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
15 212
🔍 Deep-diving into opendatalab/MinerU — fresh off the trending list.
🔗 https://github.com/opendatalab/MinerU
📝 Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.
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MinerU is a high-accuracy document parsing engine designed for LLM, RAG, and Agent workflows. It converts various file formats, including PDF, DOCX, PPTX, XLSX, images, and web pages, into structured Markdown or JSON. Key features include a VLM+OCR dual engine, support for 109 languages, and native integration with popular frameworks like LangChain and Dify.
The engine offers
pipeline, vlm-engine, and hybrid-engine backends for inference, supporting domestic AI chips such as Ascend and Cambricon. MinerU provides various deployment options, including a no-code web version, Gradio WebUI, and a fully offline desktop client.
Developers can utilize MinerU through Python, Go, or TypeScript SDKs, as well as a REST API and Docker support. The engine is compatible with multiple AI coding tools and RAG frameworks, making it a versatile solution for document parsing needs.
MinerU is perfect for developers, researchers, and businesses seeking a reliable and accurate document parsing engine. With its high-performance capabilities and flexible deployment options, MinerU is an ideal choice for a wide range of applications.
One-liner takeaway: MinerU is a powerful, high-accuracy document parsing engine that simplifies the process of converting unstructured data into actionable insights, making it an essential tool for anyone working with documents and LLMs.
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🧠 Channel: https://t.me/GithubRe15 212
💡 altic-dev/FluidVoice just hit the trending charts — here's why it matters.
🔗 https://github.com/altic-dev/FluidVoice
📝 FluidVoice - Fastest macOS Offline Dictation app - Voice to Text fully Local. One ⭐ takes us a long way :))
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FluidVoice is an open-source, on-device AI-enhanced voice-to-text dictation app for macOS. It offers real-time transcription with support for multiple speech models, including Nemotron Speech, Parakeet, and Whisper. The app features
Fluid Intelligence, a local AI runtime that provides smart formatting, context-aware capitalization, and post-processing without sending data to the cloud.
Key Features:
- Command Mode for controlling your Mac by voice
- Write Mode for writing or rewriting text in any text field
- Live Preview with real-time transcription overlay
- Multiple Speech Models for different languages and latency needs
- AI Enhancement with optional post-processing via OpenAI, Groq, or local Fluid Intelligence
Technical Highlights:
- Built with Swift and managed via Swift Package Manager
- Supports macOS 15.0 (Sequoia) or later
- Requires Apple Silicon Mac for all models, with Intel Mac support via Whisper models
Audience:
- Individuals who need efficient voice-to-text dictation on their Mac
- Developers interested in contributing to an open-source project
To get started, simply brew install --cask fluidvoice or download the latest release.
One-liner takeaway: With FluidVoice, experience the power of voice-to-text dictation on your Mac, enhanced by on-device AI, and never look back at your keyboard again.
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🧠 Channel: https://t.me/GithubRe
15 212
⚡ cupy/cupy is making waves. Here's the full picture.
🔗 https://github.com/cupy/cupy
📝 NumPy & SciPy for GPU
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CuPy is a NumPy and SciPy-compatible array library for GPU-accelerated computing with Python. It acts as a drop-in replacement to run existing NumPy/SciPy code on NVIDIA CUDA or AMD ROCm platforms.
You can import
cupy as cp and use it like NumPy, with features like ndarray and array operations. It also provides access to low-level CUDA features, including RawKernels and Streams.
CuPy is ideal for data scientists, machine learning engineers, and anyone looking to accelerate their Python code with GPU power.
To get started, you can install CuPy via Pip or Conda, and explore the documentation and tutorial for more information.
pip install cupy-cuda12x or conda install -c conda-forge cupy to install.
One-liner takeaway: CuPy unleashes GPU acceleration for Python with a simple, NumPy-compatible API.
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🧠 Channel: https://t.me/GithubRe15 212
🔍 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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Codebase-Memory-MCP is a blazing-fast code intelligence engine designed for AI coding agents. It full-indexes an average repository in milliseconds and answers structural queries in under 1ms. This engine supports
158 languages through tree-sitter AST analysis and Hybrid LSP semantic type resolution for languages like Python, TypeScript, and Rust.
Key features include:
- Extreme indexing speed: Indexes the Linux kernel in 3 minutes
- Plug and play: Single static binary for macOS, Linux, and Windows
- Built-in graph visualization: 3D interactive UI for exploring codebases
- Infrastructure-as-code indexing: Supports Dockerfiles, Kubernetes manifests, and more
To get started, simply run the install command, and the engine will auto-detect and configure your coding agents. With features like semantic search, cross-service linking, and cross-repo intelligence, this engine is perfect for developers looking to supercharge their coding workflow.
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
15 212
🔥 Robbyant/lingbot-map is trending — and it deserves your attention.
🔗 https://github.com/Robbyant/lingbot-map
📝 A feed-forward 3D foundation model for reconstructing scenes from streaming data
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The LingBot-Map is a groundbreaking tool for streaming 3D reconstruction, boasting a
feed-forward architecture that enables high-efficiency streaming inference and state-of-the-art reconstruction. Its key features include a Geometric Context Transformer that unifies various components for robust and accurate results, as well as paged KV cache attention for stable inference.
To get started, users can follow the installation instructions to set up the required environment and dependencies, including PyTorch and FlashInfer. The model can be downloaded from Hugging Face or ModelScope, and users can choose from various checkpoints, including lingbot-map-long and lingbot-map.
The demo.py script provides an interactive way to visualize and test the model on various example scenes, with options for sky masking, keyframe intervals, and windowed inference. For longer sequences, the offline rendering pipeline offers a way to render high-quality videos.
Overall, the LingBot-Map is designed for researchers and developers working on 3D reconstruction and computer vision tasks, and its ease of use and high performance make it an attractive choice for a wide range of applications.
Here's a simple command to get you started:
python demo.py --model_path /path/to/lingbot-map-long.pt --image_folder example/courthouse --mask_sky
15 212
🔍 Deep-diving into xbtlin/ai-berkshire — fresh off the trending list.
🔗 https://github.com/xbtlin/ai-berkshire
📝 AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Codex. 4 masters' methodologies + multi-agent adversarial analysis.
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Ai Berkshire is a revolutionary investment research framework that leverages AI to redefine the depth and efficiency of investment research. It systematizes and structures the methodologies of four investment masters: Warren Buffett, Charlie Munger, Yongping Duan, and Lu Li. By utilizing AI agents, it provides professional-level investment research, enabling individuals to make informed decisions.
The framework offers various
Skills for different purposes, such as /investment-research for comprehensive analysis, /investment-team for parallel research, and /industry-research for industry-wide scans. These skills are designed to provide structured and consistent outputs, allowing users to compare and contrast different companies and industries.
Technical highlights of the framework include the use of Python for precise calculations, multiple data sources for validation, and a mirror test to ensure that the research is thorough and unbiased. The framework also employs a four-dimensional assessment to evaluate companies based on their business model, moat, management, and valuation.
Ai Berkshire is suitable for investors, researchers, and financial professionals looking to enhance their investment research capabilities. With its robust framework and AI-driven approach, it has the potential to revolutionize the investment research industry. One key takeaway: Ai Berkshire turns individuals into a full-fledged investment research team.
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🧠 Channel: https://t.me/GithubRe
15 212
🚀 Meet ripienaar/free-for-dev: a gem from today's GitHub trending list.
🔗 https://github.com/ripienaar/free-for-dev
📝 A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
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The ripienaar/free-for-dev GitHub repository is a curated list of software and services offering free tiers, specifically tailored for infrastructure developers, including System Administrators and DevOps Practitioners. This list is the result of contributions from over 1600 people, making it a community-driven effort.
The repository covers a wide range of categories, including
Major Cloud Providers, Cloud management solutions, Analytics, Events, and Statistics, and many more. It provides detailed information on the free tiers offered by top cloud providers like Google Cloud Platform, Amazon Web Services, Microsoft Azure, Oracle Cloud, and IBM Cloud.
To be included in the list, a service must offer a perpetual free tier, not just a trial, with a minimum of one year if it's time-bucketed. The free tier must also be evaluated from a security perspective, allowing for Single Sign-On (SSO) but not restricting Transport Layer Security (TLS) to paid tiers.
Whether you're a seasoned developer or just starting out, this repository is an invaluable resource for finding the best free services to support your projects. So, why pay when you can get it for free - explore the ripienaar/free-for-dev repository today and start building without breaking the bank!
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🧠 Channel: https://t.me/GithubRe15 212
🎯 simplex-chat/simplex-chat landed on trending. Worth a proper look.
🔗 https://github.com/simplex-chat/simplex-chat
📝 SimpleX - the first messaging network operating without user identifiers of any kind - 100% private by design! iOS, Android and desktop apps 📱!
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SimpleX Chat is a messaging platform that prioritizes user privacy, with no user identifiers of any kind. It features double ratchet end-to-end encryption and an additional encryption layer to protect messages and metadata.
The app is available for
Android and iOS, with a TestFlight preview for iOS that offers new features 1-2 weeks earlier. You can also use it as a terminal app on Linux, MacOS, and Windows.
To get started, install the app, then connect to the team or join user groups to ask questions or share ideas. You can also make a private connection with a friend by sharing a link or scanning a QR code.
SimpleX Chat is for anyone who values privacy, including individuals and developers who want to build on the SimpleX platform.
Contribute to the project by developing features, translating the app, or donating to support the team.
Here's the punchy one-liner takeaway: SimpleX Chat is the ultimate private messaging platform where your conversations are truly yours alone.
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🧠 Channel: https://t.me/GithubRe
15 212
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15 212
💡 every-app/open-seo just hit the trending charts — here's why it matters.
🔗 https://github.com/every-app/open-seo
📝 Open source alternative to Semrush and Ahrefs
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Introducing OpenSEO, an open-source alternative to expensive SEO tools like Semrush and Ahrefs. This pay-as-you-go platform is designed for the people, giving you complete control over your SEO data. With OpenSEO, you can connect with any AI agent, such as Claude Code or Hermes, and utilize pre-built skills to tailor the tool to your needs.
The platform offers a range of key features, including
keyword research, rank tracking, competitor insights, backlinks, site audits, and AI visibility. You can also use OpenSEO's MCP server to expose your SEO data directly to your AI agent.
To get started, you can choose from two self-hosting options: Docker for personal use and Cloudflare for internet-facing self-hosting. OpenSEO is completely free to use, with costs limited to DataForSEO API usage.
The OpenSEO community is active and welcoming, with a Discord channel for discussion and a mailing list for updates. Whether you're an SEO expert or just starting out, OpenSEO is an excellent choice for managing your online presence.
Take control of your SEO data and join the OpenSEO community today - your wallet (and your website) will thank you!
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🧠 Channel: https://t.me/GithubRe
15 212
🌟 keycloak/keycloak caught my eye on GitHub Trending today.
🔗 https://github.com/keycloak/keycloak
📝 Open Source Identity and Access Management For Modern Applications and Services
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Keycloak is an open-source identity and access management solution that simplifies adding authentication to applications and securing services. It provides user federation, strong authentication, user management, and fine-grained authorization. To get started, you can download the distribution from the website and run it using
bin/kc.[sh|bat] start-dev or use the Docker image with docker run quay.io/keycloak/keycloak start-dev.
The project has a strong focus on community involvement and security, with guidelines for contributing and a Code of Conduct in place. Keycloak is written in Java and has a permissive Apache License, Version 2.0.
Keycloak is perfect for developers and organizations looking for a robust and scalable identity management solution. Whether you're building a web application, a mobile app, or a microservices architecture, Keycloak has the features and flexibility you need. So why wait? Dive into the world of Keycloak and discover the power of secure, scalable, and open-source identity management - add authentication to your apps in minutes, not months!
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🧠 Channel: https://t.me/GithubRe15 212
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15 212
🌟 HKUDS/Vibe-Trading caught my eye on GitHub Trending today.
🔗 https://github.com/HKUDS/Vibe-Trading
📝 "Vibe-Trading: Your Personal Trading Agent"
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Vibe-Trading is a personal trading agent that empowers users with comprehensive trading capabilities. The project offers a range of key features, including a Shadow Account, demo, quick start, and examples.
pip install vibe-trading-ai is the command to get started.
The project is built using Python 3.11+, FastAPI, and React 19, and has a PyPI package. It also has a Feishu group, WeChat group, and a Discord channel for community support.
The project's technical highlights include a global data layer with 18 market-data sources, 18 read-only data tools, and a local Data Bridge loader. It also features Research Autopilot, which runs hypothesis → signal-engine → backtest end to end.
Vibe-Trading is suitable for traders, researchers, and developers looking for a powerful trading agent. With its comprehensive features and active community, it's an ideal choice for those seeking a reliable and customizable trading solution.
The one command to rule them all: pip install vibe-trading-ai and trade away.
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🧠 Channel: https://t.me/GithubRe