🌟 HKUDS/Vibe-Trading caught my eye on GitHub Trending today.

🔗 https://github.com/HKUDS/Vibe-Trading
📝 "Vibe-Trading: Your Personal Trading Agent"
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Vibe-Trading is a personal trading agent that empowers users with comprehensive trading capabilities. The project offers a range of key features, including a Shadow Account, demo, quick start, and examples. pip install vibe-trading-ai is the command to get started.

The project is built using Python 3.11+, FastAPI, and React 19, and has a PyPI package. It also has a Feishu group, WeChat group, and a Discord channel for community support.

The project's technical highlights include a global data layer with 18 market-data sources, 18 read-only data tools, and a local Data Bridge loader. It also features Research Autopilot, which runs hypothesis → signal-engine → backtest end to end.

Vibe-Trading is suitable for traders, researchers, and developers looking for a powerful trading agent. With its comprehensive features and active community, it's an ideal choice for those seeking a reliable and customizable trading solution.
The one command to rule them all: pip install vibe-trading-ai and trade away.

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🧠 Channel: https://xn--r1a.website/GithubRe

🌟 keycloak/keycloak caught my eye on GitHub Trending today.

🔗 https://github.com/keycloak/keycloak
📝 Open Source Identity and Access Management For Modern Applications and Services
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Keycloak is an open-source identity and access management solution that simplifies adding authentication to applications and securing services. It provides user federation, strong authentication, user management, and fine-grained authorization. To get started, you can download the distribution from the website and run it using bin/kc.[sh|bat] start-dev or use the Docker image with docker run quay.io/keycloak/keycloak start-dev.

The project has a strong focus on community involvement and security, with guidelines for contributing and a Code of Conduct in place. Keycloak is written in Java and has a permissive Apache License, Version 2.0.

Keycloak is perfect for developers and organizations looking for a robust and scalable identity management solution. Whether you're building a web application, a mobile app, or a microservices architecture, Keycloak has the features and flexibility you need. So why wait? Dive into the world of Keycloak and discover the power of secure, scalable, and open-source identity management - add authentication to your apps in minutes, not months!

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🧠 Channel: https://xn--r1a.website/GithubRe

💡 every-app/open-seo just hit the trending charts — here's why it matters.

🔗 https://github.com/every-app/open-seo
📝 Open source alternative to Semrush and Ahrefs
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Introducing OpenSEO, an open-source alternative to expensive SEO tools like Semrush and Ahrefs. This pay-as-you-go platform is designed for the people, giving you complete control over your SEO data. With OpenSEO, you can connect with any AI agent, such as Claude Code or Hermes, and utilize pre-built skills to tailor the tool to your needs.

The platform offers a range of key features, including keyword research, rank tracking, competitor insights, backlinks, site audits, and AI visibility. You can also use OpenSEO's MCP server to expose your SEO data directly to your AI agent.

To get started, you can choose from two self-hosting options: Docker for personal use and Cloudflare for internet-facing self-hosting. OpenSEO is completely free to use, with costs limited to DataForSEO API usage.

The OpenSEO community is active and welcoming, with a Discord channel for discussion and a mailing list for updates. Whether you're an SEO expert or just starting out, OpenSEO is an excellent choice for managing your online presence.

Take control of your SEO data and join the OpenSEO community today - your wallet (and your website) will thank you!

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🧠 Channel: https://xn--r1a.website/GithubRe

🎯 simplex-chat/simplex-chat landed on trending. Worth a proper look.

🔗 https://github.com/simplex-chat/simplex-chat
📝 SimpleX - the first messaging network operating without user identifiers of any kind - 100% private by design! iOS, Android and desktop apps 📱!
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SimpleX Chat is a messaging platform that prioritizes user privacy, with no user identifiers of any kind. It features double ratchet end-to-end encryption and an additional encryption layer to protect messages and metadata.

The app is available for Android and iOS, with a TestFlight preview for iOS that offers new features 1-2 weeks earlier. You can also use it as a terminal app on Linux, MacOS, and Windows.

To get started, install the app, then connect to the team or join user groups to ask questions or share ideas. You can also make a private connection with a friend by sharing a link or scanning a QR code.

SimpleX Chat is for anyone who values privacy, including individuals and developers who want to build on the SimpleX platform.

Contribute to the project by developing features, translating the app, or donating to support the team.

Here's the punchy one-liner takeaway: SimpleX Chat is the ultimate private messaging platform where your conversations are truly yours alone.

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🧠 Channel: https://xn--r1a.website/GithubRe

🚀 Meet ripienaar/free-for-dev: a gem from today's GitHub trending list.

🔗 https://github.com/ripienaar/free-for-dev
📝 A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
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The ripienaar/free-for-dev GitHub repository is a curated list of software and services offering free tiers, specifically tailored for infrastructure developers, including System Administrators and DevOps Practitioners. This list is the result of contributions from over 1600 people, making it a community-driven effort.

The repository covers a wide range of categories, including Major Cloud Providers, Cloud management solutions, Analytics, Events, and Statistics, and many more. It provides detailed information on the free tiers offered by top cloud providers like Google Cloud Platform, Amazon Web Services, Microsoft Azure, Oracle Cloud, and IBM Cloud.

To be included in the list, a service must offer a perpetual free tier, not just a trial, with a minimum of one year if it's time-bucketed. The free tier must also be evaluated from a security perspective, allowing for Single Sign-On (SSO) but not restricting Transport Layer Security (TLS) to paid tiers.

Whether you're a seasoned developer or just starting out, this repository is an invaluable resource for finding the best free services to support your projects. So, why pay when you can get it for free - explore the ripienaar/free-for-dev repository today and start building without breaking the bank!

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🧠 Channel: https://xn--r1a.website/GithubRe

🔍 Deep-diving into xbtlin/ai-berkshire — fresh off the trending list.

🔗 https://github.com/xbtlin/ai-berkshire
📝 AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Codex. 4 masters' methodologies + multi-agent adversarial analysis.
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Ai Berkshire is a revolutionary investment research framework that leverages AI to redefine the depth and efficiency of investment research. It systematizes and structures the methodologies of four investment masters: Warren Buffett, Charlie Munger, Yongping Duan, and Lu Li. By utilizing AI agents, it provides professional-level investment research, enabling individuals to make informed decisions.

The framework offers various Skills for different purposes, such as /investment-research for comprehensive analysis, /investment-team for parallel research, and /industry-research for industry-wide scans. These skills are designed to provide structured and consistent outputs, allowing users to compare and contrast different companies and industries.

Technical highlights of the framework include the use of Python for precise calculations, multiple data sources for validation, and a mirror test to ensure that the research is thorough and unbiased. The framework also employs a four-dimensional assessment to evaluate companies based on their business model, moat, management, and valuation.

Ai Berkshire is suitable for investors, researchers, and financial professionals looking to enhance their investment research capabilities. With its robust framework and AI-driven approach, it has the potential to revolutionize the investment research industry. One key takeaway: Ai Berkshire turns individuals into a full-fledged investment research team.

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🧠 Channel: https://xn--r1a.website/GithubRe

🔥 Robbyant/lingbot-map is trending — and it deserves your attention.

🔗 https://github.com/Robbyant/lingbot-map
📝 A feed-forward 3D foundation model for reconstructing scenes from streaming data
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The LingBot-Map is a groundbreaking tool for streaming 3D reconstruction, boasting a feed-forward architecture that enables high-efficiency streaming inference and state-of-the-art reconstruction. Its key features include a Geometric Context Transformer that unifies various components for robust and accurate results, as well as paged KV cache attention for stable inference.

To get started, users can follow the installation instructions to set up the required environment and dependencies, including PyTorch and FlashInfer. The model can be downloaded from Hugging Face or ModelScope, and users can choose from various checkpoints, including lingbot-map-long and lingbot-map.

The demo.py script provides an interactive way to visualize and test the model on various example scenes, with options for sky masking, keyframe intervals, and windowed inference. For longer sequences, the offline rendering pipeline offers a way to render high-quality videos.

Overall, the LingBot-Map is designed for researchers and developers working on 3D reconstruction and computer vision tasks, and its ease of use and high performance make it an attractive choice for a wide range of applications.

Here's a simple command to get you started:

python demo.py --model_path /path/to/lingbot-map-long.pt --image_folder example/courthouse --mask_sky

With LingBot-Map, you can achieve state-of-the-art 3D reconstruction results with ease - so why wait, dive in and start reconstructing your world today!

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🧠 Channel: https://xn--r1a.website/GithubRe

🔍 Deep-diving into DeusData/codebase-memory-mcp — fresh off the trending list.

🔗 https://github.com/DeusData/codebase-memory-mcp
📝 High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.
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Codebase-Memory-MCP is a blazing-fast code intelligence engine designed for AI coding agents. It full-indexes an average repository in milliseconds and answers structural queries in under 1ms. This engine supports 158 languages through tree-sitter AST analysis and Hybrid LSP semantic type resolution for languages like Python, TypeScript, and Rust.

Key features include:
- Extreme indexing speed: Indexes the Linux kernel in 3 minutes
- Plug and play: Single static binary for macOS, Linux, and Windows
- Built-in graph visualization: 3D interactive UI for exploring codebases
- Infrastructure-as-code indexing: Supports Dockerfiles, Kubernetes manifests, and more

To get started, simply run the install command, and the engine will auto-detect and configure your coding agents. With features like semantic search, cross-service linking, and cross-repo intelligence, this engine is perfect for developers looking to supercharge their coding workflow.

One-liner takeaway: Supercharge your coding workflow with Codebase-Memory-MCP, the fastest and most efficient code intelligence engine for AI coding agents.

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🧠 Channel: https://xn--r1a.website/GithubRe

⚡ cupy/cupy is making waves. Here's the full picture.

🔗 https://github.com/cupy/cupy
📝 NumPy & SciPy for GPU
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CuPy is a NumPy and SciPy-compatible array library for GPU-accelerated computing with Python. It acts as a drop-in replacement to run existing NumPy/SciPy code on NVIDIA CUDA or AMD ROCm platforms.

You can import cupy as cp and use it like NumPy, with features like ndarray and array operations. It also provides access to low-level CUDA features, including RawKernels and Streams.

CuPy is ideal for data scientists, machine learning engineers, and anyone looking to accelerate their Python code with GPU power.

To get started, you can install CuPy via Pip or Conda, and explore the documentation and tutorial for more information.

pip install cupy-cuda12x or conda install -c conda-forge cupy to install.

One-liner takeaway: CuPy unleashes GPU acceleration for Python with a simple, NumPy-compatible API.

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🧠 Channel: https://xn--r1a.website/GithubRe