Github Top Repositories

💡 lfnovo/open-notebook just hit the trending charts — here's why it matters. 🔗 https://github.com/lfnovo/open-notebook 📝 An Open Source implementation of Notebook LM with more flexibility and features ────────────────────────────── Welcome to Open Notebook, a private, multi-model, 100% local, full-featured alternative to Notebook LM. This platform empowers you to control your data, choose your AI models, and organize multi-modal content. With support for 18+ AI providers, including OpenAI, Anthropic, and Ollama, you can generate professional podcasts, search intelligently, and chat with context. Key Features include privacy-first design, multi-notebook organization, and universal content support. The platform also offers advanced podcast generation, intelligent search, and context-aware chat. To get started, simply download the docker-compose.yml file, set your encryption key, and start the services. Then, configure your AI provider and you're ready to create your first notebook. Open Notebook is perfect for researchers, students, and professionals who value data privacy and customization. With its comprehensive REST API and optional password protection, you can integrate Open Notebook into your existing workflow. In short, Open Notebook is the ultimate tool for anyone looking for a private, customizable, and powerful research platform. Take control of your data and unlock your full potential with Open Notebook. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 CopilotKit/CopilotKit is trending — and it deserves your attention. 🔗 https://github.com/CopilotKit/CopilotKit 📝 The Frontend Stack for Agents & Generative UI. React + Angular. Makers of the AG-UI Protocol ────────────────────────────── CopilotKit is a best-in-class SDK for building full-stack agentic applications, Generative UI, and chat applications. The key features include Chat UI, Backend Tool Rendering, Generative UI, Shared State, and Human-in-the-Loop workflows. To get started, you can use the npx copilotkit@latest create -f <framework> command for new projects or npx copilotkit@latest init for existing projects. The useAgent hook provides a superset of useCoAgent and offers more control over the agent connection. The Generative UI pattern allows agents to dynamically render UI as part of their workflow. With a strong focus on community and documentation, CopilotKit is perfect for developers looking to build cutting-edge applications. You can install it as a Claude Code plugin and explore the various skills and lifecycle journey skills. One-liner takeaway: CopilotKit is revolutionizing the way we build agentic applications, and you can get started in just one minute! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 chopratejas/headroom landed on trending. Worth a proper look. 🔗 https://github.com/chopratejas/headroom 📝 Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server. ────────────────────────────── Headroom is a context compression layer for AI agents that reduces the number of tokens sent to language models, resulting in significant savings. It achieves this through a combination of library, proxy, and agent wrap modes. Key features include cross-agent memory, reversible compression, and support for multiple algorithms. Technical highlights include the use of SmartCrusher for JSON compression, CodeCompressor for AST-aware compression, and Kompress-base for text compression. The CacheAligner ensures that provider KV caches are utilized effectively. Headroom is suitable for developers and researchers working with AI agents, particularly those who need to reduce the token count for their models. It supports various agents, including Claude, Codex, and Cursor, and can be integrated into existing workflows using the provided SDKs and APIs. To get started, simply install headroom-ai using pip or npm and follow the documentation for your specific use case. In summary, Headroom is a powerful tool for reducing token count in AI agent workflows, and its flexible architecture makes it easy to integrate into existing projects. With Headroom, you can compress everything, sacrifice nothing. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 NousResearch/hermes-agent caught my eye on GitHub Trending today. 🔗 https://github.com/NousResearch/hermes-agent 📝 The agent that grows with you ────────────────────────────── Hermes Agent is a self-improving AI agent built by Nous Research, designed to learn from experience and improve over time. It features a closed learning loop, allowing it to create skills from experience, improve them during use, and search its own past conversations. The agent can be run on a variety of platforms, including a $5 VPS, a GPU cluster, or serverless infrastructure, and can be accessed from Telegram, Discord, Slack, WhatsApp, Signal, or the command line. Key features include: - A real terminal interface with multiline editing, slash-command autocomplete, and conversation history - The ability to live where you do, with support for multiple messaging platforms - A closed learning loop with agent-curated memory and periodic nudges - Scheduled automations with a built-in cron scheduler - The ability to delegate and parallelize tasks using isolated subagents To get started, you can install Hermes Agent using a simple one-liner command, and then configure it using the hermes setup command. The agent supports a wide range of models and providers, including Nous Portal, OpenRouter, and Hugging Face. Technical highlights include support for multiple terminal backends, a research-ready architecture, and a scalable design that allows it to run on a variety of hardware configurations. The target audience for Hermes Agent includes developers, researchers, and anyone interested in building and interacting with AI agents. In summary, Hermes Agent is a powerful and flexible AI agent that can be used for a wide range of applications, from research and development to personal productivity and automation - it's an AI agent that learns and adapts to your needs. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 mvanhorn/last30days-skill is trending — and it deserves your attention. 🔗 https://github.com/mvanhorn/last30days-skill 📝 AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary ────────────────────────────── Introducing the /last30days-skill GitHub repository, a game-changing AI-powered search engine that aggregates information from various sources, including Reddit, X, YouTube, TikTok, and GitHub. This innovative tool scores results based on upvotes, likes, and real money, providing a more accurate and unbiased view of what's currently trending. Key features include a zero-config setup, immediate access to various platforms, and the ability to unlock additional sources with a simple setup wizard. The engine also features intelligent search, best takes, cross-source cluster merging, single-pass comparisons, and auto-discovered competitor comparisons. /last30days can be used in various ways, such as before a meeting to gather information about a person or company, when something drops to stay up-to-date on the latest news, or to compare tools and understand the world. Technical highlights include a Python pre-research brain that resolves topics and searches the right people and communities, a second judge that scores results for humor and virality, and a cross-source cluster merging feature that combines similar stories from different platforms. Audience includes anyone looking for a more accurate and comprehensive search engine, such as professionals, researchers, and individuals seeking to stay informed about current events. To get started, simply install the last30days-skill using Claude Code or other supported platforms, and begin searching with the /last30days command. In conclusion, /last30days-skill is a revolutionary search engine that provides a more accurate and unbiased view of what's currently trending, making it an essential tool for anyone seeking to stay informed in today's fast-paced world: Stay ahead of the curve with /last30days-skill, the ultimate AI-powered search engine. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 reconurge/flowsint is trending — and it deserves your attention. 🔗 https://github.com/reconurge/flowsint 📝 A modern platform for visual, flexible, and extensible graph-based investigations. For cybersecurity analysts and investigators. ────────────────────────────── Introduction to Flowsint: Flowsint is an open-source OSINT graph exploration tool designed for ethical investigation, transparency, and verification. It's built to help users explore relationships between entities through a visual graph interface and automated enrichers. Key Features: - Graph-based investigation - Automated enrichers for domains, IPs, social media, and more - Support for multiple data types, including domains, IPs, ASNs, and more - Modern and user-friendly interface Usage: To get started, users can install Flowsint using Docker and Make on Linux/macOS or using Docker Desktop on Windows. The application is accessible at http://localhost:5173. Technical Highlights: - Modular structure with separate modules for core utilities, enrichers, API, and frontend - Built using Python, FastAPI, and Pydantic - Supports PostgreSQL and Neo4j databases Audience: Flowsint is designed for cybersecurity researchers, journalists, law enforcement, and organizations conducting internal threat intelligence or digital risk analysis. Important Note: Flowsint is strictly for lawful, ethical investigation and research purposes. Any misuse of this software is prohibited. In short, Flowsint is a powerful tool for OSINT investigations - use it to uncover hidden connections, and always remember: with great power comes great responsibility. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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⚡ openclaw/openclaw-windows-node is making waves. Here's the full picture. 🔗 https://github.com/openclaw/openclaw-windows-node 📝 Windows companion suite for OpenClaw - System Tray app, Shared library, Node, and PowerToys Command Palette extension ────────────────────────────── The openclaw-windows-node repository is a native Windows companion suite for OpenClaw, the AI-powered personal assistant. This monorepo contains the Windows hub, shared client libraries, and CLI utilities. The suite includes a system tray application, a shared gateway client library, and a CLI validator for WebSocket connections. To get started, users can download the latest stable installer from the OpenClaw Windows docs or build the project using the provided build.ps1 script. The suite features a modern Windows 11-style system tray companion with dark/light mode support, quick send functionality, and auto-updates. It also includes an embedded chat window with WebView2, toast notifications, and channel control. Technical highlights of the project include the use of WinUI 3 for the system tray application and WebView2 for the embedded chat window. The project also utilizes dotnet for building and running the application. The audience for this project includes users of the OpenClaw personal assistant who want a native Windows companion suite. The project is designed to be user-friendly, with a simple setup process and an intuitive interface. In summary, the openclaw-windows-node repository provides a powerful and user-friendly native Windows companion suite for OpenClaw, with a range of features and technical capabilities. Transform your Windows PC into a node that OpenClaw can control, and unlock a world of possibilities! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet aquasecurity/trivy: a gem from today's GitHub trending list. 🔗 https://github.com/aquasecurity/trivy 📝 Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more ────────────────────────────── Trivy is a versatile security scanner that can detect security issues in various targets, including container images, filesystems, Git repositories, and Kubernetes. It has multiple scanners that look for known vulnerabilities, sensitive information, and misconfigurations. Key features include support for most programming languages, operating systems, and platforms, as well as integration with popular tools like GitHub Actions and VS Code. To get started with trivy, you can install it using common distribution channels like brew install trivy or docker run aquasec/trivy. The trivy command can be used to scan targets, such as trivy image python:3.4-alpine or trivy fs --scanners vuln,secret,misconfig myproject/. Technical highlights include canary builds generated with every push to the main branch, which can be used for testing but are not recommended for production use. Audience includes developers, security professionals, and anyone looking to improve the security of their applications and infrastructure. In summary, Trivy is a powerful tool for detecting security issues, and its ease of use and flexibility make it a great choice for anyone looking to improve their security posture - scan your code with Trivy today and sleep better tonight! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 github/copilot-sdk is trending — and it deserves your attention. 🔗 https://github.com/github/copilot-sdk 📝 Multi-platform SDK for integrating GitHub Copilot Agent into apps and services ────────────────────────────── The GitHub Copilot SDK is a game-changer for developers, allowing you to embed Copilot's intelligent workflows into your applications. With SDKs available for Python, TypeScript, Go, .NET, Java, and Rust, you can define agent behavior and let Copilot handle the heavy lifting. The SDKs communicate with the Copilot CLI server via JSON-RPC, managing the CLI process lifecycle automatically. You can install your preferred SDK using the provided commands and get started with the Getting Started Guide. The GitHub Copilot SDK supports multiple authentication methods, including GitHub signed-in user, OAuth GitHub App, and BYOK (Bring Your Own Key). It's production-ready, following semantic versioning, and has a CHANGELOG for release notes. Whether you're looking to speed up development or extend the functionality of Copilot, this SDK has got you covered. So, what are you waiting for? Get started today and unlock the full potential of GitHub Copilot - Automate your workflow, amplify your code. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 jwasham/coding-interview-university is trending — and it deserves your attention. 🔗 https://github.com/jwasham/coding-interview-university 📝 A complete computer science study plan to become a software engineer. ────────────────────────────── The jwasham/coding-interview-university repository is a comprehensive study plan for becoming a software engineer, covering everything you need to know for a technical interview at top companies like Amazon, Facebook, Google, and Microsoft. The plan is designed for those with some coding experience, and it's meant to be completed in a few months, with dedication and persistence. The repository includes a step-by-step guide on how to use it, with tasks lists to track progress, and it covers a wide range of topics, from data structures and algorithms to system design and scalability. It also provides additional resources for further learning, including books, video series, and computer science courses. The best part? You don't need to be a genius programmer to follow this plan - the creator of the repository, John Washam, is a self-taught software engineer who used this plan to get hired at Amazon. So, don't feel like you aren't smart enough - with dedication and hard work, you can achieve your goal of becoming a software engineer. Get started with the jwasham/coding-interview-university repository today and land your dream job in no time - with persistence and dedication, the sky's the limit! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into Open-LLM-VTuber/Open-LLM-VTuber — fresh off the trending list. 🔗 https://github.com/Open-LLM-VTuber/Open-LLM-VTuber 📝 Talk to any LLM with hands-free voice interaction, voice interruption, and Live2D taking face running locally across platforms ────────────────────────────── Open-LLM-VTuber is an innovative, voice-interactive AI companion that combines real-time voice conversations, visual perception, and a lively Live2D avatar. This project is designed to be a personal AI companion, offering a range of features and functionalities. Key Features: - Cross-platform support for macOS, Linux, and Windows - Offline mode support for complete privacy and security - Advanced interaction features, including visual perception, voice interruption, and touch feedback - Extensive model support for Large Language Models, Automatic Speech Recognition, and Text-to-Speech - Highly customizable with simple module configuration, character customization, and flexible Agent implementation To get started, you can refer to the Quick Start section in the documentation. The project is under active development, with a focus on v2.0 development. Audience: This project is suitable for developers, AI enthusiasts, and anyone looking for a unique AI companion experience. It offers a range of features and customization options, making it an attractive choice for those interested in AI technology. Technical Highlights: - Modular design for easy extension and customization - Support for GPU acceleration on macOS - Integration with various LLM, ASR, and TTS solutions In summary, Open-LLM-VTuber is a cutting-edge AI companion project that offers a unique blend of features, customization options, and technical capabilities. With its cross-platform support, offline mode, and advanced interaction features, it's an exciting project to explore. Join the community, contribute to the development, and experience the future of AI companionship - your personal AI friend is just a conversation away! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe