The Evolution of Web Development: Trends to Watch in 2024

The landscape of web development is continuously shifting, driven by user demands and technological advancements. With a staggering 5.3 billion internet users worldwide, it's crucial for businesses to stay abreast of the latest trends to maintain a competitive edge. An Adobe study emphasizes this, stating that 59% of users prioritize a well-designed web experience. To help businesses navigate this complex field, we've curated a list of the most significant web development trends expected to shape the digital realm in 2024.

Progressive Web Apps (PWAs)

PWAs blend the best of web and mobile apps, offering a native app-like experience without requiring an actual download. They bring numerous benefits, such as ease of installation, device storage and power savings, reduced support and development costs, faster market launch, and flexible distribution. Ericsson's research predicts that 5G networks, which are set to handle a majority of mobile data traffic, will improve the performance of PWAs, further cementing their status as a pivotal trend.

Accelerated Mobile Pages (AMP)

AMPs, a collaborative project by Google and Twitter, ensure quick page loading across devices. Around 884,954 live websites use AMP technology, which helps improve user retention through faster loading times and better performance.

Mobile-First Development

The mobile-first approach is gaining traction as mobile devices account for a substantial share of internet traffic. Ensuring mobile adaptability through responsive design and mobile-optimized features, like one-click ordering and Geo-location data, can boost user engagement and brand recognition significantly.

Single Page Applications (SPA)

SPAs offer a frictionless user experience, loading dynamic content without refreshing the entire page. They are perfect for simplifying navigation and reducing bounce rates, crucial for modern web applications.

JavaScript Frameworks

JavaScript and its various frameworks (React, Angular, Vue, Node, etc.) continue to lead the web development space. Around 98.6% of websites utilize JavaScript, allowing for the creation of agile and scalable applications that enhance the user experience.

Micro Frontend Architecture

Micro frontend architecture decentralizes monolithic front-end development, enabling teams to manage and scale their codebases independently. This approach is aligned with DevOps practices and facilitates faster launches.

Cloud Computing

Cloud technology has witnessed a spike in adoption, especially with the advent of remote work. It promises scalability, data security, and cost efficiency. The global cloud computing market is valued at 591.79 billion USD, indicating its significance in modern web strategies.

Serverless Architecture

Serverless computing allows developers to build applications without server management concerns, reducing costs and time-to-market while enhancing scalability.

AI-Powered Chatbots

AI chatbots are expected to reach a market size of $4.9 billion by 2032. They provide round-the-clock customer support, enhanced engagement, lead generation, and cost savings.

Content Personalization with AI/ML

Content tailored to user preferences is crucial for engagement. AI/ML technology enables real-time analytics and personalized recommendations, significantly improving user experiences and conversion rates.

API-First Development

By prioritizing APIs, businesses can allow for simultaneous coding and user access, facilitating a seamless web experience and reducing development costs.

B2B SaaS Solutions

Integration of SaaS solutions enables businesses to manage data efficiently, leading to improved operations and customer service.

Dark Mode UI

A popular feature that improves readability and reduces eye strain, dark mode continues to gain adoption among big tech companies and users.

Voice Search Optimization

The convenience of voice assistants has popularized voice search. With markets for voice recognition technology growing, optimizing for voice search is becoming an integral part of web development.

Motion UI

Creative and interactive design elements like Motion UI can enhance user engagement and set a website apart, encouraging better user experiences and increased conversions.

Augmented Reality (AR)

AR is revolutionizing how users interact with websites, providing immersive experiences that blend the digital and physical realms.

Blockchain Technology

Blockchain's secure and transparent nature makes it suitable for websites with payment integrations, financial transactions, and in industries demanding high data integrity.

These trends reflect the industry's shift toward more interactive, efficient, and user-centric solutions. Businesses aiming to forge a strong online presence must consider these developments to enhance their web offerings.

As the digital landscape evolves, staying ahead will require adaptability, foresight, and a commitment to embracing emerging trends in web development.

MindInventory can assist in leveraging these trends for your business, offering expertise in web development, UI/UX design, and maintaining a competitive edge in the fast-paced digital environment.

FAQs about Web Development Trends

The future of web development: It's trending towards bespoke web software powered by PWAs, SPAs, serverless architectures, and voice-enabled experiences with technologies like AI, AR, Blockchain, Web 3.0, and IoT staying relevant.
Languages for web development: Common languages include Golang, PHP, Python, Laravel, and JavaScript, which handle both front-end and back-end development.
Changes in web development: It's becoming more user-centric, focusing on UX research and strategy, responsive UI design, and using industry-leading technologies to fulfill consumer requirements.

To engage effectively in this dynamic digital era, understanding and implementing these web development trends is indispensable for businesses. Establish your brand in the competitive market by adopting these cutting-edge strategies.

Tags

Web Development Trends
Technology Advancements
Digital Strategy
Competitive Edge

https://www.mindinventory.com/blog/web-development-trends/

Understanding Undici: A Node.js HTTP Client

Introduction to Undici

The Undici project is an HTTP/1.1 client written specifically for Node.js, aiming to provide a high-performance interface for making HTTP requests. Named after the Italian word for eleven ('Undici'), reflecting the HTTP/1.1 version that it supports, this client offers an alternative to the built-in http module in Node.js.

Features and Benefits

Undici boasts several features that make it an attractive choice for developers needing to perform HTTP requests in their Node.js applications:

Performance: Undici demonstrates superior performance compared to other HTTP clients available in Node.js, as evidenced by its benchmark results which showcase its ability to handle more requests per second.
Fetch API Compliance: Adhering to the Fetch Standard, Undici includes methods like fetch(), which developers familiar with the Fetch API in the browser will recognize and be able to use seamlessly in a Node.js environment.
Streaming and Pipelining: The client supports HTTP pipelining, allowing multiple requests to be sent out without waiting for the corresponding responses, as well as the ability to work efficiently with streams.
Garbage Collection Considerations: Given Node.js's less aggressive garbage collection compared to browsers, Undici recommends manually consuming response bodies to avoid issues such as excessive connection usage or deadlocks.

Installation and Usage

Installing Undici is straightforward, and it can be done using package managers like npm. Once installed, importing and using it is relatively simple, with methods available to send HTTP requests (undici.request), stream responses (undici.stream), and work with upgraded HTTP protocols (undici.upgrade). Here's a basic example of how to perform a GET request and print the response:

import { request } from 'undici';

const { statusCode, headers, body, trailers } = await request('http://localhost:3000/foo');
console.log('response received', statusCode);
console.log('headers', headers);
for await (const data of body) {
  console.log('data', data);
}
console.log('trailers', trailers);

Advanced Features

Apart from its basic usage, Undici provides several advanced features:

Body Mixins: Simplify the process of consuming response bodies by providing methods like .json(), .text(), and .formData().
Global Dispatcher: Configure a global dispatcher to manage how requests are made across an application.
Specification Compliance: While aiming to comply with HTTP/1.1 specifications, Undici also documents any deviations or unsupported features, such as the 'Expect' header.
Workarounds: For example, network address family autoselection can be controlled using the autoSelectFamily option in undici.request or the undici.Agent class.

Collaborators and Licensing

Undici benefits from the contributions of a community of collaborators, including notable individuals such as Matteo Collina and Robert Nagy, among others. The project is available under the MIT license, allowing for permissive free usage and contribution.

Conclusion

In summary, Node.js developers in search of a high-performance HTTP client that complies with the Fetch Standard may find Undici to be an excellent fit. Its fast performance, support for streaming and pipelining, and feature set aimed at both ease of use and compliance with standards make it a competitive choice in the landscape of Node.js HTTP clients.

Tags: #Undici #Nodejs #HTTPClient #FetchAPI #Performance

https://github.com/nodejs/undici

Overview of Privy: A Privacy-First Coding Assistant

Introduction to Privy

Privy is introduced as a coding assistant that prioritizes privacy. This assistant is available as an extension for Visual Studio Code and is also listed on the Open VSX Registry. Its primary features range from conducting AI-driven chats about code, explaining code sections, generating unit tests, finding bugs, and diagnosing errors within the codebase.

Core Features and Functionalities

AI Chat

Privy offers an AI Chat feature that allows users to converse with the assistant regarding their code and related software development queries. It takes into account the editor selection to provide context to the conversation.

To initiate a chat, users can use the "Start new chat" button in the side panel or utilize keyboard shortcuts such as Ctrl + Cmd + C or Ctrl + Alt + C. For MacOS, there's also a touch bar option.

Explain Code

The Explain Code feature provides users with explanations for the code they select in their editor.

Users can select any part of the code and request an explanation through the Privy UI or commands.

Generate Unit Test

Privy can automatically generate unit tests for selected pieces of code, thereby saving developers significant time in test creation.

After code selection, the generated test case will appear in a new editor tab, which can then be refined.

Finding Bugs

Privy aids in the identification of potential defects in code segments.

Similar to generating tests, users select code and use Privy's commands to reveal a list of potential bugs.

Diagnose Errors

Error diagnosis is made simpler with Privy's ability to suggest fixes for compiler and linter errors, which improves efficiency in debugging.

Again, after selecting the problematic code, Privy will provide potential solutions in the chat window.

Tips for Utilizing Privy

To get the most out of Privy, users are encouraged to be specific in their requests, provide adequate context when chatting, not trust answers blindly, and use separate chat threads for distinct topics. These practices enhance the accuracy and relevance of Privy's assistance.

Credits and Contributions

Privy owes its development to a community of contributors and RubberDuck AI. It acknowledges the efforts of multiple individuals such as Lars Grammel, Iain Majer, and Nicolas Carlo, amongst others, for their diverse contributions to the project, ranging from code to documentation and bug fixing.

External Community Engagement

The assistant is not just a standalone tool but is also integrated with social platforms for broader reach. For instance, it has a badge linking to its Twitter handle @getprivydev and a Discord badge, implying a wider community engagement where users can interact and discuss.

Contribution Guidelines

Those interested in contributing to Privy's development are directed to the contributing guide and a list of good first issues, making it easier for newcomers to start participating in the project.

Considering its extensive functionality such as AI chatting, code explanations, test generation, and debugging support, combined with a strong emphasis on privacy and community contributions, Privy positions itself as a robust tool for developers seeking intelligent coding assistance within their preferred coding environment.

Tags: #Privy #CodingAssistant #VisualStudioCode #AIChat #DebuggingTool

https://github.com/srikanth235/privy

The Ambition for AI Supremacy: Zuckerberg’s Vision and the Talent Wars

Fueling the generative AI craze, there's a belief in superhuman AI potential. Zuckerberg's Meta is gunning for general intelligence. The industry competes fiercely for AI talent, with researchers earning top dollar. Zuckerberg, involving himself in talent acquisition, notes the uniqueness of this talent war. Meta has developed significant generative AI capabilities, aiming for industry leadership despite lacking precise definitions of Artificial General Intelligence (AGI). Progress towards AGI is viewed as gradual by Zuckerberg, who sees no distinct thresholds.

The Drive for Industry Dominance

The tech industry's pursuit of AI is marked by an intense battle for a limited pool of experts. Meta’s shift in focus under Zuckerberg’s direction emphasizes the company’s commitment to harnessing the full potential of general AI. With substantial investments and the promise of pushing boundaries, Meta seeks to attract and retain leading researchers.

Generative AI and Its Importance to Meta

Even seemingly unrelated functionalities like coding are integral for AI development, as demonstrated by the importance of coding in LLM (Large Language Model) understanding. Zuckerberg’s ambition is transparent—he wants Meta to lead with the most advanced, state-of-the-art models, building a framework for AI that grasps complex knowledge structures and intuitive logic.

The Open vs. Closed Debate

Zuckerberg addresses the distinction between open and closed AI development, touting the benefits of open sourcing to ensure broad access and mitigate concentration of power. He subtly criticizes peers in the industry for their less transparent practices and alignment of safety concerns with proprietary interests.

Autonomy in Deciding Meta’s AI Future

Zuckerberg retains the final word on whether Meta will open source its potentially groundbreaking AGI. While he leans towards openness for as long as it's safe and responsible, he acknowledges the fluidity of the situation and avoids committing firmly.

Meta’s Multi-faceted Mission

Finally, Zuckerberg clarifies that Meta's focus on AI isn't a pivot from its metaverse ambitions but rather an expansion. The utilization of AI in virtual worlds and the development of AI characters for Meta’s social platforms are parts of a concerted effort to shape the future of how people connect, blurring lines between human-to-human interactions and human-to-AI engagements.

Overall, Zuckerberg’s statements reflect a determined move to make Meta a key player in the AI landscape, a landscape where power, transparency, and innovation are at constant play. As the tech industry marches towards a future where AI is intricately woven into the fabric of connectivity and interaction, Zuckerberg positions Meta at the forefront of this shift, with an eye on both the opportunities and ethical implications it presents.

Tags: #ArtificialIntelligence #TechIndustry #TalentWar #GenerativeAI #MetaAIInitiative

https://www.theverge.com/2024/1/18/24042354/mark-zuckerberg-meta-agi-reorg-interview

WhisperSpeech: An Overview

WhisperSpeech is an ambitious project aimed at pioneering the field of speech synthesis. The project's goal is to create a model equivalent to Stable Diffusion but in the domain of speech – promising powerful capabilities and easy customization. The project operates with a commitment to Open Source code and the use of properly licensed speech recordings, ensuring safety for commercial applications.

Key Features and Updates

WhisperSpeech is currently utilizing the English LibreLight dataset for model training and aims to expand to multiple languages in its forthcoming release, with support for languages like Whisper and EnCodec.

Progress Report as of January 18, 2024

The project showcases the ability to mix languages within a single sentence, with English project names flowing smoothly into Polish speech. They highlight:

Whisper Speech
Collabora
Laion
Jewels

Additionally, they provide a sample of voice cloning using a speech by Winston Churchill, demonstrating the technology's advanced capabilities.

Progress as of January 10, 2024

The team reports on a new SD S2A model that is notably faster and maintains high-quality speech output. They included a voice cloning example utilizing a reference audio file.

Progress as of December 10, 2023

The update included samples of English speech with a female voice and a Polish speech sample with a male voice.

Older updates have been archived, indicating a progression and commitment to continual improvement.

Downloads and Roadmap

Downloads available include pre-trained models and converted datasets. The roadmap proposes gathering a more extensive emotive speech dataset, exploring generation conditioning on emotions and prosody, establishing a community-driven collection of freely licensed multilingual speech, and training finalized multi-language models.

Architecture and Recognition

The architecture involves several components:

AudioLM: Not described in the text but likely a component of the overall speech synthesis framework.
SPEAR TTS: Likely another component of the framework or a technology used in conjunction with WhisperSpeech.
MusicGen: Possibly related to generating music or controlling prosody in speech.
Whisper: Used for modeling semantic tokens through OpenAI's Whisper encoder block.
EnCodec: Handles modeling of acoustic tokens, delivering audio quality at reasonable bitrates.
Vocos: A vocoder pretrained on EnCodec tokens, enhancing audio quality.

The block diagram visualizes the EnCodec's framework, detailing its function within the project architecture.

Acknowledgments and Citations

WhisperSpeech extends appreciation to its sponsors: Collabora, LAION, Jülich Supercomputing Centre, and www.gauss-centre.eu. Individual contributors, such as 'inevitable-2031' and 'qwerty_qwer', receive thanks for their assistance in the model's development.

Citations listed without details suggest the project's reliance on numerous Open Source ventures and research. The project stands on the shoulders of the broader research community, which it acknowledges through these provisional citation placeholders.

WhisperSpeech projects itself as not only a technical endeavor but also a community-focused initiative promoting openness and collaboration, as indicated by the mention of its presence on the LAION Discord server.

Note: This overview is based on the provided information and the context of the WhisperSpeech project documents. Specific insightful presentations and detailed technical mechanisms were mentioned but not thoroughly described in the text given.

Overview of node-auto-launch

Introduction to node-auto-launch

node-auto-launch is a package that provides functionality to automatically start Node.js applications upon a user's login. It's particularly useful for desktop applications built with NW.js or Electron that need to start running without user intervention when the system boots up.

Installation

To include node-auto-launch in a project, install it via npm:

npm install --save auto-launch

Basic Usage

The basic usage involves creating an instance of AutoLaunch with the application's name and path, and then calling the enable() method to set up auto-launch:

var AutoLaunch = require('auto-launch');
var minecraftAutoLauncher = new AutoLaunch({
  name: 'Minecraft',
  path: '/Applications/Minecraft.app',
});

minecraftAutoLauncher.enable();

API Highlights

Creation:

new AutoLaunch(options): Instantiate with application details.

Options include:

options.name: The app's name.
options.path: Absolute path to the app.
options.isHidden: Launch app without showing window (default false).

Methods:

.enable(): Enable auto-launch at startup.
.disable(): Disable auto-launch.
.isEnabled(): Check if auto-launch is enabled.

Platform-Specific Startup Mechanisms

node-auto-launch works across different operating systems, utilizing various mechanisms:

Linux/FreeBSD: Uses Desktop Entry specification to add a .desktop file into ~/.config/autostart/.
Mac: By default, uses AppleScript to add an app to Login Items. There's also an option to use a Launch Agent, a .plist file within Library/LaunchAgents, for a more daemon-like behavior.
Windows: Modifies registry keys in \HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Run. Also, it supports Squirrel.Windows for Electron apps.

Considerations for Mac Users

For Mac users, there are additional considerations:

Using Launch Agent doesn't add the app to the Login Items list in System Preferences, so auto-launch setting must be managed within the app.
Launch Agents are more suitable for apps without a UI or daemons.
If an app is removed, a Launch Agent file could be left behind on the user's machine.

Considerations for Windows Store Apps

For Electron apps in the Windows Store, the auto-launch functionality requires a different approach because of sandboxing. The AutoLaunch config would look something like this:

new AutoLaunch({
  name: 'YourApp',
  // Other details omitted for brevity
});

Refer to a specific article for a detailed method for creating such an enabled app.

Contributing to node-auto-launch

Developers are invited to contribute to the node-auto-launch project. They should refer to the CONTRIBUTING.md file for guidelines.

By integrating node-auto-launch into applications, developers can ensure a seamless experience for users who prefer applications to start automatically at login, while also providing the flexibility to enable or disable this feature as needed.

Tags: #NodeAutoLaunch #AutoLaunchPackage #NodejsAutoStart #ElectronAppAutomation

https://www.npmjs.com/package/auto-launch

Exploring 2024 Trends in Back-End and Web Development

The digital realm is in perennial flux, presenting both hurdles and openings for developers and product owners. As we navigate towards 2024, understanding the imminent trends in back-end and web development is crucial. This article serves as a blueprint to master these trends, ensuring you remain at the vanguard of technological evolution.

AI and Machine Learning Integration

Artificial Intelligence (AI) and machine learning are revolutionizing back-end development by automating tasks, simplifying complex data analysis, and refining decision-making processes:

Automated Code Generation

Employ AI to craft code snippets effectively, as exemplified by tools like OpenAI’s ChatGPT which interprets natural language into code.

Security and Code Quality Enhancement

Leverage AI-powered code review mechanisms such as DeepCode and CodeClimate for preemptive bug detection and security audits.

User Experience Personalization

AI facilitates bespoke user experiences by evaluating user activities and preferences, fostering higher engagement and retention rates.

Predictive Analytics

Implement machine learning models to anticipate user actions and proactively address potential issues.

AI-Driven Recommendation Systems

Enhance user engagement and conversion rates with AI-created recommendations tailored to client behaviors and inclinations.

Chatbots and Virtual Assistants

Integrate AI-powered chatbots to furnish round-the-clock customer assistance, refining the service quality.

Serverless Architecture Advancements

Serverless architecture, or Function as a Service (FaaS), allows developers to focus on code while bypassing server management concerns. Providers like AWS, Azure Functions, and Google Cloud Functions offer cost-effective, resource-based services that cater to multiple business needs, including image recognition and IoT.

Edge Computing

Positioned to decrease latency and offer real-time data management, edge computing is invaluable for dynamic applications demanding swift, localized data handling.

Reduced Latency

Edge computing diminishes response times significantly, resulting in more responsive web applications.

Enhanced Performance

Content delivery networks (CDNs) typify edge computing, minimizing back-end loads while accelerating delivery times.

Bandwidth Economization

Shifting data processing to the edge diminishes the need for full-scale data center involvement, conserving bandwidth.

Real-Time Processing

Edge nodes can immediately analyze and react to data, beneficial for immediate-response applications such as IoT systems.

Zero Trust Architecture (ZTA)

ZTA is reshaping cybersecurity by assuming potential threats from all quarters, mandating rigorous user and device verification at every phase.

Identity Verification

This process mandates substantial authentication steps like multi-factor authentication for access.

Least Privilege Access

Access is confined to only what is essential for user roles, thereby mitigating the impact of breaches.

Micro-Segmentation

Finely partitioning network access shields each resource distinctly.

Data Encryption

Information is protected consistently, whether being transferred or stored.

Internet of Things (IoT)

IoT's expansive network of connected devices is set to deepen, generating colossal data volumes that require efficient backend systems to manage.

Ergonomic Keyboards

Addressing developer well-being, ergonomic keyboards provide enhanced comfort, potentially leading to increased productivity and lower strain-related disruptions.

Prominent Programming Languages

Rust

Esteemed for its safety features, Rust is ideal for performance-sensitive and secure back-end applications.

JavaScript

The staple of web development continues its reign, also powering server-side programming via Node.js.

Python

Python remains a top choice for back-end development, especially for data-driven and cloud-enabled applications.

Popular Frameworks

Django

Django accelerates web development with its DRY principle and automatic admin interfaces.

Node.js

This JavaScript environment is celebrated for its event-driven model, adept at handling concurrent demands.

Svelte

Svelte's unique compile-time approach to component conversion yields fast-loading web pages compared to rival frameworks.

Qwick

Focused on speed, Qwick excels in delivering swift page loads by eschewing traditional framework limitations.

Harnessing Trends for Success

As we approach 2024, the trajectory of back-end and web development is set to incorporate these trends profoundly. Embracing them now ensures you remain at the forefront, ready to innovate and excel in a competitive digital landscape.

Are you keen to develop an app leveraging the latest advancements? Reach out and let's craft an up-to-date product.

#back-enddevelopment #webdevelopmenttrends #techinnovation #softwaredevelopment

https://shakuro.com/blog/back-end-web-development-trends-for-2024

A Comprehensive Overview of the Awesome-LLM repository

The Awesome-LLM repository is a rich resource for anyone interested in exploring large language models (LLMs), presenting a wide range of information including trending projects, milestones, papers, open-source frameworks, tools for deployment, opinions, courses, and more.

Trending LLM Projects

Trending projects within the LLM space are influential in the evolution of AI and language understanding. Examples include:

llm-course: A course dedicated to understanding and working with LLMs.
Mixtral 8x7B: Likely a reference to a specific model or framework used in the development of LLMs.
promptbase, ollama, anything-llm: Platforms or repositories that may provide resources, prompts, or datasets for LLM training and experimentation.
phi-2: Possibly referencing an advanced iteration of a language model.

Milestone Papers

The repository highlights milestone papers, charting the course of LLM development through significant contributions:

Transformers such as Google's "Attention Is All You Need" in 2017, establishing a new benchmark for machine learning models.
GPT and BERT, released by OpenAI and Google respectively, set new standards for language understanding.
Megatron-LM from NVIDIA and GPT variants, including GPT-2, GPT-3, and later models, demonstrate scalability and advanced language tasks.
T5, ZeRO, and work from DeepMind like Retro and Gopher, explore specialized architectures and training methods for LLMs.
Google's PaLM, Minerva, and models like Mistral and Meta's LLaMA, continue to push boundaries in terms of model size and capabilities.

Open LLM

Open LLM reflects the movement towards transparency and accessibility in LLMs:

Pre-training, Instruction Tuning, and Alignment are identified as key stages in developing a ChatGPT-like model.
Leaderboards such as Open LLM Leaderboard provide competitive evaluation grounds for these models.

Tools for Deploying LLM

Numerous tools exist to facilitate the deployment of LLMs, including:

HuggingFace, known for its transformer models and easy-to-use interfaces.
Haystack and LangChain for building applications that leverage the power of language models.
BentoML and other libraries are essential for deploying models into production environments.

Tutorials, Courses, and Opinions

Educational resources and community opinions shape how LLMs are perceived and applied:

Video tutorials and courses, available on platforms like YouTube, provide instruction in LLM-related technologies.
Books such as "Generative AI with LangChain" offer in-depth understanding and practical guidance.
Thought pieces and opinions, such as Noam Chomsky's view on ChatGPT's potential and limitations, contribute to the discourse around the ethical and practical implications of LLMs.

Other Useful Resources

To stay abreast of developments and tools, the repository includes additional resources like:

Arize-Phoenix for model monitoring and analytics.
Emergent Mind and platforms like ShareGPT for collaborative exploration.
Major LLMs + Data Availability section provides insight into the various available models and datasets aiding in LLM research.

Contributing to the Repository

The repository is maintained as a collaborative effort and encourages contributions. Individuals can participate by voting on pull requests to help decide the inclusion of new resources.

Tags: #LLM, #AI, #MachineLearning, #LanguageModels

https://github.com/Hannibal046/Awesome-LLM

Understanding GraphQL Subscriptions with Apollo Router

GraphQL subscriptions offer real-time data updates to clients. Apollo Router now supports self-hosted instances enabling subscriptions over WebSocket and HTTP.

The Role of Subscriptions in GraphQL

Subscriptions in GraphQL are operations allowing clients to receive real-time data, ideal for time-sensitive applications like stock trading or live sports updates. Unlike queries and mutations, subscriptions are long-lasting, meaning they can deliver multiple updates over time.

How They Work

GraphQL subscriptions operate by maintaining a persistent connection between the client and server. The Apollo Router facilitates executing these subscriptions against relevant subgraphs and returning the updates using a WebSocket subprotocol or an HTTP-callback protocol.

An example Subscription Request:

subscription OnStockPricesChanged {
  stockPricesChanged {
    ...
  }
}

In response, the server does not send a single response. Instead, it sends multiple pieces of data as they become available, allowing clients to stay updated in real-time.

Configuring Apollo Router for Subscriptions

Prerequisites

Before enabling subscriptions on Apollo Router, you need to:

Update Apollo Router instances to at least version 1.22.0.
Ensure your router is part of a GraphOS Enterprise organization.
Update your Apollo Federation to version 2.4 or later.
Modify your subgraph schemas to support Apollo Federation 2.4, adding necessary directives.
Update to Apollo Server version 4 for implementing subgraph.

Setting up the Router

Apollo Router's YAML configuration file needs to be updated with the communication protocols for handling subscriptions. The router supports various WebSocket subprotocols and an HTTP-callback protocol based on the subgraphs' expectations.

WebSocket Setup Example:

subscriptions:
  over_websocket:
  # subgraph configuration details...

HTTP Callback Setup Example:

public_url: https://example.com:4000/callback

Special Considerations

Any update to the supergraph schema causes all active subscriptions to terminate. Clients can detect this and initiate a new subscription.

Subscription Deduplication

Apollo Router can deduplicate subscriptions, reducing the load by using one connection for multiple identical subscriptions.

Subscription Termination on Schema Update

With every supergraph schema update, Apollo Router terminates active subscriptions, requiring clients to reconnect.

Advanced Configuration and Management

WebSocket Authentication Support

Apollo Router can propagate HTTP Authorization headers as connection parameters for WebSocket handshakes with subgraphs.

Event Queue Capacity

To manage a high volume of events, Apollo Router maintains an in-memory event queue, configurable for each active subscription.

Limiting Client Connections

You can set the maximum number of open subscription connections to prevent overloading the router's resources.

In conclusion, Apollo Router's support for GraphQL subscriptions expands its capability to cater to real-time data requirements. Its flexible configuration options for WebSocket and HTTP protocols, along with features like subscription deduplication and event queue management, make it a dependable choice for GraphQL-based enterprise solutions.

Tags:

#GraphQL
#ApolloRouter
#RealTimeData
#Subscription
#EnterpriseFeature

https://www.apollographql.com/docs/router/executing-operations/subscription-support/

Comprehensive Guide to Kotlin Multiplatform Mobile Libraries

Kotlin Multiplatform technology provides a way to use common logic across different platforms while maintaining the benefits of native programming. This guide introduces various libraries and tools available for Kotlin Multiplatform development, covering categories like tooling, networking, storage, UI components, and more.

Tooling Libraries and Plugins

Kotlin Multiplatform Mobile (KMM) Plugin

The KMM plugin aids developers in creating cross-platform applications that work on Android and iOS.

CocoaPods with Kotlin/Native

Kotlin/Native's integration with CocoaPods enables developers to add Pod library dependencies and use multiplatform projects as CocoaPods dependencies.

Swift Package for Kotlin

The Swift Package plugin helps developers in interoperability between Kotlin and Swift Package Multiplatform projects.

Carthage Integration

Carthage support allows for the integration of Carthage dependencies into KMM projects.

Libres

This tool generates string and image resources in Kotlin Multiplatform projects.

Storage Libraries

Multiplatform-Settings

It provides a way for key-value data persistence in Multiplatform apps.

SQLDelight

Generates typesafe Kotlin APIs from SQL statements, supporting schema and statement verification.

Realm

A mobile database that can be used directly on mobile devices.

Store 5

An abstraction for managing data requests and in-memory and on-disk caching.

Device Interaction Libraries

MOKO Permissions

This library offers runtime permissions on both iOS & Android platforms.

MOKO Geo

Allows for geolocation access in mobile Kotlin Multiplatform development.

Kable

A Kotlin library for Bluetooth Low Energy device interactions using coroutines.

Dependency Injection Libraries

Koin

A lightweight dependency injection framework for Kotlin, supporting a DSL.

Kodein

A simple dependency retrieval container for Kotlin Multiplatform development.

Logging Libraries

Napier

Provides multiplatform logging capabilities, with support for various platforms.

Kermit

A logging utility with adjustable log outputs and platform-specific implementations.

Networking Libraries

Ktor Client

Includes an asynchronous multiplatform HTTP client supporting various plugins.

Apollo GraphQL

A strongly-typed client for GraphQL, supporting the JVM, Android, and Kotlin multiplatform.

Architecture Libraries

MVI Kotlin

An MVI framework that supports shared code and includes debugging tools.

Mobius.kt

An implementation of Mobius, a functional reactive framework for managing state evolution and side effects.

Decompose

Aids in breaking down code into lifecycle-aware components with routing functionality.

Analytics Libraries

MOKO Crash Reporting

Enables crash reporting to Firebase Crashlytics for Kotlin Multiplatform Mobile.

UI Libraries

Compose Multiplatform

Libraries that provide UI components and enable shared UI code for different platforms, including Android and iOS.

Serialization Libraries

kotlinx.serialization

A Kotlin library that handles serialization, providing a runtime library and support for various formats.

Asynchronous Programming

Kotlinx Coroutines

An official Kotlin library that offers coroutine support for asynchronous programming.

Reaktive

Provides Kotlin multiplatform implementation of Reactive Extensions with coroutines support.

Generating Unique Identifiers

UUID

A Kotlin Multiplatform generator for creating UUIDs that works across various platforms.

Utility Libraries

Uri KMP

A multiplatform library enabling URI handling across different platforms.

Resources Management

MOKO Resources

Provides access to iOS and Android resources and supports system localization.

Final Remarks

The Kotlin Multiplatform ecosystem is rich with libraries that cater to various aspects of development. From foundation tools to specific domain libraries, developers can benefit from a wide range of functionalities, making cross-platform development more efficient and maintaining the advantages of native programming.

Tags: #KotlinMultiplatform, #MobileDevelopment, #CrossPlatformLibraries, #KMM

https://github.com/terrakok/kmp-awesome