Showing location response in SUSI.AI bots

SUSI.AI has a capability to tell the basic information about a location, it is asked for. Along with the basic information about that place, it shows a map (i.e. open street map) pointing to that location. The task at hand is to inculcate this “location” feature to the SUSI.AI messenger bots. The SUSI Tweetbot and SUSI Fbbot are used as examples in this blog.

Let’s first check on what response do we get, when a person asks a query like “where is london” to the SUSI API. Along with the basic information about that location, the result as shown below has the type of reply (i.e. map), latitude, longitude and a link to the open street map.

"actions": [
      {
        "type": "answer",
        "language": "en",
        "expression": "Ludhiana is a city and a municipal corporation in Ludhiana district in the Indian state of Punjab, and is the largest city north of Delhi."
      },
      {
        "type": "anchor",
        "link": "https://www.openstreetmap.org/#map=13/30.912040570244187/75.85379021980509",
        "text": "Here is a map",
        "language": "en"
      },
      {
        "type": "map",
        "latitude": "30.912040570244187",
        "longitude": "75.85379021980509",
        "zoom": "13",
        "language": "en"
      }
    ]

The response for a location type query has these 3 main parts:

  1. Clickable static map image.
  2. A basic information of the place asked about.
  3. The link i.e. when the static map image is clicked it should redirect to the corresponding map location.

Let’s try to make up with the 1st part of the response i.e. Static map image.

The map quest API is used to result in a static map image of the location. We need an API key to access the map quest API, which can be requested from their developer site.

Along with that we need the latitude and longitude of the location at hand.

The SUSI API’s response helps us to get the latitude value:

// if body represents the response object 
var lat = body.answers[0].actions[2].latitude;

And the longitude value:

var lon = body.answers[0].actions[2].longitude;

Using the three values that are API key, latitude and longitude, the static image is rendered by this link:

var static_image_url = "https://open.mapquestapi.com/staticmap/v4/getmap?key=API_KEY&size=600,400&zoom=13&center="+lat+","+lon;

The second part is, basic information about the place asked, can be fetched from:

// if body is the JSON response object from SUSI API
var mapMessage = body.answers[0].actions[0].expression;

The link to the map location can be easily fetched from the SUSI API’s response:

var link = body.answers[0].actions[1].link;

As all the three parts are ready, let’s look on how to render them on the SUSI.AI bot’s screen.

Facebook:

Sending a generic template message object:

message = {
        "type":"template",
        "payload":{
                    "template_type":"generic",
                    "elements":[{
                        "title": mapMessage,
                       "image_url": static_image_url,
                       "Item_url": link
                    }]
        }
};

sendTextMessage(sender, message, 1);

Twitter:

The Twitter API does not need a static image of the map to be rendered. It does that work for us. We just need to send an event to the Twitter API with the message data object constituting of the map message, the latitude and longitude values:

"message_data": {
            "text": mapMessage,
            "attachment": {
                "type": "location",
                "location": {
                    "type": "shared_coordinate",
                    "shared_coordinate": {
                        "coordinates": {
                            "type": "Point",
                            "coordinates": [lon, lat]
                        }
                    }
                }
            }
}

Resources:

  1. Speed up customer service with quick replies and welcome messages by Ian Cairns from Twitter blog.
  2. Drive discovery of bots and other customer experiences in direct messages by By Travis Lull from Twitter blog.
  3. By Seth Rosenberg from Facebook developers blogLink Ads to Messenger, Enhanced Mobile Websites, Payments and More.
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Showing sample queries in SUSI.AI Bots

We need to give the user a good start to their chat with SUSI.AI. Engaging the users with some good skills at the start of the conversation, can leave a good impression about SUSI.AI. In SUSI messenger bots, we show up with some sample queries to try, during the conversation with SUSI.AI. In this blog, SUSI_Tweetbot and SUSI_FBbot are used as examples.

These queries are shown as quick replies i.e. the user can click on any of these sample queries and get an answer from SUSI.AI.  

Facebook:

When the user clicks on the “Start chatting” button, we send a descriptive message on what can the user ask to SUSI.AI .

Code snippet used for this step is:

var queryUrl = 'http://api.susi.ai/susi/chat.json?q='+'Start+chatting';
var startMessage = '';
// Wait until done and reply
request({
        url: queryUrl,
        json: true
}, function (error, response, body) {
if (!error && response.statusCode === 200) {
        startMessage = body.answers[0].actions[0].expression;
    }
else{
    startMessage = errMessage;
    }
sendTextMessage(sender, startMessage, 0);

Just a text message is not much engaging. To further enhance the experience of the user, we show some quick reply options to the user. We have finalized some skills to show to the user:

Due to the character limit for the text shown on buttons, we try to show short queries as shown in the above picture. This way the user gets an idea about what type of queries can be asked.

Generic template, help us achieve this feature in SUSI_FBbot.

The code snippet used:

var messageT = {
               "type": "template",
               "payload": {
                "template_type": "generic",
                "elements": [{
                                    "title": 'You can try the following:',
                                    "buttons": [{                                               
                                               "type":"postback",
                                               "title":"What is FOSSASIA?",                                  
                                               "payload":"What is FOSSASIA?"            
                                            }]
                            }]
                }
            };
sendTextMessage(sender, messageT, 1);

As seen in the code above, each button has a corresponding postback text. So that whenever that button is clicked the postback text is sent to our chat automatically:

This postback text acts as a query to SUSI API which fetches the response from the server and shows it back to the user.

Twitter:

As SUSI.AI bots must be generic among all the messenger platforms available , we will inculcate the same skills available in SUSI_FBbot to SUSI_Tweetbot. The quick reply feature provided by Twitter devs help us to accomplish this task at hand.

As in SUSI_FBbot a descriptive message is shown to the users first and then some quick reply options following it.

Message_create event helps in adding quick replies:

var msg = {
               "event": {
               "type": "message_create",
               "message_create": {
                   "target": {
                       "recipient_id": senderId
                    },
                    "message_data": {
                        "text": "You can try the following:",
                        "quick_reply": {
                            "type": "options",
                            "options": [{
                                "label": "What is FOSSASIA?",
                                "metadata": "external_id_4"
                            }]
                        }
                    }
                }
           }
    };
T.post('direct_messages/events/new', msg, sent);

One thing to keep in mind while coding is to send the quick reply message after the initial descriptive message i.e. the code used to send quick replies should be written inside the function, which sends the descriptive message first and aafter that step is complete it runs the code for quick replies. If we accidentally write quick reply code outside that function, it’s highly likely to find bugs in the replies by SUSI.AI.

Resources

  1. Speed up customer service with quick replies and welcome messages by Ian Cairns from Twitter blog.
  2. Link Ads to Messenger, Enhanced Mobile Websites, Payments and More by Seth Rosenberg from Facebook developers blog
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Making SUSI.AI reach more users through messenger bots

SUSI.AI learns from the queries asked to it by the users. More are the number of queries asked, the better is the learning by SUSI.AI. More are the number of users involved with SUSI.AI, better is the amount of content available to SUSI to learn from. Now, the challenge in front of us is to indulge more users with SUSI.AI. In this blog post, SUSI Tweetbot and SUSI FBbot are used as examples to show how we increase our user base through messenger bots.

Twitter:

Twitter has a 328 million user base according to this article’s data. Integration of SUSI.AI to just Twitter makes it available to around 300 million users. Even if some percentage of these users start using SUSI.AI, increase in the user base of SUSI.AI could be exponential. Increasing the user base is advantageous as it provides with more training data for SUSI.AI to learn from.

Sharing by public tweet:

Integrating to it is just the first step towards increasing SUSI.AI’s user base. Next step is to reach the users and indulge them into chatting with SUSI.AI.

Suppose a user asked something to SUSI.AI and really liked the reply from it. He/she wants to share it with his/her followers. This can prove to be a golden opportunity for us, to increase the reach of SUSI.AI. This way we can indulge their friends to try SUSI.AI and have an amazing time with it.

It becomes clear that sharing messages is an indispensable feature and can help us a lot. Twitter doesn’t provide sharing with friends through direct messages but with a feature much better than it. We can share that message as a public tweet and cover more users including the followers of the user.

 

To show this button we use Call to action support by twitter:

"message_data": {
          "text": txt,
          "ctas": [{
                      "type": "web_url",
                      "label": "Share with your followers",
                      "url": ""
          }]
}

The url key in the above code must have a value that redirects to a U.I. that allows to publicly tweet this reply by SUSI.AI.

Using this “https://twitter.com/intent/tweet?text=” as the url value shows a new page with an empty tweet message, as the text query in the url has no value. We set the text field with a value such that we end up like this:

and after tweeting it:

Sending a direct message link with the tweet:

Twitter provides with a lot of features when sending direct messages. Shifting a user from tweets to direct messages is beneficial in a way that we can efficiently tell the user about the capabilities of SUSI.AI and show important links to him/her like of its repository, web chat client etc.

When a user tweets to the SUSI.AI page with a query, we reply with a tweet back to the user. Along with that, we provide a link to privately message SUSI.AI account if the user wants to.

This way if user ends up visiting SUSI.AI in a chat window:

To achieve this in SUSI Tweetbot, Twitter provides with a direct message url. This url – https://twitter.com/messages/compose?recipient_id= redirects us to the chat window of the account having that recipient id, passed as a query string. In our case the url turns out to be – https://twitter.com/messages/compose?recipient_id=871446601000202244 as “871446601000202244” is the recipient id of @SusiAI1 account on twitter.

If we send this url as a text in our “tweet back” to the user, Twitter beautifully shows it as a clickable button with the label as “send a private message” as shown above.

Hence we call the tweet function like this:

tweetIt('@' + from + ' ' + message + date +"\nhttps://twitter.com/messages/compose?recipient_id=871446601000202244");

Facebook:

As we all know Facebook is the giant of social networking sites. Integrating SUSI.AI to Facebook is beneficial for us.

Unlike Twitter, in Facebook we can share messages with other friends through direct messaging to them. The last topic of this blog post walks you through on adding sharing feature in SUSI FBbot:

We also take advantage from the SUSI FBbot to make SUSI.AI better. We can direct the users using SUSI messenger bots to SUSI.AI repository and show them all the required information on how to contribute to the project.

The best way to do this is by showing a “How to contribute” button when the user clicks on “Get started” in the messenger bot.

This blog post will help you showing buttons along with the replies (by SUSI.AI).

When the user clicks this button, we send two messages back to the user as shown:

This way through bots, we have somehow got the user to visit SUSI.AI repository and contribute to it or indulge him/her in the discussion, through our Gitter channel on what can be the next steps in improving SUSI.AI.

Resources:

  1. Link Ads to Messenger, Enhanced Mobile Websites, Payments and More by Seth Rosenberg from Facebook developers blog.
  2. Drive discovery of bots and other customer experiences in direct messages by  Travis Lull from Twitter blog.
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Advanced functionality in SUSI FBbot

SUSI AI is integrated to Facebook (blog). During the initial phase, SUSI FBbot had basic UI and functionalities like just “plain text” replies. Facebook provides many more features like replies enclosed in templates (blog link), sharing the replies by SUSI A.I. with friends, get started button or a persistent menu to show quick reply options to the user etc. All these features to enhance the user experience with SUSI AI chatbot.

This blog post walks you through on adding these functionalities to the SUSI FBbot:

Adding Get Started button

A Get Started button is added to the SUSI FBbot to give the user a brief introduction about SUSI AI and what the user can try next.

Clicking on the get started button , will send the message as “Get Started” to the SUSI FBbot:

The reply message, provides the user with options to visit SUSI A.I. repository or to just start chatting.

To have this button in our bot, we use this code snippet:

// Add a get started button to the messenger
request({
    url: 'https://graph.facebook.com/v2.6/me/messenger_profile',
    qs: {access_token:token},
    method: 'POST',
    json: { 
      "get_started":{
        "payload":"GET_STARTED_PAYLOAD"
      }
    }
}, function(error, response, body) {
    // handle errors and response here
})

When a user clicks this button, a postback is sent to the webhook of SUSI FBbot with payload as “GET_STARTED_PAYLOAD”. When we receive such postback, we reply with a message as shown above using generic template.

Adding a persistent menu to the bot

If not at the start, while chatting with SUSI AI for sometime, it is quite possible that the user becomes curious to visit the repository of SUSI A.I. . So we need a quick access to the “Visit repository” button all the time. Persistent menu, helps us with this feature:

This way it is accessible at each point of time. Some other buttons can also be added to the menu like “Latest News” as shown in the image above.

To have a persistent menu for the SUSI FBbot, the following code snippet is used:

request({
        url: 'https://graph.facebook.com/v2.6/me/messenger_profile',
        qs: {access_token:token},
        method: 'POST',
        json: {
                "persistent_menu":[{
                    "locale":"default", 
                        "composer_input_disabled":false,
                        "call_to_actions":[{
                            "type":"web_url",
                            "title":"Visit Repository",
                            "url":"https://github.com/fossasia/susi_server",
                            "webview_height_ratio":"full"
                        }]
                 }]
            }
    }, function(error, response, body) {
        // handle errors and response
    })

We can add more buttons to the menu. JSON object having the required properties of that button can be appended to the key “call_to_actions” to do so.

Adding a messenger code to join SUSI FBbot

To enable Facebook users to chat with SUSI AI by scanning a code through messenger. This feature is added to the bot by making the following POST request:

request({
        url: 'https://graph.facebook.com/v2.6/me/messenger_codes',
        qs: {access_token:token},
        method: 'POST',
        json: {
                type: "standard",
                image_size: 1000
        }
    }, function(error, response, body) {
        // handle errors and response.
});

Adding message sharing feature

To increase the reach of SUSI A.I. to more users on Facebook, message sharing proves to be a big boon. The reply by SUSI A.I. to users can be shared with their friends. Along with the message we can also send a promotional message(related to SUSI A.I.), to the people with which the message was shared.

This sharing can end up having more users trying SUSI A.I., leading to increase the user base of SUSI AI and its popularity.

We can allow sharing of just the message(i.e. the reply) or a promotional message with it. In case of just the reply:

Clicking the share button, will share just the reply with another person. To add capabilities of sharing the reply along with one more message(prompting to try SUSI A.I.), some changes to the code are done:

We need to set the buttons property in generic template like:

buttons : [
            {
                "type":"element_share",
                    "share_contents": { 
                      "attachment": {
                        "type": "template",
                        "payload": {
                          "template_type": "generic",
                          "elements": [
                            {
                              "title": "I had an amazing chat with SUSI.",
                              "buttons": [
                                {
                                  "type": "web_url",
                                  "url": "https://m.me/asksusisu", 
                                  "title": "Chat with SUSI AI"
                                }
                              ]
                            }
                          ]
                        }
                      }
                   }
            } 
       ];

This way when a user shares the message with other, an extra message is sent with the original message, tempting the user to try a chat with SUSI A.I.:

Resources:

  1. By Seth Rosenberg from Facebook developers blogLink Ads to Messenger, Enhanced Mobile Websites, Payments and More.
  2. By Slobodan Stojanović from smashing magazineDevelop a chat bot with node js.
Continue Reading

Using Templates in SUSI FBbot

The SUSI AI Fbbot previously showed rss and table type replies as plain text to the user. To enhance the user experience, Facebook provides with templates which can be used in it’s messenger. Using those, we show rss and table type replies wrapped up in a better U.I. creating a better user experience.

The 4 basic template structures that can be used for this task are:

  1. Button template
  2. Generic template
  3. List template
  4. Receipt template

List template is used in SUSI A.I. Fbbot because rss reply and table type reply both are lists of data.
The basic syntax for list template with reference to Fb official docs is:

"message": {
    "attachment": {
        "type": "template",
        "payload": {
            "template_type": "list",
            "top_element_style": "compact",
            "elements": [
                {
                    "title": "Classic White T-Shirt",
                    "subtitle": "100% Cotton, 200% Comfortable",
                    "default_action": {
                        "type": "web_url",
                        "url": "https://peterssendreceiveapp.ngrok.io/view?item=100"
                    },
                    "buttons": [
                        {
                            "title": "Buy",
                            "type": "web_url",
                            "url": "https://peterssendreceiveapp.ngrok.io/shop?item=100"                     
                        }
                    ]                
                }
            ]
        }
    }
}

This code shows a reply to the user like this:

If we want to show a “View more” button at the end of the list, we can add a “buttons” key and an array as its value which will have information regarding all the buttons we want to show.

The code below will show a “View more” button at the end of the list:

"elements": [
            {
                // all the elements, like shirt in the above case               
            }
       ],
       "buttons": [
            {
                "title": "View More",
                "type": "postback",
                "payload": "payload"                        
               }
       ]

Let’s learn how to incorporate these features to rss results in SUSI Fbbot:

When sending a reply using list template, “elements” key must have an array type value which will be constituted of list items. Therefore, we need to push all the rss results into that array and set it as the value of the “elements” key.

Let’s develop the code part:

Fetch the JSON object from SUSI API url with query as “why” i.e. http://api.susi.ai/susi/chat.json?q=why. Let body be a variable which stores the returned JSON object.

  • The below code fills up an array (namely elementsVal) with all the rss results:
var elementsVal = [];
var metaCnt = body.answers[0].metadata.count;
for(var i=0;i<((metaCnt>4)?4:metaCnt);i++){
    elementsVal.push(
        {
            "title": body.answers[0].data[i].title,
            "subtitle": body.answers[0].data[i].link
        }
    );
}
  • Setting the elementsVal array as the value of the “elements” key:
var message = {
    "type": "template",
    "payload": 
    {
        "template_type": "list",
        "top_element_style": "compact",
        "elements": elementsVal
    }
};
  • Sending this message as a reply to the user:
sendTextMessage(sender, message);

Same procedure can be used to render table type replies in the bot using the list template.

Generic template provided by Facebook can also used to render the web and table type replies. This template helps in showing the results in square boxes, which can be changed using left or right arrows.

Resources:

  1. By Mikhail Larionov from Facebook blogsList templates and check box plugin
  2. By Slobodan Stojanović from smashing magazineDevelop a chat bot with node js.
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Integration of SUSI AI to Facebook

It’s easy to create your own SUSI AI Facebook messenger bot. You can read the official documentation by Facebook to get started.

Messenger bots use a web server to send and receive messages. You also need to have the bot be authenticated to speak with the web server and be approved by Facebook before getting public.

If any problems faced, visit the susi_fbbot repository which hosts the code for SUSI Facebook Messenger bot.

We will be using Node js technology to develop the FB bot. First, let’s see on how to request an answer from the SUSI API.

To call Susi API and fetch an answer from it for a query (‘hi’ in this case). Let’s first visit http://api.asksusi.com/susi/chat.json?q=hi from the browser. We will get a JSON object as follows:

The answer can be found as the value of the key named expression. In this case, it is “Hallo!”.

To fetch the answer through coding, we can use this code snippet in Node js:

// including request module
var request = require(‘request’);

// setting options to make a successful call to Susi API.
var options = {
            method: 'GET',
            url: 'http://api.asksusi.com/susi/chat.json',
            qs: 
            {
                timezoneOffset: '-330',
                q: 'hi'
            }
        };

// A request to the Susi bot
request(options, function (error, response, body) {
    if (error)
        throw new Error(error);
    // answer fetched from susi
    ans = (JSON.parse(body)).answers[0].actions[0].expression;
}

The properties required for the call are set up through a JSON object (i.e. options). Pass the options object to our request function as its 1st parameter. The response from the API will be stored in ‘body’ variable. We need to parse this body, to be able to access the properties of that body object. Hence, fetching the answer from Susi API.

Now let’s dive into the code of receiving and messaging back to the user on Facebook:

  • A generic function to send a message to the user.
// the first argument is the sender id and the second is the text to send.
function sendTextMessage(sender, text) {
    var messageData = { text:text };
    
    // making a post request to facebook graph API to send message.
    request({
        url: 'https://graph.facebook.com/v2.6/me/messages',
        qs: {access_token:token},
        method: 'POST',
        json: {
            recipient: {id:sender},
            message: messageData,
        }
    }, function(error, response, body) {
        if (error) {
            console.log('Error sending messages: ', error);
        } else if (response.body.error) {
            console.log('Error: ', response.body.error);
        }
    });
}
  • According to step 9, in the below instructions we need to include this code snippet too:
// for facebook verification
app.get('/webhook/', function (req, res) {
    if (req.query['hub.verify_token'] === 'my_voice_is_my_password_verify_me') {
        res.send(req.query['hub.challenge']);
    }
    res.send('Error, wrong token');
});
  • When user messages to our bot, we need to extract the text of the message from the request body. Then we need to extract the reply from the SUSI API and send it back to the user.
// when a message from a user is received.
app.post('/webhook/', function (req, res) {
    var messaging_events = req.body.entry[0].messaging
    for (var i = 0; i < messaging_events.length; i++) {
        // fetching the current event
        var event = req.body.entry[0].messaging[i];

        // fetching the sender id
        var sender = event.sender.id;
        
        // if the event is a message event
        if (event.message && event.message.text) {
            var text = event.message.text;

            // Construct the query for susi
            var queryUrl = 'http://api.susi.ai/susi/chat.json?q='+encodeURI(text);
            var message = '';

            // Wait until done then reply
            request({
                url: queryUrl,
                json: true
            }, function (error, response, body) {
                if (!error && response.statusCode === 200) {
              // fetch the answer from the response body and save it in message variable.
                    // send the reply
                    sendTextMessage(sender, message);
                } 
                
            // if, due some reasons the answer couldn’t be fetched
            else {
                    message = 'Oops, Looks like Susi is taking a break, She will be back soon';
                    sendTextMessage(sender, message);
                }
            });
        }
        if (event.postback) {
            var text = JSON.stringify(event.postback);
            sendTextMessage(sender, "Postback received: "+text.substring(0, 200), token);
            continue;
        }
    }
    res.sendStatus(200)
})

Upload the code developed to a repository.

Let’s follow the below steps, to achieve a working fb messenger bot:

  1. Create a Facebook page here.

    Creating a FB Page
    New FB Page

    1. Create a new Heroku app here.

    New Heroku App

    1. Connect the Heroku app to the repository hosting our code.

    Connect to Github

    4. Deploy on the development branch. If you intend to contribute, it is recommended to Enable Automatic Deploys.

    Branch Deployment

    Successful Deployment

    5. Create or configure a Facebook App or Page here.

    New FB App

    6. Get started with Messenger tab in the created app.


    7.
    In the Page Access Token select the FB page that you created and generate the token and save it somewhere for future use.

    Token Generation

    8. Now, go to the Heroku app, select the settings tab and add the environment variable as shown, where the key is FB_PAGE_ACCESS_TOKEN and value is the token generated in the previous step.

    9. Create a web hook on the facebook app dashboard. The Callback URL should be https://<your_app_name>.herokuapp.com/webhook/ and rest should be as shown in the image below.

    App Complete

    10. Go to Terminal and type in this command to trigger the Facebook app to send messages. Remember to use the token you requested earlier.
    “`
    curl -X POST “https://graph.facebook.com/v2.6/me/subscribed_apps?access_token=<PAGE_ACCESS_TOKEN>”
    “`

    11. Go to the Facebook page created and locate ‘Message Now’ or go to https://m.me/PAGE_USERNAME

    12. Enjoy chatting with Susi.

    Resources

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