Github Top Repositories

💡 cathrynlavery/diagram-design just hit the trending charts — here's why it matters. 🔗 https://github.com/cathrynlavery/diagram-design 📝 29 editorial diagram types for Claude Code. Self-contained HTML + SVG. No shadows, no Mermaid-slop. ────────────────────────────── The diagram-design GitHub repository is a game-changer for creating editorial-quality diagrams that match your brand in just 60 seconds. This innovative tool offers 27 visual types, including architecture, flowcharts, and pyramids, all with a focus on simplicity and clarity. With diagram-design, you can say goodbye to generic rounded boxes and tedious design sessions. The repository provides a Claude Code skill that can be easily installed and updated, allowing you to create diagrams that are accessible by default. The skill also includes features like automatic brand matching, which extracts your website's colors and typography to ensure a consistent look and feel. Whether you're a developer, designer, or writer, diagram-design is an essential tool for anyone looking to create high-quality diagrams without the hassle. So why wait? Explore the live gallery at cathrynlavery.github.io/diagram-design and discover the power of editorial-quality diagrams for yourself. Create stunning diagrams that elevate your brand - no design experience required! ────────────────────────────── 🧠 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

🌟 lightningpixel/modly caught my eye on GitHub Trending today. 🔗 https://github.com/lightningpixel/modly 📝 Desktop app to generate 3D models from images using local AI — runs entirely on your GPU ────────────────────────────── Modly is a local, open source, AI-powered image-to-3D mesh generation tool that turns any photo into a 3D model using open source AI models running entirely on your GPU. It's a desktop application for Windows, Linux, and Apple Silicon macOS. Key features include AI-powered 3D mesh generation, extension system for external model and process extensions, and a CLI for automation. To get started, simply download the latest installer, install JS dependencies with npm install, and set up the Python backend. You can then run Modly in development with npm run dev and start experimenting with its features. The tool is designed for developers, 3D artists, and anyone interested in AI-powered 3D modeling. With its user-friendly interface and extensive documentation, Modly is an excellent choice for those looking to explore the world of 3D modeling. One-liner takeaway: Transform your photos into stunning 3D models with Modly, the local, open-source, AI-powered 3D mesh generation tool! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 Lightricks/LTX-2 is trending — and it deserves your attention. 🔗 https://github.com/Lightricks/LTX-2 📝 Official Python inference and LoRA trainer package for the LTX-2 audio–video generative model. ────────────────────────────── The Lightricks/LTX-2 GitHub repository introduces the LTX-2 model, a cutting-edge DiT-based audio-video foundation model that incorporates all core capabilities of modern video generation in one model. This includes synchronized audio and video, high fidelity, multiple performance modes, production-ready outputs, API access, and open access. To get started, users can git clone the repository, install dependencies with uv sync --extra natten, and download the required models from Hugging Face. The repository provides a Quick Start guide, which demonstrates how to generate videos using the distilled model and pipeline. From a technical standpoint, LTX-2 boasts an array of impressive features, including diffusion-based video and audio VAEs, text encoders, and spatial upscalers. The model is designed to be highly flexible, with support for various pipelines, such as DistilledPipeline, DFRPipeline, and TI2VidTwoStagesPipeline, each offering unique capabilities and trade-offs between speed and quality. The target audience for LTX-2 appears to be developers, researchers, and content creators interested in exploring the latest advancements in video generation technology. With its extensive documentation, pre-trained models, and open-access policy, the Lightricks/LTX-2 repository is an invaluable resource for anyone looking to push the boundaries of audio-video production. In short, LTX-2 is a game-changer for video generation, and its impact will be felt across various industries - get ready to revolutionize your video content creation with LTX-2! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ msitarzewski/agency-agents is making waves. Here's the full picture. 🔗 https://github.com/msitarzewski/agency-agents 📝 A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes, and proven deliverables. ────────────────────────────── Welcome to The Agency, a collection of AI agent personalities that can transform your workflow. Each agent is specialized in their domain, has a unique personality, and is production-ready. The Agency offers a range of agents, including Frontend Developer, Backend Architect, and AI Engineer, each with their own strengths and expertise. You can use The Agency in various ways, including: * Installing the Agency Agents app, which allows you to browse and install agents into your preferred tools, such as Claude Code, Cursor, or Codex. * Using the command line to install agents into your tools. * Browsing the agents and copying/adapting the ones you need. The Agency is technical highlight is its ability to provide deliverable-focused agents that can help you with real code, processes, and measurable outcomes. The Agency is suitable for developers, engineers, and anyone looking to streamline their workflow and improve productivity. One-liner takeaway: Transform your workflow with The Agency's specialized AI agents, and never sleep on innovation again! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 3b1b/manim is trending — and it deserves your attention. 🔗 https://github.com/3b1b/manim 📝 Animation engine for explanatory math videos ────────────────────────────── Manim is a powerful engine for creating precise programmatic animations, specifically designed for explanatory math videos. It allows users to create custom animations using Python, with features like LaTeX support, FFmpeg integration, and OpenGL rendering. To get started, simply install manimgl using pip install manimgl and try out the example scenes. The engine runs on Python 3.10 or higher and has system requirements like FFmpeg, OpenGL, and optional LaTeX. For Linux, additional dependencies like Pango are needed. Manim is suitable for math educators, animators, and anyone looking to create engaging explanatory content. With its extensive documentation and active community, including a subreddit and Discord, users can easily find resources and support. The project is licensed under MIT and welcomes contributions. With its flexibility and customization options, Manim is an ideal choice for creating high-quality educational content. One-liner takeaway: Create stunning math animations with ease using Manim, the perfect tool for educators and animators alike! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 kepano/obsidian-skills is trending — and it deserves your attention. 🔗 https://github.com/kepano/obsidian-skills 📝 Agent skills for Obsidian. Teach your agent to use Obsidian CLI and open formats including Markdown, Bases, JSON Canvas. ────────────────────────────── The kepano/obsidian-skills GitHub repository offers a collection of skills designed for use with Obsidian, following the Agent Skills specification. These skills enable users to interact with Obsidian vaults, create and edit various file types, and more. Key features include skills for Obsidian Flavored Markdown, Obsidian Bases, JSON Canvas, Obsidian CLI, and Defuddle. Users can install these skills via the marketplace, npx skills, or manual methods, depending on their preferred agent, such as Claude Code, Codex, or Open Code. To get started, users can install the skills using npx skills add https://github.com/kepano/obsidian-skills or by following the manual installation guides for their specific agent. The skills are useful for developers and power users of Obsidian, providing a range of functionalities to enhance their workflow. In a nutshell, the kepano/obsidian-skills repository is a game-changer for Obsidian users, offering a suite of skills to boost productivity and unlock new possibilities - Supercharge your Obsidian workflow with these powerful skills! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into holaboss-ai/holaOS — fresh off the trending list. 🔗 https://github.com/holaboss-ai/holaOS 📝 Open-source All in One AI agent workspace. Run any agent — Claude Code, Codex — across your tools (100+ integrations + MCP), apps, browser, and files, with shared memory. Built-in models or BYOK. ────────────────────────────── Meet holaOS, the ultimate workspace for you and your agent. It allows you to run any agent, including Claude Code, Codex, or the built-in holaOS agent, in one local-first workspace. This means you can work with multiple agents, sharing the same memory, tools, and skills, without having to switch between them. Key features include: - Running any agent in one workspace - Shared memory across agents and sessions - Support for frontier models, including Kimi K3, GLM 5.2, GPT 5.6, Claude Opus 5, and Fable 5 - Ability to bring your own model keys - HolaApps, which allow you to install apps from the in-workspace marketplace and use them side-by-side with your agent - Skills, integrations, and Model Context Protocol (MCP) support Usage is straightforward: simply download and install the desktop app, and you're ready to go. The app is open-source and free to start, with optional enterprise features available. From a technical standpoint, holaOS is built using TypeScript and Electron, and supports macOS, Windows, and Linux platforms. The target audience for holaOS includes anyone looking for a flexible and powerful workspace for their agent, including developers, researchers, and business users. In summary, holaOS is a game-changer for anyone working with agents, offering a flexible, powerful, and easy-to-use workspace that can be customized to meet your needs. Get started with holaOS today and experience the power of a unified workspace for you and your agent! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ NVIDIA-NeMo/Switchyard is making waves. Here's the full picture. 🔗 https://github.com/NVIDIA-NeMo/Switchyard 📝 No description. ────────────────────────────── Introducing Switchyard, a Rust proxy and library designed for Large Language Model (LLM) traffic management. It routes requests across multiple providers, translates between OpenAI and Anthropic APIs, records operational metrics, and provides typed, composable routing algorithms. Main features include protocol translation, multi-backend routing, and operational metrics. You can use Switchyard as a launcher, server, or library, making it a versatile tool for managing LLM traffic. To get started, you can choose the launcher path to run coding agents like Claude Code or Codex through Switchyard, the server path to run Switchyard as a standalone proxy, or the library path to embed routing algorithms in your own Rust application. Technical highlights include support for various routing strategies, such as LLM classifier, stage router, escalation router, and random routing. Switchyard also provides a simple architecture for routing and translation. Switchyard is designed for developers and researchers working with LLMs, especially those who need to manage traffic across multiple models and providers. In a nutshell, Switchyard is your one-stop solution for LLM traffic management - route, translate, and optimize your way to AI efficiency. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 smicallef/spiderfoot is trending — and it deserves your attention. 🔗 https://github.com/smicallef/spiderfoot 📝 SpiderFoot automates OSINT for threat intelligence and mapping your attack surface. ────────────────────────────── SpiderFoot is an open-source intelligence (OSINT) automation tool that integrates with numerous data sources and utilizes various methods for data analysis. It offers a web-based interface and command-line functionality, all written in Python 3 and MIT-licensed. Key features include over 200 modules, a YAML-configurable correlation engine, and support for CSV/JSON/GEXF export. It also has TOR integration for dark web searches and a Dockerfile for Docker-based deployments. This tool can be used for both offensive and defensive purposes, such as reconnaissance or gathering information about exposed internet assets. It's highly configurable, fully documented, and has a visual interface. The target audience includes security professionals, developers, and anyone interested in OSINT and data analysis. Overall, SpiderFoot is a powerful tool for automating OSINT tasks and analyzing large amounts of data. With its extensive features and customization options, it's an essential tool for anyone looking to streamline their OSINT workflow: SpiderFoot is your ultimate OSINT sidekick! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: megadose/holehe — let's break it down. 🔗 https://github.com/megadose/holehe 📝 holehe allows you to check if the mail is used on different sites like twitter, instagram and will retrieve information on sites with the forgotten password function. ────────────────────────────── Holehe is an Open-Source Intelligence (OSINT) tool that efficiently finds registered accounts from emails. It checks if an email is attached to an account on over 120 sites like Twitter, Instagram, and Imgur. Key features include: - retrieving information using the forgotten password function - not alerting the target email - running on Python 3 To use Holehe, you can install it via pip3 install holehe, git clone, or docker. holehe test@gmail.com is a simple command to run the tool. For more complex usage, you can integrate it into your Python applications. The output is a dictionary with information like rate limits, account existence, and sometimes partially obfuscated recovery emails and phone numbers. This tool is perfect for security researchers, OSINT investigators, and anyone interested in email reconnaissance. One-liner takeaway: Holehe is a must-have OSINT tool that helps you uncover hidden email accounts without alerting the target. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ macro-inc/macro is making waves. Here's the full picture. 🔗 https://github.com/macro-inc/macro 📝 Macro is a unified workspace for teams: email, chat, docs, tasks, agents, calls, and CRM — @-linked together with shared AI memory. ────────────────────────────── Hey there, let's check out the Macro GitHub repo. Macro is an all-in-one workspace that combines email, messages, docs, tasks, agents, and CRM into a single, fast interface with shared team-level memory. It's designed to be a single operating system for your team, eliminating the need for multiple tools. The key features of Macro include: - Modular blocks that work together like Lego, allowing for customization and extensibility - Bidirectional graph for cross-references between different surfaces, such as docs and tasks - Real-time collaborative editing with CRDTs, making it feel like you're editing on the same computer In terms of technical highlights, Macro is built with SolidJS and Rust for speed and reliability. The CRDT collaboration system allows for seamless editing and conflict resolution, even with multiple agents operating simultaneously. Macro is suitable for small companies or teams within larger companies, looking for an all-in-one workspace solution. The ideal audience includes teams seeking to streamline their workflow, reduce tool clutter, and improve collaboration. One-liner takeaway: Simplify your team's workflow with Macro, the all-in-one workspace that's about to revolutionize how you get things done! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into unslothai/unsloth — fresh off the trending list. 🔗 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 cutting-edge desktop app that allows users to run and train AI models locally, with support for various types of models. It features a user-friendly interface, native support for CPU, NVIDIA, AMD, and Intel hardware, and multi-GPU setups. Users can download the app for Windows, macOS, or Linux, and start using it right away. The app offers a range of features, including model training, fine-tuning, and deployment, as well as private and unlimited web search, deep research, and RAG. It also supports image and video diffusion, audio models, and reinforcement learning. Unsloth is designed for developers, researchers, and AI enthusiasts who want to work with AI models locally, without relying on cloud services. The app is free to use and offers a range of community resources, including documentation, tutorials, and forums. To get started with Unsloth, users can simply download the app and follow the installation instructions. The app also offers a web-based interface and a command-line interface for more advanced users. One of the key benefits of Unsloth is its ability to run AI models locally, which provides a high level of security and control for users. The app also offers remote access capabilities, allowing users to access their models from anywhere. Overall, Unsloth is a powerful and flexible tool for working with AI models locally, and it offers a range of features and benefits that make it an attractive choice for developers, researchers, and AI enthusiasts. Takeaway: Unsloth is the ultimate tool for running and training AI models locally, offering a unique combination of power, flexibility, and security. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe