Github Top Repositories
Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
نمایش بیشتر📈 تحلیل کانال تلگرام Github Top Repositories
کانال Github Top Repositories (@githubre) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 15 216 مشترک است و جایگاه 13 409 را در دسته آموزش و رتبه 26 085 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 15 216 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 05 نوامبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 393 و در ۲۴ ساعت گذشته برابر 6 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 0.92% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 0.62% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 140 بازدید دریافت میکند. در اولین روز معمولاً 95 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 1 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند repository, fork, programming, statistic, description تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 06 نوامبر, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته آموزش تبدیل کردهاند.
online ingest, adding vectors without a train step, and is faster than FAISS with hand-written NEON and AVX-512BW kernels. Key features include filter-at-search-time capabilities, pure local deployment, and support for stable external ids.
Technical highlights include a 10-16x compression ratio, Lloyd-Max scalar quantization, and bit-packing. The length-renormalized scoring ensures unbiased inner-product estimation.
Audience: Developers building RAG (Retrieval-Augmented Generation) stacks where privacy, memory, or latency matters.
To get started, install via pip install turbovec or cargo add turbovec, and explore the Python or Rust APIs.
Turbovec is ideal for applications requiring efficient and private vector search. Try it out and experience the power of TurboQuant! You'll be searching faster and more efficiently in no time: Turbovec - search at the speed of thought.
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🧠 Channel: https://t.me/GithubRe/last30days command that can be run in various platforms, including Claude Code, Codex, and Gemini CLI.
Key features include shareable HTML briefs, intelligent search, and cross-source cluster merging. It's useful for research, sales calls, and staying up-to-date with the latest information on a topic. The skill is designed for anyone looking for a more accurate and comprehensive search engine, including researchers, sales professionals, and anyone looking to stay informed.
One-liner takeaway: With last30days-skill, you can search what actually matters, not just what editors think is relevant.
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🧠 Channel: https://t.me/GithubRegoose is built in Rust for performance and portability, and it works with 15+ providers, including Anthropic, OpenAI, and Google. You can connect to 70+ extensions via the Model Context Protocol open standard. To get started, you can download the desktop app or install the CLI using a simple script:
curl -fsSL https://github.com/aaif-goose/goose/releases/download/stable/download_cli.sh | bash
goose is perfect for developers, researchers, and anyone looking for a versatile AI agent. So, why wait? Join the goose community today and start "migrating" your workflows to the next level - goose is the ultimate AI sidekick that will help you "fly" through your tasks!
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🧠 Channel: https://t.me/GithubRecopy-paste templates, and a guided learning path that takes you from beginner to power user in 11-13 hours.
Key features include:
* 10 tutorial modules covering every Claude Code feature
* Copy-paste configs for slash commands, CLAUDE.md templates, hook scripts, MCP configs, subagent definitions, and full plugin bundles
* Mermaid diagrams showing how each feature works internally
* A guided learning path with time estimates and interactive quizzes to identify knowledge gaps
The guide is suitable for developers of all levels, from those who have just installed Claude Code to experienced users looking to combine features into workflows. It's actively maintained, compatible with Claude Code 2.1+, and available under the MIT license, making it free to use forever.
To get started, you can clone the repository, copy a slash command template, and try it in 15 minutes. The guide also includes a 1-hour essential setup to get you up and running quickly.
In summary, luongnv89/claude-howto is the ultimate resource for unlocking Claude Code's full potential, and with it, you can master Claude Code in a weekend and take your productivity to the next level - start learning now and 10x your productivity!
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🧠 Channel: https://t.me/GithubRemergePDFs-windows-amd64.exe program provided in the repository.
The project encourages open-source contributions and community involvement. You can support the project by donating or joining their Telegram community to stay updated on the latest developments.
One-liner takeaway: ChinaTextbook is a valuable resource for anyone looking for free access to Chinese educational materials, promoting education equality and open access to knowledge.
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🧠 Channel: https://t.me/GithubReAG-UI Protocol, which is adopted by major companies like Google, LangChain, AWS, Microsoft, Mastra, and PydanticAI. CopilotKit provides a range of tools and features, including a useAgent hook, generative UI, and self-learning agents. The framework is designed to be easy to use, with a simple installation process and a comprehensive documentation.
CopilotKit is suitable for developers, product teams, and companies looking to build agentic applications and integrate AI into their products. The framework is constantly evolving, with new features and updates being added regularly. To get started with CopilotKit, you can install it using npx copilotkit@latest create -f <framework> or npx copilotkit@latest init for existing projects.
With CopilotKit, you can add AI to your app in just 1 minute and unlock the power of agentic applications. Build the future of AI-powered applications with CopilotKit - where agents meet applications.
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🧠 Channel: https://t.me/GithubRepip install supervision. The library supports various models and datasets, including Ultralytics, Transformers, and MMDetection, and provides connectors for popular libraries.
Technical highlights of Supervision include its ability to load and annotate images and videos, as well as its support for customizable annotators. The library is designed for data scientists and machine learning engineers who want to build and deploy computer vision applications quickly and efficiently.
In summary, Supervision is a powerful library that simplifies computer vision development - build computer vision apps faster with Supervision.
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🧠 Channel: https://t.me/GithubReuv tool install mempalace or pipx install mempalace, then initialize it with mempalace init ~/projects/myapp. The mempalace mine command is used to mine content into the palace, while mempalace search retrieves relevant information.
MemPalace boasts an impressive 96.6% R@5 raw on the LongMemEval benchmark, with no API calls required. It also includes a temporal entity-relationship graph and supports MCP tools for palace reads/writes, knowledge-graph operations, and more.
The target audience for MemPalace includes developers, researchers, and individuals seeking a robust, local-first AI memory solution.
Overall, MemPalace offers a powerful and flexible solution for storing and retrieving conversation history, making it an excellent choice for those seeking a reliable and efficient AI memory system.
Takeaway: MemPalace revolutionizes local-first AI memory, making it a game-changer for anyone seeking to harness the power of semantic search.
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🧠 Channel: https://t.me/GithubRewhichllm to get a copy-paste Python snippet for any model, and it supports various model formats like GGUF, AWQ, and GPTQ.
Technical highlights include architecture-aware estimates, live data from the HuggingFace API, and a simple, scriptable command-line interface. whichllm is designed for developers, researchers, and anyone who wants to work with LLMs.
To get started, simply run uvx whichllm@latest or install it using brew install andyyyy64/whichllm/whichllm or pip install whichllm.
Here's a punchy one-liner takeaway: With whichllm, you can easily find the perfect LLM for your hardware and start building amazing AI projects!
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🧠 Channel: https://t.me/GithubReplugin.json manifest and optional supporting files like skills/, agents/, and assets/.
Some highlighted examples include plugins for Figma, Notion, iOS and macOS app development, web apps, Expo, and more. These plugins are designed to make your life easier, whether you're working on design systems, planning and research, or building and deploying apps.
The technical details are straightforward: each plugin has a required plugin.json file and may include additional files and directories. For example, a plugin might include a hooks.json file for custom hooks or an agents/ directory for custom agent implementations.
This repository is perfect for developers, designers, and makers looking to tap into the power of Codex and automate their workflows.
In short, the openai/plugins repository is your one-stop shop for unlocking Codex's full potential - join the community and start building today!
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🧠 Channel: https://t.me/GithubReskills are the building blocks, encoding proven PM frameworks and guiding users through specific tasks. Commands chain one or more skills into end-to-end processes, while plugins group related skills and commands into installable packages.
To get started, users can install the marketplace using Claude Cowork or Claude Code, or even use the skills with other AI assistants like Codex, Gemini CLI, OpenCode, Cursor, or Kiro.
The repository includes a range of plugins, such as pm-product-discovery, pm-product-strategy, and pm-execution, each with its own set of skills and commands. For example, the /discover command chains four skills together: brainstorm-ideas, identify-assumptions, prioritize-assumptions, and brainstorm-experiments.
In summary, the pm-skills repository empowers product managers to make better product decisions with its comprehensive AI-powered operating system - Upgrade your product management workflow with pm-skills and start making data-driven decisions today!
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🧠 Channel: https://t.me/GithubRe6-block evaluation system and negotiation scripts, Career-Ops provides a comprehensive approach to job searching.
The system is agentic, using AI to navigate career pages, evaluate fit, and adapt resumes per listing. It's built with technologies like Claude Code, OpenCode, and Gemini CLI, and supports Node.js and Go.
To get started, users can clone and install the repository, configure their profiles, and add their CVs. The system is designed to be customized by Claude Code itself, allowing users to change modes, archetypes, and scoring weights.
The key features of Career-Ops include auto-pipeline, interview story bank, and pipeline integrity. It also supports Gemini CLI integration and provides a dashboard TUI for browsing and filtering the pipeline.
In summary, Career-Ops is a powerful tool for job seekers, providing a personalized and efficient approach to finding their dream roles: it's like having a personal recruiter in your pocket.
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🧠 Channel: https://t.me/GithubRe