Github Top Repositories

💼 20 GitHub Repositories to Help You Get Hired 1. coding-interview-university A complete self-study roadmap originally created to prepare for Google software engineering interviews. 2. awesome-interview-questions A curated collection of technical interview questions across dozens of programming languages and technologies. 3. system-design-primer One of the best resources for mastering system design interviews at top tech companies. 4. build-your-own-x Learn by building your own database, operating system, Git, Docker, Redis, and dozens of other technologies. 5. developer-roadmap Interactive roadmaps showing exactly what to learn for frontend, backend, DevOps, AI, cybersecurity, and more. 6. project-based-learning Learn programming by building real projects instead of following endless tutorials. 7. app-ideas Hundreds of project ideas ranging from beginner to advanced to strengthen your portfolio. 8. public-apis A massive collection of free APIs you can use to build real-world portfolio projects. 9. free-programming-books Thousands of free programming books, courses, and learning resources in multiple languages. 10. first-contributions A step-by-step guide that teaches you how to make your first pull request. 11. frontend-practice Practice rebuilding real company websites to improve your frontend development skills. 12. Frontend Mentor Challenges Realistic UI challenges that help you build an employer-ready frontend portfolio. 13. awesome-resume A professional, ATS-friendly resume template widely used by software engineers. 14. The Algorithms A huge collection of algorithms and data structures implemented in dozens of programming languages. 15. Tech Interview Handbook Covers coding interviews, behavioral interviews, resume tips, salary negotiation, and more. 16. awesome The original Awesome list containing thousands of carefully curated developer resources. 17. realworld Build the same production-grade application in different frameworks to learn industry architecture. 18. awesome-for-beginners Find beginner-friendly open source projects to make your first GitHub contributions. 19. awesome-cheatsheets A collection of programming and DevOps cheat sheets for quick reference during development. 20. Awesome Job Boards A curated collection of the best tech job boards, including remote, startup, and developer-focused hiring platforms. 💻 Master these repositories, build projects from them, contribute to open source, and you'll have both the skills and portfolio that recruiters actually look for. #GitHub #DevCommunity #OpenSource #Programming #SoftwareEngineering #CareerGrowth ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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Duplicati – a free, open-source tool for encrypted and deduplicated backup 🛡️🔐 It stores data as encrypted blocks in a local folder, on an external drive, or in the cloud ☁️💾 Duplicati is focused on automatic, scheduled backups with a web interface, making it convenient for home users 🏠📅 Languages: C# (93.0%), JavaScript (3.0%), HTML (1.6%), ... 💻📊 ⭐️ Star 14.4k https://github.com/duplicati/duplicati 🔗🌐 #Backup #OpenSource #DataSecurity #Tech #Cloud #Duplicati

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💡 EveryInc/compound-engineering-plugin just hit the trending charts — here's why it matters. 📈 🔗 https://github.com/EveryInc/compound-engineering-plugin 📝 Official Compound Engineering plugin for Claude Code, Codex, Cursor, and more ────────────────────────────── The compound-engineering-plugin is designed to make each unit of engineering work easier than the last. 🛠️ It inverts traditional development by focusing 80% on planning and review, and 20% on execution. The plugin provides 37 skills and 51 agents to help with tasks such as brainstorming, planning, coding, reviewing, and compounding knowledge. 🧠 To use the plugin, start by installing it using the following commands: /plugin marketplace add EveryInc/compound-engineering-plugin /plugin install compound-engineering For other platforms like Codex, Copilot, or Qwen Code, use equivalent commands. Once installed, run the setup: /ce-setup Key features include: * 🤔 /ce-brainstorm for interactive Q&A * 📋 /ce-plan for turning ideas into implementation plans * 🔄 /ce-compound for documenting learnings The plugin is suitable for developers looking to streamline their workflow and improve productivity. 🚀 /ce-strategy, /ce-ideate, /ce-brainstorm, /ce-plan, /ce-work, /ce-debug, /ce-code-review, /ce-compound These skills work together to create a cyclical workflow that sharpens plans, informs future plans, and catches issues. 💡 Takeaway: With the compound-engineering-plugin, each unit of work makes the next one easier, not harder. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe #CompoundEngineering #Plugin #DevTools #Coding #Productivity #GitHub ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

🎯 citrolabs/ego-lite landed on trending. Worth a proper look. 🔗 https://github.com/citrolabs/ego-lite 📝 The fastest browser for AI agents to run browser automation, built for sharing your logged-in browser state with your AI agents, like Codex or Claude Code, without disturbing you. Zero cost, zero config. ────────────────────────────── Introducing ego lite, a browser designed for parallel work between humans and AI agents. It allows agents to run multiple browser tasks in isolated Spaces, increasing task completion speed and reducing token usage. Key features include a dedicated Space for each agent, multitasking capabilities, and high-quality page snapshots. The ego-browser skill enables any agent to drive the browser, exposing it as a set of in-page JavaScript tools. To get started, simply download and install the ego lite app, add the ego-browser skill, or let your agent set it up. Then, run your first task using the /ego-browser command. Technical highlights include a code base approach for faster runs, a dedicated Space for each agent, and the strongest page snapshot on the market. The target audience is developers and users of AI agents looking for a more efficient and parallel browsing experience. In summary: ego lite is a game-changer for AI-powered browser automation - it's the browser that lets you work alongside your AI agents, not against them. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 cactus-compute/needle landed on trending. Worth a proper look. 🔗 https://github.com/cactus-compute/needle 📝 14MB foundation model for tiny devices; phones, wearables, smart home, and robots. ────────────────────────────── Needle 2 is an open-source, 45M-parameter model designed for tool calling, device use, and structured extraction. It's a compact, self-contained model that runs on a single 14MB binary, using approximately 28MB of RAM. Key features include a simple contract for tool calls, confidence-gated responses, and tool retrieval capabilities. To get started, you can install the cactus-needle package using pip install cactus-needle, then describe your tools and call them from Python. The model supports fine-tuning with LoRA, allowing you to adapt it to your specific use case. The model is suitable for developers and researchers looking to integrate a compact, versatile AI model into their applications. One-liner takeaway: Needle 2 packs a punch as a tiny, 14MB model that delivers big on tool calling and structured extraction capabilities. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 cordiverse/cordis is trending — and it deserves your attention. 🔗 https://github.com/cordiverse/cordis 📝 Meta-Framework of Spatiotemporal Composability ────────────────────────────── The Cordis repository on GitHub is an open-source project that focuses on data science and machine learning applications. The purpose of Cordis is to provide a framework for building and deploying scalable data pipelines. Key features of Cordis include modular design, flexible configuration options, and support for various data sources. To use Cordis, users can import the necessary modules and define their data pipelines using a simple and intuitive API. From a technical perspective, Cordis is built using modern JavaScript and TypeScript, and it leverages popular data science libraries. Cordis is designed for data scientists and engineers who want to streamline their data workflows. In a nutshell, Cordis simplifies data science: Build once, deploy anywhere - that's the power of Cordis. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🚀 Meet HKUDS/CLI-Anything: a gem from today's GitHub trending list. 🔗 https://github.com/HKUDS/CLI-Anything 📝 "CLI-Anything: Making ALL Software Agent-Native" -- CLI-Hub:https://clianything.cc/ ────────────────────────────── CLI-Anything is an innovative project that bridges the gap between AI agents and the world's software by making any software agent-ready. The project's primary goal is to create a community-driven hub where users can browse, install, and manage various Command-Line Interfaces (CLIs) for different software applications. Key Features: - CLI-Hub: A centralized registry where users can discover, install, and manage CLIs for various software applications. - One Command Line: A unified interface for interacting with different software applications. - Community-Driven: Users can contribute to the project by creating and sharing their own CLIs. Technical Highlights: - Built using Python and Click. - Uses Pytest for testing and coverage. - Supports multiple output formats, including JSON and human-readable text. The project is suitable for developers, researchers, and power users who want to automate tasks, integrate different software applications, or create custom workflows. With CLI-Anything, users can harness the power of AI agents to interact with a wide range of software applications, from productivity tools to creative software. In a nutshell, CLI-Anything is revolutionizing the way we interact with software by providing a unified, community-driven platform for creating and sharing CLIs - Empowering humans and agents to achieve more, one command line at a time! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ unslothai/unsloth is making waves. Here's the full picture. 🔗 https://github.com/unslothai/unsloth 📝 Local UI to run and train LLMs and diffusion models, including Qwen3.8, Kimi K3, MiniMax-H3, Gemma 4, DeepSeek-V4, FLUX and more. ────────────────────────────── Unsloth is a revolutionary desktop app that allows you to run, train, and deploy AI models locally. With support for various types of models, including LLMs, diffusion, embedding, and audio models, Unsloth provides a comprehensive platform for AI development. Key Features: Unsloth offers a range of features, including running and training models, fine-tuning, and deploying models with support for multiple hardware configurations, including CPU, NVIDIA, AMD, and Intel. It also provides remote access to your local models through secure Cloudflare HTTPS. Usage: To get started with Unsloth, you can download the native desktop app for your operating system or install it manually using the provided installation scripts. Unsloth can be used in three ways: Unsloth Desktop, Unsloth Studio (web UI), and Unsloth Core (code-based version). Technical Highlights: Unsloth supports various backends, including PyTorch, MLX, and GGUF, allowing for flexible model deployment. It also provides tools like Claude Code, Codex, and MCP for local model usage. Audience: Unsloth is designed for developers, researchers, and AI enthusiasts who want to run, train, and deploy AI models locally. With its user-friendly interface and comprehensive documentation, Unsloth is accessible to both beginners and experienced users. Takeaway: Unsloth is the ultimate AI development platform, providing a seamless and secure way to run, train, and deploy AI models locally, making it an essential tool for anyone working with AI. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: infiniflow/ragflow — let's break it down. 🔗 https://github.com/infiniflow/ragflow 📝 RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs ────────────────────────────── The RAGFlow project on GitHub is an open-source Retrieval-Augmented Generation engine that combines cutting-edge RAG with Agent capabilities. It offers a streamlined RAG workflow adaptable to enterprises of any scale. The key features of RAGFlow include deep document understanding, template-based chunking, grounded citations with reduced hallucinations, and compatibility with heterogeneous data sources. To get started with RAGFlow, you can try the cloud service at https://cloud.ragflow.io or self-host the server using Docker. The project has a system architecture that includes a converged context engine and pre-built agent templates. RAGFlow enables developers to transform complex data into high-fidelity, production-ready AI systems with exceptional efficiency and precision. The primary audience for RAGFlow appears to be developers and enterprises looking to leverage the power of RAG and Agent capabilities to create superior context layers for LLMs. Overall, RAGFlow is a powerful tool for anyone looking to harness the potential of Retrieval-Augmented Generation. So, why wait? Dive into RAGFlow and unlock the full potential of your AI systems today! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into basecamp/omarchy — fresh off the trending list. 🔗 https://github.com/basecamp/omarchy 📝 Beautiful, Modern & Opinionated Linux ────────────────────────────── Check out Omarchy, a sleek Linux distribution from Basecamp and created by DHH. It's designed to be modern and opinionated, making it a unique offering in the Linux world. To learn more, head over to omarchy.org. Omarchy is released under the MIT License, making it accessible to everyone. Whether you're a seasoned developer or just starting out, Omarchy is worth exploring. With its beautiful design and modern approach, it's perfect for those looking for a fresh take on Linux. One thing is for sure: Omarchy is a game-changer, and you should try it out - Omarchy is the Linux distribution that will make you wonder how you ever lived without it! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet OpenCut-app/OpenCut: a gem from today's GitHub trending list. 🔗 https://github.com/OpenCut-app/OpenCut 📝 The open-source CapCut alternative ────────────────────────────── OpenCut is a free and open source video editor designed for web, desktop, and mobile platforms. Its key features include a Rust core for seamless performance across devices, a plugin-first architecture, and a headless mode for automation and batch rendering. The Editor API and MCP server for AI agents are also in the pipeline. To get started with development, you can install proto and use it to set up the required tools. The repository provides scripts for web:dev, api:dev, and desktop:dev environments. Although the project is not yet open to outside contributions, you can join the Discord community to follow along, ask questions, or simply hang out. OpenCut is supported by companies like fal.ai, which provides generative image, video, and audio models. One-liner takeaway: OpenCut is revolutionizing video editing with its open source, cross-platform approach, and it's definitely one to watch in the world of creator tools! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: ToolJet/ToolJet — let's break it down. 🔗 https://github.com/ToolJet/ToolJet 📝 ToolJet is the open-source foundation of ToolJet AI - the enterprise app generation platform for building internal tools, dashboard, business applications, workflows and AI agents 🚀 ────────────────────────────── ToolJet is an open-source, AI-native platform for building and deploying internal tools, workflows, and AI agents. The community edition offers a visual builder, drag-and-drop UI, and integrations with databases, APIs, SaaS apps, and object storage. Key features include a built-in no-code database, multi-page apps, and collaboration tools. To get started, you can try ToolJet Cloud or self-host using Docker with the following command: docker run \ --name tooljet \ --restart unless-stopped \ -p 80:80 \ --platform linux/amd64 \ -v tooljet_data:/var/lib/postgresql/13/main \ tooljet/try:ee-lts-latest ToolJet is perfect for developers, DevOps teams, and businesses looking for a flexible, extensible, and secure platform. Join the community and start building today - your next-gen internal tool is just a click away! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 ToolJet/ToolJet just hit the trending charts — here's why it matters. 🔗 https://github.com/ToolJet/ToolJet 📝 ToolJet is the open-source foundation of ToolJet AI - the enterprise app generation platform for building internal tools, dashboard, business applications, workflows and AI agents 🚀 ────────────────────────────── ToolJet is an open-source platform for building and deploying internal tools, workflows, and AI agents. It offers a visual builder with a drag-and-drop UI, integrations with databases, APIs, SaaS apps, and object storage. Key features include a built-in no-code database, multi-page apps and multiplayer editing, and 80+ data sources. To get started, you can create a ToolJet Cloud account or self-host using Docker with the following command: docker run \ --name tooljet \ --restart unless-stopped \ -p 80:80 \ --platform linux/amd64 \ -v tooljet_data:/var/lib/postgresql/13/main \ tooljet/try:ee-lts-latest ToolJet is ideal for developers, businesses, and organizations looking to streamline their workflows and build custom tools. With its extensive documentation and community support, it's easy to get started and find help when needed. One-liner takeaway: ToolJet empowers you to build and deploy custom tools and workflows with ease, making it a game-changer for businesses and developers alike. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: akitaonrails/ai-memory — let's break it down. 🔗 https://github.com/akitaonrails/ai-memory 📝 Solution for long term memory for agent coding CLIs and to facilitate handoff between different agent vendors ────────────────────────────── ai-memory is a tool that gives long-term memory to AI coding agents, allowing them to pick up where they left off, even if they're switched out for a different agent. It does this by creating a shared, persistent wiki compiled from sanitized lifecycle observations. Key features include zero-friction lifecycle capture, opt-in managed workstreams, per-repository capture exclusions, and optional per-operator memory slots. ai-memory supports a wide range of agents, including Claude Code, Codex, Command Code, and more. To use ai-memory, simply run it in the same directory as your agent, and it will take care of the rest. From a technical standpoint, ai-memory uses a git repo to store its wiki, making it easy to grep and backup. This tool is ideal for developers who use multiple AI coding agents and want to streamline their workflow. In short, ai-memory is a game-changer for AI coding agents - it's like having a personal assistant that remembers where you left off, so you can pick up right where you started! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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