                            'onClick': {
                                'action': {
                                    'actionMethodName': 'newvote',
                                }
                            }
                        }
                    }]
                }]
            }]
        }]
    }

class VoteBot(webapp2.RequestHandler):
    def post(self):
        event = json.loads(self.request.body)
        user = event['user']['displayName']
        if event['type'] == 'CARD_CLICKED':
            method = event['action']['actionMethodName']
            if method == 'newvote':
                body = create_message(user)
            else:
                delta = 1 if method == 'upvote' else -1
                vote_count = int(event['action']['parameters'][0]['value']) + delta
                body = create_message(user, vote_count, True)
        elif event['type'] == 'MESSAGE':
            body = create_message(user)
        else: # no response for ADDED_TO_SPACE or REMOVED_FROM_SPACE
            return

        self.response.headers['Content-Type'] = 'application/json'
        self.response.out.write(json.dumps(body))

app = webapp2.WSGIApplication([
    ('/', VoteBot),
], debug=True)
Yep, the entire bot is made up of just these 2 files. While porting to Flask is fairly straightforward and Flask apps are supported by App Engine, Flask itself doesn't come with App Engine (quickstart here), so you'll need to upload all of Flask (in addition to those 2 files) to host a Flask version of your bot on GAE.

Both files are also available from this app's GitHub repo which you can fork. I'm happy to entertain PRs for any bugs you find or ways we can simplify this code even more. Below are some additional resources for learning about Hangouts Chat bots and GAE:
Python's a great language to implement bots with because not only can you create something quickly, but choose any platform to host it on, Google App Engine, Amazon EC2/Google Compute Engine, or any cloud that runs Python apps.

Epilogue: code challenge

While usable, this vote bot can be significantly improved. Once you get the basic bot working, I recommend the following enhancements as exercises for the reader:
  1. Support vote topics: users starting new votes must state topic in bot message; use as card header
  2. Add images (like the Node.js version of our vote bot in the docs hosted on Google Cloud Functions)
  3. Track users who have voted (you decide on implementation)
  4. Don't let the vote count to go below zero
  5. Allow downvotes only from users who have at least one upvote
  6. Port your working bot from webapp2 to Flask

Friday, April 6, 2012

Integrating Google APIs and Technologies

In 1997, long before my tenure at Google, I became a member of the Python community in helping to create Yahoo!Mail, one of the most popular web-based email systems in the world. There were only two Python books on the market back then, and neither addressed my developer’s need to learn Python quickly and competently, so I had to resort to the online docs. This absence, and consequently my development of class materials for a Python course, inspired me to write Prentice Hall’s bestselling Core Python Programming over a decade ago. Since then, I’ve used Python to work on all kinds of interesting applications, from web-based e-mail to geolocalized product search engines, social media games, antispam/antivirus e-mail appliances, and most interestingly, software for doctors to help them analyze and assess patients with spinal fractures. (Ask me about osteoporosis!)

Today at Google, my work involves advocating our tools and APIs to the global developer community. Now that I've been part of the Google family for the past 2.5 years, I thought it would be fun to integrate some of our technologies into the book. With the just-published 3rd edition, readers will find revised but also brand new material they can use to build real applications with. Some of the Google technologies I've integrated into Core Python Applications Programming include accessing your Gmail, parsing Google News XML feeds, and a complete chapter on cloud computing with Google App Engine. It’s also the first published book to feature code that utilizes the Google+ API. While the book contains a longer example using that API, I want to show you how easy it is to connect to Google+ using Python right now!

The bulk of the work in connecting to Google+ (and other Google APIs) is done by my fellow colleagues who maintain the Google APIs Client Library for Python, easily downloaded with pip or easy_install as "google-api-python-client." With this library, the most difficult step to connect with your API of choice has basically been reduced to a single line... see the fourth line of this short Python 2.x example:

# plus.py (by Wesley Chun under CC-SA3.0 license)
from apiclient import discovery

API_KEY = YOUR_KEY_FROM_CONSOLE_API_ACCESS_PAGE
service = discovery.build("plus", "v1", developerKey=API_KEY)
feed = service.activities().search(query='android').execute()
for record in feed['items']:
post = ' '.join(record['title'].strip().split())
if post:
print '\nFrom:', record['actor']['displayName']
print 'Post:', post
print 'Date:', record['published']

In that one line of code (italicized above), we use the Google APIs Client Library's apiclient.discovery.build() method, passing in: a) the desired API ("plus" for Google+), b) the version (currently "v1"), and c) the API key you obtained from your project's development console in the "Simple API Access" section. This key gives your project access to APIs that do not need to access user data. Once we have a handle to the service, we can execute generic queries on the available data stream.

In this code snippet, we're simply querying for the latest (public) Google+ posts that are related to Android and displaying them on the command-line (code can be easily repurposed into any mobile or web application). Naturally, you need to go through the OAuth flow if you do want access to authenticated data. Give it a try!

If you like the code, dig into Core Python Applications Programming for a longer, more detailed example. Both scripts can be downloaded at the website (the code is part of Chapter 15), and you can get involved in the conversation on the Google+ page. I'm open to all feedback, suggestions, and fixes. You can find me at +wescpy or @wescpy. Looking forward to meeting you at an upcoming Google or Python event or in one of my public courses!