Github Top Repositories
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π― iv-org/invidious landed on trending. Worth a proper look.
π https://github.com/iv-org/invidious
π Invidious is an alternative front-end to YouTube
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Invidious is an open-source alternative front-end to YouTube, offering a lightweight and ad-free experience. Its key features include
From a technical standpoint, Invidious has an
To get started, users can select a public instance or host Invidious themselves by following the installation instructions. The project is suitable for anyone looking for a private and customizable YouTube experience.
Invidious is perfect for those who want to ditch YouTube's ads and tracking - and it's completely free and open-source. Join the Invidious community today and experience the power of open-source video sharing!
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π§ Channel: https://t.iss.one/GithubRe
π https://github.com/iv-org/invidious
π Invidious is an alternative front-end to YouTube
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Invidious is an open-source alternative front-end to YouTube, offering a lightweight and ad-free experience. Its key features include
no tracking, customizable homepage, and audio-only mode. Users can import subscriptions from YouTube and other platforms, and export them as needed. From a technical standpoint, Invidious has an
embedded video support and a developer API, making it a great option for developers. The project is hosted on GitHub and has a large community of contributors, with translations available in many languages.To get started, users can select a public instance or host Invidious themselves by following the installation instructions. The project is suitable for anyone looking for a private and customizable YouTube experience.
Invidious is perfect for those who want to ditch YouTube's ads and tracking - and it's completely free and open-source. Join the Invidious community today and experience the power of open-source video sharing!
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π§ Channel: https://t.iss.one/GithubRe
π ansible/ansible caught my eye on GitHub Trending today.
π https://github.com/ansible/ansible
π Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to cloud management, in a language that approaches plain English, using SSH, with no agents to install on remote systems.https://docs.ansible.com.
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Ansible is a simple IT automation system that handles configuration management, application deployment, and more. Its key features include an extremely simple setup process, agentless architecture, and the ability to describe infrastructure in a human-friendly language.
To use Ansible, you can install it with
From a technical perspective, Ansible focuses on security and auditability, and allows module development in any dynamic language. The project is coded in a variety of languages, including Python, and has a
Ansible is suitable for a wide range of users, from system administrators to developers, and is widely used in the industry.
The project is licensed under the GNU General Public License v3.0 or later.
In short, Ansible is all about making complex IT tasks radically simple - and that's a game-changer!
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π§ Channel: https://t.iss.one/GithubRe
π https://github.com/ansible/ansible
π Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to cloud management, in a language that approaches plain English, using SSH, with no agents to install on remote systems.https://docs.ansible.com.
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Ansible is a simple IT automation system that handles configuration management, application deployment, and more. Its key features include an extremely simple setup process, agentless architecture, and the ability to describe infrastructure in a human-friendly language.
To use Ansible, you can install it with
pip or a package manager, and power users can run the devel branch for the latest features. The community is active, with a forum for asking questions, getting help, and interacting with other users.From a technical perspective, Ansible focuses on security and auditability, and allows module development in any dynamic language. The project is coded in a variety of languages, including Python, and has a
devel branch for ongoing development.Ansible is suitable for a wide range of users, from system administrators to developers, and is widely used in the industry.
The project is licensed under the GNU General Public License v3.0 or later.
In short, Ansible is all about making complex IT tasks radically simple - and that's a game-changer!
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π‘ microsoft/TRELLIS.2 just hit the trending charts β here's why it matters.
π https://github.com/microsoft/TRELLIS.2
π Native and Compact Structured Latents for 3D Generation
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TRELLIS.2 is a state-of-the-art 3D generative model that enables high-fidelity image-to-3D generation. It features a novel "field-free" sparse voxel structure called
Some of the key features of TRELLIS.2 include:
- Arbitrary topology handling: The
- Rich texture modeling: The model supports arbitrary surface attributes, including base color, roughness, metallic, and opacity, enabling photorealistic rendering and transparency support.
- Minimalist processing: Data processing is streamlined for instant conversions that are fully rendering-free and optimization-free.
To use TRELLIS.2, you'll need to install the dependencies, including the CUDA Toolkit and Conda, and then clone the repository. You can then use the pretrained model for image-to-3D generation or PBR texture generation. The repository also provides a web demo for easy testing.
From a technical standpoint, TRELLIS.2 is a 4B-parameter model that utilizes a Sparse 3D VAE with 16Γ spatial downsampling to encode assets into a compact latent space. The model is designed for high-performance and can generate high-resolution assets with exceptional fidelity.
The target audience for TRELLIS.2 includes researchers, developers, and artists working with 3D generation and image-to-3D applications. With its powerful features and streamlined processing, TRELLIS.2 is an ideal choice for anyone looking to push the boundaries of 3D generation.
In short, TRELLIS.2 is a game-changer for 3D generation, offering unparalleled fidelity, efficiency, and flexibility - and with its open-source availability, the possibilities are endless!
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π§ Channel: https://t.iss.one/GithubRe
π https://github.com/microsoft/TRELLIS.2
π Native and Compact Structured Latents for 3D Generation
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TRELLIS.2 is a state-of-the-art 3D generative model that enables high-fidelity image-to-3D generation. It features a novel "field-free" sparse voxel structure called
O-Voxel, which allows for the reconstruction and generation of complex 3D assets with sharp features and full PBR materials. The model boasts high-quality, resolution, and efficiency, generating high-resolution fully textured assets with exceptional fidelity. Some of the key features of TRELLIS.2 include:
- Arbitrary topology handling: The
O-Voxel representation can handle complex structures without lossy conversion, including open surfaces, non-manifold geometry, and internal enclosed structures.- Rich texture modeling: The model supports arbitrary surface attributes, including base color, roughness, metallic, and opacity, enabling photorealistic rendering and transparency support.
- Minimalist processing: Data processing is streamlined for instant conversions that are fully rendering-free and optimization-free.
To use TRELLIS.2, you'll need to install the dependencies, including the CUDA Toolkit and Conda, and then clone the repository. You can then use the pretrained model for image-to-3D generation or PBR texture generation. The repository also provides a web demo for easy testing.
From a technical standpoint, TRELLIS.2 is a 4B-parameter model that utilizes a Sparse 3D VAE with 16Γ spatial downsampling to encode assets into a compact latent space. The model is designed for high-performance and can generate high-resolution assets with exceptional fidelity.
The target audience for TRELLIS.2 includes researchers, developers, and artists working with 3D generation and image-to-3D applications. With its powerful features and streamlined processing, TRELLIS.2 is an ideal choice for anyone looking to push the boundaries of 3D generation.
In short, TRELLIS.2 is a game-changer for 3D generation, offering unparalleled fidelity, efficiency, and flexibility - and with its open-source availability, the possibilities are endless!
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π§ Channel: https://t.iss.one/GithubRe
Github Top Repositories
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π Deep-diving into TencentCloud/TencentDB-Agent-Memory β fresh off the trending list.
π https://github.com/TencentCloud/TencentDB-Agent-Memory
π TencentDB Agent Memory is a team-level memory hub for AI Agents β 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 designed to help agents learn from workflows, retain task context, and reuse past experiences. It achieves this through a layered system consisting of symbolic memory for in-task information and memory layering for cross-session experience.
Key features include
Technical highlights include a unified architectural paradigm with short-term context layering, long-term personalization layering, and skill generation layering. The system also ensures full traceability and lossless recovery through a deterministic path from high-level abstractions to ground-truth evidence.
The target audience includes developers and users of OpenClaw and Hermes agents, who can integrate this plugin to enhance their agents' memory capabilities.
To get started, users can follow the
In summary, the TencentDB Agent Memory plugin is a powerful tool for improving agent performance by enabling them to learn from experience and retain context. Let the agents remember, so humans can innovate.
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π§ Channel: https://t.iss.one/GithubRe
π https://github.com/TencentCloud/TencentDB-Agent-Memory
π TencentDB Agent Memory is a team-level memory hub for AI Agents β 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 designed to help agents learn from workflows, retain task context, and reuse past experiences. It achieves this through a layered system consisting of symbolic memory for in-task information and memory layering for cross-session experience.
Key features include
memory layering with heterogeneous storage, symbolic memory using Mermaid syntax, and context offloading with `node_id` tracing. This approach enables agents to reason better, not just remember more. Technical highlights include a unified architectural paradigm with short-term context layering, long-term personalization layering, and skill generation layering. The system also ensures full traceability and lossless recovery through a deterministic path from high-level abstractions to ground-truth evidence.
The target audience includes developers and users of OpenClaw and Hermes agents, who can integrate this plugin to enhance their agents' memory capabilities.
To get started, users can follow the
quick start guide, which includes installation and configuration instructions for OpenClaw and Hermes. In summary, the TencentDB Agent Memory plugin is a powerful tool for improving agent performance by enabling them to learn from experience and retain context. Let the agents remember, so humans can innovate.
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π§ Channel: https://t.iss.one/GithubRe
Github Top Repositories
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π₯ NomaDamas/k-skill is trending β and it deserves your attention.
π https://github.com/NomaDamas/k-skill
π νκ΅μΈμ μν μ€ν¬ λͺ¨μμ§ - μμ΄μ νΈλ₯Ό νκ΅μΈμΌλ‘
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Hey, junior dev! Let's explore the k-skill GitHub repo. This project is a collection of skills for automating various tasks, mainly focused on Korean services. With k-skill, you can automate tasks like SRT and KTX booking, lottery checks, and even interactions with government services like tax and business registration.
The key features of k-skill include support for multiple coding agents like Claude Code and Codex, as well as a simple installation process using
Some of the skills available in k-skill include:
- SRT and KTX booking
- Lottery checks
- Interactions with government services like tax and business registration
- Automated tasks for Korean services like banking and insurance
The technical highlights of k-skill include its support for multiple coding agents and its use of
This project is aimed at developers who want to automate tasks related to Korean services. If you're interested in contributing to k-skill, be sure to check out the CONTRIBUTING.md file for more information.
In short, k-skill is an amazing resource for automating tasks related to Korean services - and with great power comes great automation!
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π§ Channel: https://t.iss.one/GithubRe
π https://github.com/NomaDamas/k-skill
π νκ΅μΈμ μν μ€ν¬ λͺ¨μμ§ - μμ΄μ νΈλ₯Ό νκ΅μΈμΌλ‘
ββββββββββββββββββββββββββββββ
Hey, junior dev! Let's explore the k-skill GitHub repo. This project is a collection of skills for automating various tasks, mainly focused on Korean services. With k-skill, you can automate tasks like SRT and KTX booking, lottery checks, and even interactions with government services like tax and business registration.
The key features of k-skill include support for multiple coding agents like Claude Code and Codex, as well as a simple installation process using
npx. You can install all skills at once or choose specific ones to install.Some of the skills available in k-skill include:
- SRT and KTX booking
- Lottery checks
- Interactions with government services like tax and business registration
- Automated tasks for Korean services like banking and insurance
The technical highlights of k-skill include its support for multiple coding agents and its use of
Node.js for installation and execution.This project is aimed at developers who want to automate tasks related to Korean services. If you're interested in contributing to k-skill, be sure to check out the CONTRIBUTING.md file for more information.
In short, k-skill is an amazing resource for automating tasks related to Korean services - and with great power comes great automation!
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π§ Channel: https://t.iss.one/GithubRe
Github Top Repositories
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π Meet bytedance/deer-flow: a gem from today's GitHub trending list.
π https://github.com/bytedance/deer-flow
π An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
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DeerFlow is an open-source super agent harness that lets you orchestrate sub-agents, memory, and sandboxes to do almost anything, powered by extensible skills. Its key features include skills and tools, session goals, sub-agents, and context engineering. To get started, you can use the
You can also use the
DeerFlow 2.0 is a ground-up rewrite with no shared code with version 1, and it's designed to be extensible and customizable. The project has a official website with real demos and a sister project called LLM Space.
The recommended models include GPT-4o, Gemini 2.5 Flash, and Qwen3 32B. You can also use the
One-line takeaway: With DeerFlow, you can build a super agent harness that can do almost anything, and it's free and open-source.
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π§ Channel: https://t.iss.one/GithubRe
π https://github.com/bytedance/deer-flow
π An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
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DeerFlow is an open-source super agent harness that lets you orchestrate sub-agents, memory, and sandboxes to do almost anything, powered by extensible skills. Its key features include skills and tools, session goals, sub-agents, and context engineering. To get started, you can use the
make setup command to run the setup wizard, which guides you through choosing an LLM provider and configuring your setup. You can also use the
make dev command for local development or make docker-start for Docker development. For a quick start, you can clone the repository, run the setup wizard, and then start the application using make up. DeerFlow 2.0 is a ground-up rewrite with no shared code with version 1, and it's designed to be extensible and customizable. The project has a official website with real demos and a sister project called LLM Space.
The recommended models include GPT-4o, Gemini 2.5 Flash, and Qwen3 32B. You can also use the
embedded Python client to interact with DeerFlow. One-line takeaway: With DeerFlow, you can build a super agent harness that can do almost anything, and it's free and open-source.
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π§ Channel: https://t.iss.one/GithubRe
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Github Top Repositories
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π microsoft/AI-For-Beginners caught my eye on GitHub Trending today.
π https://github.com/microsoft/AI-For-Beginners
π 12 Weeks, 24 Lessons, AI for All!
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The Microsoft AI-For-Beginners GitHub repository is an excellent starting point for those new to Artificial Intelligence (AI). This 12-week, 24-lesson curriculum is designed to be beginner-friendly and covers a wide range of topics, including
The curriculum is divided into sections, including an Introduction to AI, Symbolic AI, and Introduction to Neural Networks. Each section includes practical lessons, quizzes, and labs to help reinforce learning.
One of the key features of this repository is its multi-language support, with translations available in over 50 languages. To get started, you can clone the repository locally, and to make the process faster, you can use
Here's an example of how to do this:
The repository also includes a mindmap of the course to help visualize the topics covered. You can join the community and get involved through the Microsoft Foundry Discord server.
Overall, the Microsoft AI-For-Beginners repository is a comprehensive resource for anyone looking to learn about AI. So, dive in and start exploring - with this curriculum, you'll be well on your way to becoming an AI master in no time!
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π§ Channel: https://t.iss.one/GithubRe
π https://github.com/microsoft/AI-For-Beginners
π 12 Weeks, 24 Lessons, AI for All!
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The Microsoft AI-For-Beginners GitHub repository is an excellent starting point for those new to Artificial Intelligence (AI). This 12-week, 24-lesson curriculum is designed to be beginner-friendly and covers a wide range of topics, including
TensorFlow and PyTorch, as well as ethics in AI. The curriculum is divided into sections, including an Introduction to AI, Symbolic AI, and Introduction to Neural Networks. Each section includes practical lessons, quizzes, and labs to help reinforce learning.
One of the key features of this repository is its multi-language support, with translations available in over 50 languages. To get started, you can clone the repository locally, and to make the process faster, you can use
sparse checkout to exclude translations. Here's an example of how to do this:
git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git
cd AI-For-Beginners
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'
The repository also includes a mindmap of the course to help visualize the topics covered. You can join the community and get involved through the Microsoft Foundry Discord server.
Overall, the Microsoft AI-For-Beginners repository is a comprehensive resource for anyone looking to learn about AI. So, dive in and start exploring - with this curriculum, you'll be well on your way to becoming an AI master in no time!
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π§ Channel: https://t.iss.one/GithubRe