Github Top Repositories

💡 penpot/penpot just hit the trending charts — here's why it matters. 🔗 https://github.com/penpot/penpot 📝 Penpot: The open-source design tool for design and code collaboration ────────────────────────────── Penpot is an open-source design platform for teams that build digital products at scale, giving them full ownership of their design infrastructure. It's built on open source, supports self-hosting, and works with open standards like SVG, CSS, HTML, and JSON. Key features include real-time collaboration, design tokens for consistency, and a powerful open API for automation and integrations. The platform is designed for developers, with features like inspect mode and support for webhooks. Penpot offers a full-stack design platform for building scalable design systems and integrated product development processes. It's perfect for teams that need security, flexibility, and ownership without vendor lock-in. To get started, you can use Penpot in the cloud or deploy it on your own servers. The community is active, with many resources available, including tutorials, documentation, and a contributing guide. Penpot is licensed under the Mozilla Public License, v. 2.0. Takeaway: Penpot is the ultimate open-source design platform that puts teams in control of their design infrastructure, and that's a game-changer! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 continuedev/continue landed on trending. Worth a proper look. 🔗 https://github.com/continuedev/continue 📝 open-source coding agent ────────────────────────────── The Continue project is an open-source coding agent that's available as a CLI, VS Code extension, and JetBrains plugin. Although the repository is no longer actively maintained, it's still a valuable resource for developers. To get started, you can check out the Continue Docs for configuration, customization, and usage information. The final 2.0.0 release includes a polished version of the VS Code extension, CLI, and JetBrains plugin, with features like removed anonymous telemetry and bug fixes. The project is licensed under Apache 2.0 and has a community-driven codebase. One-liner takeaway: Continue may be discontinued, but its open-source codebase remains a pioneering foundation for AI-powered coding tools. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 RocketChat/Rocket.Chat is trending — and it deserves your attention. 🔗 https://github.com/RocketChat/Rocket.Chat 📝 The Secure CommsOS™ for mission-critical operations ────────────────────────────── Rocket.Chat is an open-source, secure communications platform for teams, developed in TypeScript. It offers real-time conversations, file sharing, and audio/video conferencing. With end-to-end encryption and role-based access control, it ensures data protection. Key features include deployment flexibility, customizable workspaces, and integration with external systems. Rocket.Chat supports various deployment methods, including Docker, Podman, and Kubernetes. The platform is used by millions of users worldwide, including organizations like Deutsche Bahn and Credit Suisse. It has desktop and mobile apps for seamless communication. Rocket.Chat is designed for teams, organizations, and developers looking for a secure and customizable communication solution. With a strong focus on community involvement and open-source development, Rocket.Chat is a platform that's constantly evolving. Rocket.Chat is the ultimate secure communication solution for teams - join the community and experience it for yourself! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 google-research/timesfm just hit the trending charts — here's why it matters. 🔗 https://github.com/google-research/timesfm 📝 TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting. ────────────────────────────── Introducing TimesFM: a pretrained time-series foundation model developed by Google Research for time-series forecasting. The model is pretrained and available for use, with a paper detailing its development and capabilities. TimesFM has been integrated into various Google products, including BigQuery ML and Google Sheets, for easy access and scalability. To get started with TimesFM, you can install it via PyPI using pip install timesfm[torch] or pip install timesfm[flax]. The model also supports XReg for covariate support. Some of the key features of TimesFM include: - ForecastConfig for customizing forecasting settings - Support for continuous quantile forecast - Flax version for faster inference Here's an example of how to use TimesFM:

import torch
import numpy as np
import timesfm

model = timesfm.TimesFM_2p5_200M_torch.from_pretrained("google/timesfm-2.5-200m-pytorch")
model.compile(timesfm.ForecastConfig(...))
point_forecast, quantile_forecast = model.forecast(...)

TimesFM is suitable for data scientists, researchers, and developers working with time-series data. One-liner takeaway: TimesFM makes time-series forecasting more accessible and scalable, and is a game-changer for anyone working with time-series data. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 obra/superpowers caught my eye on GitHub Trending today. 🔗 https://github.com/obra/superpowers 📝 An agentic skills framework & software development methodology that works. ────────────────────────────── Superpowers is a software development methodology that transforms your coding agents into powerhouses. Its purpose is to make your agent use composable skills and initial instructions to ensure effective coding. The key features include brainstorming, test-driven development, systematic debugging, and collaboration tools. To use Superpowers, you can install it via various platforms like Claude Code, Antigravity, Codex App, and more. The installation process differs depending on the harness you use. From a technical standpoint, Superpowers uses a skills library that includes testing, debugging, collaboration, and meta skills. It also emphasizes test-driven development, systematic over ad-hoc approaches, complexity reduction, and evidence over claims. The target audience for Superpowers includes coding agents, developers, and anyone looking to streamline their coding process. In a nutshell, Superpowers is a game-changer for coding agents - with Superpowers, your agent doesn't just write code, it crafts solutions. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ meshery/meshery is making waves. Here's the full picture. 🔗 https://github.com/meshery/meshery 📝 Meshery, the cloud native manager ────────────────────────────── Meshery is a cloud native manager that enables the design and management of Kubernetes-based infrastructure and applications. It offers visual and collaborative GitOps, freeing you from YAML while managing multi-cluster deployments. Key features include infrastructure lifecycle management, multiple Kubernetes clusters and clouds, and visually managing infrastructure. Meshery provides a single pane of glass to manage multiple clusters and supports 380+ integrations. It's perfect for teams looking to collaborate on cloud native projects with features like Workspaces and Environments. With Meshery, you can manage your connections and credentials with ease and preview changes to your infrastructure before merging. Meshery is a self-service engineering platform that simplifies cloud native management - try it now and transform your cloud native experience! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet Panniantong/Agent-Reach: a gem from today's GitHub trending list. 🔗 https://github.com/Panniantong/Agent-Reach 📝 Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees. ────────────────────────────── Agent Reach 是一个让 AI Agent 拥有互联网能力的工具。它通过一键安装，让你的 AI Agent 可以读网页、搜索 Twitter、看 YouTube、刷小红书 等。 它的关键特点包括： - 完全免费：所有工具开源，所有 API 免费 - 隐私安全：Cookie 只存在你本地，不上传不外传 - 持续换代：每个平台都是「首选 + 备选」多后端路由 使用方法非常简单： - 安装：帮我安装 Agent Reach：https://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/install.md - 更新：帮我更新 Agent Reach：https://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/update.md 支持的平台包括： - 网页 - YouTube - RSS - 全网搜索 - GitHub - Twitter - B站 - Reddit - 小红书 - LinkedIn 技术亮点是： - 每个平台 = 首选 + 备选的有序后端列表 - agent-reach doctor 告诉你每个渠道的状态 适合的受众是： - AI 爱好者 - 研发人员 - 互联网企业 一句话总结：Agent Reach 让你的 AI Agent 拥有互联网能力，简单、免费、安全。 ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🔍 Deep-diving into n0-computer/iroh — fresh off the trending list. 🔗 https://github.com/n0-computer/iroh 📝 IP addresses break, dial keys instead. Modular networking stack in Rust. ────────────────────────────── Iroh is an open-source project that provides a unique approach to networking by allowing users to connect to each other using public keys. The project's main goal is to reduce the complexity of networking and make it more efficient. At its core, iroh is built on top of the QUIC protocol, which provides features like authenticated encryption, concurrent streams, and datagram transport. The project also includes a relay system that helps establish connections between users, even if they are behind firewalls or NATs. One of the key features of iroh is its ability to "hole-punch" - establishing a direct connection between two users, even if they are behind firewalls or NATs. If hole-punching is not possible, iroh falls back to using public relay servers. Iroh is designed to be highly extensible, with a number of pre-existing protocols built on top of it, including iroh-blobs for content-addressed blob transfer and iroh-gossip for establishing publish-subscribe overlay networks. To get started with iroh, users can install the Rust library using cargo add iroh and then use the library to establish connections to other users. The project also provides a number of examples and documentation to help users get started. The iroh project is licensed under the Apache 2.0 and MIT licenses, and contributions are welcome. Overall, iroh is a powerful and flexible networking platform that has the potential to revolutionize the way we think about networking - connect to anyone, anywhere, with just a public key. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: DeusData/codebase-memory-mcp — let's break it down. 🔗 https://github.com/DeusData/codebase-memory-mcp 📝 High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies. ────────────────────────────── The codebase-memory-mcp GitHub repository offers the fastest and most efficient code intelligence engine for AI coding agents, capable of full-indexing an average repository in milliseconds. This engine features high-quality parsing across 158 languages through tree-sitter AST analysis and Hybrid LSP semantic type resolution for languages like Python, TypeScript, and Java. The repository provides 14 MCP tools, including search, trace, architecture, impact analysis, and dead code detection, and supports 11 coding agents with a single static binary. Key features include extreme indexing speed, plug-and-play installation, and built-in graph visualization. The codebase-memory-mcp has been evaluated across 31 real-world repositories, demonstrating high answer quality and efficiency. It's designed with security and trust in mind, with every release binary signed, checksummed, and scanned by antivirus engines. To get started, users can install the engine using a one-line command and access the graph visualization UI at localhost:9749. With its cutting-edge technology and user-friendly interface, codebase-memory-mcp is the ultimate tool for coding agents - supercharge your coding experience with the power of AI-driven code intelligence. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 freeCodeCamp/freeCodeCamp landed on trending. Worth a proper look. 🔗 https://github.com/freeCodeCamp/freeCodeCamp 📝 freeCodeCamp.org's open-source codebase and curriculum. Learn math, programming, and computer science for free. ────────────────────────────── freeCodeCamp is a non-profit platform that offers a completely free and self-paced full-stack web development and machine learning curriculum. With thousands of interactive coding challenges, you can expand your skills and earn free developer certifications in areas like Responsive Web Design, JavaScript, and Python. The platform is community-driven, with a forum, YouTube channel, and Discord server where you can get help, feedback, and connect with other developers. To report bugs or security issues, you can create a new GitHub issue or follow the steps outlined in the security policy. The codebase is open-source and licensed under the BSD-3-Clause license, allowing you to contribute to the community and help others learn to code. With its donor-supported 501(c)(3) charity status, freeCodeCamp has already helped over 100,000 people get their first developer job. Whether you're a beginner or an experienced developer, freeCodeCamp has something for everyone. So, what are you waiting for? Join the community today and start coding your way to a new career! Learn to code, change your life: code for free, certify for free, and get hired. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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💡 n0-computer/iroh just hit the trending charts — here's why it matters. 🔗 https://github.com/n0-computer/iroh 📝 IP addresses break, dial keys instead. Modular networking stack in Rust. ────────────────────────────── Iroh is a library that provides an API for dialing by public key, allowing for direct connections between endpoints. Its key features include hole-punching for direct connections, relay servers for fallback connections, and QUIC connections for authenticated encryption and concurrent streams. The library is built on noq and uses QUIC for connections. It also includes pre-existing protocols like iroh-blobs for content-addressed blob transfer and iroh-gossip for publish-subscribe overlay networks. To get started, you can use the Rust library by installing it with cargo add iroh and then establishing connections using the Endpoint and Router APIs. Iroh is suitable for developers who want to establish secure and direct connections between endpoints, and its MIT and Apache 2.0 licenses make it a flexible choice for various projects. In short, iroh makes it easy to connect devices directly and securely, so you can focus on building your application. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet alibaba/zvec: a gem from today's GitHub trending list. 🔗 https://github.com/alibaba/zvec 📝 A lightweight, lightning-fast, in-process vector database ────────────────────────────── Zvec is an open-source, in-process vector database designed for production-grade similarity search. It's lightweight, fast, and embeds directly into applications. Key features include blazing-fast search, support for dense and sparse vectors, full-text search, and hybrid retrieval. zvec offers official SDKs for multiple languages, including Python, Node.js, Go, and Rust. To get started, you can install zvec using pip install zvec or npm install @zvec/zvec. The library runs anywhere, from notebooks to edge devices, and supports concurrent access and durable storage. Here's a simple

example

to demonstrate its usage:

import zvec
schema = zvec.CollectionSchema(name="example", vectors=zvec.VectorSchema("embedding", zvec.DataType.VECTOR_FP32, 4))
collection = zvec.create_and_open(path="./zvec_example", schema=schema)
collection.insert([zvec.Doc(id="doc_1", vectors={"embedding": [0.1, 0.2, 0.3, 0.4]})])
results = collection.query(zvec.VectorQuery("embedding", vector=[0.4, 0.3, 0.3, 0.1]), topk=10)
print(results)

Zvec is ideal for demanding production workloads, delivering exceptional speed and efficiency. With its active community and contributing guide, it's easy to get involved and make Zvec better. One-liner takeaway: Zvec makes vector search and AI applications blazingly fast and super easy to deploy. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 OpenBMB/VoxCPM just hit the trending charts — here's why it matters. 🔗 https://github.com/OpenBMB/VoxCPM 📝 VoxCPM2: Tokenizer-Free TTS for Multilingual Speech Generation, Creative Voice Design, and True-to-Life Cloning ────────────────────────────── VoxCPM2 is a tokenizer-free Text-to-Speech system that generates continuous speech representations via an end-to-end diffusion autoregressive architecture. It supports 30 languages, voice design, controllable voice cloning, and 48kHz studio-quality audio output. To get started, you can install VoxCPM using pip install voxcpm and use the Python API for text-to-speech, voice design, and voice cloning. For example:

from voxcpm import VoxCPM
model = VoxCPM.from_pretrained("openbmb/VoxCPM2")
wav = model.generate(text="VoxCPM2 is the current recommended release for realistic multilingual speech synthesis.")

The system is fully open-source and commercial-ready, with support for real-time streaming and production deployment using Nano-vLLM or vLLM-Omni. VoxCPM2 is suitable for developers, researchers, and businesses looking for a high-quality and customizable text-to-speech solution. Overall, VoxCPM2 is a powerful tool for multilingual speech synthesis and voice creation - transforming text into realistic speech, one voice at a time. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe