December 2021 Summaries

This tutorial guides through building an appointment scheduler web application using Node.js, Express, Firebase, and the Vonage Messages API. The project structure is set up with a `public` folder for static files, including HTML content and CSS styling, and a `server.js` file that handles Express requests and interacts with the Firebase Realtime Database and Vonage API. The code includes functions to check if a slot is available, add slots to the database, send SMS confirmations, and cancel appointments. The application uses Express for routing, Firebase Admin SDK for interacting with the database, and Vonage Messages API for sending SMS messages.

The author of this text has been using Test-Driven Development and PHPUnit for a long time, but recently discovered PEST, a new testing framework that could potentially replace PHPUnit as the de-facto tool of choice for writing TDD PHP. The author tested PEST on their own Vonage PHP SDK project, which already had a comprehensive test suite, to see how it would run and compare its performance to PHPUnit. PEST is backwards compatible with PHPUnit and has a similar syntax, making it an attractive option for developers who want to adopt a more functional programming style. However, the author found that using the Pest Converter tool, which aims to automatically convert PHPUnit suites to PEST, was not smooth sailing due to edge cases in the Vonage PHP SDK project. The author concludes that while PEST is an attractive option, it's essential to fix any complex or over-engineered test suites before attempting automation with tools like the Pest Converter.

The text discusses adding transcription/closed captioning to a Vonage Video application, leveraging Symbl.ai's web SDK. The goal is to provide accessibility and insights into video calls. To achieve this, the application uses a custom React hook called `useSymblai`, which abstracts away the complexity of opening a WebSocket connection with Symbl.ai. The hook returns captions, the other party's captions, and the name of the speaker. The application also sets up a preferences context to store user information, such as username and conversation ID. The custom hook uses React hooks like `useState` and `useEffect` to manage state and side effects. The text concludes by mentioning additional features provided by Symbl.ai, including sentiment analysis, insights extraction, summary of the call, analytics, and more.

The Vonage Voice API allows developers to create Interactive Voice Response (IVR) menus that capture user input with Automatic Speech Recognition (ASR). To improve the IVR experience, developers need to provide context for ASR to better understand the caller's response. However, ASR is prone to errors and can be frustrating for callers. Developers can use tools such as Vonage's speech recognition settings and NCCOs (Nexmo Call Control Objects) to track conversation history and handle repeated errors. By abstracting out repeated properties in NCCOs, developers can create lightweight error-handling endpoints that switch to DTMF or live operators when necessary. The Vonage Voice API provides a well-documented and useful experience for developers building IVR menus, with resources available for learning more and troubleshooting.

As we reflect on 2021, we're grateful for the opportunity to share some of our favorite content with you. This year saw a range of exciting articles and videos covering topics like technical updates, tutorials, and life during the pandemic. We also showcased innovative projects, such as Passwordless and 2FA Workflows using Node.js, and Machine Learning, including a compelling story about creating a Facebook Bot in Node.js due to hunger pangs during coding sessions. Additionally, we shared bite-sized learning opportunities like One Dev Minute and JavaScript Tutorials, and revisited past episodes of "Now We're Talking" on Twitch. As we look forward to 2022, we invite you to revisit our content, follow us on Twitter for updates, and be on the lookout for new articles and videos in the coming year.

This tutorial provides a step-by-step guide on how to set up a conference call using ASP.NET Core and NancyFX, allowing multiple people to join the same call. The process involves creating an ASP.NET Core app, setting up a Vonage voice application, and configuring the application to handle incoming calls using NancyFX. Once configured, the application will respond with a NCCO that guides the user through the conference call process, including greeting them and adding them to the conference. To test the application, it requires linking a Vonage phone number, setting up an answer URL using Ngrok, and running the app locally before calling the TO_NUMBER to initiate the conference call.

This tutorial helps developers build a video conferencing web app using Python, Flask, JavaScript, and Vonage's Video API. To start, you need to create a Vonage Video API account, register for a free account, and set up an initial project with the provided GitHub repository. The tutorial then guides you through creating a Flask application that maps URLs to HTML templates, which render video conferencing functionality using the Vonage Video API. On the front-end, JavaScript code initializes a session object, subscribes to streams, and connects to the session using a token generated on the back-end. The tutorial concludes by providing resources for further learning and community engagement.

This tutorial sets up an ASP.NET project to connect to The Vonage Voice API, allowing users to add phone call abilities to their application. To complete this setup, developers need a Vonage API account and create a virtual phone number. They also need to set up a Vonage application with security and configuration information, generating private keys and creating JSON Web Tokens (JWT) for authentication. The tutorial covers both ASP.NET Web and Core project setups, installing the Vonage .Net SDK and adding configuration files to the project. With this setup, developers can now dive into code and learn how to make a Text-to-Speech phone call in their ASP.NET project with the Voice API.

In a recent hackathon, Team Subarashi created an innovative e-learning web application called Senpai, which connects programming mentors and mentees for one-on-one tutoring, utilizing Vonage Video API to provide a seamless experience for users interested in learning frontend technologies. The app was designed to streamline the process of scheduling appointments, video chat, screen sharing, and collaboration, making it suitable for virtual classrooms or tuition centers. By leveraging MongoDB, Express, React, Nodejs, Docker, and the Vonage Video API, Senpai offers a unique solution for programmers to provide one-on-one tutorial services, allowing users to learn frontend technologies in an interactive and real-time environment.

Vonage AI Studio is a low-code/no-code conversation designer that empowers developers and non-developers to create customer engagement applications in natural language. It offers multiple channels, connects to various sources for building an omni-channel experience, and utilizes Natural Language Understanding (NLU), Automatic Speech Recognition (ASR), and Text to Speech (TTS) APIs. The platform has a visual drag-and-drop builder, nodes that guide the conversation flow, and reports to gain insights into virtual agent performance. Vonage AI Studio is distinct from other conversational AI design platforms due to its end-to-end conversational design capabilities, graphical user interface, support for multiple channels, and proprietary NLU algorithms. It aims to eliminate common issues in customer engagement, such as long call queues and outdated IVRs, by providing human-like conversations and minimizing friction and conversation abandonment rates. The platform offers various use cases, including intelligent IVR, travel updates, customer support, scheduling & confirmations, and delivery statuses, and provides access to developer preview for customers to experiment with the solution.