๐ NousResearch/hermes-agent caught my eye on GitHub Trending today.
๐ https://github.com/NousResearch/hermes-agent
๐ The agent that grows with you
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Hermes Agent is a self-improving AI agent built by Nous Research, designed to learn from experience and improve over time. It features a closed learning loop, allowing it to create skills from experience, improve them during use, and search its own past conversations. The agent can be run on a variety of platforms, including a $5 VPS, a GPU cluster, or serverless infrastructure, and can be accessed from Telegram, Discord, Slack, WhatsApp, Signal, or the command line.
Key features include:
- A real terminal interface with multiline editing, slash-command autocomplete, and conversation history
- The ability to live where you do, with support for multiple messaging platforms
- A closed learning loop with agent-curated memory and periodic nudges
- Scheduled automations with a built-in cron scheduler
- The ability to delegate and parallelize tasks using isolated subagents
To get started, you can install Hermes Agent using a simple one-liner command, and then configure it using the
Technical highlights include support for multiple terminal backends, a research-ready architecture, and a scalable design that allows it to run on a variety of hardware configurations.
The target audience for Hermes Agent includes developers, researchers, and anyone interested in building and interacting with AI agents.
In summary, Hermes Agent is a powerful and flexible AI agent that can be used for a wide range of applications, from research and development to personal productivity and automation - it's an AI agent that learns and adapts to your needs.
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/NousResearch/hermes-agent
๐ The agent that grows with you
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Hermes Agent is a self-improving AI agent built by Nous Research, designed to learn from experience and improve over time. It features a closed learning loop, allowing it to create skills from experience, improve them during use, and search its own past conversations. The agent can be run on a variety of platforms, including a $5 VPS, a GPU cluster, or serverless infrastructure, and can be accessed from Telegram, Discord, Slack, WhatsApp, Signal, or the command line.
Key features include:
- A real terminal interface with multiline editing, slash-command autocomplete, and conversation history
- The ability to live where you do, with support for multiple messaging platforms
- A closed learning loop with agent-curated memory and periodic nudges
- Scheduled automations with a built-in cron scheduler
- The ability to delegate and parallelize tasks using isolated subagents
To get started, you can install Hermes Agent using a simple one-liner command, and then configure it using the
hermes setup command. The agent supports a wide range of models and providers, including Nous Portal, OpenRouter, and Hugging Face.Technical highlights include support for multiple terminal backends, a research-ready architecture, and a scalable design that allows it to run on a variety of hardware configurations.
The target audience for Hermes Agent includes developers, researchers, and anyone interested in building and interacting with AI agents.
In summary, Hermes Agent is a powerful and flexible AI agent that can be used for a wide range of applications, from research and development to personal productivity and automation - it's an AI agent that learns and adapts to your needs.
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๐ง Channel: https://t.me/GithubRe
โค1
๐ฏ chopratejas/headroom landed on trending. Worth a proper look.
๐ https://github.com/chopratejas/headroom
๐ Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.
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Headroom is a context compression layer for AI agents that reduces the number of tokens sent to language models, resulting in significant savings. It achieves this through a combination of library, proxy, and agent wrap modes. Key features include
Technical highlights include the use of
Headroom is suitable for developers and researchers working with AI agents, particularly those who need to reduce the token count for their models. It supports various agents, including Claude, Codex, and Cursor, and can be integrated into existing workflows using the provided SDKs and APIs.
To get started, simply install
In summary, Headroom is a powerful tool for reducing token count in AI agent workflows, and its flexible architecture makes it easy to integrate into existing projects. With Headroom, you can compress everything, sacrifice nothing.
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/chopratejas/headroom
๐ Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.
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Headroom is a context compression layer for AI agents that reduces the number of tokens sent to language models, resulting in significant savings. It achieves this through a combination of library, proxy, and agent wrap modes. Key features include
cross-agent memory, reversible compression, and support for multiple algorithms. Technical highlights include the use of
SmartCrusher for JSON compression, CodeCompressor for AST-aware compression, and Kompress-base for text compression. The CacheAligner ensures that provider KV caches are utilized effectively. Headroom is suitable for developers and researchers working with AI agents, particularly those who need to reduce the token count for their models. It supports various agents, including Claude, Codex, and Cursor, and can be integrated into existing workflows using the provided SDKs and APIs.
To get started, simply install
headroom-ai using pip or npm and follow the documentation for your specific use case. In summary, Headroom is a powerful tool for reducing token count in AI agent workflows, and its flexible architecture makes it easy to integrate into existing projects. With Headroom, you can compress everything, sacrifice nothing.
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๐ง Channel: https://t.me/GithubRe
โค1
Github Top Repositories
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๐ฅ CopilotKit/CopilotKit is trending โ and it deserves your attention.
๐ https://github.com/CopilotKit/CopilotKit
๐ The Frontend Stack for Agents & Generative UI. React + Angular. Makers of the AG-UI Protocol
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CopilotKit is a best-in-class SDK for building full-stack agentic applications, Generative UI, and chat applications. The key features include Chat UI, Backend Tool Rendering, Generative UI, Shared State, and Human-in-the-Loop workflows. To get started, you can use the
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/CopilotKit/CopilotKit
๐ The Frontend Stack for Agents & Generative UI. React + Angular. Makers of the AG-UI Protocol
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CopilotKit is a best-in-class SDK for building full-stack agentic applications, Generative UI, and chat applications. The key features include Chat UI, Backend Tool Rendering, Generative UI, Shared State, and Human-in-the-Loop workflows. To get started, you can use the
npx copilotkit@latest create -f <framework> command for new projects or npx copilotkit@latest init for existing projects. The useAgent hook provides a superset of useCoAgent and offers more control over the agent connection. The Generative UI pattern allows agents to dynamically render UI as part of their workflow. With a strong focus on community and documentation, CopilotKit is perfect for developers looking to build cutting-edge applications. You can install it as a Claude Code plugin and explore the various skills and lifecycle journey skills. One-liner takeaway: CopilotKit is revolutionizing the way we build agentic applications, and you can get started in just one minute!โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ง Channel: https://t.me/GithubRe
Github Top Repositories
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๐ก lfnovo/open-notebook just hit the trending charts โ here's why it matters.
๐ https://github.com/lfnovo/open-notebook
๐ An Open Source implementation of Notebook LM with more flexibility and features
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Welcome to Open Notebook, a private, multi-model, 100% local, full-featured alternative to Notebook LM. This platform empowers you to
Key Features include privacy-first design, multi-notebook organization, and universal content support. The platform also offers
To get started, simply
Open Notebook is perfect for researchers, students, and professionals who value data privacy and customization. With its comprehensive REST API and optional password protection, you can
In short, Open Notebook is the ultimate tool for anyone looking for a private, customizable, and powerful research platform. Take control of your data and unlock your full potential with Open Notebook.
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/lfnovo/open-notebook
๐ An Open Source implementation of Notebook LM with more flexibility and features
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Welcome to Open Notebook, a private, multi-model, 100% local, full-featured alternative to Notebook LM. This platform empowers you to
control your data, choose your AI models, and organize multi-modal content. With support for 18+ AI providers, including OpenAI, Anthropic, and Ollama, you can generate professional podcasts, search intelligently, and chat with context. Key Features include privacy-first design, multi-notebook organization, and universal content support. The platform also offers
advanced podcast generation, intelligent search, and context-aware chat. To get started, simply
download the docker-compose.yml file, set your encryption key, and start the services. Then, configure your AI provider and you're ready to create your first notebook. Open Notebook is perfect for researchers, students, and professionals who value data privacy and customization. With its comprehensive REST API and optional password protection, you can
integrate Open Notebook into your existing workflow. In short, Open Notebook is the ultimate tool for anyone looking for a private, customizable, and powerful research platform. Take control of your data and unlock your full potential with Open Notebook.
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๐ง Channel: https://t.me/GithubRe
Github Top Repositories
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๐ Deep-diving into affaan-m/ECC โ fresh off the trending list.
๐ https://github.com/affaan-m/ECC
๐ The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
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The ECC repository on GitHub is a harness-native operator system designed for agentic work. It's built from real-world multi-harness engineering workflows, offering a complete system with skills, instincts, memory optimization, continuous learning, security scanning, and research-first development.
The system works across various AI agent harnesses, including
Key features include production-ready agents, skills, hooks, rules, and configurations, all of which have evolved over 10+ months of intensive daily use in building real products.
The repository has a large community with 182K+ stars, 28K+ forks, and 170+ contributors, making it a significant project in the open-source space.
The system is written in multiple programming languages, including
To get started, users can refer to the Shorthand Guide, Longform Guide, and Security Guide for detailed information on setup, foundations, philosophy, token optimization, memory persistence, and security.
In summary, ECC is a powerful tool for agentic work, with a wide range of features, a large community, and support for multiple programming languages, making it an ideal choice for developers and operators alike.
The takeaway: ECC is the ultimate operator system for agentic work, empowering developers to build and manage complex workflows with ease.
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/affaan-m/ECC
๐ The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
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The ECC repository on GitHub is a harness-native operator system designed for agentic work. It's built from real-world multi-harness engineering workflows, offering a complete system with skills, instincts, memory optimization, continuous learning, security scanning, and research-first development.
The system works across various AI agent harnesses, including
Codex, Claude Code, Cursor, OpenCode, Gemini, Zed, and GitHub Copilot. Key features include production-ready agents, skills, hooks, rules, and configurations, all of which have evolved over 10+ months of intensive daily use in building real products.
The repository has a large community with 182K+ stars, 28K+ forks, and 170+ contributors, making it a significant project in the open-source space.
The system is written in multiple programming languages, including
Shell, TypeScript, Python, Go, Java, and Perl, and it supports 12+ language ecosystems. To get started, users can refer to the Shorthand Guide, Longform Guide, and Security Guide for detailed information on setup, foundations, philosophy, token optimization, memory persistence, and security.
In summary, ECC is a powerful tool for agentic work, with a wide range of features, a large community, and support for multiple programming languages, making it an ideal choice for developers and operators alike.
The takeaway: ECC is the ultimate operator system for agentic work, empowering developers to build and manage complex workflows with ease.
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๐ง Channel: https://t.me/GithubRe
Github Top Repositories
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๐ฅ Panniantong/Agent-Reach is trending โ and it deserves your attention.
๐ https://github.com/Panniantong/Agent-Reach
๐ Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu โ one CLI, zero API fees.
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Agent Reach ๆฏไธไธช่ฎฉ AI Agent ๆ ็ผ่ฎฟ้ฎๅๅคง็ฝ็ซๅๅนณๅฐ็ๅทฅๅ ท๏ผ่งฃๅณไบ Agent ่ฎฟ้ฎ็ฝ้กตใYouTubeใTwitterใRedditใGitHub ็ญๅนณๅฐ็็็นใๅฎ้่ฟๆไพไบไธๅฅ็ฎๅ็ๅฝไปค่กๅทฅๅ ท๏ผ่ฎฉ AI Agent ๅฏไปฅ่ฝปๆพๅฐๆ็ดขใ้ ่ฏปๅไบคไบ่ฟไบๅนณๅฐ็ๅ ๅฎนใ
ไธป่ฆ็น็น๏ผ
* ๆฏๆๅคไธชๅนณๅฐ๏ผๅ ๆฌ็ฝ้กตใYouTubeใTwitterใRedditใGitHub ็ญ
* ๆไพ็ฎๅ็ๅฝไปค่กๅทฅๅ ท๏ผ่ฎฉ AI Agent ๅฏไปฅ่ฝปๆพๅฐ่ฎฟ้ฎ่ฟไบๅนณๅฐ
* ่ชๅจ้ ็ฝฎๅๅฎ่ฃ ๏ผๆนไพฟ็จๆทไฝฟ็จ
* ๆฏๆๅฎๅ จๆจกๅผ๏ผ็กฎไฟ็จๆท็ๅฎๅ จ
```
ๅธฎๆๅฎ่ฃ Agent Reach๏ผhttps://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/install.md
```
ๆป็ป๏ผAgent Reach ๆฏไธไธช็ฎๅๅดๅผบๅคง็ๅทฅๅ ท๏ผ่ฎฉ AI Agent ๅฏไปฅๆ ็ผ่ฎฟ้ฎๅๅคง็ฝ็ซๅๅนณๅฐ๏ผ่งฃๅณไบ่ฎฟ้ฎ่ฟไบๅนณๅฐ็็็นใ้่ฟๆไพ็ฎๅ็ๅฝไปค่กๅทฅๅ ทๅ่ชๅจ้ ็ฝฎ๏ผAgent Reach ่ฎฉ็จๆทๅฏไปฅ่ฝปๆพๅฐไฝฟ็จ่ฟไบๅนณๅฐใๅช่ฆไธ่กไปฃ็ ๏ผไฝ ็ AI Agent ๅฐฑๅฏไปฅๆไธบไธไธชๅ จ่ฝ็ไบ่็ฝๅฉๆใ
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/Panniantong/Agent-Reach
๐ Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu โ one CLI, zero API fees.
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Agent Reach ๆฏไธไธช่ฎฉ AI Agent ๆ ็ผ่ฎฟ้ฎๅๅคง็ฝ็ซๅๅนณๅฐ็ๅทฅๅ ท๏ผ่งฃๅณไบ Agent ่ฎฟ้ฎ็ฝ้กตใYouTubeใTwitterใRedditใGitHub ็ญๅนณๅฐ็็็นใๅฎ้่ฟๆไพไบไธๅฅ็ฎๅ็ๅฝไปค่กๅทฅๅ ท๏ผ่ฎฉ AI Agent ๅฏไปฅ่ฝปๆพๅฐๆ็ดขใ้ ่ฏปๅไบคไบ่ฟไบๅนณๅฐ็ๅ ๅฎนใ
ไธป่ฆ็น็น๏ผ
* ๆฏๆๅคไธชๅนณๅฐ๏ผๅ ๆฌ็ฝ้กตใYouTubeใTwitterใRedditใGitHub ็ญ
* ๆไพ็ฎๅ็ๅฝไปค่กๅทฅๅ ท๏ผ่ฎฉ AI Agent ๅฏไปฅ่ฝปๆพๅฐ่ฎฟ้ฎ่ฟไบๅนณๅฐ
* ่ชๅจ้ ็ฝฎๅๅฎ่ฃ ๏ผๆนไพฟ็จๆทไฝฟ็จ
* ๆฏๆๅฎๅ จๆจกๅผ๏ผ็กฎไฟ็จๆท็ๅฎๅ จ
ๅฎ่ฃ
ๅฝไปค๏ผ```
ๅธฎๆๅฎ่ฃ Agent Reach๏ผhttps://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/install.md
```
ๆป็ป๏ผAgent Reach ๆฏไธไธช็ฎๅๅดๅผบๅคง็ๅทฅๅ ท๏ผ่ฎฉ AI Agent ๅฏไปฅๆ ็ผ่ฎฟ้ฎๅๅคง็ฝ็ซๅๅนณๅฐ๏ผ่งฃๅณไบ่ฎฟ้ฎ่ฟไบๅนณๅฐ็็็นใ้่ฟๆไพ็ฎๅ็ๅฝไปค่กๅทฅๅ ทๅ่ชๅจ้ ็ฝฎ๏ผAgent Reach ่ฎฉ็จๆทๅฏไปฅ่ฝปๆพๅฐไฝฟ็จ่ฟไบๅนณๅฐใๅช่ฆไธ่กไปฃ็ ๏ผไฝ ็ AI Agent ๅฐฑๅฏไปฅๆไธบไธไธชๅ จ่ฝ็ไบ่็ฝๅฉๆใ
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๐ง Channel: https://t.me/GithubRe
Github Top Repositories
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๐ Spotted on GitHub Trending: NVIDIA/cosmos โ let's break it down.
๐ https://github.com/NVIDIA/cosmos
๐ NVIDIA Cosmos is an open platform of world models, datasets, and tools that enables developers to build Physical AI for robots, autonomous vehicles, smart infrastructure, and more.
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NVIDIA Cosmos is an open platform for building Physical AI, providing a suite of world models, datasets, and tools. Cosmos 3 is the latest model family, designed to jointly process and generate language, images, video, audio, and action sequences. It has two runtime surfaces:
Key features include:
- World understanding: analyze videos and images for captions, temporal events, and physical plausibility
- World generation: produce images, videos, sound, and action-conditioned rollouts from text, image, video, or action inputs
- Action modeling: predict policy actions for robotics and autonomous-driving settings
Cosmos 3 has a unified Mixture-of-Transformers architecture, combining an autoregressive transformer for reasoning with a diffusion transformer for multimodal generation. The model family includes
To get started, create a Hugging Face access token, authenticate locally, and set up a virtual environment with the required dependencies. You can use HuggingFace Diffusers for research, training, and model development.
One-liner takeaway: NVIDIA Cosmos is revolutionizing Physical AI by providing a powerful platform for world understanding and generation, enabling developers to build more sophisticated robots, autonomous vehicles, and smart infrastructure.
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/NVIDIA/cosmos
๐ NVIDIA Cosmos is an open platform of world models, datasets, and tools that enables developers to build Physical AI for robots, autonomous vehicles, smart infrastructure, and more.
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NVIDIA Cosmos is an open platform for building Physical AI, providing a suite of world models, datasets, and tools. Cosmos 3 is the latest model family, designed to jointly process and generate language, images, video, audio, and action sequences. It has two runtime surfaces:
Reasoner for world understanding and Generator for world generation. Key features include:
- World understanding: analyze videos and images for captions, temporal events, and physical plausibility
- World generation: produce images, videos, sound, and action-conditioned rollouts from text, image, video, or action inputs
- Action modeling: predict policy actions for robotics and autonomous-driving settings
Cosmos 3 has a unified Mixture-of-Transformers architecture, combining an autoregressive transformer for reasoning with a diffusion transformer for multimodal generation. The model family includes
Cosmos3-Nano, Cosmos3-Super, and specialized models for text-to-image and image-to-video generation.To get started, create a Hugging Face access token, authenticate locally, and set up a virtual environment with the required dependencies. You can use HuggingFace Diffusers for research, training, and model development.
One-liner takeaway: NVIDIA Cosmos is revolutionizing Physical AI by providing a powerful platform for world understanding and generation, enabling developers to build more sophisticated robots, autonomous vehicles, and smart infrastructure.
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๐ง Channel: https://t.me/GithubRe