See more about Codechella here (Twitter) and here (Devpost).

1. 😺 The Team
2. 📋 About the Project
3. 🔒 Secrets (API Keys etc)
4. 🏃 Running the Project

• Jonathan Bartlett (GitHub | Twitter)
• Akhil Nair (GitHub | Twitter)
• Abel Fikreyohanes (GitHub | Twitter)
• Shivam Soni (GitHub | Twitter)
• Shreehari Vaasistha (GitHub | Twitter)

After brainstorming ideas, we decided unanimously on a Smart Assistant application that would allow users to interact with Twitter in a meaningful way. Current offerings for Twitter "skills" on Amazon Alexa are limited in what they can do and are rated poorly on the store.

Therefore we decide to create a skill, and the supporting API, to allow users to do the following:

• Get a summary of tweets in a Hashtag
• Get the latest tweets from a User
• Follow a user
• Get the topics trending in your area

We are using the Twitter API v2 to:

• Get Tweets based on a Hashtag
• Get Tweets from a user
• Follow a user
• Get trending topics

This smart assistant application will hopefully open up Twitter to a whole new demographic. People with visual impairments may struggle when using Twitter on a conventional mobile app or website. A smart assistant allows users to interact with Twitter purely through voice and we wanted to implement features we feel are key to the Twitter experience.

.
+-- .gitignore               # Ignore secrets, venv, lock files etc
+-- README.md
+-- requirements.txt         # Project Requirements
+-- lambda
|   +-- lambda-function.py   # Handler for lambda functions
|   +-- twitter_functions.py # Helper functions for interacting with twitter API
|   +-- tweet_summary.py     # Tweet summarizer
+-- interactionModels
|   +-- custom
|   |   +-- en-US.json       # Interaction model for the Alex Skill

A sample environment file exists at .env.sample you should source this file when running the serverless deployment.

1. Create a new Alexa Skill from the Alexa Skills Dashboard
   • Make sure to choose the option to provision your own!
2. Copy the interactModel json in the json editor on the Alexa Skills Dashboard
3. Build the model

1. Source your environment file with the required environment variables
2. Make sure you have serverless installed and aws credentials configured
3. Run npm install to install serverless plugins
4. Run serverless deploy to deploy the lambda function

1. Copy the ARN for the twitter digest lambda function
2. Paste the ARN into the Endpoints field on the Alexa Skills Dashboard
3. Enjoy!