GitHub Trends

#go OpenCloud is an open-source server backend written in Go that lets you securely store, access, and share files without using a database, instead saving data directly on your filesystem for simplicity and scalability. It supports user authentication via OpenID Connect with external or built-in identity providers. You can build and run it locally with simple commands, and contribute by reporting issues, adding features, or improving documentation. This setup benefits you by offering a flexible, scalable, and secure cloud solution that is easy to install, customize, and control, helping you manage your data efficiently and privately. https://github.com/opencloud-eu/opencloud

#python#hackintosh#hackintosh_efi#lzhoang2601#lzhoang2801#macos#opencore#opencore_efi#opencoresimplify OpCore Simplify is a tool that makes it much easier to set up OpenCore EFI for Hackintosh systems by automatically creating the right configuration for your specific hardware. It checks your hardware, adds needed patches and drivers, and builds a ready-to-use EFI folder, saving you time and reducing mistakes. This means you can start installing macOS on your PC with a solid setup, even if you are new to Hackintosh. https://github.com/lzhoang2801/OpCore-Simplify

#python You can use an AI-powered call center solution built with Azure and OpenAI GPT to automate phone calls for tasks like insurance claims, IT support, and customer service. This system handles calls in multiple languages, streams conversations in real-time, resumes after disconnections, and stores data securely. It uses advanced AI models to understand complex information, manage sensitive data safely, and customize conversations to your needs. The solution scales easily on Azure, offers call recording, human fallback, and brand-specific voices, improving customer experience and reducing costs by automating routine calls while keeping quality and compliance high. This helps you provide 24/7 support efficiently and with personalized service. https://github.com/microsoft/call-center-ai

#qml#dotfiles#hyprland#linux#material_design#quickshell#rice#ricing#unixporn#wayland This Hyprland dotfiles setup gives you a modern, easy-to-use Linux desktop with features like a live app overview, AI integration (Gemini and Ollama), and automatic, beautiful color themes that match your wallpaper. Installation is simple with a one-line command, and the default keybinds are familiar if you’ve used Windows or GNOME. The system uses Quickshell for widgets (not Waybar), shows every command during setup for transparency, and offers a friendly Discord community for help. You benefit from a polished, customizable environment that’s both visually appealing and practical, with support for new users and advanced customization options. https://github.com/end-4/dots-hyprland

#cplusplus#oculus#oculus_quest#oculus_quest_2#openxr#vr WiVRn lets you wirelessly connect your standalone VR headset (like Meta Quest or Pico) to a Linux PC, so you can play PC VR games with the computer doing all the processing. It supports many headsets and uses OpenXR for compatibility with most VR apps, including SteamVR games. You install a server on your Linux PC and a client app on your headset, then connect over WiFi or USB. This setup gives you a wireless VR experience with good tracking and audio, letting you enjoy PC-quality VR without cables. It’s open source and works well on various Linux distributions. https://github.com/WiVRn/WiVRn

#other Kimi K2 is a powerful AI language model with 1 trillion parameters, designed to understand very long texts and perform complex tasks like coding, reasoning, and using tools autonomously. It excels at writing and debugging code, solving math and science problems, and managing multi-step workflows by calling external tools or APIs automatically. You can access it via an easy-to-use API or deploy it on popular platforms. This means you get a smart assistant that not only answers questions but also acts to complete tasks, making your work faster and more efficient, especially for coding and research projects. https://github.com/MoonshotAI/Kimi-K2

#go#a2a#agents#agents_sdk#ai#aiagentframework#gemini#genai#go#llm#mcp#multi_agent_collaboration#multi_agent_systems#sdk#vertex_ai The Agent Development Kit (ADK) for Go is an open-source toolkit that makes it easy to build, test, and deploy smart AI agents using the Go programming language. It lets you create simple or complex agent workflows, use ready-made or custom tools, and run your agents anywhere, especially in cloud environments. With ADK, you get full control, flexibility, and the ability to scale your applications, making it faster and simpler to develop powerful AI solutions for real-world tasks. https://github.com/google/adk-go

#shell#aesthetic#dark_mode#dynamic#hyde#hyprdots#light_mode#themes#unix_porn#wallpapers HyDE is a clean, modular, and visually appealing development environment designed for Hyprland on Arch Linux and some Arch-based distros. It offers easy installation via a script that auto-detects NVIDIA cards and configures necessary drivers, but it may conflict with existing desktop environments or theming. You can customize it with many official and community themes using a tool called themepatcher. HyDE keeps your configuration organized and separate from core scripts, making updates safer and simpler. It also supports running in a virtual machine for testing. Joining the HyDE Discord community helps you get support and share ideas. This setup benefits you by providing a stylish, maintainable, and customizable desktop environment with a smooth update process and community support. https://github.com/HyDE-Project/HyDE

#rust#librespot#rust#spotify#spotify_connect Librespot is a free, open-source tool that lets you play and control Spotify music on your own devices, acting like a Spotify Connect receiver. It works with Spotify Premium and supports many audio systems, letting you stream music easily and privately. You can install it on different operating systems and customize how it works, making it simple to use Spotify on devices that don’t officially support it. https://github.com/librespot-org/librespot

#python This project teaches you how to build a real-world AI research assistant that automatically finds, reads, and answers questions about academic papers using a technique called Retrieval-Augmented Generation (RAG)[1][2][3]. RAG works by first searching for the most relevant information from a large collection of documents, then using a language model to generate clear, accurate answers based on that information—this means you get answers that are up-to-date and grounded in real sources, not just what the AI remembers from its training[1][2][3]. The course is hands-on: each week, you add a new piece, starting with setting up the technical infrastructure, then building automated data pipelines to fetch and process papers, adding powerful search tools (first with keywords, then with AI-powered semantic search), and finally connecting everything to a local AI model that can chat with you and explain complex topics in simple language. By the end, you’ll have a working system you can use to quickly find and understand research papers, and you’ll gain the skills to build similar AI tools for any field—all while learning the best practices used by professional engineers. The main benefit is that you get practical, production-ready AI skills and a tool that makes research faster and more reliable, with answers you can trust because they come directly from the latest papers. https://github.com/jamwithai/arxiv-paper-curator

#python You can use Tinker and Tinker Cookbook to easily fine-tune large language models (LLMs) for your specific needs without managing complex training infrastructure. Tinker handles distributed training and uses efficient LoRA adapters to reduce costs and speed up customization. The Cookbook offers ready-made examples and tools for tasks like chat, math reasoning, and reinforcement learning, helping you quickly build and improve AI models. This means you can create AI that better fits your domain, runs faster, and follows your rules, all while saving time and computing resources. It’s great for researchers, developers, and teams wanting powerful, flexible AI customization. https://github.com/thinking-machines-lab/tinker-cookbook

#python#agents#artificial_intelligence#cybersecurity#generative_ai#llm#penetration_testing Strix is a free, open-source tool that uses AI agents to automatically find and fix security problems in your apps by acting like real hackers—running your code, hunting for vulnerabilities, and proving they’re real by actually exploiting them, not just guessing[1][2]. It works fast, gives clear reports, and can even suggest fixes or create pull requests to help you secure your code quickly. You can run it on your own computer, in your development pipeline, or use a cloud version for easier setup. The main benefit is that you get thorough, real-world security testing without the slow pace and high cost of manual checks, helping you catch and fix issues before they become serious problems. https://github.com/usestrix/strix