June 2020 Summaries

In June 2020, Stream Chat's Swift SDK released updates 2.2.3, 2.2.4, and 2.2.5, enhancing its capacity to provide high-quality chat experiences for iOS apps. These updates introduced significant features such as live message translation, which supports 55 languages, catering to multilingual communication needs within apps. The addition of multi-tenancy in version 2.2.3 allows businesses to isolate messages and channels, making it ideal for services like team chat apps. New server location options in Singapore and Sydney were also introduced to improve message delivery speed and reliability for users in those regions. Additional enhancements, improvements, and deprecations were included, with further details available in the full changelog on the Stream Chat Swift repository.

Android Studio facilitates seamless integration with GitHub, enabling developers to contribute to Open Source projects easily without using the command-line interface. This tutorial outlines the process of contributing to an Android project by using Stream Chat's library as a practical example. It begins by selecting a project that the developer is familiar with and identifies a bug to fix, which in this case is a crash issue when clicking an image in the chat. Android Studio's UI allows cloning the repository, creating a new branch from the development branch, and making necessary changes to fix the issue, such as initializing Facebook's Fresco library. After making changes, the developer can commit and push these to a forked repository if they do not have write access to the original repository. The tutorial then guides on creating a pull request on GitHub, ensuring it targets the correct branch, and highlights the importance of following project-specific contribution guidelines. Finally, it emphasizes that once submitted, the pull request will be reviewed by the project's maintainers, who may request further changes.

This tutorial provides a step-by-step guide to building an in-app support system using Stream Chat's Swift SDK, aimed at providing real-time assistance to users in apps such as banking, e-commerce, and ride-sharing. The process involves setting up a Stream Chat dependency using CocoaPods, configuring the Stream Chat dashboard, and integrating the Stream Chat SDK into a Swift application. It guides users through creating a "Join" screen with buttons for users and agents, and setting up handlers to navigate between different views, including a UserViewController for regular users and a ChannelsViewController for support agents. The tutorial also covers creating a support chat channel accessible via a navigation bar button, allowing users to connect with support agents through a ChatViewController. The tutorial emphasizes the importance of securing credentials and provides code snippets for setting up user interfaces and chat functionalities.

Stream has released a new Video API that allows developers to integrate live video calling, conferencing, voice calling, audio rooms, and livestreaming into their applications using a single unified API. This tutorial demonstrates building a basic telemedicine app for iOS using Stream Chat for chat components and Dolby.io for audio and video, both of which offer HIPAA compliance. The guide includes setting up the project in Xcode, installing necessary dependencies via CocoaPods, configuring Stream Chat and Dolby.io dashboards, and coding functionalities such as user registration and interface navigation. It also involves creating a "Join" screen for user selection and a "Consult" screen for chat and video call interactions. Additionally, the tutorial explains setting up button functions and handling conference call initiation through the Dolby.io SDK, ensuring the app can operate in both light and dark modes. Upon completion, users are encouraged to explore further documentation and experiment with the project to enhance their telemedicine app development.

Presend Message Hooks offer a moderation tool that allows users to intercept and modify or discard messages before they are saved and visible in a chat channel, ensuring compliance with content guidelines and preventing the sharing of sensitive information. These hooks are particularly useful in applications where privacy laws or regulations, such as HIPAA, require the removal of personally identifiable information. Presend Message Hooks can scrub messages for sensitive data using AI, restrict the sharing of contact information, and use regular expressions to detect specific words or phrases. The feature integrates with Stream Chat, requiring a fast response from the webhook endpoint to prevent delays, and provides functionality to either rewrite or discard messages according to predefined rules. If the webhook becomes unavailable, Stream Chat will pause its use until it is restored, ensuring seamless operation.

This tutorial focuses on enhancing a simple chat application for iOS and macOS, previously developed using SwiftUI and Stream Chat's Swift SDK, by adding functionalities for managing multiple channels. It guides users through updating the existing Chat View to accommodate various channels, creating a Channels View to list channels the user is part of, and implementing features for channel creation and search. The tutorial highlights using the low-level client to develop custom components with SwiftUI, despite Stream Chat offering UIKit components for such tasks. Key steps include modifying the login view to navigate to the Channels View, implementing a channel creation function that allows users to create channels and join them, and setting up a channel search feature that filters channels based on user input. The tutorial concludes by encouraging further exploration of SwiftUI and Stream Chat's documentation to refine and expand the chat application's capabilities.

User-generated content (UGC) plays a crucial role in engaging a brand's audience by building trust through shared experiences, particularly through impactful images that capture attention and convey emotions more effectively than words. However, the downside to UGC is the potential for negative impacts on a brand's reputation when explicit or inappropriate images are shared, which can lead to diminished trust and even legal issues. Therefore, image moderation is essential to maintain a brand's integrity and protect its online community by ensuring that the imagery aligns with the company's values and goals. Stream Chat's image moderation system flags and labels potentially unsafe content, such as explicit or violent images, to prevent them from tarnishing a brand's image. Implementing robust image moderation processes, along with clear legal and policy frameworks, is vital for safeguarding a company's reputation and ensuring compliance with content standards.

Stream's Silent Messages feature allows for sending system, administrative, or transactional messages without triggering user alerts or increasing the unread message count in conversations. This functionality is particularly useful for non-urgent notifications, such as "your ride is waiting" or "You and Jane are now matched!" Implementing Silent Messages is straightforward, requiring only the addition of a silent field in the message object set to true, after which the API manages the process.

Stream Chat has introduced a new feature called the queryMembers endpoint to enhance its chat product's capability to manage large channels efficiently, particularly those in medical chat apps with stringent privacy and security requirements. This endpoint enables users to access and paginate through comprehensive member lists in channels with hundreds or thousands of members, offering filtering options for efficient member information retrieval. By supporting features like read receipts and @mentions in large channels, which were previously disabled for member counts above 100, Stream Chat enhances its competitive edge over rivals like SendBird by not imposing user limits per channel. The new endpoint is being integrated into Stream's SDKs, ensuring these features are readily available with Stream's pre-built UI components.

TaskRabbit is a platform that connects users with local independent contractors, known as "Taskers," for a variety of home-related tasks, offering a user-friendly system for booking, paying, and reviewing services. Communication between clients and Taskers is crucial, and TaskRabbit's original in-house chat system was unreliable, leading them to seek an external solution. After evaluating several vendors, TaskRabbit chose Stream for its high-performance real-time chat capabilities and its React Native library, which other alternatives lacked. Stream's flexibility and adaptability, along with its supportive partnership approach, convinced TaskRabbit to integrate it into their app, enhancing communication with features like multi-party groups and internationalization. TaskRabbit's integration with Stream allows users to book appointments directly through chat, which is expected to significantly benefit the business by streamlining communication and improving user experience. This partnership aligns with TaskRabbit’s broader goal of simplifying everyday life for users while providing Taskers with flexible work opportunities.

Stream Chat has introduced a message translation feature that allows users speaking different languages to communicate seamlessly in the same channel, either on-demand or automatically. This feature is not enabled by default, but users can request access through Stream's support team, after which it can automatically translate all messages or individual ones via an API endpoint. The translation process detects the source language automatically and updates the message for all users in the channel. The feature supports automatic translation, translating messages immediately as they are added to a channel, and works effectively in one-on-one or group conversations with two main languages. The system includes an internationalization (i18n) object that contains the original and translated message text in specified languages, making it adaptable with minimal development effort. However, the translation is limited to messages with up to 5,000 characters, does not apply to error messages or commands, and does not retroactively affect already translated messages if translation settings are changed.

"The Stream" is a tutorial project that demonstrates how to build a simple social network using Android and Stream's Activity Feed API. The application allows users to post messages and follow other users, with each interaction facilitated through a combination of a backend built with Express (Node.js) and a frontend developed in Kotlin. The backend generates secure tokens for the mobile application to interact directly with the Stream API, enabling users to post messages to their followers and view a timeline of posts from those they follow. The system architecture is divided into two main components: the mobile application, which handles most of the user interactions, and the backend, which manages authentication and token generation. The process involves creating user feeds and timeline feeds within the Stream platform, enabling seamless message posting and retrieval. Users can view and follow others through a simple list view interface, and the app uses Kotlin coroutines for asynchronous network operations. The tutorial includes detailed instructions on setting up the development environment and requires basic knowledge of Node.js and Android development.

Healthline is a leading provider of health information, surpassing WebMD and attracting millions of unique visitors to its platforms such as Healthline.com and MedicalNewsToday.com. As part of its efforts to support individuals with chronic conditions, Healthline introduced Healthline Together, a suite of mobile apps designed to foster peer-supported communities and reduce social isolation. These apps offer a secure space for users to connect and access curated healthcare content, with privacy features ensuring user anonymity. To enhance user experience, Healthline partnered with Stream to integrate personalized activity feeds into the apps, enabling real-time, relevant interactions and content tailored to individual health needs. Stream's technology facilitated a rapid market launch and allowed Healthline to focus on its core competencies by providing scalable, feature-rich feeds. This partnership has increased user retention and engagement, allowing Healthline Together Apps to expand their reach to web platforms, further connecting individuals on their health journeys.