Github Top Repositories

🔍 Deep-diving into harveyai/harvey-labs — fresh off the trending list. 🔗 https://github.com/harveyai/harvey-labs 📝 A benchmark built to evaluate and improve agent capabilities for supporting legal work. ────────────────────────────── The Harvey LAB is an open-source benchmark for evaluating agents on real legal work. It consists of a dataset of tasks and an execution harness for running and evaluating agents. The key features of Harvey LAB include 1671 tasks across 24+ legal practice areas, with a test suite to validate the task schema. To get started, users can follow the full walkthrough in the tutorial.md guide. The project is designed for researchers and developers interested in evaluating the performance of large language models (LLMs) in legal work. The architecture, evaluation methodology, and contributing guidelines are well-documented, making it easy for users to understand and contribute to the project. The takeaway: Harvey LAB is revolutionizing the way we evaluate AI agents in legal work, and you can be a part of it! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 huggingface/transformers is trending — and it deserves your attention. 🔗 https://github.com/huggingface/transformers 📝 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. ────────────────────────────── The huggingface/transformers GitHub repository provides a comprehensive library for state-of-the-art machine learning models, supporting text, computer vision, audio, video, and multimodal tasks. At its core, Transformers serves as a model-definition framework, allowing for seamless compatibility across various training frameworks, inference engines, and modeling libraries. The library offers over 1 million model checkpoints on the Hugging Face Hub, making it easy to find and use pre-trained models for specific tasks. With a simple and customizable API, users can quickly get started with tasks like text generation, chat, automatic speech recognition, image classification, and visual question answering. Key features of the library include: * Easy-to-use state-of-the-art models with high performance and low barrier to entry * Lower compute costs and smaller carbon footprint through shared trained models and reduced compute time * Flexibility to choose the right framework for training, evaluation, and production * Customizable models and examples for specific use cases The library is suitable for researchers, engineers, and developers, providing a unified API for using pre-trained models and a few user-facing abstractions to learn. To get started, users can install the library using pip or uv and explore the Hugging Face Hub for pre-trained models. The library also provides a Pipeline API for high-level inference and a range of examples for different tasks and modalities. In summary, the huggingface/transformers library is a powerful tool for machine learning tasks, offering a wide range of pre-trained models, a simple API, and flexibility to choose the right framework. Whether you're a researcher, engineer, or developer, this library can help you achieve state-of-the-art results with ease. Transform your machine learning workflow with huggingface/transformers - the ultimate library for state-of-the-art models! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet paperclipai/paperclip: a gem from today's GitHub trending list. 🔗 https://github.com/paperclipai/paperclip 📝 The open-source app everyone uses to manage agents at work ────────────────────────────── Paperclip is an open-source platform that helps you manage AI agents for work. It's like a task manager, but under the hood, it's a powerful tool that lets you define goals, assign tasks, and track progress. You can bring your own agents, assign them roles, and track their work and costs from one dashboard. Key features include a Node.js server, React UI, and support for multiple agents like OpenClaw, Codex, and Claude. It also has features like goal alignment, cost control, and governance. The platform is built around four pillars: Agentic Task Manager, Org Chart for Agents, Agent Employee Training, and Agentic OS. those who want to build autonomous AI companies, coordinate multiple agents, and manage their work from one place. It's also great for those who want to monitor costs, enforce budgets, and have a process for managing agents that feels like using a task manager. Paperclip is special because it handles the hard orchestration details correctly, with features like atomic execution, persistent agent state, and governance with rollback. In short, Paperclip is the ultimate tool for managing AI agents for work, and with it, you can manage business goals, not pull requests. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 stablyai/orca just hit the trending charts — here's why it matters. 🔗 https://github.com/stablyai/orca 📝 Orca is the ADE for working with a fleet of parallel agents. Run any coding agent with your own subscription. Available on desktop, mobile and VPS. ────────────────────────────── Meet Orca, the AI orchestrator designed for 100x builders. It allows you to run multiple agents like Codex, ClaudeCode, and OpenCode in parallel worktrees, all tracked in one place. Key features include a mobile companion app, parallel worktrees, terminal splits, design mode, and native GitHub and Linear integration. You can use Orca with any CLI agent, and it supports a wide range of agents, including Claude Code, Codex, and OpenCode. With Orca, you can streamline your workflow, increase productivity, and focus on building. Orca is perfect for developers, builders, and anyone looking to unlock their full potential. In short, Orca is the ultimate tool for builders who want to build faster and smarter - it's like having a superpower in your workflow. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into HKUDS/DeepTutor — fresh off the trending list. 🔗 https://github.com/HKUDS/DeepTutor 📝 DeepTutor: Lifelong Personalized Tutoring.https://deeptutor.info/. ────────────────────────────── Introducing DeepTutor, a lifelong personalized tutoring platform that aims to revolutionize the way we learn. With a wide range of features, DeepTutor provides a comprehensive learning experience, including Guided Learning, Knowledge Center, and Chat functionality. The platform is built using Python 3.11+ and Next.js 16, and is designed to be highly customizable and extensible. Key features include support for multiple LLM providers, Document Parsing engines, and retrieval roles for queries. Technical highlights include a LightRAG Server retrieval engine, a PyMuPDF4LLM parsing engine, and a FAISS vector backend for large knowledge-base retrieval. Audience includes anyone looking for a personalized learning experience, from students to professionals. Get started with DeepTutor today and discover a new way to learn! One-liner takeaway: DeepTutor is your personalized learning companion, empowering you to reach new heights with AI-driven insights and guidance. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet 3b1b/manim: a gem from today's GitHub trending list. 🔗 https://github.com/3b1b/manim 📝 Animation engine for explanatory math videos ────────────────────────────── Manim is a powerful animation engine designed for creating explanatory math videos. It allows for precise programmatic control over animations, making it perfect for educational content. The project has two versions: the original 3b1b/manim repository and the community-driven ManimCommunity/manim fork. To get started with Manim, you can install it via pip using pip install manimgl. The engine requires FFmpeg, OpenGL, and optionally LaTeX for rendering mathematical equations. You can also install it on Linux, Windows, or Mac OSX by following the provided instructions. Manim offers a range of features, including: - Customizable animations and scenes - Support for various input formats, such as Python scripts and LaTeX equations - Options for rendering animations as videos or images The project has an active community, with documentation available at 3b1b.github.io/manim and a Chinese version at docs.manim.org.cn. Contributions are welcome, and the project is licensed under the MIT license. In short, Manim is a game-changer for creating engaging, math-focused animations - and the best part? It's free and open-source, empowering creators to bring complex concepts to life with ease! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 anthropics/skills is trending — and it deserves your attention. 🔗 https://github.com/anthropics/skills 📝 Public repository for Agent Skills ────────────────────────────── The anthropics/skills repository on GitHub is a treasure trove of skills for Claude, designed to enhance its performance on specialized tasks. These skills are essentially folders containing instructions, scripts, and resources that Claude can load dynamically. The repository includes a wide range of skills, from creative applications like art and music to technical tasks like testing web apps and enterprise workflows. To get started with these skills, you can browse through the repository and explore the different folders, each containing a SKILL.md file with instructions and metadata. You can also use the template-skill as a starting point to create your own custom skills. The repository provides a spec folder with the Agent Skills specification and a template folder for skill templates. The skills in this repository are easy to use and can be installed through Claude Code, Claude.ai, or the Claude API. For example, you can register the repository as a Claude Code Plugin marketplace and install specific skills like document-skills or example-skills. You can then use these skills by mentioning them in your commands, such as "Use the PDF skill to extract the form fields from path/to/some-file.pdf". The anthropics/skills repository is a valuable resource for developers, partners, and anyone looking to improve Claude's capabilities. With its open-source and source-available skills, it's an excellent starting point for creating custom skills and exploring the possibilities of Agent Skills. So, why not dive in and start creating your own skills today - the possibilities are endless with Claude and the anthropics/skills repository! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 vitali87/code-graph-rag caught my eye on GitHub Trending today. 🔗 https://github.com/vitali87/code-graph-rag 📝 The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs ────────────────────────────── Code-Graph-RAG is a powerful tool that parses a multi-language codebase, builds a knowledge graph, and allows you to query, edit, and optimize the code in plain English. Key features include support for multiple languages, structural search and replace, data-flow tracing, and optimization against language best practices. Usage is straightforward: point Code-Graph-RAG at a repository, and it extracts functions, classes, methods, and relationships, storing them as an interconnected graph. You can then ask questions about the codebase, retrieve source code, edit code through the agent, and optimize it. From a technical perspective, Code-Graph-RAG uses Tree-sitter for parsing and Memgraph for the knowledge graph. The system has two components: a multi-language parser and an interactive CLI that turns natural language into Cypher queries. This tool is designed for developers and organizations looking to streamline their code management and optimization processes. With Code-Graph-RAG, you can query and edit your codebase directly, making it an essential tool for any development team. In short, Code-Graph-RAG is a game-changer for code management - it's like having a superpower for your codebase. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ ZhuLinsen/daily_stock_analysis is making waves. Here's the full picture. 🔗 https://github.com/ZhuLinsen/daily_stock_analysis 📝 LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost-free scheduled runs. ────────────────────────────── Daily Stock Analysis is a powerful tool for stock market analysis, utilizing AI models to provide insights and recommendations. The project's primary goal is to assist investors in making informed decisions by analyzing various stocks and providing a decision dashboard with key information, such as buy/sell signals, risk alerts, and trend analysis. The tool supports multiple markets, including A-share, Hong Kong, US, Japan, Korea, and Taiwan, and can handle various data sources, including free and paid APIs. It also features a web-based interface for easy configuration and monitoring. To get started, users can fork the repository and configure the project using environment variables, or use the provided Docker image for a hassle-free deployment. The project also includes example configurations and a comprehensive guide to help users get up and running quickly. Key Features: - AI-powered stock analysis and recommendations - Support for multiple markets and data sources - Web-based interface for configuration and monitoring - Customizable notification channels, including email, Telegram, and more - Integrated agent for strategy queries and execution Technical Highlights: - Utilizes popular AI models, such as Anspire, AIHubMix, and OpenAI - Supports multiple programming languages, including Python - Features a modular design for easy extension and customization The project is designed for investors, researchers, and anyone interested in stock market analysis. By leveraging the power of AI and machine learning, Daily Stock Analysis aims to provide accurate and reliable insights to help users make informed investment decisions. Takeaway: With Daily Stock Analysis, investors can harness the power of AI to stay ahead of the market and make data-driven decisions with confidence. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 addyosmani/agent-skills caught my eye on GitHub Trending today. 🔗 https://github.com/addyosmani/agent-skills 📝 Production-grade engineering skills for AI coding agents. ────────────────────────────── The Agent Skills repository provides a collection of production-grade engineering skills for AI coding agents. These skills encode the workflows, quality gates, and best practices that senior engineers use when building software, ensuring that AI agents follow them consistently across every phase of development. Key features include 8 slash commands that map to the development lifecycle, allowing for automated activation of the right skills. The repository also includes a quick start guide that enables fast integration with various agents, such as Claude Code, Cursor, and Codex. The skills are divided into categories, including define, plan, build, verify, review, and ship, each with its own set of specific skills and workflows. For example, the spec-driven-development skill helps to write a PRD covering objectives, commands, structure, code style, testing, and boundaries before any code. The repository supports a wide range of agents and provides a native integration for each, making it easy to get started. Whether you're a junior developer or a seasoned engineer, the Agent Skills repository provides a valuable resource for improving your coding skills and workflows. One-liner takeaway: Level up your coding skills with Agent Skills, the ultimate resource for production-grade engineering workflows and best practices. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: nvm-sh/nvm — let's break it down. 🔗 https://github.com/nvm-sh/nvm 📝 Node Version Manager - POSIX-compliant bash script to manage multiple active node.js versions ────────────────────────────── The nvm-sh/nvm GitHub repository is home to the popular Node Version Manager (nvm) tool. nvm allows developers to easily install and switch between different versions of Node.js via the command line. To get started with nvm, you can install it by running a simple curl or wget command that downloads and runs the install script. Once installed, you can use nvm install to download and install specific versions of Node.js, and nvm use to switch between them. Some of the key features of nvm include its ability to work on any POSIX-compliant shell, support for long-term support (LTS) versions of Node.js, and the ability to migrate global packages between installed versions. The tool also supports deeper shell integration, allowing you to automatically use a specific version of Node.js when navigating to a directory with a .nvmrc file. nvm is a must-have tool for any Node.js developer, and its simplicity and flexibility make it an essential part of many development workflows. One-liner takeaway: With nvm, you can easily manage multiple versions of Node.js and switch between them with a single command, streamlining your development process and freeing you to focus on writing code. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ semantica-agi/semantica is making waves. Here's the full picture. 🔗 https://github.com/semantica-agi/semantica 📝 Graph-Native Infrastructure for Context and Accountable AI Systems ────────────────────────────── Semantica is an open-source graph-native infrastructure for building context and accountable AI systems. It's designed to provide a transparent and explainable decision-making process, making it ideal for high-stakes, regulated domains. Key features include context graphs, decision intelligence, ontology management, knowledge modeling, and end-to-end traceability. To get started, simply run pip install semantica and begin building your knowledge graph. Semantica is suitable for AI/ML platform teams, data platform teams, compliance and audit teams, and regulated enterprises. From a technical standpoint, Semantica supports polyglot graph storage, RDF and LPG, and W3C standards, making it highly interoperable. It's built using a real end-to-end pipeline with independently importable modules. In summary, Semantica is the perfect solution for anyone looking to add transparency and accountability to their AI decision-making process: with Semantica, you can finally ask your AI "why" and get a real answer. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 msitarzewski/agency-agents just hit the trending charts — here's why it matters. 🔗 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. ────────────────────────────── Imagine a dream team of AI specialists at your fingertips, each with their own personality, expertise, and deliverables. The Agency Agents repository offers a collection of meticulously crafted AI agent personalities, specialized in various domains such as frontend development, backend architecture, and AI engineering. These agents are production-ready, with real code, processes, and measurable outcomes. You can use them as is or adapt to fit your needs. The repository provides various installation options, including a native app for macOS, Linux, and Windows, as well as script-based installations for tools like Claude Code, Cursor, and Codex. Technical highlights include support for multiple tools and platforms, auto-updating, and extensive documentation. The target audience includes developers, engineers, and anyone looking to transform their workflow with AI. To get started, you can download the app or explore the repository to find the agents that suit your needs. With Agency Agents, you can assemble your dream team and take your projects to the next level. One-liner takeaway: Unlock the power of AI with Agency Agents and revolutionize your workflow with a team of specialized experts at your fingertips! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe