Github Top Repositories
Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
Show more📈 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 13 641 subscribers, ranking 14 714 in the Education category and 30 179 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 13 641 subscribers.
According to the latest data from 14 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 308 over the last 30 days and by 18 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 1.09%. Within the first 24 hours after publication, content typically collects 0.81% reactions from the total number of subscribers.
- Post reach: On average, each post receives 149 views. Within the first day, a publication typically gains 111 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.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Thanks to the high frequency of updates (latest data received on 15 July, 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.
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| Date | Subscriber Growth | Mentions | Channels | |
| 15 July | +14 | |||
| 14 July | +18 | |||
| 13 July | +21 | |||
| 12 July | +22 | |||
| 11 July | +19 | |||
| 10 July | +7 | |||
| 09 July | +8 | |||
| 08 July | +17 | |||
| 07 July | +15 | |||
| 06 July | +14 | |||
| 05 July | +15 | |||
| 04 July | +17 | |||
| 03 July | +14 | |||
| 02 July | +23 | |||
| 01 July | +10 |
18 chapters that cover topics like vectors, matrices, calculus, statistics, probability, machine learning, and more.
To get the most out of the compendium, the author suggests a two-phase approach: cumulative reading after classes, and shadow reading before exams. This approach helps to connect patterns and develop muscle memory for each concept.
The compendium is suitable for anyone who wants to learn maths, CS, and AI, regardless of their background or experience. All you need is elementary maths and basic Python programming, and you're ready to start.
One-liner takeaway: The Maths, CS & AI Compendium is your one-stop shop for learning maths, computing, and artificial intelligence, with a unique approach that helps you truly understand these subjects and apply them in the real world.
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🧠 Channel: https://t.me/GithubRe| 2 | 📌 Spotted on GitHub Trending: Graphify-Labs/graphify — let's break it down.
🔗 https://github.com/Graphify-Labs/graphify
📝 AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and more). Turn any folder of code, SQL schemas, R scripts, shell scripts, docs, papers, images, or videos into a queryable knowledge graph. App code + database schema + infrastructure in one graph.
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Graphify is a powerful tool that helps you extract knowledge from your files and build a graph of concepts and relationships. With multimodal support, you can drop in code, PDFs, markdown, screenshots, diagrams, and images, and graphify will use Claude vision to extract concepts and connect them into one graph.
To use graphify, simply type /graphify in Claude Code, and it will read your files, build a knowledge graph, and give you back structure you didn't know was there. You can install graphify using pip install graphifyy && graphify install, then run it on any folder using /graphify ..
Graphify is perfect for developers, researchers, and anyone looking to extract insights from their files. The tool provides a range of features, including interactive graph visualization, persistent graph storage, and querying capabilities.
The tool uses a tech stack that includes NetworkX, Leiden, tree-sitter, Claude, and vis.js, and is designed to run entirely locally, with no server required.
Overall, graphify is an incredibly powerful tool that can help you unlock hidden insights in your files - try it out and see what connections you can discover!
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🧠 Channel: https://t.me/GithubRe | 52 |
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| 5 | 🚀 Meet chenyme/grok2api: a gem from today's GitHub trending list.
🔗 https://github.com/chenyme/grok2api
📝 面向 Grok Build、Grok Web 与 Grok Console 的多账号 API 网关
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Grok2API 是一个多账号 API 网关,用于 Grok Build、Grok Web 和 Grok Console。它提供了一个统一的 API 接口,支持多种功能,如 Responses、Chat Completions、Images 和 Videos 生成。
该项目使用 Go 作为后端,React 作为前端,支持 Docker 部署。它提供了一个管理后台,用于配置和管理账号、模型、客户端密钥和请求审计。
主要特点:
* 支持多账号和多模型
* 提供标准化的 API 接口
* 支持图片和视频生成
* 有一个管理后台用于配置和管理
技术亮点:
* 使用 Go 实现的高性能后端
* 使用 React 实现的现代化前端
* 支持 Docker 部署和 HTTPS 加密
目标受众:
* 需要一个统一的 API 网关 来管理多个 Grok 账号的开发者
* 需要一个高性能和可扩展的 API 解决方案的企业
总结:Grok2API 是一个功能强大且高性能的 API 网关,可以帮助开发者和企业更好地管理他们的 Grok 账号和模型。所以,用 Grok2API 来简化你的 API 管理吧!
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🧠 Channel: https://t.me/GithubRe | 47 |
| 6 | 🎯 par274/sharpemu landed on trending. Worth a proper look.
🔗 https://github.com/par274/sharpemu
📝 An experimental PlayStation 5 emulator project.
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SharpEmu is an experimental PlayStation 5 emulator for Windows, Linux, and macOS, developed from scratch in C#. The project focuses on accuracy and infrastructure setup, with the goal of emulating PS5 games.
Key features include loading game files, executing native CPU instructions, and partial kernel functionality support.
To use SharpEmu, build or download the project, then run the Emulator GUI or use the command line.
Technical highlights include native code execution, kernel function support, and video output in some games.
The project is aimed at developers and researchers interested in system architecture and reverse engineering.
One-liner takeaway: SharpEmu is paving the way for PS5 emulation on multiple platforms, and it's an exciting project to watch.
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🧠 Channel: https://t.me/GithubRe | 61 |
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| 8 | 🔥 AIEraDev/Clypra is trending — and it deserves your attention.
🔗 https://github.com/AIEraDev/Clypra
📝 A modern video editor built with Tauri, React, and TypeScript. Focus on building free capabilities of premium capcut functionalities
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Clypra is a free, open-source video editor built on Tauri v2, React 19, and Rust, offering professional-grade features without watermarks, feature limits, or subscriptions. It provides hardware-accelerated processing, cross-platform compatibility (desktop and mobile), and optional AI-powered features like natural language editing and auto-captions.
Key features include multi-format media import, frame-accurate trimming, multi-track timeline, and undo/redo system. Clypra also supports high-fidelity waveforms, audio synchronization, and volume control. For visuals, it offers filmstrip thumbnails, text overlays, and preview canvas with transform controls.
Clypra's technology stack includes React, Zustand, Vite, Rust, Tauri, and FFmpeg. Its architecture is designed for native performance, with a desktop-first approach and hardware acceleration using native FFmpeg hardware decoders.
Developers can build from source using Node.js, Rust, and FFmpeg, and contribute to the project. Clypra's codebase is organized by domain, with clear separation of concerns.
Get started with Clypra today and experience the power of open-source video editing - empowering creators, one edit at a time!
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🧠 Channel: https://t.me/GithubRe | 60 |
| 9 | 🌟 penpot/penpot caught my eye on GitHub Trending today.
🔗 https://github.com/penpot/penpot
📝 Penpot: The open-source design platform for Product teams that need scalable collaboration.
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Penpot is an open-source design platform for teams building digital products at scale, giving users full ownership of their design infrastructure. It offers real-time collaboration, open standards like SVG, CSS, HTML, and JSON, and best-in-class native Design Tokens for consistent design systems. With a powerful open API and plugin system, Penpot enables automation, AI-driven workflows, and integrations with other tools. Developers can use Penpot with ease, as design is expressed as code, allowing for direct translation and faster product shipping. Whether used in the browser or self-hosted, Penpot provides full flexibility, security, and ownership without vendor lock-in. Join the Penpot community to contribute, learn, and grow with the platform. Penpot is perfect for teams seeking a full-stack design platform for scalable design systems and integrated product development processes: Design with freedom, scale with confidence.
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🧠 Channel: https://t.me/GithubRe | 75 |
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| 11 | 🌟 hasaneyldrm/exercises-dataset caught my eye on GitHub Trending today.
🔗 https://github.com/hasaneyldrm/exercises-dataset
📝 1,324-exercise fitness dataset — animation GIFs, 180×180 thumbnails, muscle-group & equipment data, and step-by-step instructions in 6 languages. The exercise data layer behind the LogPress app.
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The hasaneyldrm/exercises-dataset repository offers a comprehensive dataset of 1,324 exercises, each with an animation GIF, thumbnail image, and detailed metadata like category, body part, equipment, and instructions in 9 languages. Key features include a wide range of exercises covering various muscle groups and equipment types, as well as step-by-step instructions and media assets.
To get started, users can leverage the index.html interactive browser to explore exercises or the setup.html developer guide for integrating the dataset into their own applications. The dataset is ideal for building fitness or workout planning applications, machine learning projects, health and wellness research, or educational demonstrations.
Technically, the dataset is structured with a clear JSON schema for validation, and each exercise entry contains fields such as unique ID, name, category, equipment, instructions, and media URLs.
The primary audience for this dataset includes fitness app developers, researchers, and enthusiasts looking for a robust and accessible collection of exercise data to power their projects or studies.
In summary, the hasaneyldrm/exercises-dataset is an invaluable resource for anyone looking to create engaging fitness experiences, with its extensive and structured collection of exercise data.
Drop this dataset into your next fitness project and unleash a world of workout possibilities!
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🧠 Channel: https://t.me/GithubRe | 79 |
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| 13 | 🚀 Meet Raphire/Win11Debloat: a gem from today's GitHub trending list.
🔗 https://github.com/Raphire/Win11Debloat
📝 A simple, lightweight PowerShell script that allows you to remove pre-installed apps, disable telemetry, as well as perform various other changes to declutter and customize your Windows experience. Win11Debloat works for both Windows 10 and Windows 11.
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Introducing Win11Debloat, a lightweight PowerShell script designed to simplify the process of customizing and decluttering your Windows experience. The script allows you to easily remove pre-installed apps, disable telemetry, and remove intrusive interface elements with minimal effort.
Key features include app removal, privacy and suggested content customization, and system tweaks such as disabling Windows location services and Microsoft 365 ads.
To get started, you can use the quick method by running a PowerShell command, or the traditional method by downloading and extracting the script.
Technical highlights include a powerful command-line interface, support for Windows Audit mode, and the ability to export and import preferred settings.
This script is ideal for system administrators and power users looking to streamline their Windows experience.
In short, Win11Debloat is an easy-to-use tool that helps you take control of your Windows settings - debloat your Windows, declutter your life.
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🧠 Channel: https://t.me/GithubRe | 77 |
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| 15 | 🔥 HKUDS/Vibe-Trading is trending — and it deserves your attention.
🔗 https://github.com/HKUDS/Vibe-Trading
📝 "Vibe-Trading: Your Personal Trading Agent"
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Check out Vibe-Trading, your personal trading agent, built with Python 3.11+ and featuring a FastAPI backend and React 19 frontend. This project provides comprehensive trading capabilities, including a strategy development manager, real-time market data, and a robust API server. With Vibe-Trading, you can create and manage your own trading strategies, backtest them, and analyze performance metrics. The project also includes a range of features such as support for multiple exchanges, data providers, and a user-friendly interface. Whether you're a seasoned trader or just starting out, Vibe-Trading has something to offer. Join the community and start trading with confidence - one command to empower your agent!
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🧠 Channel: https://t.me/GithubRe | 86 |
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| 17 | 🔥 Nutlope/hallmark is trending — and it deserves your attention.
🔗 https://github.com/Nutlope/hallmark
📝 Anti-AI-slop design skill for Claude Code, Cursor, and Codex.
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Hallmark is a design skill for Claude Code, Cursor, and Codex that generates unique, human-like designs. It comes with twenty themes and four verbs: hallmark (build new UI), hallmark audit (score existing code), hallmark redesign (rebuild with a different fingerprint), and hallmark study (extract design DNA).
To use Hallmark, simply run npx skills add nutlope/hallmark and follow the instructions.
Hallmark is perfect for developers and designers who want to create custom, AI-generated designs without the templated look. With its 57 slop-test gates and pre-emit self-critique, Hallmark ensures that each design is unique and refined.
In short, Hallmark is a game-changer for design automation - it's like having a personal designer at your fingertips, refusing to look AI-generated.
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🧠 Channel: https://t.me/GithubRe | 89 |
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| 19 | 💡 virattt/ai-hedge-fund just hit the trending charts — here's why it matters.
🔗 https://github.com/virattt/ai-hedge-fund
📝 An AI Hedge Fund Team
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The AI Hedge Fund is a proof of concept project that explores the use of AI to make trading decisions. It's an educational project, not intended for real trading or investment. The system employs multiple agents, each with its own strategy, such as value investing, growth investing, and risk analysis. These agents include:
- Aswath Damodaran Agent
- Ben Graham Agent
- Bill Ackman Agent
- Cathie Wood Agent
- Charlie Munger Agent
- Michael Burry Agent
- Mohnish Pabrai Agent
- Nassim Taleb Agent
- Peter Lynch Agent
- Phil Fisher Agent
- Rakesh Jhunjhunwala Agent
- Stanley Druckenmiller Agent
- Warren Buffett Agent
- Valuation Agent
- Sentiment Agent
- Fundamentals Agent
- Technicals Agent
- Risk Manager
- Portfolio Manager
To use the AI Hedge Fund, you can run it via command line interface or a web application. The project is still evolving, with a vision to become a persistent, always-on AI hedge fund.
The project is for educational and research purposes only. You can contribute to the project by forking the repository, creating a feature branch, committing your changes, and creating a pull request.
One-liner takeaway: The AI Hedge Fund is a cutting-edge, community-driven project that's pushing the boundaries of AI in finance, and you can be a part of it.
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🧠 Channel: https://t.me/GithubRe | 84 |
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