Github Top Repositories
Open in Telegram
Top GitHub repositories in one place π Explore the best projects in programming, AI, data science, and more.
Show moreπ Analytical overview of Telegram channel Github Top Repositories
Channel Github Top Repositories (@githubre) in the English language segment is an active participant. Currently, the community unites 14 268 subscribers, ranking 13 983 in the Education category and 28 170 in the India region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 14 268 subscribers.
According to the latest data from 05 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 255 over the last 30 days and by 8 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 0.92%. Within the first 24 hours after publication, content typically collects 0.61% reactions from the total number of subscribers.
- Post reach: On average, each post receives 131 views. Within the first day, a publication typically gains 87 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 1.
- Thematic interests: Content is focused on key topics such as repository, fork, programming, statistic, description.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βTop GitHub repositories in one place π
Explore the best projects in programming, AI, data science, and more.β
Thanks to the high frequency of updates (latest data received on 06 September, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.
14 268
Subscribers
+824 hours
+1197 days
+25530 days
Posts Archive
14 268
π‘ refactoringhq/tolaria just hit the trending charts β here's why it matters.
π https://github.com/refactoringhq/tolaria
π Desktop app to manage markdown knowledge bases
ββββββββββββββββββββββββββββββ
Meet Tolaria, a desktop app for managing markdown knowledge bases on macOS, Windows, and Linux. It's designed for personal knowledge management, company documentation, and storing AI assistant memory.
Key features include:
-
files-first approach with plain markdown files,
- git-first with every vault being a git repository,
- offline-first with no accounts or subscriptions needed, and
- open source with a permissive license.
To get started, you can install Tolaria via Homebrew or download the latest release. The app is built with Tauri, React, and TypeScript, and its tech docs provide a detailed overview of the system design and data flow.
Tolaria is perfect for power-users who want to manage their knowledge base efficiently.
One notable takeaway: Tolaria is the ultimate tool for organizing your digital life - it's like having your own personal superpower.
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe
14 268
IΜnter-bahiΜs ResmiΜ: YeniΜ Γyelere Γzel Deneme Bonusu
IΜnterbahiΜs
IΜnter-bahiΜs ResmiΜ: YeniΜ Γyelere Γzel Deneme Bonusu
Ad. 18+
14 268
π openai/plugins caught my eye on GitHub Trending today.
π https://github.com/openai/plugins
π OpenAI Plugins
ββββββββββββββββββββββββββββββ
The openai/plugins repository is a treasure trove of Codex plugin examples, each with its own unique features and use cases. You'll find plugins for popular tools like Figma, Notion, and Expo, as well as plugins for building iOS, macOS, and web apps. Each plugin comes with a
plugin.json manifest and may include additional files like skills/, agents/, and hooks.json. The highlighted examples in this repo showcase the potential of Codex plugins, from design systems to app development and deployment. Whether you're a developer or just starting out, this repository has something for everyone. Take a look and get inspired to build your own plugins - the possibilities are endless, and with openai/plugins, you can code your way to creation!
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe14 268
π‘ TapXWorld/ChinaTextbook just hit the trending charts β here's why it matters.
π https://github.com/TapXWorld/ChinaTextbook
π ζζε°ει«γ倧ε¦PDFζζγ
ββββββββββββββββββββββββββββββ
ChinaTextbook is a GitHub repository that aims to provide free access to Chinese textbooks, promoting equal education opportunities. The repository contains a wide range of textbooks, including mathematics for primary, secondary, and university levels.
Key features of this repository include:
- A vast collection of textbooks, covering various subjects and levels
-
PDF files for easy access and download
- A mergePDFs-windows-amd64.exe program to merge split files
To use the repository, simply browse through the folders, download the desired textbooks, and use the provided program to merge any split files.
This repository is ideal for students, teachers, and overseas Chinese who want to access Chinese educational resources.
The project is open-source, and contributions are welcome. You can support the project by donating or joining the Telegram community to share your thoughts and ideas.
In short, ChinaTextbook is a valuable resource for anyone seeking free access to Chinese educational materials - and it's completely free!
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe14 268
π RyanCodrai/turbovec caught my eye on GitHub Trending today.
π https://github.com/RyanCodrai/turbovec
π A vector index built on TurboQuant, written in Rust with Python bindings
ββββββββββββββββββββββββββββββ
Turbovec is an open-source vector index built on Google Research's TurboQuant algorithm, providing a data-oblivious quantizer that matches the Shannon lower bound on distortion. It features
online ingest, faster-than-FAISS search, and filter-at-search-time capabilities, making it suitable for building RAG (Retrieval-Augmented Generation) systems where privacy, memory, or latency matters.
Key features include:
- Online ingest: add vectors without requiring a train step or parameter tuning
- Faster-than-FAISS search: hand-written NEON (ARM) and AVX-512BW (x86) kernels beat FAISS IndexPQFastScan
- Filter at search time: pass an id allowlist to restrict search results
- Pure local: no managed service, no data leaving your machine or VPC
The library is available in both Python and Rust, with Python bindings for easy integration. It also includes framework integrations for popular libraries like LangChain, LlamaIndex, Haystack, and Agno.
Turbovec achieves high compression ratios (up to 16x) and fast search speeds, making it an attractive solution for applications requiring efficient vector search. With its length-renormalized scoring and Lloyd-Max scalar quantization, Turbovec provides a robust and accurate search experience.
In summary, Turbovec is a powerful and efficient vector index library that is perfect for building high-performance RAG systems.
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe
14 268
β‘ ggml-org/llama.cpp is making waves. Here's the full picture.
π https://github.com/ggml-org/llama.cpp
π LLM inference in C/C++
ββββββββββββββββββββββββββββββ
The ggml-org/llama.cpp repository is a C/C++ implementation of LLM inference, focusing on minimal setup and state-of-the-art performance.
Its key features include:
- Plain C/C++ implementation
- Support for various hardware, including Apple silicon, x86 architectures, and RISC-V
- Integer quantization for faster inference
- Custom CUDA kernels for NVIDIA GPUs
- Vulkan and SYCL backend support
Usage is straightforward: install using
brew, nix, or winget, run with Docker, or download pre-built binaries.
Technical highlights include optimized performance on a wide range of hardware, hybrid CPU+GPU inference, and support for models like LLaMA, Mistral 7B, and more.
The repository is suitable for audiences interested in LLM inference, including developers and researchers.
In a nutshell: llama.cpp brings fast and efficient LLM inference to your fingertips, making it an exciting project to explore.
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe14 268
π Crosstalk-Solutions/project-nomad caught my eye on GitHub Trending today.
π https://github.com/Crosstalk-Solutions/project-nomad
π Project N.O.M.A.D, is a self-contained, offline survival computer packed with critical tools, knowledge, and AI to keep you informed and empoweredβanytime, anywhere.
ββββββββββββββββββββββββββββββ
Introducing Project N.O.M.A.D., a self-contained, offline-first knowledge and education server that empowers you with critical tools, knowledge, and AI. This innovative platform is designed to keep you informed and connected, even without an internet connection.
Main Features:
-
AI Chat with Knowledge Base powered by Ollama or OpenAI API compatible software
- Information Library with offline Wikipedia, medical references, and ebooks via Kiwix
- Education Platform with Khan Academy courses and progress tracking via Kolibri
- Offline Maps with downloadable regional maps via ProtoMaps
- Data Tools for encryption, encoding, and analysis via CyberChef
- Notes for local note-taking via FlatNotes
- System Benchmark for hardware scoring with a community leaderboard
Technical Highlights:
- Built using Docker for containerized tools and resources
- Easy setup wizard for guided first-time configuration
- Customizable with a Docker Compose template for advanced users
- Compatible with Debian-based operating systems, including Ubuntu
Audience:
- Individuals seeking offline access to knowledge and education
- Communities in areas with limited or no internet connectivity
- Educators and students looking for a self-contained learning platform
- Anyone interested in exploring the capabilities of AI and offline technology
Get started today and experience the power of knowledge without boundaries!
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe14 268
β‘ aaif-goose/goose is making waves. Here's the full picture.
π https://github.com/aaif-goose/goose
π an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
ββββββββββββββββββββββββββββββ
The goose project is a native open-source AI agent that can be used for various tasks, from code and workflows to research and data analysis. It offers a desktop app for macOS, Linux, and Windows, a full CLI for terminal workflows, and an API for embedding it anywhere. Built in
Rust for performance and portability, goose works with 15+ providers and supports 70+ extensions via the Model Context Protocol open standard.
To get started, you can download the desktop app or install the CLI using the command:
curl -fsSL https://github.com/aaif-goose/goose/releases/download/stable/download_cli.sh | bash14 268
π Spotted on GitHub Trending: yikart/AiToEarn β let's break it down.
π https://github.com/yikart/AiToEarn
π Let's use AI to Earn!
ββββββββββββββββββββββββββββββ
AiToEarn is an innovative platform designed for creators, brands, and enterprises to build, distribute, and monetize content on multiple global platforms. With its AI Agent automation, it simplifies the process of content creation, publication, engagement, and monetization.
The platform supports various social media channels, including TikTok, YouTube, Facebook, Instagram, and more. It offers five ways to use the platform: through its website, within OpenClaw, with AI assistants like Claude, via Docker deployment, or by developing with its source code.
Key Features include:
-
Monetize: Helps creators earn money through content sales and promotion tasks.
- Publish: Automates content distribution across multiple platforms.
- Engage: Enhances content interaction through automated operations and AI-powered comment replies.
- Create: Employs AI to generate content, including videos and graphic texts.
The platform is suitable for one-person companies (OPCs), creators, brands, and enterprises seeking to leverage AI for efficient content management and monetization.
Technical Highlights:
- Supports Node.js 20.18.x
- Offers Docker one-click deployment
- Compatible with MCP protocol for use with various AI assistants
For those interested in contributing or learning more, the platform welcomes developers and provides a contributing guide.
In summary, AiToEarn is a powerful tool for simplifying content creation, distribution, and monetization, making it an attractive solution for anyone looking to streamline their online presence and revenue streams: AiToEarn empowers you to effortlessly create, share, and profit from your content across the globe.
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe
14 268
β‘ lfnovo/open-notebook is making waves. Here's the full picture.
π https://github.com/lfnovo/open-notebook
π An Open Source implementation of Notebook LM with more flexibility and features
ββββββββββββββββββββββββββββββ
Open Notebook is an open source, privacy-focused alternative to Google's Notebook LM. It's designed to give you full control over your data and provide a flexible AI model choice, with support for 18+ providers including OpenAI, Anthropic, and Ollama.
The platform allows you to organize multi-modal content such as PDFs, videos, and web pages, and even generate professional podcasts with advanced multi-speaker capabilities. You can also use intelligent search and context-aware chat features to get the most out of your research.
Technical Highlights include a
REST API for custom integrations, content transformations for summarizing and extracting insights, and support for reasoning models like DeepSeek-R1 and Qwen3.
The project is built with Python, Next.js, React, SurrealDB, and LangChain, making it a great choice for developers who want to contribute or customize the platform.
Whether you're a researcher, student, or developer, Open Notebook is a powerful tool that can help you take control of your data and unlock new insights. So why not give it a try? Open Notebook: empowering your research, one note at a time.
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe
14 268
π Spotted on GitHub Trending: NousResearch/hermes-agent β let's break it down.
π https://github.com/NousResearch/hermes-agent
π The agent that grows with you
ββββββββββββββββββββββββββββββ
The Hermes Agent is a self-improving AI agent that creates skills from experience, improves them during use, and builds a deepening model of who you are across sessions. It's designed to be flexible, allowing you to use any model you want, such as Nous Portal, OpenRouter, or Hugging Face, and switch between them with ease using the
hermes model command.
The agent has a range of key features, including a real terminal interface, the ability to live where you do (e.g., Telegram, Discord, Slack), a closed learning loop, scheduled automations, and the ability to delegate and parallelize tasks. It also has a range of technical highlights, including support for six terminal backends and the ability to run on a variety of infrastructure, from a $5 VPS to a GPU cluster.
The Hermes Agent is suitable for a range of users, from developers to researchers, and is designed to be easy to use and customize. With its flexible architecture and range of features, it's an ideal tool for anyone looking to build a self-improving AI agent.
To get started with the Hermes Agent, you can install it using a simple one-liner command, and then start chatting with it using the hermes command. You can also customize the agent's behavior using a range of configuration options and tools.
One punchy takeaway: With the Hermes Agent, you can have a self-improving AI assistant that learns and adapts to your needs, all at a cost that's nearly nothing when idle.
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe14 268
π‘ Leonxlnx/taste-skill just hit the trending charts β here's why it matters.
π https://github.com/Leonxlnx/taste-skill
π Taste-Skill - gives your AI good taste. stops the AI from generating boring, generic slop
ββββββββββββββββββββββββββββββ
The Taste Skill repository offers a collection of portable agent skills designed to upgrade AI-built interfaces with stronger layout, typography, motion, and spacing. These skills can be used with various coding agents like ChatGPT, Codex, or Claude Code. The repo includes
image-generation skills for creating reference boards, which can be paired with image generators and then implemented using coding agents.
To use Taste Skill, simply install the desired skill using npx skills add https://github.com/Leonxlnx/taste-skill --skill "skill-name". The repository features multiple specialized variants, adjustable dials, and anti-repetition rules, making it a unique solution for AI design.
The skills are framework-agnostic and work with popular frameworks like React, Vue, and Svelte. The repository also includes a research directory with background writing that shaped the skills, as well as a CHANGELOG that details the updates and changes.
Taste Skill is suitable for developers, designers, and anyone looking to improve their AI-built interfaces. With its easy installation process and versatile skills, it's an excellent tool for enhancing the design and functionality of various projects.
In short, Taste Skill is a game-changer for AI design, and its punchy one-liner takeaway is: Level up your AI-built interfaces with Taste Skill - where design meets code!
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe
14 268
π‘ opencv/opencv just hit the trending charts β here's why it matters.
π https://github.com/opencv/opencv
π Open Source Computer Vision Library
ββββββββββββββββββββββββββββββ
The OpenCV library is a powerful open-source computer vision tool that enables developers to build a wide range of applications, from image and video processing to object detection and tracking. With its extensive documentation and large community of contributors, OpenCV provides a comprehensive framework for computer vision and machine learning.
To get started, you can explore the
official documentation and tutorials on the OpenCV website. The library is written in C++ and has interfaces for Python, Java, and other languages.
Whether you're a student, researcher, or developer, OpenCV has something to offer. So why not join the community and start building your own computer vision projects today? OpenCV is the key to unlocking the power of computer vision - start coding and see what you can create!
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe14 268
π Spotted on GitHub Trending: mvanhorn/last30days-skill β let's break it down.
π https://github.com/mvanhorn/last30days-skill
π AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary
ββββββββββββββββββββββββββββββ
Last30Days Skill is a revolutionary search engine that uses AI to synthesize information from various sources like Reddit, X, YouTube, and GitHub, scoring it by what real people engage with, not editors. It's like having a superpower that helps you stay up-to-date on the latest developments in any field.
To use it, simply type
/last30days [topic] and the AI agent will search all relevant sources in parallel, synthesizing the information into a brief. No more tedious searching or outdated information.
The skill has many features, including shareable HTML briefs, intelligent search that understands your topic before searching, and cross-source cluster merging that combines similar stories from different sources.
It's perfect for researchers, entrepreneurs, and anyone who wants to stay informed. Whether you're looking for information on a person, company, or topic, Last30Days Skill is the ultimate tool for you.
With its ability to search multiple sources at once and synthesize the information into a concise brief, Last30Days Skill is an indispensable tool for anyone looking to stay ahead of the curve. Get the latest scoop in seconds, not hours.
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe14 268
π₯ github/copilot-sdk is trending β and it deserves your attention.
π https://github.com/github/copilot-sdk
π Multi-platform SDK for integrating GitHub Copilot Agent into apps and services
ββββββββββββββββββββββββββββββ
The Github Copilot SDK is a set of APIs that allows you to integrate the capabilities of Github Copilot into your own applications. With this SDK, you can embed Copilot's agentic workflows into your app and invoke them programmatically. The SDK exposes the same engine as the Copilot CLI, handling planning, tool invocation, and file edits.
The SDK supports multiple programming languages, including Node.js/TypeScript, Python, Go, .NET, Java, and Rust. You can install the SDK using the respective package managers, such as
npm install @github/copilot-sdk for Node.js or pip install github-copilot-sdk for Python.
To get started, you can follow the Getting Started Guide, which provides a walkthrough of the installation and usage process. The SDK also provides a range of features, including support for custom agents, skills, and tools, as well as BYOK (Bring Your Own Key) for using your own API keys.
The SDK is designed to be production-ready 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 powerful tool for integrating Copilot's capabilities into your own applications, with support for multiple programming languages and a range of features. With this SDK, you can unlock the full potential of Copilot and take your development to the next level.
ββββββββββββββββββββββββββββββ
π§ Channel: https://t.me/GithubRe