(Go: >> BACK << -|- >> HOME <<)

Skip to content

Sranabhat1/Trading-with-Alexa

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

80 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Trading-with-Alexa

Table of Contents

Introduction


There is a lack of user-friendly tools to retrieve stock information real-time and websites often become too complex to navigate. The Trading with Alexa Skill is a user friendly application that gives real-time stock information and allows users to make more informed investment decisions and at the very least, educate users on the state of the stock market.

Built With


Dependencies


Please see the requirements.txt file for all dependencies.

You will also need:

  • An Amazon Echo or other Alexa-enabled device
  • An AWS account (AWS Lambda, Alexa-skill configuration, optional Cloudwatch logging)

Installation


  1. Create a Python virtual environment, and install the contents of the requirements.txt file into it using pip

  2. Zip the contents of the site-packages folder within your virtual environment (remember, zip the contents of the director, not the directory itself)

  3. Add the contents of lambda/py to the zip file also (alexa/.. and lambda_function.py)

  4. Once this zip is ready, create your Lambda function using AWS Lambda (a quick google search should return some useful guides, see this guide)

  5. Create your Alexa skill, and when editing intents, you can use "manual edit", and paste in the contents of the models/skill.json file (see this guide)

  6. Take the skill ID of the Alexa skill, and add "Alexa Skills Kit" as a trigger in your Lambda function. Enable Skill ID verification, and paste in your skill ID.

  7. Under Endpoints in the Alexa skill, paste the ARN of your Lambda function.

You should be good to test it at this point! We recommend using the built-in Test console on the Alexa skill before you load it on your own Alexa.

License


This project is licensed under the MIT License - see the LICENSE.md file for details

Attribution


Authors


  • Madhav Mehta
  • Sabal Ranabhat
  • Cameron O'Brien
  • Karina Scott
  • Yohan Flores
  • Brian Nguyen

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors 4

  •  
  •  
  •  
  •  

Languages