🌟 PriorLabs/TabPFN caught my eye on GitHub Trending today.

🔗 https://github.com/PriorLabs/TabPFN
📝 ⚡ TabPFN: Foundation Model for Tabular Data ⚡
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The TabPFN repository on GitHub offers a powerful solution for tabular data classification and regression tasks. At its core, TabPFN is a PyTorch-based model that leverages a unique combination of techniques to achieve high performance.

To get started with TabPFN, you can install it via pip using pip install tabpfn or try out the interactive Colab notebook for a hands-on experience. The model is relatively simple to use, with a basic example looking like this:

from tabpfn import TabPFNClassifier, TabPFNRegressor

clf = TabPFNClassifier()
clf.fit(X_train, y_train)  
predictions = clf.predict(X_test)

Key Features of TabPFN include support for both classification and regression tasks, the ability to handle large datasets, and a range of tools for interpretability and unsupervised learning. For those looking to extend the capabilities of TabPFN, the tabpfn-extensions repository provides a wealth of additional functionality.

Whether you're a data scientist looking for a high-performance model or a developer seeking to integrate TabPFN into your application, this repository has something to offer. So why not dive in and explore the world of TabPFN today - your next machine learning breakthrough could be just a click away!

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💡 aaif-goose/goose just hit the trending charts — here's why it matters.

🔗 https://github.com/aaif-goose/goose
📝 an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
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The goose project is a native open source AI agent that runs on your machine, offering a desktop app, CLI, and API for various tasks such as code, workflows, research, writing, automation, and data analysis. It supports 15+ providers like Anthropic, OpenAI, and Google, and connects 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 bash script. The project is part of the Agentic AI Foundation (AAIF) at the Linux Foundation and is built in Rust for performance and portability.

The target audience includes developers, researchers, and anyone looking for a versatile AI agent. With its wide range of features and extensions, goose is an excellent choice for those seeking to streamline their workflows.

In a nutshell, goose is the ultimate AI sidekick that helps you "migrate" your tasks to production - and that's no fowl play!

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🧠 Channel: https://t.iss.one/GithubRe

🌟 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.
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Introducing OpenReel Video, the open-source CapCut alternative for professional video editing in your browser. With no uploads or installs required, this 100% client-side editor offers a wide range of features, including a multi-track timeline, keyframe animations, color grading, audio effects, and GPU acceleration for smooth 4K editing and fast exports.

Key highlights include:
- 100% client-side editing for complete privacy
- No installation needed, works in Chrome/Edge
- Professional features like multi-track timeline and color grading
- GPU acceleration for fast exports and smooth playback

Technical highlights include the use of React, TypeScript, WebCodecs, and WebGPU for a high-performance editing experience.

Audience: OpenReel Video is designed for anyone looking for a free, open-source video editing solution, from hobbyists to professionals.

To get started, simply visit openreel.video to try it live, or check out the GitHub repository for more information.

Takeaway: OpenReel Video is revolutionizing the world of video editing by making professional-grade tools accessible to everyone, for free, and with complete privacy.

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🧠 Channel: https://t.iss.one/GithubRe

⚡ anthropics/financial-services is making waves. Here's the full picture.

🔗 https://github.com/anthropics/financial-services
📝 No description.
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The anthropics/financial-services GitHub repository offers a suite of reference agents, skills, and data connectors designed for financial services workflows, including investment banking, equity research, private equity, and wealth management. These agents can be installed as Claude Cowork plugins or deployed via the Claude Managed Agents API. The repository includes a range of named agents that automate specific workflows, such as pitch deck creation, market research, and earnings review, as well as vertical plugins that bundle skills and data connectors by financial services industry (FSI) vertical.

The repository is divided into several sections, including plugins/ for agent and vertical plugins, managed-agent-cookbooks/ for Claude Managed Agent templates, and scripts/ for deployment and management scripts. To get started, users can install the agents and vertical plugins using Claude Code or by uploading a zip file to Claude Cowork.

The repository also includes a range of technical highlights, such as integration with MCP servers for data connectivity and support for Claude Code and Claude Managed Agents. The repository is designed for financial services professionals and developers who want to automate and streamline their workflows using Claude agents and skills.

Overall, the anthropics/financial-services repository provides a powerful toolkit for financial services teams to boost productivity and efficiency. With its flexible deployment options and customizable agents and skills, it's an ideal solution for teams looking to leverage the power of Claude to drive their workflows forward. Automate your financial workflows with Claude and focus on high-value tasks — the future of finance is here.

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🧠 Channel: https://t.iss.one/GithubRe

🌟 addyosmani/agent-skills caught my eye on GitHub Trending today.

🔗 https://github.com/addyosmani/agent-skills
📝 Production-grade engineering skills for AI coding agents.
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Agent Skills is a GitHub repository that provides production-grade engineering skills for AI coding agents. The skills encode workflows, quality gates, and best practices used by senior engineers during software development. They are packaged to ensure AI agents follow them consistently across every development phase.

The repository includes 7 slash commands that map to the development lifecycle, activating the right skills automatically. These commands include /spec, /plan, /build, /test, /review, /code-simplify, and /ship.

To get started, you can use the Quick Start guide, which provides instructions for installing the skills using various tools like Claude Code, Cursor, Gemini CLI, Windsurf, OpenCode, and GitHub Copilot.

The repository includes 20 skills, each representing a structured workflow with steps, verification gates, and anti-rationalization tables. These skills cover various aspects of software development, such as defining what to build, planning, building, verifying, reviewing, and shipping.

The skills are designed to work with any agent that accepts system prompts or instruction files, making them versatile and widely applicable.

Key technical highlights include the use of plain Markdown for skill definitions, making them easy to understand and modify. The skills also include anti-rationalization tables to help agents overcome common excuses for skipping steps.

The repository is suitable for developers, engineers, and AI researchers looking to improve the quality and consistency of their software development workflows.

In summary, Agent Skills is a valuable resource for anyone looking to leverage AI agents in software development, providing a comprehensive set of skills to ensure high-quality and consistent results - automate your workflow with Agent Skills and take your development to the next level!

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🧠 Channel: https://t.iss.one/GithubRe

📌 Spotted on GitHub Trending: Hmbown/DeepSeek-TUI — let's break it down.

🔗 https://github.com/Hmbown/DeepSeek-TUI
📝 Coding agent for DeepSeek models that runs in your terminal
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Meet DeepSeek TUI, a terminal coding agent that streamlines your workflow. It's built around DeepSeek V4 and offers features like auto mode, which chooses the model and thinking level for each turn, and streaming reasoning blocks to see the model's thought process.

With DeepSeek TUI, you can manage files, run shell commands, and even coordinate sub-agents. It's available on various platforms, including Linux, macOS, and Windows, and can be installed via npm, Cargo, or Homebrew.

The tool is designed for developers and power users who want to automate repetitive tasks and improve their coding efficiency. Whether you're working on a small project or a large-scale application, DeepSeek TUI is a valuable addition to your toolkit.

So, what are you waiting for? Give DeepSeek TUI a try and experience the power of AI-assisted coding - it's like having a super-smart pair programming partner in your terminal!

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🧠 Channel: https://t.iss.one/GithubRe

🔍 Deep-diving into z-lab/dflash — fresh off the trending list.

🔗 https://github.com/z-lab/dflash
📝 DFlash: Block Diffusion for Flash Speculative Decoding
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DFlash is a lightweight block diffusion model designed for speculative decoding, enabling efficient and high-quality parallel drafting. It's a powerful tool for users seeking to accelerate their language models.

The key features of DFlash include its ability to support various models, such as Qwen3, Qwen3.5, and Gemma-4, and its compatibility with different backends like vLLM, SGLang, and Transformers.

To use DFlash, you can follow the provided installation and quick start guides, which cover the setup for different backends and models. The repository also includes benchmarking tools to evaluate the performance of DFlash with various models and datasets.

Technically, DFlash achieves its efficiency through block diffusion, allowing for parallel drafting and reducing the computational requirements. The model is also designed to be flexible, supporting different attention backends and configurable parameters.

The target audience for DFlash includes developers and researchers working with language models, particularly those interested in accelerating their models for improved performance.

In summary, DFlash is a powerful tool for accelerating language models, and its flexibility and efficiency make it an attractive choice for users seeking to improve their model's performance. Get ready to turbocharge your language models with DFlash!

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🧠 Channel: https://t.iss.one/GithubRe

🎯 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.
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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.

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🧠 Channel: https://t.iss.one/GithubRe

⚡ 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.
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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.

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🧠 Channel: https://t.iss.one/GithubRe

🚀 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
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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.

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🧠 Channel: https://t.iss.one/GithubRe

⚡ 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"
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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!

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🧠 Channel: https://t.iss.one/GithubRe

🚀 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.
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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.

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🧠 Channel: https://t.iss.one/GithubRe