There’s a party at Alexa’s place

February 6, 2016
By

(This article was first published on Blag's bag of rants, and kindly contributed to R-bloggers)

This post was originally posted on There’s a party at Alexa’s place.

This is my first blog of the year…so I want it to be something really nice and huge -:) You know how much I love the R Programming Language…but I also love other technologies as well…so taking a bunch of them and hooking them up together is what really brings me joy.

Now…you may be wondering about the blog title…”There’s a party at Alexa’s place”…well…I wanted it to describe the blog in a funny way…so let’s see what we’re going to build -;)
Got any idea? Basically…we’re going to use Amazon Alexa as our UI…when we ask a command…we’re going to call a NodeJS Server on Heroku (Which BTW has a PhantomJS client installed)…this NodeJS will call an R Server on Heroku (Using the Rook Server)…and this R Server is going to call HANA Cloud Platform to get some Flights information and generate nice graphics that are going to be returned to the NodeJS Server which is going to call our web browser to display the graphic generated by the R Server…of course…by using PhantomJS were going to read the generated web page on the browser and this will be sent back to Amazon Alexa so she can read out the response…interesting enough for you? I hope -:) I took me more than two weeks to get all this up and running…so you better like it -:P
So…let’s go in some simple steps…
GET A HANA CLOUD PLATFORM ACCOUNT
You should have one already…if not…just go here to create one…
Then…we need to download the HANA Cloud Platform SDK extract it and modify the file tools/neo.sh on line 57…
Instead of this…
javaExe=”$JAVA_HOME/bin/$javaCommand”
Use this…
javaExe=”$JAVA_HOME”
Why? Well…it will make sense later on…or maybe it will make sense now  If you have the SAP HANA Client installed…otherwise download it from here take a note that will need to copy the ngdbc.jar file…
GETTING THE DATA THAT WE’RE GOING TO USE
As always…in almost all my blogs…we’re going to use tables from the Flight model…which of course…doesn’t exist on HANA Cloud Platform…
The easiest way (at least for me) was to access an R/3 server…and simply download the tables as XLS files…convert them into CSV files and upload them into HCP…
And BTW…for some weird reason my R/3 didn’t have American Airlines listen on the SCARR table…so I just added it -;)
Now…if you don’t have access to an R/3 system…then you can download the tables in CSV format from here
CREATE THE R SERVER ON HEROKU
If you don’t have the Heroku Tool Belt installed…then go and grab it…
Steps to install R on Heroku with Graphic Capabilities
mkdkir myproject && cd myproject
mkdir bin
echo “puts ‘OK’ > config.ru
echo “source ‘http://rubygems.org’n gem ‘rack’” > Gemfile
#Open your project folder and modify the Gemfile to replace the “n” with an actual break line…
bundle install
git init . && git add . && git commit –m “Init”
heroku apps:create myproject –stack=cedar
git push heroku master
#Copy and paste the content of my installR.sh into the /bin folder of your project
git add . && git commit –am “message” && git push heroku master
heroku ps:scale web=0

installR.sh
#!/bin/bash

function download() {
if [ ! -f "$2" ]; then
echo Downloading $2...
curl $1 -o $2
else
echo Got $2...
fi
}

set -e

r_version="${1:-3.2.3}"
r_version_major=${r_version:0:1}

if [ -z "$r_version" ]; then
echo "USAGE: $0 VERSION"
exit 1
fi

basedir="$( cd -P "$( dirname "$0" )" && pwd )"

# create output directory
vendordir=/app/vendor
mkdir -p $vendordir

# R
download http://cran.r-project.org/src/base/R-$r_version_major/R-$r_version.tar.gz R-$r_version.tar.gz
tar xzf R-$r_version.tar.gz

# build R
echo ============================================================
echo Building R
echo ============================================================
cd $basedir/R-$r_version/

./configure --prefix=$vendordir/R --with-blas --with-lapack --enable-R-shlib --with-readline=no --with-x=yes
make

cd /app/bin
ln -s R-$r_version/bin/R

rm R-3.2.3.tar.gz
rm -rf erb gem irb rake rdoc ri ruby testrb
rm ruby.exe

cd /app/bin/R-$r_version

rm -rf src
rm Make*
rm -rf doc
rm -rf tests
rm README ChangeLog COPYING INSTALL SVN-REVISION VERSION

Now…we need to do a very important step -:) We need to install the totally awesome heroku-buildpack-multi from ddollar.

heroku buildpacks:set https://github.com/ddollar/heroku-buildpack-multi.git

After that…we need to create a couple of files…one called .buildpacks and the other Aptfile.

.buildpacks
https://github.com/ddollar/heroku-buildpack-apt
https://github.com/heroku/heroku-buildpack-ruby
Aptfile
gfortran
libatlas-base-dev
libatlas-dev
liblapack-dev

Now comes the interesting part…installing R -;)

Finally…installing R…
git add . && git commit –am “message” && git push heroku master
heroku ps:scale web=0
heroku run bash
cd bin/
./installR.sh

With this done…we will have all the missing libraries needed to compile R on the new Cedar Stack on Heroku and also…we will have a nicely installed R instance with Graphic capabilities…but of course…we’re not done yet…

Installing the R Libraries
#This will open R on Heroku…
R
#This will install the libraries with their corresponding dependencies
install.packages("Rook",dependencies=TRUE)
install.packages("Cairo",dependencies=TRUE)
install.packages("maps",dependencies=TRUE)
install.packages("forecast",dependencies=TRUE)
install.packages("plotrix",dependencies=TRUE)
install.packages("ggplot2",dependencies=TRUE)
install.packages("ggmap",dependencies=TRUE)
install.packages("rJava",dependencies=TRUE)
install.packages("RJDBC",dependencies=TRUE)
q()

All right…we’re almost there -;) The problem with Heroku is that is not writable…meaning that once you get disconnected…you will lost all your work -:(

So…we need to back it up and sent it somewhere else…I used my R Server on Amazon WebServices for this…

First…we need to compress the bin folder like this…

tar -cvzf bin.tar.gz bin

and then we need to save this file in our external server…

scp -i XXX.pem bin.tar.gz [email protected]:~/Blag/bin.tar.gz

and of course after that we need it on our project folder…so we need to send it from our external server to our project folder, where will simply would need to uncompressed it…

scp -i XXX.pem [email protected]:~/Blag/bin.tar.gz bin.tar.gz

Once this is done…we need to something real quick…

If you’re still inside the Heroku bash…simply run

which java

and take note of the location…

Now…we can close Heroku and keep going…copy the bin.tar.gz file into your project folder and extract it…then…create the following files…

config.ru
`/app/bin/R-3.2.3/bin/R –e “source(‘/app/demo.R’)”`
demo.R
library("Rook")
library("ggmap")
library("maptools")
library("maps")
library("Cairo")
library("RJDBC")

myPort <- as.numeric(Sys.getenv("PORT"))
#myPort <- 8000
myInterface <- "0.0.0.0"
status <- .Call(tools:::startHTTPD, myInterface, myPort)

newapp<-function(env){
req<-Rook::Request$new(env)
res<-Rook::Response$new()

pass<-system('./hcp.sh',intern=T)
jdbcDriver <- JDBC("com.sap.db.jdbc.Driver","ngdbc.jar", identifier.quote="`")
conn_server <- dbConnect(jdbcDriver, "jdbc:sap://localhost:30015", "DEV_6O3Q8EAM96G64Q8M0P5KLA1A3",pass[1])
airports_param<- dbGetQuery(conn_server, "SELECT ID FROM NEO_BLR8NOQVY6TG8KXKQJ003WVOJ.SAIRPORT")
sairport<-data.frame(IATA=airports_param$ID)
airports<-read.csv("airports.dat", header = FALSE)
colnames(airports)<-c("ID", "name", "city", "country", "IATA", "ICAO", "lat", "lon")
airports<-subset(airports, IATA %in% sairport$IATA)
keeps <- c("city","country","IATA","lat","lon")
airports<-airports[keeps]

if(req$params()$airports != '')
{
count_sairport<-nrow(airports)
mp <- NULL
mapWorld <- borders("world", colour="gray50")
mp <- ggplot() + mapWorld
CairoJPEG(filename = "R_Plot.jpg", width = 680, height = 680)
mp <- mp+ geom_point(aes(x=airports$lon, y=airports$lat) ,color="red", size=3)
show(mp)
dev.off()
}else if(req$params()$us_airports != '')
{
US_Airports<-airports[airports$country == "United States", ]
count_sairport<-nrow(US_Airports)
mp <- NULL
mapWorld <- borders("state", colour="gray50")
mp <- ggplot() + mapWorld
mp <- mp+geom_point(aes(x=US_Airports$lon, y=US_Airports$lat) ,color="red", size=3)+
geom_text(data=US_Airports, aes(US_Airports$lon, US_Airports$lat, label = US_Airports$city), size=6)
CairoJPEG(filename = "R_Plot.jpg", width = 680, height = 680)
show(mp)
dev.off()
}else if(req$params()$carriers != '')
{
US_Airports<-airports[airports$country == "United States", ]
US_Airports<-as.vector(t(US_Airports))
US_Airports<-paste(shQuote(US_Airports), collapse=", ")
#query<-paste("SELECT CARRID, DISTANCE FROM NEO_BLR8NOQVY6TG8KXKQJ003WVOJ.SPFLI WHERE AIRPFROM IN (",US_Airports,")")
query<-paste("SELECT SPFLI.CARRID,CARRNAME,DISTANCE FROM NEO_BLR8NOQVY6TG8KXKQJ003WVOJ.SPFLI
INNER JOIN NEO_BLR8NOQVY6TG8KXKQJ003WVOJ.SCARR ON SPFLI.CARRID = SCARR.CARRID
WHERE AIRPFROM IN (",US_Airports,")")
result<-dbGetQuery(conn_server,query)
result$DISTANCE<-sub(",\d+","",result$DISTANCE)
result$DISTANCE<-sub("\.","",result$DISTANCE)
carriers<-data.frame(CARRID=result$CARRID,CARRNAME=result$CARRNAME,
DISTANCE=as.numeric(result$DISTANCE),stringsAsFactors = FALSE)
carriers_sum<-aggregate(DISTANCE~CARRID + CARRNAME,data=carriers,FUN=sum)
cols<-c('CARRNAME','DISTANCE')
data <- apply( carriers_sum[ , cols ] , 1 , paste , collapse = " " )
count_sairport<-paste(shQuote(data), collapse=", ")
mp <- NULL
CairoJPEG(filename = "R_Plot.jpg", width = 680, height = 680)
mp<-ggplot(carriers_sum,aes(x=CARRID,y=DISTANCE,fill=CARRID))+
geom_bar(position="dodge",stat="identity")
show(mp)
dev.off()
}

size <- as.integer(system("stat --format %s R_Plot.jpg", intern=T))
to.read = file("R_Plot.jpg", "rb")
#x<-readBin(to.read, raw(),n=18674)
x<-readBin(to.read, raw(),n=size)
hex<-paste(x, collapse = "")
hex<-paste(hex,count_sairport,sep = "/")
close(to.read)

res$write(hex)
res$finish()
}

unlockBinding("httpdPort", environment(tools:::startDynamicHelp))
assign("httpdPort", myPort, environment(tools:::startDynamicHelp))

server = Rhttpd$new()
server$listenAddr <- myInterface
server$listenPort <- myPort
server$add(app = newapp, name = "summarize")

while(T) {
Sys.sleep(10000)
}

So…let’s take some time to understand what’s going on with this code…we’re going to create a Rook server…which will allow us to host webpages from R…then, we’re going to use our hcp.sh script to get the password for our HANA Cloud Platform bridge…so we can get an JDBC connection to the database…from there we want to get a list of all the airports and also read the airports from a file detailed later (this airports file contains the geolocation of the airports). With this…we want to filter out the airports from HANA with the airports from the flight…so we don’t have any extra data…now…we have three choices…airports, US airports or carriers…the first one will generate a map of the world with all the airports as little red dots…the second one will generate a map of the US with the airports as little red dots but also showing the name of the cities…the last one will generate a geometric histogram with the details of the flights distance according to their carriers…later on…we’re going to read the information of the generated graphic to create a hexadecimal string of the graphic along with some information that Alexa should spell out…easy as cake, huh?
Procfile
web: bundle exec rackup config.ru

We want this R Server to be able to access HANA Cloud Platform…so let’s do that before we keep going…

With the location of Java…apply this command…

heroku config:set JAVA_HOME=’/usr/bin/java’

Now…Copy the following files into your project folder…

“tools” folder from the HANA Cloud Platform SDK
ngdbc.jar from SAP HANA Client

Also…create this little script which is going to allow us to connect to HCP…

hcp.sh
#!/bin/bash -e

user=i830502
account=i830502trial
HCP_PASSWORD=Kiarita2018

json=$(tools/./neo.sh open-db-tunnel -i blaghanax -h hanatrial.ondemand.com -a 
       "$account" -u "$user" -p "$HCP_PASSWORD" --background --output json)
regex='.*"host":"([^"]*)".*"port":([^,]*),.*"instanceNumber":"([^"]*)".
        *"dbUser":"([^"]*)".*"dbUserPassword":"([^"]*)".*"sessionId":"([^"]*)".*'
[[ $json =~ $regex ]]
dbHost=${BASH_REMATCH[1]}
dbPort=${BASH_REMATCH[2]}
dbInstance=${BASH_REMATCH[3]}
dbUser=${BASH_REMATCH[4]}
dbPassword=${BASH_REMATCH[5]}
tunnelSessionId=${BASH_REMATCH[6]}

echo $dbPassword

Awesome…we’re almost there…please download this airports file and place it on your project folder…

Finally…with all files in place we can send everything back to heroku…so log into your Heroku tool belt and do the following…

Getting everything in place
git add .
git commit –am “message”
git push heroku master
heroku ps:scale web=1

R should be installed and ready to go -;) So we should move on and continue with our NodeJS server on Heroku…

Creating NodeJS on Heroku with PhantomJS

Create a folder called mynodeproject and inside create the following files…

package.json
{
"dependencies": {
"ws": "1.0.1",
"request": "2.67.0",
"express": "4.13.3",
"phantomjs-prebuilt": "2.1.3"
},
"engines": {
"node": "0.12.7"
}
}
Procfile
web: node index.js
index.js
var WebSocketServer = require("ws").Server
, http = require("http")
, express = require("express")
, request = require('request')
, fs = require('fs')
, app = express()
, arr = []
, msg = ""
, port = process.env.PORT || 5000
, childProcess = require('child_process')
, phantomjs = require('phantomjs-prebuilt')
, path = require('path')
, binPath = phantomjs.path;

app.use(express.static(__dirname + "/"))

var server = http.createServer(app)
server.listen(port)

var wss = new WebSocketServer({server: server})

var childArgs = [path.join(__dirname, 'phantom.js')]
var childStats = [path.join(__dirname, 'readphantom.js')]

app.get('/path', function (req, res) {
if(req.query.command == 'map'){
URL = "http://blagrookheroku.herokuapp.com/custom/summarize?airports=xyz&us_airports=&carriers=";
request(URL, function (error, response, body) {
if (!error) {
arr = body.split("/");
msg = "There are " + arr[1] + " airports around the world";
var bitmap = new Buffer(arr[0], 'hex');
var jpeg = new Buffer(bitmap,'base64');
fs.writeFileSync('Graph.jpg', jpeg);
res.redirect('/');
};
});
}else if(req.query.command == 'usmap'){
URL = "http://blagrookheroku.herokuapp.com/custom/summarize?airports=&us_airports=xyz&carriers=";
request(URL, function (error, response, body) {
if (!error) {
arr = body.split("/");
msg = "There are " + arr[1] + " airports in the US";
var bitmap = new Buffer(arr[0], 'hex');
var jpeg = new Buffer(bitmap,'base64');
fs.writeFileSync('Graph.jpg', jpeg);
res.redirect('/');
};
});
}else if(req.query.command == 'carriers'){
URL = "http://blagrookheroku.herokuapp.com/custom/summarize?airports=&us_airports=&carriers=xyz";
request(URL, function (error, response, body) {
if (!error) {
arr = body.split("/");
msg = "" + arr[1];
var bitmap = new Buffer(arr[0], 'hex');
var jpeg = new Buffer(bitmap,'base64');
fs.writeFileSync('Graph.jpg', jpeg);
res.redirect('/');
};
});
}else if(req.query.command == 'stat') {
childProcess.execFile(binPath, childArgs, function(err, stdout, stderr){
if(!err){
res.redirect('/');
};
});
}else if(req.query.command == 'readstat') {
childProcess.execFile(binPath, childStats, function(err, stdout, stderr){
if(!err){
res.write(stdout);
res.end();
};
});
}else if(req.query.command == 'bye'){
if(fs.existsSync('Graph.jpg')){
fs.unlink('Graph.jpg');
}
res.redirect('/');
}
});

wss.on("connection", function(ws) {
var id = setInterval(function() {

fs.readFile('Graph.jpg', function(err, data) {
if(!err){
ws.send(JSON.stringify("Graph.jpg/" + msg), function() { })
}else{
ws.send(JSON.stringify("Gandalf.jpg/No problem...I'm crunching your data..."), function() { })
}
});
}, 3000)

ws.on("close", function() {
clearInterval(id)
})
})

Let’s explain the code for a little bit and believe me…I’m far from being a NodeJS expert…this is really the first time I develop something this complex…and it took me a really long time and tons of research…so please try not to criticize me too much -:(
We’re going to create a express application that uses Web Sockets in order to refresh the browser in order to show the graphics generated by our R Server…it will also call PhantomJS to both create and read the generated web page so we can send it back to Alexa…
Here…we have six choices…map, usmap and carriers…the first three are going to call our R Server passing all parameters but leaving the ones that we don’t need empty…and just passing “xyz” as parameter…
When we got the response from R it’s going to be a long string separated by an “/”…which is going to be the hexadecimal string for the graphic along with the text intended for Alexa…Node will read the graphic…generated it and then refresh the browser in order to show it on the screen…
The stats option will call our PhantomJS script to simply read the page and create a new file with the Javascript part already executed…the readstat will read this information and extract the text that we need for Alexa…finally…bye will delete the graphic and the web socket will call the main graphic to be displayed on the screen.
Finally…the web socket is going to constantly check…every 3 seconds to see if there’s a graphic or not…and the display the related image…
index.html
<html>
<head>
<title>I'm a NodeJS Page!</title>
<div id="container" align="center"/>
<script>
var host = location.origin.replace(/^http/, 'ws')
var ws = new WebSocket(host);
ws.onmessage = function (event) {
var container = document.getElementById('container');
var data = JSON.parse(event.data);
data = data.split("/");
var url = data[0];
var msg = data[1];

container.innerHTML = '<img src="' + url + '"></br><p><b>' + msg + '</b></p>';
};
</script>
</head>
<body>
</body>
</html>

This one is going to be called by our express application and it will simply call the web socket to determine what it needs to display…it has some Javascript…that’s why we need PhantomJS to interact with it…

phantom.js
var page = require('webpage').create();
var fs = require('fs');
page.open('http://blagnodeheroku.herokuapp.com/', function () {
window.setTimeout(function () {
page.evaluate(function(){

});

fs.write('stats.html', page.content, 'w');
phantom.exit();
},4000);
});

Not the best and most describing name…but who cares -:P Anyway…this script will load the page…that is the express application…wait for 4 seconds for the Javascript to get generated and then create a web page called stats.html


readphantom.js
var page = require('webpage').create(),
address = "stats.html";

page.open(address, function (status) {
if (status == 'success') {
var results = page.evaluate(function() {
return document.querySelector('p').innerText.trim();
});
console.log(results);
phantom.exit();
}
});

This script will simply read the stats.html page and return the text that it’s located inside the “p” tag…dead simple…

SETTING UP ALEXA

Creating the Lambda function

Now…we need to setup Alexa…so we can control everything via voice commands -:)
First…we need to go to Amazon Lambda and log in if you have an account…otherwise…please create one…and make sure you’re on the West Virginia region…

In the list of functions…look for color…
Choose the NodeJS one…Python has been included as well…but wasn’t when I started to work on this blog -:)
Here, just click next….
I already create the function…but you shouldn’t have a problem…
Basic execution role is more than enough…
This will provide a pop up window…simply press the “Allow” button and then “Create function”…we will include the source code later on…but notice the ARN generated number…because we’re going to need it on the next step…
Creating the Skill
Go to http://developer.amazon.com and log in…then choose Apps & Services –> Alexa –> Alexa Skills Set
Choose Alexa Skills Kit and fill the blanks…
As soon as we hit next an application number will be generated on a new field called Application ID. Grab this number as we’re going to need it for our application code.
The Interaction Model section is very important as here we’re going to define the “Intent Schema” and “Sample Utterances”…the first will define the parameters that we’re going to send to Alexa and the second is how we are going to call our application.
Intent Schema
{
"intents": [
{
"intent": "GetFlightsIntent",
"slots": [
{
"name": "command",
"type": "LITERAL"
}
]
},
{
"intent": "HelpIntent",
"slots": []
}
]
}

Our variable is going to be called “command” and it’s going to be a LITERAL…other types are NUMBER, DATE, TIME and DURATION. The intent is the method that we’re going to call in our code…
Sample Utterances
GetFlightsIntent airports from {around the world|command}
GetFlightsIntent airports from {united states|command}
GetFlightsIntent flight distance from {carriers|command}
GetFlightsIntent {thank you|command}

The test section help us to say commands and see how Alexa responds…but we’re not going to do that here…we’re going to test it using a real Alexa device -;)

Forget about the Publishing Information section unless you really want to publish your application…
Create a folder call Flights…Alexa_Party…or whatever you fancy…then create a folder call src and copy this file in there…calling it AlexaSkills.js

We’re going to need to install only one library….”request”…

sudo npm install –prefix=~/Flights/src request

This will create a folder called “node_modules” with the package in our project folder…then create a file called “index.js” and copy and paste the following code…

index.js
var request = require("request")
, AlexaSkill = require('./AlexaSkill')
, APP_ID = 'amzn1.echo-sdk-ams.app.8c0bd993-723f-4ab2-80b5-84402a7a59ce';

var error = function (err, response, body) {
console.log('ERROR [%s]', err);
};

var getJsonFromFlights = function(command, callback){
var msg = "";
if(command == "thank you"){
request("http://blagnodeheroku.herokuapp.com/path/?command=bye", function (error, response, body) {
if (!error) {
console.log("Done");
};
});
setTimeout(function() {
callback("thank you");
},2000);
}else if (command == "around the world"){
request("http://blagnodeheroku.herokuapp.com/path/?command=bye", function (error, response, body) {
if (!error) {
request("http://blagnodeheroku.herokuapp.com/path/?command=map", function (error, response, body) {
if (!error) {
request("http://blagnodeheroku.herokuapp.com/path/?command=stat", function (error, response, body) {
if (!error) {
request("http://blagnodeheroku.herokuapp.com/path/?command=readstat", function (error, response, body) {
if (!error) {
msg = body;
};
});
};
});
};
});
}
});
setTimeout(function() {
callback(msg.trim());
},15000);
}else if (command == "united states"){
request("http://blagnodeheroku.herokuapp.com/path/?command=bye", function (error, response, body) {
if (!error) {
request("http://blagnodeheroku.herokuapp.com/path/?command=usmap", function (error, response, body) {
if (!error) {
request("http://blagnodeheroku.herokuapp.com/path/?command=stat", function (error, response, body) {
if (!error) {
request("http://blagnodeheroku.herokuapp.com/path/?command=readstat", function (error, response, body) {
if (!error) {
msg = body;
};
});
};
});
};
});
}
});
setTimeout(function() {
callback(msg.trim());
},15000);
}else if (command == "carriers"){
request("http://blagnodeheroku.herokuapp.com/path/?command=bye", function (error, response, body) {
if (!error) {
request("http://blagnodeheroku.herokuapp.com/path/?command=carriers", function (error, response, body) {
if (!error) {
request("http://blagnodeheroku.herokuapp.com/path/?command=stat", function (error, response, body) {
if (!error) {
request("http://blagnodeheroku.herokuapp.com/path/?command=readstat", function (error, response, body) {
if (!error) {
msg = body;
};
});
};
});
};
});
}
});
setTimeout(function() {
callback(msg.trim());
},15000);
}
};
var handleFlightsRequest = function(intent, session, response){
getJsonFromFlights(intent.slots.command.value, function(data){
if(data != "thank you"){
var text = data;
var reprompt = 'Please say a command?';
response.ask(text, reprompt);
}else{
response.tell("You're welcome");
}
});
};

var Flights = function(){
AlexaSkill.call(this, APP_ID);
};

Flights.prototype = Object.create(AlexaSkill.prototype);
Flights.prototype.constructor = Flights;

Flights.prototype.eventHandlers.onSessionStarted = function(sessionStartedRequest, session){
console.log("onSessionStarted requestId: " + sessionStartedRequest.requestId
+ ", sessionId: " + session.sessionId);
};

Flights.prototype.eventHandlers.onLaunch = function(launchRequest, session, response){
// This is when they launch the skill but don't specify what they want.
var output = 'Welcome to Flights. ' +
'Please, say a command.';

var reprompt = 'Please, say a command?';

response.ask(output, reprompt);

console.log("onLaunch requestId: " + launchRequest.requestId
+ ", sessionId: " + session.sessionId);
};

Flights.prototype.intentHandlers = {
GetFlightsIntent: function(intent, session, response){
handleFlightsRequest(intent, session, response);
},

HelpIntent: function(intent, session, response){
var speechOutput = 'Get the information for airports and flights. ' +
'Please say a command?';
response.ask(speechOutput);
}
};

exports.handler = function(event, context) {
var skill = new Flights();
skill.execute(event, context);
};

Time to explain what I was trying to do here -:P

The handleFlightsRequest method will manage the response that Alexa will spell out for us…and inside this method we can find getJsonFromFlights which will take the command defined in the our Intent Schema. This function will call our NodeJS server for the following commands…”thank you” will simply call the bye command….”around the world” will call the bye, map, stat and readstat commands…”united states” will call the bye, usmap, stat and readstat commands…finally carriers will call the bye, carriers, stat and readstat commands…

After 15 seconds (Yep…I know it’s too much but there are a lot of processes going on) Alexa will get the response message and simply speak it to us -;)

That’s pretty much it…now…I can show some images before we jump into the video…

Ok…enough…let’s watch this in real live action 😉

Greetings,

Blag.
Development Culture.

To leave a comment for the author, please follow the link and comment on their blog: Blag's bag of rants.

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