Github Top Repositories
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Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
Показати більше📈 Аналітичний огляд Telegram-каналу Github Top Repositories
Канал Github Top Repositories (@githubre) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 15 212 підписників, посідаючи 13 433 місце в категорії Освіта та 26 115 місце у регіоні Індія.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 15 212 підписників.
За останніми даними від 04 листопада, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 407, а за останні 24 години на 27, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 0.93%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.62% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 142 переглядів. Протягом першої доби публікація в середньому набирає 95 переглядів.
- Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 1.
- Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як repository, fork, programming, statistic, description.
📝 Опис та контентна політика
Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Завдяки високій частоті оновлень (останні дані отримано 05 листопада, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.
15 212
Підписники
+2724 години
+807 днів
+40730 днів
Архів дописів
15 213
⚡ twentyhq/twenty is making waves. Here's the full picture.
🔗 https://github.com/twentyhq/twenty
📝 The open alternative to Salesforce, designed for AI.
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The Twenty repository is home to an open-source CRM that's highly customizable. Its key features include defining objects, fields, and views as code, building custom apps, and utilizing version control. To get started, you can
npx create-twenty-app my-app to scaffold a new app and then define objects as code, like so:
import { defineObject, FieldType } from 'twenty-sdk/define';
export default defineObject({
nameSingular: 'deal',
namePlural: 'deals',
labelSingular: 'Deal',
labelPlural: 'Deals',
fields: [
{ name: 'name', label: 'Name', type: FieldType.TEXT },
{ name: 'amount', label: 'Amount', type: FieldType.CURRENCY },
{ name: 'closeDate', label: 'Close Date', type: FieldType.DATE_TIME },
],
});
15 213
📌 Spotted on GitHub Trending: google-research/timesfm — let's break it down.
🔗 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.
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The TimesFM repository on GitHub is home to a pretrained time-series foundation model developed by Google Research. This model is designed for time-series forecasting, and its key features include support for continuous quantile forecasting and a range of configuration options. To get started, you can install the
timesfm package from PyPI using pip install timesfm[torch] or pip install timesfm[flax].
The repository includes a range of examples and documentation, including a fine-tuning example using HuggingFace Transformers and a code example that demonstrates how to use the model for forecasting. The model has been used in a variety of applications, including Google's BigQuery ML and Google Sheets.
From a technical perspective, the model is implemented in both PyTorch and Flax, and supports a range of hardware accelerators. The code is well-organized and includes a range of tests and examples to help you get started.
The TimesFM model is suitable for a range of audiences, including data scientists and machine learning engineers who are interested in time-series forecasting. Whether you're looking to build a forecasting model from scratch or simply want to use a pre-trained model for your own applications, TimesFM is definitely worth checking out.
In short, TimesFM is a powerful tool for time-series forecasting that's easy to use and highly customizable - give it a try and see what it can do for you!
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🧠 Channel: https://t.me/GithubRe15 213
🔍 Deep-diving into DeusData/codebase-memory-mcp — fresh off the trending list.
🔗 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.
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Unlock the Power of Code Intelligence: The
codebase-memory-mcp GitHub repository offers a revolutionary code intelligence engine designed for AI coding agents. This powerful tool can full-index an average repository in milliseconds and the Linux kernel in just 3 minutes, answering structural queries in under 1ms.
With high-quality parsing through tree-sitter AST analysis and Hybrid LSP semantic type resolution for 9 languages, it produces a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. The engine ships as a single static binary for macOS, Linux, and Windows, making it easy to download and install.
Key features include extreme indexing speed, plug-and-play functionality, support for 158 languages, and built-in graph visualization. The engine also offers advanced features like dead code detection, cross-service linking, and infrastructure-as-code indexing.
The codebase-memory-mcp is designed for developers, researchers, and anyone looking to unlock the full potential of their codebase. With its ease of use, flexibility, and powerful features, it's an essential tool for anyone working with code.
One-liner takeaway: Supercharge your coding workflow with codebase-memory-mcp, the fastest and most efficient code intelligence engine for AI coding agents.
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🧠 Channel: https://t.me/GithubRe
15 213
📌 Spotted on GitHub Trending: tursodatabase/turso — let's break it down.
🔗 https://github.com/tursodatabase/turso
📝 Turso is an in-process SQL database, compatible with SQLite.
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The Turso Database is an in-process SQL database, compatible with SQLite, written in Rust. It offers key features like
BEGIN CONCURRENT for improved write throughput, change data capture for real-time tracking, and multi-language support for languages such as Go, JavaScript, Java, .NET, Python, and Rust.
To get started, you can install the latest turso release or build and run the latest development version. The database provides an interactive shell where you can execute SQL statements. It also supports asynchronous I/O, cross-platform compatibility, and vector support.
The Turso Database has a wide range of use cases, from simple embedded databases to complex, distributed systems. Its technical highlights include SQLite compatibility, multi-version concurrency control, and support for various programming languages.
Whether you're a developer, data scientist, or simply looking for a reliable database solution, Turso Database is an excellent choice. With its active community and extensive documentation, you'll find all the resources you need to get started and succeed.
Turso Database is for anyone looking for a fast, reliable, and scalable database solution - join the community and experience the power of Turso today! Take the leap and discover a database that's truly designed for the future!
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🧠 Channel: https://t.me/GithubRe
15 213
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15 213
🔥 calesthio/OpenMontage is trending — and it deserves your attention.
🔗 https://github.com/calesthio/OpenMontage
📝 World's first open-source, agentic video production system. 12 pipelines, 52 tools, 500+ agent skills. Turn your AI coding assistant into a full video production studio.
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Introducing OpenMontage, the first open-source, agentic video production system. This powerful tool allows you to create stunning videos by simply describing what you want in plain language. The agent handles research, scripting, asset generation, editing, and final composition, making it easy to produce high-quality videos.
Key features include the ability to start from a reference video, paste a YouTube link, and have the agent analyze the transcript, pacing, scenes, keyframes, and style to create a grounded production plan. You can also use
Python 3.10+ and FFmpeg to install and run OpenMontage.
Technical highlights include the use of Remotion for React-based rendering, HyperFrames for HTML/CSS/GSAP rendering, and FFmpeg for post-production. The system also supports a range of API keys for additional tools and services, such as image and video gateways, free stock media, music, and voice services.
Audience includes anyone looking to create high-quality videos without extensive video production experience. Whether you're a marketer, educator, or simply a video enthusiast, OpenMontage is designed to be user-friendly and accessible.
In summary, OpenMontage is a revolutionary video production system that makes it easy to create stunning videos with minimal effort. With its powerful features and user-friendly interface, it's perfect for anyone looking to take their video production to the next level. Turn your ideas into professional-looking videos with OpenMontage - the future of video production is here!
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🧠 Channel: https://t.me/GithubRe15 213
💡 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
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Penpot is an open-source design platform for teams that build digital products at scale, giving you full ownership of your design infrastructure. With
real-time collaboration, open standards like SVG, CSS, HTML, and JSON, and self-hosting capabilities, Penpot puts teams in complete control of their design environment.
Key features include best-in-class native Design Tokens, a powerful open API and plugin system, and multi-directional workflows between design and code. With CSS Grid and Flex Layout, teams can design responsive interfaces that behave like real code from the start.
Penpot is perfect for teams scaling their design systems, and its full-stack design platform helps build scalable design systems and integrated product development processes. Whether you're a designer or developer, Penpot's code-based approach makes designs readable by developers and AI.
Join the Penpot community to contribute, ask questions, and get inspired. You can participate in various ways, such as creating and sharing libraries and templates, reporting bugs, or contributing to the code.
Penpot is licensed under the Mozilla Public License, v. 2.0, and its source code is available on GitHub.
Takeaway: With Penpot, you can own your design infrastructure and build scalable design systems with ease.
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🧠 Channel: https://t.me/GithubRe
15 213
📌 Spotted on GitHub Trending: palmier-io/palmier-pro — let's break it down.
🔗 https://github.com/palmier-io/palmier-pro
📝 macOS video editor built for AI
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Palmier Pro is an open-source video editor built for AI, available for macOS 26 (Tahoe) on Apple Silicon. This Swift-native editor integrates generative AI features, allowing users to generate and edit videos together inside the timeline. Key features include built-in support for SOTA models like Seedance and Kling, as well as integration with agents like Claude, Codex, and Cursor via
MCP server. To connect, users can follow the provided claude mcp add --transport http palmier-pro http://127.0.0.1:19789/mcp
15 213
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15 213
📌 Spotted on GitHub Trending: Lightricks/LTX-2 — let's break it down.
🔗 https://github.com/Lightricks/LTX-2
📝 Official Python inference and LoRA trainer package for the LTX-2 audio–video generative model.
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Lightricks/LTX-2 is a groundbreaking DiT-based audio-video foundation model that packs all the core capabilities of modern video generation into one powerful package: synchronized audio and video, high fidelity, multiple performance modes, production-ready outputs, API access, and open access.
To get started, clone the repository and set up your environment with the required models, including the LTX-2.3 model checkpoint, spatial upscaler, temporal upscaler, distilled LoRA, and Gemma text encoder.
The model boasts several key features, such as available pipelines for production-quality text/image-to-video generation, video-to-video transformations, and audio-to-video generation. It also offers optimization tips for faster inference, including using distilled pipelines, enabling FP8 quantization, and installing attention optimizations.
Prompting for LTX-2 requires detailed, chronological descriptions of actions and scenes, including specific movements, appearances, camera angles, and environmental details. The model also supports automatic prompt enhancement via an `enhance_prompt` parameter.
The target audience for LTX-2 includes developers, researchers, and creators looking to generate high-quality videos using a versatile and powerful model.
Here's a
quick start example:
git clone https://github.com/Lightricks/LTX-2.git
cd LTX-2
uv sync --frozen
source .venv/bin/activate15 213
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15 213
🔍 Deep-diving into Kong/insomnia — fresh off the trending list.
🔗 https://github.com/Kong/insomnia
📝 The open-source, cross-platform API client for GraphQL, REST, WebSockets, SSE and gRPC. With Cloud, Local and Git storage.
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Insomnia is an open-source, cross-platform API client for various protocols like GraphQL, REST, and more. With Insomnia, you can debug, design, test, mock, and build CI/CD pipelines for APIs. It offers features like a native OpenAPI editor, test suites, and collection runner.
Insomnia supports multiple storage options, including Local Vault, Git Sync, and Cloud Sync, allowing users to choose how they want to store their projects.
The Insomnia API client is suitable for developers, testers, and teams who need to collaborate on API development. It's available for Mac, Windows, and Linux, and can be downloaded from the official website.
For developers who want to contribute to Insomnia, the project is structured as a monorepo and requires Node.js and Git to develop.
One-liner takeaway: Insomnia is the ultimate API client for developers, offering a wide range of features and flexibility to streamline API development and testing.
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🧠 Channel: https://t.me/GithubRe15 213
🌟 penpot/penpot caught my eye on GitHub Trending today.
🔗 https://github.com/penpot/penpot
📝 Penpot: The open-source design tool for design and code collaboration
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Penpot is an open-source design platform for teams that build digital products at scale, giving you full ownership of your 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. With CSS Grid and Flex Layout, teams can design responsive interfaces that behave like real code from the start.
Penpot is suitable for designers and developers, offering a fluid design-code process and real-time collaboration. The platform is deployment agnostic, allowing use in the cloud or deployment on your own servers.
To get started, you can use Penpot in the cloud or deploy it anywhere, and the community is always available to help. Whether you're a developer or designer, Penpot provides a single source of truth for design and development, making it a full-stack design platform for building scalable design systems.
Penpot's code-based approach and open API make it an ideal choice for teams that want to integrate design and development workflows. With its flexible and customizable nature, Penpot is perfect for teams of all sizes.
In short, Penpot empowers teams to own their design infrastructure, streamline collaboration, and build scalable design systems - all while maintaining full control and flexibility. Design, code, and collaborate - all in one place.
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🧠 Channel: https://t.me/GithubRe