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For registering this skill in the Amazon’s Developer Portal the skill must run behind a HTTPS server or must be hosted on AWS lambda function for which you will require to have a Amazon Web Services Account.

There can be a work around for this, by generating a public HTTPS endpoint for localhost:8080 using the ngok client from https://ngrok.com/download and run,on Unix/Mac: Once logged into the Amazon’s Developer Portal click on Alexa and start creating a new skill.

On Windows, follow these installation instructions. The bot uses a My SQL database to store the information about the conference and uses the following python modules:1. flask-mysql You can install these modules by running the following command,pip install flask-ask flask flask-mysql Now create a file called conference.py, and use the snippet of the code I have written to build your server side logic.__author__ = 'krishnateja'import loggingfrom flaskext.mysql import My SQLfrom flask import Flask, render_templatefrom flask_ask import Ask, statement, questionmysql = My SQL()app = Flask(__name__)app.config.from_object(__name__)app.config[' MYSQL_DATABASE_USER'] = 'xxxxxxx'app.config[' MYSQL_DATABASE_PASSWORD'] = 'xxxxxxx'app.config[' MYSQL_DATABASE_DB'] = 'xxxxxxxx'app.config[' MYSQL_DATABASE_HOST'] = 'xxx.xxx'mysql.init_app(app)ask = Ask(app, "/")Logger("flask_ask")Level(logging.

Flask-Ask (https://flask-ask.readthedocs.io/en/latest/)2. DEBUG)@ask.launchdef new_conference(): welcome_msg = render_template('welcome') return question(welcome_msg)@ask.intent("Speaker Intent")def ask_if_speaker(speaker_name): speaker_name = speaker_name cursor = mysql.connect().cursor() cursor.execute( "SELECT * from JOIN conference.speaker " "ON speaker = conference.speaker.speakerid " "JOIN " "ON slot = slotid " "WHERE conference.LIKE '%" speaker_name "%';") data = cursor.fetchall() if data is None: message = "There was no speaker by that name." else: hours_start, remainder = divmod(data[13].seconds, 3600) minutes_start, seconds_start = divmod(remainder, 60) time_start = str(hours_start) ":" str(minutes_start) hours_end, remainder = divmod(data[14].seconds, 3600) minutes_end, seconds_start = divmod(remainder, 60) time_end = str(hours_end) ":" str(minutes_end) message = "Session that you are looking for is " data[ 2] " which starts at " time_start " and ends at " time_end ", given by " data[9] return statement(message)if __name__ == '__main__': app.run(debug=True, port=8080)This starts a server on localhost:8080.

Here I wanted to talk about the ease of building an Alexa skill using python which could be used as information provider to a attendee for a conference.

The term Chatbot is closely related to chat bot and chatterbot. Therefore, many “Alicebot clones” populate the internet, having been created based upon the original implementation of A. However, web based bots are not as easy to set up as a stand-alone chatbot application.While the “Pixel phone will put Google’s AI front and center, Google Home is where it will really shine, that’s where we will most naturally interact with AI assistants using voice commands.”[xxiii] The assistant will harness the search giant’s massive knowledge graph to deliver results that make sense.And like Alexa, Google Home will be constantly listening, always at the ready to do your bidding. It is a layer on top of, or a gateway to, a service.Sometimes it is powered by machine learning (the chatbot gets smarter the more you interact with it). Important life-saving health messages, to check the weather forecast or to purchase a new pair of shoes, and anything else in between. )The chatbot can talk to you through different channels; such as Facebook Messenger, Siri, We Chat, Telegram, SMS, Slack, Skype and many others.A lot of people were very astonished and awed when Apple announced Siri, a voice assistance unlike any other which could understand and carry out the task for you.