Github Top Repositories
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🔥 roboflow/supervision is trending — and it deserves your attention.
🔗 https://github.com/roboflow/supervision
📝 We write your reusable computer vision tools. 💜
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The roboflow/supervision GitHub repository offers a comprehensive toolkit for building computer vision applications. Its purpose is to provide a set of reusable tools for tasks such as loading datasets, drawing detections, and counting objects in zones. The repository includes key features like model-agnostic design, connectors for popular libraries, customizable annotators, and dataset utilities.
To get started, users can
The target audience for this repository includes data scientists, machine learning engineers, and developers working on computer vision projects. With its extensive documentation, tutorials, and community support, the roboflow/supervision repository is an excellent resource for anyone looking to build and deploy computer vision applications.
The repository is well-documented, with a comprehensive guide, tutorials, and a community-driven discussion forum. It is also actively maintained, with a strong focus on community engagement and contribution.
In summary, roboflow/supervision is a powerful toolkit for building computer vision applications, offering a wide range of features, tools, and resources to support developers and data scientists. With its flexible design, extensive documentation, and active community, it's an excellent choice for anyone working on computer vision projects: build computer vision applications faster and more reliably with roboflow/supervision.
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🧠 Channel: https://t.iss.one/GithubRe
🔗 https://github.com/roboflow/supervision
📝 We write your reusable computer vision tools. 💜
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The roboflow/supervision GitHub repository offers a comprehensive toolkit for building computer vision applications. Its purpose is to provide a set of reusable tools for tasks such as loading datasets, drawing detections, and counting objects in zones. The repository includes key features like model-agnostic design, connectors for popular libraries, customizable annotators, and dataset utilities.
To get started, users can
pip install supervision and explore the quickstart guide, which covers topics like loading models, using annotators, and working with datasets. The repository also provides technical highlights such as support for various model types, including classification, detection, and segmentation models, and integration with popular libraries like Ultralytics and Transformers.The target audience for this repository includes data scientists, machine learning engineers, and developers working on computer vision projects. With its extensive documentation, tutorials, and community support, the roboflow/supervision repository is an excellent resource for anyone looking to build and deploy computer vision applications.
The repository is well-documented, with a comprehensive guide, tutorials, and a community-driven discussion forum. It is also actively maintained, with a strong focus on community engagement and contribution.
In summary, roboflow/supervision is a powerful toolkit for building computer vision applications, offering a wide range of features, tools, and resources to support developers and data scientists. With its flexible design, extensive documentation, and active community, it's an excellent choice for anyone working on computer vision projects: build computer vision applications faster and more reliably with roboflow/supervision.
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🧠 Channel: https://t.iss.one/GithubRe
🎯 vercel/next.js landed on trending. Worth a proper look.
🔗 https://github.com/vercel/next.js
📝 The React Framework
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Next.js is a popular React framework for building server-rendered, statically generated, and performance-optimized web applications. Its main purpose is to simplify the development process, allowing developers to focus on creating amazing user experiences.
Key features include server-side rendering, static site generation, and internationalization. To get started, simply create a new project using
From a technical perspective, Next.js provides a comprehensive set of tools and features, including built-in support for Webpack and Babel, as well as API routes for building custom server-side logic.
The framework is designed for frontend developers of all levels, from beginners to experienced professionals. Whether you're building a small blog or a complex e-commerce platform, Next.js has the tools and features you need to succeed.
In short: Next.js is the ultimate React framework for building fast, scalable, and performance-optimized web applications - so why wait, start building today!
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🧠 Channel: https://t.iss.one/GithubRe
🔗 https://github.com/vercel/next.js
📝 The React Framework
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Next.js is a popular React framework for building server-rendered, statically generated, and performance-optimized web applications. Its main purpose is to simplify the development process, allowing developers to focus on creating amazing user experiences.
Key features include server-side rendering, static site generation, and internationalization. To get started, simply create a new project using
npm init next-app or yarn create next-app, and you're ready to go.From a technical perspective, Next.js provides a comprehensive set of tools and features, including built-in support for Webpack and Babel, as well as API routes for building custom server-side logic.
The framework is designed for frontend developers of all levels, from beginners to experienced professionals. Whether you're building a small blog or a complex e-commerce platform, Next.js has the tools and features you need to succeed.
In short: Next.js is the ultimate React framework for building fast, scalable, and performance-optimized web applications - so why wait, start building today!
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🧠 Channel: https://t.iss.one/GithubRe
⚡ tailwindlabs/tailwindcss is making waves. Here's the full picture.
🔗 https://github.com/tailwindlabs/tailwindcss
📝 A utility-first CSS framework for rapid UI development.
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Tailwind CSS is a utility-first CSS framework that enables rapid building of custom user interfaces. Its key features include a
To use Tailwind CSS, simply include it in your project and start writing classes. The framework is
From a technical standpoint, Tailwind CSS is built using
The target audience for Tailwind CSS includes frontend developers, designers, and anyone looking to
In short, Tailwind CSS is the go-to framework for building custom and responsive user interfaces - write CSS faster, not more.
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🧠 Channel: https://t.iss.one/GithubRe
🔗 https://github.com/tailwindlabs/tailwindcss
📝 A utility-first CSS framework for rapid UI development.
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Tailwind CSS is a utility-first CSS framework that enables rapid building of custom user interfaces. Its key features include a
configurable and highly customizable design system, making it easy to create unique and consistent designs. To use Tailwind CSS, simply include it in your project and start writing classes. The framework is
easy to learn and has a low barrier to entry, making it accessible to developers of all levels.From a technical standpoint, Tailwind CSS is built using
PostCSS and JavaScript, allowing for seamless integration with existing projects. The target audience for Tailwind CSS includes frontend developers, designers, and anyone looking to
streamline their CSS workflow. In short, Tailwind CSS is the go-to framework for building custom and responsive user interfaces - write CSS faster, not more.
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⚡ uber/ADR is making waves. Here's the full picture.
🔗 https://github.com/uber/ADR
📝 ADR secures enterprise AI agents through observability, security benchmarking, and threat detection. Deployed at Uber.
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Meet ADR, an enterprise security system designed to secure AI agents. It's already being used in production at Uber and has been recognized in a paper accepted to MLSys 2026. ADR's key features include
The repository contains the open-source
ADR is perfect for organizations looking to secure their AI agents, whether they're employee-facing or customer-facing. With ADR, you can ensure your AI systems are safe and reliable.
One-liner takeaway: ADR is revolutionizing AI security by providing a robust system to detect and respond to potential threats, giving you peace of mind in the ever-evolving world of AI.
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🧠 Channel: https://t.iss.one/GithubRe
🔗 https://github.com/uber/ADR
📝 ADR secures enterprise AI agents through observability, security benchmarking, and threat detection. Deployed at Uber.
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Meet ADR, an enterprise security system designed to secure AI agents. It's already being used in production at Uber and has been recognized in a paper accepted to MLSys 2026. ADR's key features include
Observability, which captures agent activity, Benchmark, a testing system for agent security, Detection, which identifies risky behavior, and upcoming Prevention capabilities. The repository contains the open-source
ADR Sensor, ADR-Bench, and ADR Detector. To get started with ADR Detection, simply git clone the repository, navigate to the Detection directory, and run uv sync. ADR is perfect for organizations looking to secure their AI agents, whether they're employee-facing or customer-facing. With ADR, you can ensure your AI systems are safe and reliable.
One-liner takeaway: ADR is revolutionizing AI security by providing a robust system to detect and respond to potential threats, giving you peace of mind in the ever-evolving world of AI.
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🧠 Channel: https://t.iss.one/GithubRe
Github Top Repositories
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🎯 lyogavin/airllm landed on trending. Worth a proper look.
🔗 https://github.com/lyogavin/airllm
📝 AirLLM 70B inference with single 4GB GPU
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AirLLM is a game-changer for large language models, allowing massive models like 70B Llama 3.1 to run on a single 4GB GPU card without quantization, distillation, or pruning. This is achieved through sparse MoE models that stream one expert at a time.
Key Features:
- Support for various large language models, including Llama 3.x, DeepSeek V2/V3, and more
- Model compression for up to 3x inference speedup with minimal accuracy loss
- Easy usage with the
Technical Highlights:
-
-
- Supports
Audience:
- Developers and researchers working with large language models
- Those looking to deploy models on limited hardware
Takeaway: With AirLLM, you can run massive language models on minimal hardware, making AI more accessible and efficient.
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🧠 Channel: https://t.iss.one/GithubRe
🔗 https://github.com/lyogavin/airllm
📝 AirLLM 70B inference with single 4GB GPU
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AirLLM is a game-changer for large language models, allowing massive models like 70B Llama 3.1 to run on a single 4GB GPU card without quantization, distillation, or pruning. This is achieved through sparse MoE models that stream one expert at a time.
Key Features:
- Support for various large language models, including Llama 3.x, DeepSeek V2/V3, and more
- Model compression for up to 3x inference speedup with minimal accuracy loss
- Easy usage with the
AutoModel.from_pretrained(...) methodTechnical Highlights:
-
pip install airllm for easy installation-
from airllm import AutoModel for initializing models- Supports
compression for 4-bit or 8-bit block-wise quantizationAudience:
- Developers and researchers working with large language models
- Those looking to deploy models on limited hardware
Takeaway: With AirLLM, you can run massive language models on minimal hardware, making AI more accessible and efficient.
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🧠 Channel: https://t.iss.one/GithubRe
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Github Top Repositories
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🌟 TencentCloud/TencentDB-Agent-Memory caught my eye on GitHub Trending today.
🔗 https://github.com/TencentCloud/TencentDB-Agent-Memory
📝 TencentDB Agent Memory is a team-level memory hub for AI Agents — turning conversations, docs, and code into four reusable memory assets (Chat Memory, Skill, LLM-Wiki, Code-Graph) that are governed, shared, and equipped across agents and frameworks.
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The TencentDB Agent Memory is a powerful tool designed to enhance the memory capabilities of AI agents, allowing them to learn from workflows, retain task context, and reuse past experiences. This is achieved through a layered memory system, consisting of symbolic short-term memory and layered long-term memory.
The
When integrated with OpenClaw, it significantly cuts token usage and improves pass rates. The system also features
To get started, simply install the plugin using
This tool is perfect for developers and researchers looking to improve the performance of their AI agents.
In short, with TencentDB Agent Memory, agents remember, so humans can innovate!
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🧠 Channel: https://t.iss.one/GithubRe
🔗 https://github.com/TencentCloud/TencentDB-Agent-Memory
📝 TencentDB Agent Memory is a team-level memory hub for AI Agents — turning conversations, docs, and code into four reusable memory assets (Chat Memory, Skill, LLM-Wiki, Code-Graph) that are governed, shared, and equipped across agents and frameworks.
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The TencentDB Agent Memory is a powerful tool designed to enhance the memory capabilities of AI agents, allowing them to learn from workflows, retain task context, and reuse past experiences. This is achieved through a layered memory system, consisting of symbolic short-term memory and layered long-term memory.
The
symbolic short-term memory offloads heavy tool logs into compact Mermaid symbols, reducing token usage and improving task success. Meanwhile, the layered long-term memory distills fragmented conversations into structured personas and scenes.When integrated with OpenClaw, it significantly cuts token usage and improves pass rates. The system also features
memory layering and symbolic memory, ensuring agents can reason better, not just remember more.To get started, simply install the plugin using
openclaw plugins install @tencentdb-agent-memory/memory-tencentdb and enable it in your OpenClaw config. This tool is perfect for developers and researchers looking to improve the performance of their AI agents.
In short, with TencentDB Agent Memory, agents remember, so humans can innovate!
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🧠 Channel: https://t.iss.one/GithubRe
📌 Spotted on GitHub Trending: addyosmani/agent-skills — let's break it down.
🔗 https://github.com/addyosmani/agent-skills
📝 Production-grade engineering skills for AI coding agents.
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The addyosmani/agent-skills GitHub repository provides a comprehensive set of production-grade engineering skills for AI coding agents. These skills encode workflows, quality gates, and best practices used by senior engineers across various development phases.
The repository includes 8 slash commands that map to the development lifecycle, allowing for automatic activation of the right skills. Key features include
Technical highlights of the repository include the use of
The repository supports various agents, including Claude Code, Cursor, and Codex, and provides detailed setup instructions for each. The skills are designed to be used by anyone working with AI coding agents, from developers to project managers.
In summary, addyosmani/agent-skills is a powerful repository that helps streamline the development process by providing a set of pre-defined skills for AI coding agents. With these skills, you can automate your development workflow and focus on what matters most - building high-quality software.
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🧠 Channel: https://t.iss.one/GithubRe
🔗 https://github.com/addyosmani/agent-skills
📝 Production-grade engineering skills for AI coding agents.
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The addyosmani/agent-skills GitHub repository provides a comprehensive set of production-grade engineering skills for AI coding agents. These skills encode workflows, quality gates, and best practices used by senior engineers across various development phases.
The repository includes 8 slash commands that map to the development lifecycle, allowing for automatic activation of the right skills. Key features include
/spec for defining what to build, /plan for planning how to build it, and /build for incremental implementation. Technical highlights of the repository include the use of
npx skills add addyosmani/agent-skillsfor fast installation and the ability to grab individual skills using
npx skills add addyosmani/agent-skills --skill code-review-and-quality.
The repository supports various agents, including Claude Code, Cursor, and Codex, and provides detailed setup instructions for each. The skills are designed to be used by anyone working with AI coding agents, from developers to project managers.
In summary, addyosmani/agent-skills is a powerful repository that helps streamline the development process by providing a set of pre-defined skills for AI coding agents. With these skills, you can automate your development workflow and focus on what matters most - building high-quality software.
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🧠 Channel: https://t.iss.one/GithubRe