📦 danneauxs/pocket-tts-spokenword

pocket-tts-spokenword

pocket-tts-spokenword is the desktop-friendly audiobook generator that turns dry digital voices into emotionally expressive narration. While typical text-to-speech programs sound robotic and flat, this tool analyzes your text using advanced AI emotion classification to automatically adjust vocal tones, pacing, and feeling. It intelligently divides long texts at natural sentence boundaries, maps six distinct emotional states like joy or sadness to the speech generator, and even lets you clone custom voices. Because it runs incredibly fast using only a standard computer processor, you can easily convert entire books into high-quality, expressive audio files right from a simple, interactive desktop app.

🆔 @hackernewsgithubprojects

📦 hexxt-git/ccpool

ccpool

Sharing a single Claude Code subscription with your team usually ends in disaster when someone quietly burns the entire weekly limit by noon and nobody knows who did it. ccpool solves this by giving your team a live, shared terminal dashboard that breaks down exactly who is driving the account's usage. By running a lightweight background daemon on each member's machine, it securely correlates your local coding activity with Anthropic's official usage limits. It is a read-only observer that displays beautiful, real-time usage bars and countdowns for the group, making fair use visible and easy to coordinate.

🆔 @hackernewsgithubprojects

📦 modalitydance/palmclaw

PalmClaw

You can now run a fully functional, automated AI agent directly on your Android phone without needing a computer. An open-source project called palmclaw packages an entire agent stack—including memory, tools, and automation—into a single mobile app. Instead of relying on complex desktop setups, it operates inside Android's secure app sandbox to keep your private data safe. It connects with local files, hardware like Bluetooth, and external communication channels. You get a private, safe assistant that can automate tasks and handle tools right in your pocket. Grab the app to put a capable agent on your phone.

🆔 @hackernewsgithubprojects

📦 tencent-hunyuan/hy-embodied

hy-embodied

Imagine a robot that can navigate and interact with the physical world using an incredibly efficient brain that only activates three billion parameters at a time. The hy-embodied repository introduces a vision-language foundation model designed specifically for real-world robotic agents. It solves the massive computing bottleneck of physical deployment by utilizing a clever mixture-of-experts architecture, giving robots high-level reasoning and physical awareness without needing a giant server farm. This means robots can now plan complex tasks, adapt to changing situations, and understand spatial coordinates in real time. It is a massive step toward making smart, responsive physical robots actually practical.

🆔 @hackernewsgithubprojects

📦 scottstts/threejs-awesome-graphics-agent-skills

threejs-awesome-graphics-agent-skills

Artificial intelligence models are notoriously bad at generating high-end 3D graphics because they do not understand the math behind good taste. The threejs-awesome-graphics-agent-skills repository changes this by acting as a specialized library of expert graphics techniques designed specifically for AI agents. Instead of trying to teach an LLM basic code, this tool injects production-ready math, shaders, and rendering pipelines directly into the agent's vocabulary. It allows AI coding assistants to instantly implement complex visual effects like realistic spectral oceans, volumetric clouds, and advanced lighting models without falling back on cheap visual hacks. It is a brilliant way to make AI-generated 3D scenes actually look beautiful.

🆔 @hackernewsgithubprojects

📦 smileformylove/xscientist

xscientist

This project transforms scientific research into a git-like protocol where experiments are completely diffable, forkable, and reviewable just like open-source code. Instead of simply generating a static paper, xscientist runs a continuous pipeline that treats every research attempt as a trackable commit, mapping out your entire scientific exploration as a branching tree of code, metrics, and failures. It even links written manuscript claims directly back to the exact code execution node that proved them. It is basically git for science, letting you branch off previous experiments to build a fully verifiable, automated tech tree.

🆔 @hackernewsgithubprojects

📦 ireliya/terralogic

Terralogic

Terralogic is the benchmarking framework that finally helps artificial intelligence make sense of Earth observation data by coordinating complex, multi-step search missions. Instead of just looking at a satellite image, this system acts like a coordinator for specialized remote sensing tools across optical, radar, and infrared sensors. It breaks down complex natural language requests, builds a logical execution plan, and runs detailed analysis like counting specific structures or tracking small infrared targets over time. If a sensor tool fails or returns bad data, the system automatically self-corrects and swaps in a compatible tool to finish the job, translating raw data into verified, plain-English answers.

🆔 @hackernewsgithubprojects

📦 metainfer/metainfer

MetaInfer

Build a custom, high-performance language model inference engine from scratch using an automated, agent-driven compiler approach. Instead of downloading a massive, bloated framework with endless configuration options, this project introduces a brilliant concept called Large Language Model as Compiler. It uses a structured knowledge graph and a multi-agent system of coders, reviewers, and testers to automatically assemble a lean, single-path inference engine tailored precisely to your specific model and hardware. This eliminates thousands of lines of dead code, resulting in massive speedups over traditional setups. It is a fascinating glimpse into the future of self-assembling, hyper-optimized AI infrastructure.

🆔 @hackernewsgithubprojects

📦 jetxu-llm/codex-deepseek-bridge

Codex DeepSeek Bridge

Redirect your OpenAI Codex app requests to DeepSeek using a clever local proxy that keeps your existing setup completely intact. This tool hooks directly into your configuration so you can use deepseek-pro and deepseek-flash while keeping your plugins, MCP servers, and custom workflows running exactly as they are. The best part is your API key never leaves your machine, and you get a beautiful offline dashboard to track your cache hits and latency. When you want to revert, a single restore command puts everything back to the official defaults without leaving a trace.

🆔 @hackernewsgithubprojects

📦 thudm/scale-cua

ScaleCUA

Teach your AI models to control any desktop operating system like a human. This project introduces a pipeline that generates thousands of realistic computer tasks, like browsing the web or editing spreadsheets, and builds automated judges to verify if the AI actually completed them correctly. Instead of wasting time on tasks that are too easy or too hard, it uses a smart sampling method to constantly feed the AI challenges right at the edge of its current capabilities. It is a highly efficient way to train digital agents, making them smarter and much faster at navigating real software.

🆔 @hackernewsgithubprojects

📦 starnodes2024/comfyui-starnodes-modelconverter

comfyui-starnodes-modelconverter

You can now squeeze massive diffusion models down to just a quarter of their original size without ruining your image quality. The comfyui-starnodes-modelconverter is a custom node package for ComfyUI that introduces advanced, profile-based quantization to intelligently compress heavy models like Flux, SDXL, and Wan. Instead of a basic blanket compression, this project analyzes your model layer by layer and uses smart blacklists to keep highly sensitive elements like embeddings and normalizations in high precision while safely shrinking everything else. It even lets you split all-in-one checkpoints into clean, separate components for easier management.

🆔 @hackernewsgithubprojects

📦 fiigii/ai-comp

ai-comp

The optimizing compiler that solves a complex coding challenge by translating high-level code into highly efficient parallel instructions. ai-comp was built to conquer Anthropic's performance engineering take-home exam, which asks developers to manually optimize a tree-traversal and hashing program running on a simulated virtual machine. Instead of spending hours tweaking the machine code by hand, this project automates the entire process. It takes a human-readable description of the program and intelligently schedules instructions to run simultaneously on multiple virtual execution engines. The coolest part is how it automatically eliminates redundant memory steps, ensuring the simulated processor never wastes a single clock cycle waiting for data that it already has. It...

📰 https://news.ycombinator.com/item?id=48911420

🆔 @hackernewsgithubprojects

📦 smithandrewjohn/kindalive

Kindalive

Model robot emotions through simulated body chemistry instead of simple programming labels. With kindalive, you type a plain text paragraph, and a smart interpreter translates your words into real-time chemical impulses like dopamine, cortisol, and adrenaline. A core engine constantly calculates how these simulated chemicals decay and interact, translating the balance into twelve facial muscle movements. This drives a retro LED dot-matrix face that naturally contorts to show realistic, blended emotions without hard-coded rules. You get a fascinating look at emergent behavior, complete with a responsive web dashboard, plus ready-to-use adapters to bring your physical robot face to life on real hardware.

📰 https://news.ycombinator.com/item?id=48878966

🆔 @hackernewsgithubprojects

📦 yempik-ai/cowork-os

cowork-os

AI agents work best when they do not leave their results trapped inside disposable chat threads. cowork-os is an open-source workspace layer that saves your teams decisions, process knowledge, and project state in plain Markdown files you actually own. Instead of relying on opaque memory systems, this system uses your existing local files to keep your virtual assistant grounded and fully accountable. It translates unwritten team processes into structured workflows and runs automated routines, like daily briefs and pipeline updates, directly on your disk. You get an inspectable company brain that your team can easily review, correct, and control.

🆔 @hackernewsgithubprojects

📦 tristan666666/agent-island

Agent Island

Agent Island is the desktop status companion that finally keeps you in the loop with your background Claude Code and Codex sessions. If you run long coding agent tasks, you do not have to stare at an open terminal anymore. This lightweight, local-first app sits in your macOS menu bar or Windows taskbar, silently monitoring your active runs. It spins its logo while they work, flashes red if there is an error, and plays an alarm the second it is your turn to respond. You get instant updates, cost tracking, and weekly productivity reports with zero telemetry and telemetry. Just sit back, relax, and let your code write itself.

🆔 @hackernewsgithubprojects

📦 yale-nlp/llm-metacognition

llm-metacognition

Large language models can actually monitor and regulate their own thinking process just like humans do. The llm-metacognition repository collects and organizes scientific research exploring this exact boundary, providing a complete map of how models assess their own knowledge and correct their errors. It acts as an open library for the latest techniques to measure confidence, detect when an AI is guessing, and prevent hallucinations. By organizing these breakthroughs into a structured guide, it helps developers build much more reliable AI systems. If you want to understand how artificial intelligence is learning to think about thinking, this repository is the perfect place to start.

🆔 @hackernewsgithubprojects

📦 quhongyu/lamem-vla

LaMem-VLA

Control robots with natural language and vision using a clever system that remembers past actions to make better decisions. Most modern robot brains struggle to connect what they see with what they did a moment ago, making them clumsy. This project introduces a dual memory system that keeps track of both visual cues and physical movements, helping robots perform tasks much more smoothly. While the creator is still polishing up the code for release, keeping an eye on this repository is a great way to see how the next generation of smart, adaptable robots will actually learn to navigate our messy world.

🆔 @hackernewsgithubprojects

📦 yeanroot/halo-wa

halo-wa

halo-wa is the robotics training wrapper that finally makes online reinforcement learning practical for complex physical agents. Under the hood, it connects advanced vision-language-action policies with simulated physical environments to train robots using a hybrid-attention world model. While standard setups struggle to coordinate simulation physics and deep model learning, this framework packages everything into ready-to-run tasks like hammering or ringing a bell. By utilizing pre-trained world models as reliable digital training grounds, it lets robots practice and refine their physical skills safely in simulation before taking on the real world. You can download the pre-packaged data and start training physical policies immediately.

🆔 @hackernewsgithubprojects

📦 zhinianboke/xianyu-auto-reply

xianyu-auto-reply

xianyu-auto-reply is the multi-account management assistant that finally turns your secondhand store into a hands-off, automated storefront. It uses web sockets and browser automation to handle everything from answering customer questions with smart AI replies to auto-delivering digital keys and giving ratings. You can run multiple accounts, auto-refresh your listings to keep them on top of search results, and manage your inventory with zero manual clicking. It essentially acts as a twenty-four-seven virtual employee, making sure you never miss a sale even while you sleep. Set up this Python-based automation toolkit today to let your store run itself.

🆔 @hackernewsgithubprojects

📦 apache/ossie

Apache Ossie

Apache Ossie is the open-source specification that standardizes how we share business definitions across different database tools and artificial intelligence platforms. Normally, different teams and software packages define key metrics like revenue or customer count using completely different logic, leading to frustrating calculation errors. This project solves that problem by providing a single, vendor-neutral file format that any software can read and write. It translates complex data relationships into a universal language, giving your entire technical stack a single source of truth. It is a fantastic way to keep your database logic consistent, reliable, and perfectly aligned.

🆔 @hackernewsgithubprojects