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  • By Evangelos Resvanis
    Twilio Autopilot Facebook Messenger Enhancements autopilot-facebook-messenger-enhancements.png

    In this post, I'll explain how to set up and run a Node.js application that augments Twilio Autopilot with Facebook Messenger features that Autopilot doesn’t currently support out-of-the-box.

    This code is just a baseline for your own enhancements. It can be enhanced or changed to create something more complete and robust, expanding to any number of channels and adapting to their APIs.

    Pre-requisites

    1. Clone the Node app repo and set .env values

    You can find the GitHub repo for this post here.

    Then, the following values will be required in your .env file.

    Twilio variables to set …

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  • By Evangelos Resvanis
    How to Build an Image Classifier with Twilio Autopilot image-classifier-autopilot.png

    In this article, I will show you one of the many possible ways to build an Image Classifier using Twilio Autopilot in your flow. We will use Node.js with TensorFlow and show the final result on WhatsApp.

    Let's get started.

    Pre-requisites

    Our Image Classifier is based on Transfer Learning using TensorFlow. Transfer Learning is a great way to build on top of thousands of existing training models that are already available, saving you valuable development time and resources. To learn more about it and apply your own logic, check out this TensorFlow image retraining tutorial.

    Install TensorFlow by following these relevant steps

    The Main Components

    The building blocks for this demo code are the following:

    • A Node.js Express-based app to handle all incoming requests (for example, getting the name of the new set of images you want to train the bot with; e.g. "polar bear")
    • Script for …
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  • By Evangelos Resvanis
    Small tricks: Utilize Temporary Storage under Twilio Functions Small Tricks: Utilize temporary storage under Twilio Functions

    When working with Twilio Functions, you might need to create resources you'd like to store locally for one-off activities. For example, you might like to create a file with user-provided data and send it onto the next step in a flow based on your business needs.

    In Functions, anything that you create on-the-fly gets stored in the temporary folder, which may not be obvious at first.

    In this quick tutorial, I'll show you how to access and utilize the temporary storage under Functions for your purposes. Let's get started.

    Temporary Storage in a Twilio Function

    If you try to perform operations anywhere other than the temporary folder in the underlying OS filesystem you will see something like:

    Error in Twilio Functions read-only file system

    Below I show a Twilio Function writing to and retrieving from the relevant temp folder:

    /**
    *
    *  This Function shows you how to reach and utilise the temporary storage under the …
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  • By Evangelos Resvanis
    Extend Twilio Autopilot by Adding FAQ Functionality autopilot-extend-faq.png

    When working with Twilio Autopilot, dealing with FAQs is not as straightforward as with typical user Intents and Tasks.

    In this tutorial, I'll show you how to add FAQ functionality to a Twilio Autopilot powered bot using Twilio Functions and Elasticsearch, then show you a working result running in WhatsApp.

    Let's get started.

    Components and architecture of our FAQ integration

    In our case, we use the following components to build an FAQ integration:

    • Autopilot Tasks - to direct to the FAQ module. For example, we can make an “unresolved” case, which means Autopilot could not match an existing Intent to the user input (and we then try to see if the query corresponds to something in the FAQ)
    • Twilio Function - to take the specific user input that was not matched to an intent and send it to the backend for analysis.
    • Elasticsearch - to link the backend of …
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