Github Top Repositories
Kanalga Telegram’da o‘tish
Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
Ko'proq ko'rsatish📈 Telegram kanali Github Top Repositories analitikasi
Github Top Repositories (@githubre) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 15 233 obunachidan iborat bo'lib, Taʼlim toifasida 13 394-o'rinni va Hindiston mintaqasida 26 058-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 15 233 obunachiga ega bo‘ldi.
07 Noyabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 379 ga, so‘nggi 24 soatda esa 11 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 0.92% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.62% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 140 marta ko‘riladi; birinchi sutkada odatda 95 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 1 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent repository, fork, programming, statistic, description kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 08 Noyabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
15 233
Obunachilar
+1124 soatlar
+767 kun
+37930 kun
Postlar arxiv
15 233
🌟 rohitg00/agentmemory caught my eye on GitHub Trending today.
🔗 https://github.com/rohitg00/agentmemory
📝 #1 Persistent memory for AI coding agents based on real-world benchmarks
──────────────────────────────
The agentmemory GitHub repository provides a persistent memory solution for AI coding agents, allowing them to recall previous interactions and maintain context. The key features of agentmemory include auto-capture of interactions, retrieval accuracy of 95.2%, and support for multiple agents through MCP and REST API.
To use
npx @agentmemory/agentmemory, simply run the command, and the agent will start capturing interactions and maintaining context. This eliminates the need for re-explaining previous interactions, making it a valuable tool for developers.
The technical highlights of agentmemory include its use of BM25, vector, and graph search algorithms, as well as its support for leases, signals, and SQLite storage. The repository also includes benchmarks and comparisons with other competitors, demonstrating the effectiveness of agentmemory.
agentmemory is designed for developers who work with AI coding agents, particularly those who use Claude Code, Cursor, Gemini CLI, Codex CLI, and other MCP clients. With its easy-to-use interface and robust features, agentmemory is an essential tool for anyone looking to improve their productivity and efficiency when working with AI coding agents.
In summary, agentmemory is a game-changer for AI coding agents, providing persistent memory and recall capabilities that make development faster and more efficient - with agentmemory, your coding agent remembers everything, so you don't have to.
──────────────────────────────
🧠 Channel: https://t.me/GithubRe
15 233
🔍 Deep-diving into bytedance/UI-TARS-desktop — fresh off the trending list.
🔗 https://github.com/bytedance/UI-TARS-desktop
📝 The Open-Source Multimodal AI Agent Stack: Connecting Cutting-Edge AI Models and Agent Infra
──────────────────────────────
The UI-TARS-desktop GitHub repository offers a powerful desktop application that leverages the UI-TARS model to provide a native GUI Agent. This application is part of the TARS* multimodal AI Agent stack, which includes Agent TARS and UI-TARS-desktop. Agent TARS brings the power of GUI Agent and Vision into your terminal, computer, browser, and product, primarily shipping with a CLI and Web UI for usage.
Key features of Agent TARS include a one-click out-of-the-box
CLI, hybrid browser agent, event stream, and MCP integration. The UI-TARS-desktop application provides a desktop GUI Agent based on the UI-TARS model, supporting local and remote computer operators, as well as browser operators.
To get started with Agent TARS, you can launch it with npx @agent-tars/cli@latest or install it globally with npm install @agent-tars/cli@latest -g. For more information, you can visit the comprehensive Quick Start guide.
UI-TARS-desktop is designed for users looking for a seamless and intelligent desktop experience, while Agent TARS is ideal for developers and power users who want to leverage the power of multimodal AI Agents.
In a nutshell, UI-TARS-desktop and Agent TARS are revolutionizing the way we interact with our computers and browsers, making it more human-like and efficient - experience the future of AI-powered desktop applications today!
──────────────────────────────
🧠 Channel: https://t.me/GithubRe
15 233
🔥 anthropics/financial-services is trending — and it deserves your attention.
🔗 https://github.com/anthropics/financial-services
📝 No description.
──────────────────────────────
The Claude for Financial Services GitHub repository provides a comprehensive set of tools and templates for financial services workflows, including investment banking, equity research, private equity, and wealth management. The repository offers reference agents, skills, and data connectors that can be installed as
Claude Cowork plugins or deployed via the Claude Managed Agents API.
Key features include:
- Agents: named, end-to-end workflow agents (e.g., Pitch Agent, Market Researcher) that can be installed and tuned to a firm's specific needs
- Vertical plugins: skill and command bundles for specific financial services verticals (e.g., investment banking, equity research)
- Data connectors: integrations with various data providers (e.g., Daloopa, Morningstar, S&P Global) via the Model Context Protocol (MCP)
To get started, users can install the repository as a Claude Cowork plugin or deploy it via the Claude Managed Agents API. The repository also includes a Claude for Microsoft 365 install tool for provisioning the Claude add-in in a customized Microsoft 365 environment.
The target audience for this repository includes financial services professionals, developers, and IT administrators looking to automate and streamline their workflows using AI-powered tools.
In short, the Claude for Financial Services repository is a powerful toolkit for financial services firms looking to leverage AI and automation to boost productivity and efficiency - and the best part is, it's all customizable to how your firm works.
──────────────────────────────
🧠 Channel: https://t.me/GithubRe15 233
🌟 Augani/openreel-video caught my eye on GitHub Trending today.
🔗 https://github.com/Augani/openreel-video
📝 OpenReel Video - Professional browser-based video editor. Open source CapCut alternative. 100% browser-based, no installation, no cloud uploads, no watermarks.
──────────────────────────────
OpenReel Video is a free, open-source, browser-based video editor that runs entirely client-side, offering professional-grade video editing without the need for expensive software or cloud processing. With key features like a multi-track timeline, keyframe animations, color grading, and audio effects, it's an alternative to popular video editing software.
Try it live at openreel.video or run it locally by cloning the repository and installing dependencies.
The editor is built with React, TypeScript, WebCodecs, and WebGPU for smooth 4K editing and fast exports. It's suitable for anyone looking for a free, user-friendly, and feature-rich video editing solution.
Takeaway: OpenReel Video is revolutionizing video editing by making it free, open-source, and accessible to everyone, forever.
──────────────────────────────
🧠 Channel: https://t.me/GithubRe15 233
⚠️ Right now, the TickBit AI agent is ready to credit $30 to your starting balance.
No conditions. No deposit. In just one click.
🚀 What you get in 5 seconds:
✅ $30 — a welcome bonus to get you started.
✅ Per-second profit straight to your account.
✅ 0% effort — the bot trades while you relax.
✅ Instant withdrawals from $0.1 with zero fees.
⏳ The $30 offer is limited! Grab it while it’s available
👉 START AND CLAIM $30 👈🏻
#ad 📢 InsideAd
15 233
🌟 flutter/skills caught my eye on GitHub Trending today.
🔗 https://github.com/flutter/skills
📝 No description.
──────────────────────────────
The Flutter Skills repository provides a collection of skills for happy path Flutter app development workflows. These skills offer tailored instructions to reduce mistakes and ensure agents complete tasks following best practices. You can install all skills into your project using the command
npx skills add flutter/skills --skill '*' --agent universal. The available skills include flutter-add-integration-test, flutter-add-widget-preview, and flutter-apply-architecture-best-practices, among others. Each skill has a specific use case, such as adding integration tests or creating interactive widget previews. To update the skills, run the command npx skills update. The repository is maintained by the Flutter team and is suitable for developers looking to streamline their workflow. Take your Flutter development to the next level with these skills - automate repetitive tasks and focus on what matters.
──────────────────────────────
🧠 Channel: https://t.me/GithubRe15 233
🚀 Meet datawhalechina/hello-agents: a gem from today's GitHub trending list.
🔗 https://github.com/datawhalechina/hello-agents
📝 📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
──────────────────────────────
Hello-Agents is a comprehensive open-source tutorial on building AI agents from scratch. The project aims to provide a systematic guide to constructing intelligent systems, from basic theories to practical applications.
Key features of the project include:
- A structured approach to learning, covering the fundamentals of AI agents, language models, and their applications
-
hands-on exercises and projects to help learners gain practical experience
- A community-driven approach, with opportunities for contributors to share their knowledge and experiences
The project is suitable for AI developers, software engineers, students, and self-learners with basic Python programming skills and a conceptual understanding of large language models.
The project's technical highlights include:
- constructing AI agents using popular frameworks and tools15 233
🎯 lobehub/lobehub landed on trending. Worth a proper look.
🔗 https://github.com/lobehub/lobehub
📝 The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.
──────────────────────────────
LobeHub is a revolutionary platform that enables humans and agents to co-evolve, transforming the way we work and interact with AI. The platform offers a range of key features, including the ability to create, collaborate, and evolve with agent teammates that grow with you.
To get started, users can join the LobeHub community and explore the various features and tools available. The platform provides a
unified intelligence system, allowing users to access any model and modality, and a library of over 10,000+ skills and MCP-compatible plugins.
Some of the technical highlights of LobeHub include its Agent Builder, Agent Groups, and Personal Memory features, which enable users to build, collaborate, and learn with their agent teammates. The platform also supports local large language model (LLM) support, model visual recognition, and TTS & STT voice conversation.
LobeHub is designed for a wide range of users, from professional developers to enthusiastic users, and offers a user-friendly product ecosystem that is open, transparent, and constantly evolving.
In a nutshell, LobeHub is the future of human-AI collaboration - and it's here to revolutionize the way we work and interact with AI.
──────────────────────────────
🧠 Channel: https://t.me/GithubRe
15 233
🚀 Meet LearningCircuit/local-deep-research: a gem from today's GitHub trending list.
🔗 https://github.com/LearningCircuit/local-deep-research
📝 ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.
──────────────────────────────
Local Deep Research is an AI-powered research assistant that runs locally for privacy, allowing you to use any Large Language Model (LLM) and build your own searchable knowledge base. With multiple research strategies and proper citations, it helps you perform deep, agentic research across the web, academic papers, and your own documents.
The
local-deep-research repository provides a Docker-based solution, with options for Docker Run and Docker Compose, as well as a pip install method for Windows, macOS, and Linux. You can choose from 20+ research strategies, including the new LangGraph Agent Strategy, which adaptively switches between search engines.
The tool builds your knowledge base by downloading sources, extracting text, indexing, and making them searchable. It features SQLCipher encryption with AES-256, ensuring your data stays private.
Security is a top priority, with static analysis, dependency scanning, and container security measures in place. The repository includes a Security Policy and a Security Review Process to ensure transparency.
In short, Local Deep Research is a powerful, private, and secure research assistant that helps you take control of your data and research. You own your data and can see exactly how it works, making it an ideal solution for anyone looking for a reliable and trustworthy research tool - Empowering your research, one query at a time.
──────────────────────────────
🧠 Channel: https://t.me/GithubRe15 233
⚡ HKUDS/AI-Trader is making waves. Here's the full picture.
🔗 https://github.com/HKUDS/AI-Trader
📝 "AI-Trader: 100% Fully-Automated Agent-Native Trading"
──────────────────────────────
Introduction to AI-Trader: This GitHub repository, HKUDS/AI-Trader, presents a 100% fully-automated agent-native trading platform. The primary purpose is to provide a space where AI agents can exchange ideas, sharpen their trading skills, and collaborate.
Key Features include instant agent integration, collective intelligence trading, cross-platform signal synchronization, one-click copy trading, universal market access, three signal types, and a reward system.
To use AI-Trader, agents can join by sending a simple message, while human traders can sign up directly on the platform. The repository is well-organized, with a clear architecture and comprehensive documentation for both agents and developers.
The platform is designed for all users, whether experienced traders looking to share their expertise or newcomers wanting to learn from the community. With its cutting-edge technology and user-friendly interface, AI-Trader is poised to revolutionize the trading landscape.
Technical highlights include the use of FastAPI for the backend, React for the frontend, and a modular design for easy maintenance and updates.
In short, AI-Trader is an innovative platform that empowers AI agents and human traders alike to achieve their full potential in financial markets.
Join the AI-Trader community today and start trading with the power of collective intelligence!
Automate your trades, elevate your investments, and experience the future of trading with AI-Trader!
──────────────────────────────
🧠 Channel: https://t.me/GithubRe
15 233
🚀 Meet awslabs/aidlc-workflows: a gem from today's GitHub trending list.
🔗 https://github.com/awslabs/aidlc-workflows
📝 AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI coding agents
──────────────────────────────
The awslabs/aidlc-workflows GitHub repository introduces the AI-Driven Development Life Cycle (AI-DLC), an intelligent software development workflow. This workflow is designed to adapt to the user's needs, maintain quality standards, and keep the developer in control of the process.
Key features of AI-DLC include its ability to integrate with various coding agents and platforms such as Kiro, Amazon Q Developer IDE Plugin, Cursor IDE, Cline, and Claude Code. To use AI-DLC, users need to download the latest release zip file, extract it to a folder outside their project directory, and follow the setup instructions for their chosen coding agent and platform.
Technical highlights of AI-DLC include its use of core workflow rules and detailed rules conditionally referenced by the core rules. The workflow is implemented using steering files, rules, or memory files, depending on the platform.
The target audience for AI-DLC includes software developers and teams looking to streamline their development process using AI-driven tools.
In summary, the AI-DLC workflow is a powerful tool for software development, offering an adaptive and intelligent approach to coding.
Takeaway: AI-DLC is revolutionizing the way we code, one workflow at a time.
──────────────────────────────
🧠 Channel: https://t.me/GithubRe
15 233
⚡ CloakHQ/CloakBrowser is making waves. Here's the full picture.
🔗 https://github.com/CloakHQ/CloakBrowser
📝 Stealth Chromium that passes every bot detection test. Drop-in Playwright replacement with source-level fingerprint patches. 30/30 tests passed.
──────────────────────────────
Meet CloakBrowser, a stealthy Chromium browser that evades bot detection with ease. Its source-level patches modify the Chromium binary at the C++ level, making it undetectable to antibot systems. With
launch(), you can create a new browser instance in just a few lines of code. Key features include auto-updating binary, human-like behavior with humanize=True, and passing reCAPTCHA v3 with a score of 0.9. CloakBrowser works seamlessly with Playwright and Puppeteer, and is perfect for web scraping, automation, and bypassing Cloudflare Turnstile. Give it a try with docker run --rm cloakhq/cloakbrowser cloaktest or pip install cloakbrowser. CloakBrowser is the ultimate solution for those tired of bot detection woes: it just works, and that's the cloak of stealth you need.
──────────────────────────────
🧠 Channel: https://t.me/GithubRe15 233
🎯 decolua/9router landed on trending. Worth a proper look.
🔗 https://github.com/decolua/9router
📝 Unlimited FREE AI coding. Connect Claude Code, Codex, Cursor, Cline, Copilot, Antigravity to FREE Claude/GPT/Gemini via 40+ providers. Auto-fallback, RTK -40% tokens, never hit limits.
──────────────────────────────
9Router is a revolutionary tool that helps you save up to 40% of your tokens and connect all your AI code tools to over 40 providers and 100+ models. With its RTK Token Saver and auto-fallback features, you can
maximize your subscriptions and minimize your costs.
To get started, simply install 9Router globally using npm install -g 9router, then connect a free provider like Kiro AI or OpenCode Free. You can then use 9Router with your favorite CLI tools like Claude Code, Codex, or OpenClaw.
The technical highlights of 9Router include its ability to auto-compress tool_result content, track quota, and auto-refresh tokens. With its universal compatibility, you can use 9Router with any CLI tool.
Whether you're a developer, a coder, or an AI enthusiast, 9Router is the perfect tool for you. It's designed to help you never stop coding while minimizing your costs.
Take your coding to the next level with 9Router - the ultimate token saver and AI router!
With 9Router, you can code freely, without worrying about token limits or expensive APIs.
──────────────────────────────
🧠 Channel: https://t.me/GithubRe
