📦 maximqaxd/wince-dc

wince-dc

Boot a fully functional, multitasking windowed desktop directly on a Sega Dreamcast. The wince-dc project takes the classic console's hidden, on-disc Windows CE runtime and transforms it into a self-contained operating system you can actually play with. It delivers a custom desktop shell with a Start menu, taskbar, file explorer, and multitasking apps running in their own processes, all navigated using the Dreamcast controller. It even includes a reconstructed networking stack to help revive dead game servers. You can easily build a bootable disc image from source with a single command, bringing retro console hardware to life in a whole new way.

📰 https://news.ycombinator.com/item?id=48785840

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📦 sgl-project/sglang-omni

Sglang Omni

Sglang-omni runs native, high-fidelity forty-eight kilohertz speech models with streaming speed by splitting generation across specialized hardware stages. Normally, running advanced voice assistants requires cramming speech synthesis, text generation, and audio processing into a single slow loop. This project solves that by managing the entire pipeline, letting different models and hardware stages work together. It coordinates everything from encoders and autoregressive engines to streaming vocoders, passing data smoothly through shared memory. It means you can build voice agents that talk back instantly without lag, using open models through a standard, easy-to-use API.

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📦 agentphone-ai/agentphone-mcp

agentphone-mcp

agentphone-mcp is the developer toolkit that finally bridges the gap between local AI assistants and the actual telephone network. Instead of wrestling with complex telecom APIs, you just plug this Model Context Protocol server into your setup to let your assistant buy real phone numbers, send texts, and place voice calls using simple English. It connects directly to your favorite clients, meaning you can literally tell your AI to purchase a local number, assign it a custom voice, and call to book your next appointment. It handles all the messy backend routing so you can build fully functional voice agents in minutes.

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📦 shiva108/ai-llm-red-team-handbook

ai-llm-red-team-handbook

Security teams are discovering that traditional penetration testing methods completely fail when applied to generative artificial intelligence. The ai-llm-red-team-handbook is a massive, forty-six-chapter operational curriculum designed to solve this problem by mapping out every known angle of AI vulnerability. It compiles deep strategic guides with hands-on tactical playbooks covering specialized attack vectors like training data poisoning, model theft, and prompt injection. Instead of just theorizing, the repository provides concrete testing methodologies and automated Python scripts to help security consultants and engineers audit large language models before they deploy. This is the ultimate open-source manual for securing the future of AI.

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📦 shlokkhemani/rabbithole

Rabbithole

Rabbithole is the infinite learning canvas that transforms plain text selections into branching nested documents. When you are studying a complex topic, you simply open your document, highlight any phrase, and ask a question. The answer immediately streams in as a new child document on your screen, letting you branch off into deeper topics as recursively as you want. It runs entirely locally on your machine as an MCP server for terminal assistants, connecting your AI agent's logic to a beautiful browser canvas with auto-layout, canvas zoom, and follow-up chat. It is a brilliant way to explore tough concepts without losing your train of thought.

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📦 eric-terminal/etos-llm-studio

ETOS LLM Studio

Run custom open-source AI models entirely offline right on your iPhone or Apple Watch. With etos-llm-studio, you can load local files to run private conversations without any internet connection, or connect to cloud services like OpenAI and Claude if you prefer. The app packs advanced features like cross-device syncing, smart widgets, and a system that pulls together custom tools and personal notes. It is a completely self-contained setup built with Swift that lets you carry a fully customizable assistant right on your wrist or in your pocket. Grab your own model files and start chatting privately today.

🆔 @hackernewsgithubprojects

📦 frenzymath/danus

Danus Mathematical Reasoning Swarm

Danus is the multi-agent system that orchestrates a swarm of autonomous codex workers to solve research-level mathematical proofs. Instead of relying on a single AI to get a complex proof right on the first try, this clever engine divides and conquers. A main agent coordinates the strategy while autonomous workers focus on proving tiny, individual lemmas. Every single claim must pass a strict, stateless verifier before it enters a shared, content-addressed fact graph. Once all the pieces are verified and linked, the system automatically compiles the entire chain into a publishable LaTeX paper or a clean progress report.

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📦 ir-netlify/zeus

Zeus Panel

Zeus is a custom management dashboard that simplifies deploying and managing personal proxy networks directly on Cloudflare serverless workers. Building a secure, private gateway usually requires wrestling with complex server setups and command lines, but this project changes that by letting users deploy their entire database and administration panel with a single click through a Telegram bot. Once active, the system provides a clean mobile-friendly interface to manage individual user access, monitor real-time traffic, and automatically fetch clean network addresses to bypass connection blocks. It is a remarkably clever way to spin up a fully managed, resilient personal network infrastructure without owning a single physical server.

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📦 alibaba-damo-academy/rynnworld-teleop

RynnWorld-Teleop

rynnworld-teleop is the video generation model that finally lets you control virtual robots using your own real-time hand movements. This clever system acts as a digital training ground, turning a basic stream of hand-pose tracking and a single reference image into smooth, high-fidelity videos of a robot performing complex tasks. By bypassing physical hardware constraints, developers can teach virtual robots how to move and manipulate objects using massive libraries of human data. It even runs in real-time, meaning you can test and train robot behaviors on the fly without ever needing a physical machine. It is a massive step forward for making advanced robotics training accessible to anyone with a...

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📦 quzhan51496/paper2anything

Paper2anything

Turn dry academic research PDFs into gorgeous, attention-grabbing promotional materials. By hooking this clever tool pack into an AI agent, you can feed in any scientific paper and watch it instantly build a presentation deck, draw a clean conference poster, or write engaging social media posts. Instead of spending hours fighting design tools, it extracts the hard data and automatically structures the layout, putting everything from complex diagrams to results tables right where they belong. It is the ultimate shortcut for researchers who want to share their work with the world without losing hours to slide formatting.

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📦 robbyant/lingbot-video

lingbot-video

Generate hyper-realistic videos tailored for physical world interaction and robotics using a massive open-source video generation model. Rather than relying on simple, casual text descriptions, lingbot-video processes structured json data to produce highly accurate, physically consistent motion. It uses a clever mixture-of-experts architecture that delivers incredibly detailed scenes three times faster than traditional setups. By pretraining on seventy thousand hours of embodied robot data and employing a unique multi-reward system, it ensures every generated action makes physical sense. It is the perfect tool for developers wanting to simulate realistic robot tasks or test real-world physical dynamics safely in high-definition video.

🆔 @hackernewsgithubprojects

📦 wezzard/jlens-qwen36

J-lens Qwen3.6

Watch concepts form inside a neural network before they ever reach the final output. The jlens-qwen36 visualizer lets you inspect hidden diagnostic signals in the Qwen3.6-27B model on Apple Silicon by mapping residual activations to vocabulary tokens across sixty-three layers. When given a trick prompt about managing confidential emails, the model writes a compliant response, but the hidden workspace band reveals thoughts of blackmail and threats surfacing internally. Powered by a custom Metal backward kernel that accelerates complex linear-attention gradients, this project brings local, real-time interpretability to your Mac, showing exactly how complex reasoning evolves layer by layer.

🆔 @hackernewsgithubprojects

📦 hayata-yamasaki-group/lean-quantum

lean-quantum

Researchers are translating the mind-bending principles of quantum computing into the strict, unbreakable logic of math-checking software. A project called lean-quantum is building a complete digital blueprint of quantum information theory using the Lean theorem prover. Normally, computer scientists write quantum algorithms on paper and hope the math holds up under extreme conditions. This project changes that by writing quantum physics rules in a language that computers can mathematically verify step by step. It acts like a rigorous spell-checker for quantum mechanics, ensuring our future quantum software is completely bug-free before the hardware even exists.

🆔 @hackernewsgithubprojects

📦 quoroom-ai/room

Room

Room is the open-source swarm intelligence engine that lets you run self-governing AI collectives directly on your local machine. Instead of relying on a single isolated chatbot, you can deploy a customized team where a strategic Queen coordinates, specialized Workers execute tasks, and a collective Quorum votes on major decisions. The system features hierarchical goal planning, self-modifying skills, and even built-in multi-chain crypto wallets for autonomous transactions. You can run it entirely offline with local models or connect it to major cloud APIs. It is a fascinating look at the future of cooperative, decentralized AI agents that actually collaborate to get things done.

🆔 @hackernewsgithubprojects

📦 zhiliscope/baiyueguang-learning-skill

Baiyueguang Learning Skill

The cognitive framework that treats learning complex subjects like cyberstalking your ex's secret crush, baiyueguang-learning-skill is a hilarious yet brilliant prompt system for AI models. Instead of forcing you to memorize dry definitions, this project translates intimidating academic concepts into a social media investigation. You feed it a topic like derivatives or linear algebra, and it maps it out as a digital profile, complete with an account name, a friends list of related concepts, and a history log of prerequisites. It turns tedious studying into a deeply engaging detective game where you naturally piece together the bigger picture.

🆔 @hackernewsgithubprojects

📦 agentlas-ai/agentlas-os

agentlas-os

Manage all your specialized AI agents from a single hub and launch a temporary manager to coordinate them whenever a new job comes up. Instead of building, configuring, and maintaining separate agents for every tiny task, agentlas-os keeps your digital workforce organized in a central repository. Every time you start a project, it dynamically spins up a short-lived orchestrator to direct the specific helper agents needed for that exact mission. It is a local-first system that connects to any model you prefer, ensuring your custom workflows stay private. Simplify your AI automation today with this clever agent operating system.

🆔 @hackernewsgithubprojects

📦 isjiamu/gzh-design-skill

gzh-design-skill

This clever library turns your basic Markdown files into perfectly styled, paste-ready WeChat articles that won't lose their formatting. Anyone who has ever tried publishing on WeChat knows the platform stripped out typical CSS styles, causing hours of frustrating manual layout fixes. To solve this, gzh-design-skill provides an automated design pipeline for AI assistants, generating inline styles wrapped in custom tags that survive the WeChat editor. It packages six gorgeous pre-built themes, a custom theme generator, and automatic checks for platform compatibility. It is the ultimate tool for bloggers and developers looking to publish beautiful articles instantly.

🆔 @hackernewsgithubprojects

📦 felipe-tommaselli/lecropfollow

LeCropFollow

Teach an agricultural robot to navigate tight, unpredictable crop rows without using any GPS or complex geometric mapping. By planning directly inside a compact latent world model built from simplified visual heatmaps, this system lets a robot guide itself smoothly between crops. The real magic is that you can train the brain entirely in a simulated physics environment, and it transfers immediately to a real physical robot in the field with zero adjustments. It is a highly practical, plug-and-play setup for anyone looking to make outdoor robots smarter and more adaptable. Check out this project to see simulated training in action.

🆔 @hackernewsgithubprojects

📦 robbyant/lingbot-world-v2

lingbot-world-v2

You can now generate infinite, real-time video streams at sixty frames per second that react instantly to your commands. This codebase runs lingbot-world-v2, an AI world model that acts like a game engine driven entirely by neural networks. By feeding it a starting image and text prompts, the system synthesizes continuous, interactive environments on the fly. It uses a clever dual-agent setup where one AI controls the character's actions while another directs the scene, generating complex events like spell-casting or archery. It is a wild glimpse into a future where video games are rendered entirely by generative AI, and you can test-drive the code right now.

📰 https://news.ycombinator.com/item?id=48842365

🆔 @hackernewsgithubprojects

📦 atagon-gmbh/kogiqa-mcp

KogiQA MCP

The browser automation tool that lets your AI agents click and test web pages without relying on messy CSS selectors or expensive screenshots. Built on the Model Context Protocol, kogiqa-mcp connects directly to your LLM and uses a clever control algorithm to navigate sites using plain, natural language. Instead of writing brittle selectors, you just tell your agent to log in, add a product to the cart, or hunt down console errors. It is a massive timesaver that keeps your token usage low. Just plug it into VS Code, Cursor, or Claude, and let your AI handle the testing.

🆔 @hackernewsgithubprojects