Github Top Repositories

💡 chopratejas/headroom just hit the trending charts — here's why it matters. 🔗 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 your agent reads by 60-95%, resulting in significant savings. It offers multiple modes of operation, including a library for inline compression, a proxy for zero-code-changes integration, and an agent wrap for one-command integration with popular agents like Claude and Codex. The key features of Headroom include cross-agent memory, which allows shared memory across multiple agents, and reversible compression, which stores originals locally and allows the LLM to retrieve them on demand. Headroom also includes a range of algorithms for compressing different types of content, including JSON, code, and text. Technical highlights of Headroom include its ability to integrate with a wide range of AI agents and frameworks, including Anthropic, OpenAI, and LangChain. It also includes a range of tools for evaluating and optimizing compression performance. Audience: Headroom is designed for developers and users of AI agents who want to reduce the number of tokens their agents read and improve performance. It is particularly useful for those working with large datasets or complex AI models. To get started with Headroom, simply install it using pip install headroom-ai or npm install headroom-ai, then use the headroom wrap or headroom proxy commands to integrate it with your AI agent or application. In summary, Headroom is a powerful tool for compressing context in AI agents, offering significant savings and improved performance. With its range of modes, algorithms, and integrations, it's an essential tool for anyone working with AI agents. Try Headroom today and see the difference for yourself! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into NousResearch/hermes-agent — fresh off the trending list. 🔗 https://github.com/NousResearch/hermes-agent 📝 The agent that grows with you ────────────────────────────── Hermes Agent is a self-improving AI agent that creates skills from experience, improves them during use, and builds a deepening model of the user across sessions. Key features include a real terminal interface, cross-platform conversation continuity, a closed learning loop with autonomous skill creation, and scheduled automations. It supports various models and can be run on a $5 VPS, a GPU cluster, or serverless infrastructure, with six terminal backends for flexibility. Users can interact with the agent via Telegram, Discord, Slack, WhatsApp, Signal, or CLI, and it's research-ready with batch trajectory generation and compression for training. To get started, users can install Hermes using a curl command and follow the setup wizard. With its user-centric design and extensive documentation, Hermes Agent is perfect for users who want a personalized AI experience. One agent, endless possibilities. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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💡 github/copilot-sdk just hit the trending charts — here's why it matters. 🔗 https://github.com/github/copilot-sdk 📝 Multi-platform SDK for integrating GitHub Copilot Agent into apps and services ────────────────────────────── The GitHub Copilot SDK is a powerful tool that allows developers to embed Copilot's agentic workflows into their applications. With SDKs available for Python, TypeScript, Go, .NET, Java, and Rust, you can define agent behavior and let Copilot handle the rest. The SDK exposes the same engine behind Copilot CLI, providing a production-tested agent runtime that can be invoked programmatically. To get started, simply install your preferred SDK and follow the getting started guide. The SDK manages the CLI process lifecycle automatically, and you can also connect to an external CLI server. Some key features include: * Support for BYOK (Bring Your Own Key) * Multi-language support * Customizable tool availability * Support for custom agents, skills, and tools The GitHub Copilot SDK is generally available and follows semantic versioning. If you encounter any issues or have feature requests, you can report them on the GitHub Issues page. In summary, the GitHub Copilot SDK is a game-changer for developers - with its ease of use, flexibility, and powerful features, you can supercharge your development workflow and take your applications to the next level! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into jwasham/coding-interview-university — fresh off the trending list. 🔗 https://github.com/jwasham/coding-interview-university 📝 A complete computer science study plan to become a software engineer. ────────────────────────────── The Coding Interview University is a comprehensive study plan to help you become a software engineer at a top company like Amazon, Google, or Microsoft. The plan covers everything you need to know for a technical interview, from the basics of coding to advanced topics like data structures, algorithms, and system design. Key features of the plan include a structured approach to learning, with a focus on practice and review. You'll start by choosing a programming language and then work your way through a series of topics, including Big-O notation, data structures like arrays, linked lists, and trees, and algorithms like sorting and graph traversal. To get started, you can download the plan as a zip file or fork the GitHub repo and create a new branch to track your progress. The plan is designed to be flexible, so you can work at your own pace and focus on the areas where you need the most improvement. From a technical perspective, the plan covers a wide range of topics, including

Java

and other programming languages, as well as concepts like recursion, dynamic programming, and design patterns. You'll also learn about testing, string searching, and networking, among other topics. The plan is suitable for anyone who wants to become a software engineer, regardless of their background or experience level. Whether you're a complete beginner or an experienced coder looking to improve your skills, the Coding Interview University has something to offer. So why wait? Start your journey to becoming a software engineer today and remember: with dedication and hard work, you can land your dream job in no time! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🎯 HKUDS/Vibe-Trading landed on trending. Worth a proper look. 🔗 https://github.com/HKUDS/Vibe-Trading 📝 "Vibe-Trading: Your Personal Trading Agent" ────────────────────────────── Vibe-Trading is your personal trading agent, empowering you with comprehensive trading capabilities through one command. This project features a connector-first trading layer with support for multiple brokers, including IBKR, Robinhood, and OKX. The FastAPI backend and React frontend provide a robust and user-friendly interface. Key features include paper trading, read-only account access, and bounded autonomy with a user-committed mandate. The project is written in Python 3.11+ and is available on PyPI. The target audience includes traders, investors, and developers interested in building custom trading strategies. To get started, simply run pip install vibe-trading-ai and explore the website and docs for more information. With Vibe-Trading, automate your trading decisions and take your investments to the next level - trade smart, not hard. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ aquasecurity/trivy is making waves. Here's the full picture. 🔗 https://github.com/aquasecurity/trivy 📝 Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more ────────────────────────────── Trivy is a comprehensive security scanner that can detect various security issues in different targets, including container images, file systems, Git repositories, virtual machine images, and Kubernetes. It has multiple scanners that look for known vulnerabilities, configuration issues, sensitive information, and software licenses. To use Trivy, you can install it using popular package managers like brew or download the binary from the GitHub releases page. Trivy also has a GitHub Actions integration and a Kubernetes operator. Here's a basic example of how to use Trivy:

trivy image python:3.4-alpine

Trivy is designed for security professionals, developers, and DevOps teams who want to ensure the security and integrity of their applications and infrastructure. One-liner takeaway: Trivy is a powerful security scanner that helps you identify and fix vulnerabilities in your applications and infrastructure, making it a must-have tool for any security-conscious team. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 openclaw/openclaw-windows-node is trending — and it deserves your attention. 🔗 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 is an open-source, native Windows companion suite for OpenClaw, an AI-powered personal assistant. It's designed to work seamlessly with the OpenClaw gateway, providing a system tray application, shared client libraries, and CLI utilities. Key features include a modern Windows 11-style system tray companion with dark/light mode support, quick send functionality via global hotkey, auto-updates, and embedded web chat. The suite also offers a command center with diagnostics, channel health, usage, sessions, nodes, and copyable repair commands. To get started, users can download the latest stable installer from the OpenClaw Windows docs or build the project using the provided build script. The project requires Windows 10 (20H2+) or Windows 11, .NET 10.0 SDK, Windows 10 SDK, and WebView2 Runtime. The OpenClaw Windows Node is designed for users who want a seamless and integrated experience with their OpenClaw gateway. With its robust feature set and user-friendly interface, it's an ideal choice for anyone looking to enhance their productivity and streamline their workflow. One-liner takeaway: OpenClaw Windows Node is the ultimate Windows companion for OpenClaw users, offering a powerful and intuitive system tray application that simplifies your workflow and boosts productivity! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 MemPalace/mempalace is trending — and it deserves your attention. 🔗 https://github.com/MemPalace/mempalace 📝 The best-benchmarked open-source AI memory system. And it's free. ────────────────────────────── Introduction to MemPalace: MemPalace is a local-first AI memory tool that stores conversation history as verbatim text and retrieves it with semantic search. It's designed to be private and secure, with no API calls or cloud dependencies. Main Features: - Verbatim storage of conversation history - Semantic search for retrieving stored conversations - Pluggable backend for flexibility - Local-first approach for privacy and security - CLI and Python API for easy usage Usage Example: ```bash mempalace mine ~/projects/myapp # mine project files mempalace mine ~/.claude/projects/ --mode convos # mine Claude Code sessions mempalace search "why did we switch to GraphQL" # search conversations ``` Technical Highlights: - 96.6% retrieval recall on LongMemEval benchmark - Pluggable backend with ChromaDB as the default - Support for multiple languages Audience: MemPalace is suitable for developers, researchers, and anyone looking for a private and secure way to store and retrieve conversation history. Takeaway: MemPalace is a powerful tool for storing and retrieving conversation history, with a strong focus on privacy and security, making it an excellent choice for those who value their data. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into openai/plugins — fresh off the trending list. 🔗 https://github.com/openai/plugins 📝 OpenAI Plugins ────────────────────────────── The openai/plugins repository is a treasure trove of curated Codex plugin examples. Each plugin is neatly organized under its own directory, complete with a required .codex-plugin/plugin.json manifest file and optional supporting files like skills/, .app.json, and agents/. Some of the highlighted plugins include figma for design system rules, notion for planning and knowledge capture, and build-ios-apps for SwiftUI implementation and debugging. To get started, simply explore the various plugins, such as expo, netlify, and google-slides, and discover how they can streamline your workflow. Whether you're a developer, designer, or researcher, this repository has something for everyone. The openai/plugins repo is a game-changer - and the best part is, you can plug and play your way to productivity! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 PaddlePaddle/PaddleOCR caught my eye on GitHub Trending today. 🔗 https://github.com/PaddlePaddle/PaddleOCR 📝 Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages. ────────────────────────────── PaddleOCR is a leading OCR toolkit and document AI engine that converts PDF documents and images into structured, LLM-ready data with industry-leading accuracy. It features intelligent document parsing, universal text recognition, and a developer-centric ecosystem. With 70k+ Stars and trusted by top-tier projects, PaddleOCR is the bedrock for building intelligent RAG and Agentic applications. Key features include SOTA Document VLM with 96.3% accuracy on OmniDocBench v1.6, structure-aware conversion to Markdown or JSON, and universal text recognition supporting 100+ languages. It's designed for production-ready efficiency, achieving commercial-grade accuracy with an ultra-small footprint, and is seamlessly integrated with the Hugging Face ecosystem. Whether you're a developer or researcher, PaddleOCR provides a complete pipeline to build high-quality datasets and supports various hardware backends. One-liner takeaway: PaddleOCR simplifies document parsing and text recognition, empowering you to build intelligent applications with ease and accuracy! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ mvanhorn/last30days-skill is making waves. Here's the full picture. 🔗 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 ────────────────────────────── The mvanhorn/last30days-skill GitHub repository is home to a revolutionary AI agent-led search engine. This engine scores results based on upvotes, likes, and real money, rather than editor opinions. Key features include zero-config setup, immediate functionality with Reddit, HN, Polymarket, and GitHub, and the ability to unlock more platforms like X, YouTube, and TikTok in just 30 seconds. Technical highlights of this repository include the use of a pre-research brain built in Python, which resolves topics and figures out where to search before the search begins. The engine also features intelligent search, cross-source cluster merging, and single-pass comparisons, making it a powerful tool for finding relevant information. This repository is perfect for anyone looking to stay up-to-date on the latest developments in their field, including developers, researchers, and industry professionals. With its ability to search multiple platforms at once and provide a brief summary of the most relevant information, mvanhorn/last30days-skill is an invaluable resource. To get started, users can install the skill using /plugin marketplace add mvanhorn/last30days-skill or npx skills add mvanhorn/last30days-skill -g. The repository is constantly being updated with new features and improvements, making it an exciting project to follow. One-liner takeaway: mvanhorn/last30days-skill is a game-changing search engine that uses AI to scour multiple platforms and provide you with the most relevant, up-to-date information on any topic. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 666ghj/MiroFish caught my eye on GitHub Trending today. 🔗 https://github.com/666ghj/MiroFish 📝 A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物 ────────────────────────────── MiroFish is a cutting-edge AI prediction engine that utilizes multi-agent technology to forecast outcomes. By analyzing real-world data, it creates a parallel digital world where thousands of intelligent agents interact and evolve. This allows users to rehearse the future in a digital sandbox and make informed decisions after simulating various scenarios. Key features include: - Graph Building: extracting seed information and constructing a high-fidelity digital world - Simulation: running parallel simulations to predict future trajectories - Report Generation: generating detailed prediction reports The workflow involves: 1. Graph building and environment setup 2. Simulation and report generation 3. Deep interaction with the simulated world Technical highlights include: - Utilization of OASIS (Open Agent Social Interaction Simulations) for the simulation engine - Support for LLM API and Zep Cloud configurations The target audience includes decision-makers, researchers, and individuals interested in exploring what if scenarios. To get started, users can deploy MiroFish via source code or Docker, and join the conversation on social media platforms. In a nutshell, MiroFish is all about predicting anything - from serious predictions to playful simulations, making it possible to rehearse the future and win decisions after countless simulations. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe