📦 pnnbao97/vieneu-tts

VieNeu-TTS

vieneu-tts is the text-to-speech toolkit that brings human-like voice synthesis and instant voice cloning to Vietnamese applications entirely on your local device. It turns written text into natural speech with a high-fidelity output of up to forty-eight kilohertz, and it even lets you clone any voice using just a five-second audio clip. What makes this project really special is that it can run directly on a standard computer processor without needing a heavy graphics card. This means you can easily generate natural-sounding voiceovers, podcasts, and realistic dialogues offline. Check it out to build highly responsive, localized voice applications.

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📦 quintinshaw/openasr

OpenASR

Imagine transcribing audio and meeting recordings entirely on your computer without sending a single byte to the cloud. OpenASR is a local-first speech-to-text platform that lets you run twenty-eight different voice recognition models completely offline on your own CPU or graphics card. It transcribes audio files, generates subtitles with speaker labels, and even captures system audio directly from your screen. Because it runs entirely locally with zero telemetry, your private conversations and recordings never leave your machine. It is the perfect tool for private, high-speed transcription and translation right from your desktop or terminal.

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📦 tommyjepsen/awesome-ux-skills

Awesome UX Skills

You can now automatically inject professional user experience frameworks directly into Claude Code. A new open-source repository called awesome-ux-skills acts as an automated design companion by loading specialized prompt templates straight into your terminal workflow. When you ask Claude design questions, it automatically detects the right template to evaluate your UI against accessibility guidelines, run cognitive load checks, or structure user persona research. By translating complex design concepts into automated, situational prompts, this project bridges the gap between raw code and polished product design, helping you build more intuitive interfaces without having to manually feed best practices to your AI assistant.

📰 https://news.ycombinator.com/item?id=48766415

🆔 @hackernewsgithubprojects

📦 duolahypercho/codex-router

Codex Router

codex-router is the credential-isolating local gateway that finally lets you run premium external models like Claude, DeepSeek, and Grok directly inside your favorite AI desktop editors. It acts as a clever local translation proxy, converting your app's standard requests into the native language of whatever provider you choose, while keeping your API keys and login sessions completely isolated on your own machine. My favorite feature is that it even lets you use your editor without an OpenAI login by publishing external models under native aliases so the app still recognizes them. It is the perfect weekend upgrade to make your development environment truly model-agnostic.

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📦 pyang5166/gbro-collage-broll

gbro-collage-broll

gbro-collage-broll is the clever agent tool that turns your five-second voiceover scripts into gorgeous, paper-collage stop-motion video clips. Instead of burning real money on chaotic AI video generations, this project introduces a smart three-step approval gate. First, it cooks up a solid visual metaphor. Next, it generates a beautiful halftone paper-collage static image. Finally, it uses Gemini Omni Flash to assemble everything into a slick animation where elements slide and snap into place. It gives you complete creative control at every step, saving your budget while producing stunning, high-end editorial visuals for your videos.

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📦 slvdev/esp32-ai

ESP32-AI

Run a twenty-nine million parameter language model directly on an eight-dollar microcontroller with absolutely no internet connection. The esp32-ai project makes this possible on an ESP32-S3 chip by using a clever memory design called Per-Layer Embeddings. Instead of trying to squeeze the entire model into the tiny half-megabyte of fast RAM, it stores ninety percent of the model in slow, cheap flash memory. It only pulls the tiny handful of data rows needed for each word, allowing the chip to write coherent stories to a small screen at nearly ten words per second. It is a brilliant way to make tiny, cheap hardware punch way above its weight class.

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📦 escoffier-labs/brigade

Brigade

Artificial intelligence agents can execute complex loops and generate code, but keeping track of what they actually accomplished is notoriously difficult. Brigade solves this by acting as a lightweight, local control plane that creates verifiable file receipts for every single action your agents take. Running completely on your own machine without background daemons or platform lock-in, it lets different AI tools and frameworks easily share the Model Context Protocol, custom tools, and memory. Because it records everything with tamper-resistant receipts, you can easily prove what your agents did and use real program exit codes to systematically improve their performance.

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📦 nvidia-nemo/emerging-optimizers

Emerging Optimizers

Nvidia’s emerging-optimizers repository implements advanced training algorithms that actually speed up how fast massive AI models learn. Traditional training rely on simple adjustments, but this project packages sophisticated alternatives like Muon and Soap, which use advanced matrix operations and geometry to find the best settings much faster. In fact, these exact techniques were used to train the massive Kimi K2 language model. By integrating these tools directly into standard graphics processing unit training systems, developers can achieve quicker convergence and better final model quality. It is a powerful toolbox for anyone looking to push the boundaries of neural network efficiency.

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📦 maxwell2732/pai-econ-claude

pai econ claude

Empirical economists often struggle to bridge the gap between real-world data and formal mathematical modeling. The open-source project pai-econ-claude solves this by acting as a highly structured theoretical scaffolding for empirical researchers. Instead of building models from scratch, it matches real-world economic puzzles with classic theoretical frameworks like search models, moral hazard, or rational inattention. The tool walks users through rigorous checks, auditing assumptions, outlining proof sketches, and organizing findings into draft manuscripts. It is a brilliant way to make sure your empirical insights are grounded in solid, peer-reviewed economic theory before you write your paper.

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📦 shanghai-academy-of-ai-for-science/mkb

mkb

Imagine a single AI model that can design RNA sequences, forecast global weather, and segment medical images with expert-level precision. That is exactly what mkb does. Built on an eight-billion parameter language backbone, this system pairs specialized scientific encoders and decoders with a shared core. Instead of swapping out different models for different tasks, it routes biology, chemistry, and physics data through a single natural-language interface. It actually outperforms massive one-trillion parameter models on biological tasks and rivals physics-based forecasting systems. It is a brilliant, lightweight way to solve diverse scientific problems on a single graphics card.

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📦 ibm-client-engineering/output-drift-financial-llms

Output Drift Financial LLMs

Stop relying on massive AI models for regulated tasks without checking their consistency first. This repository lets you benchmark and audit how much large language model outputs drift when running financial operations like text to SQL or compliance triage. Interestingly, testing reveals that smaller seven to twenty billion parameter models achieve up to one hundred percent consistency, while massive frontier models over one hundred billion parameters show only twelve to fifty percent consistency. You can run repeated trials on identical prompts to measure action, signature, and decision determinism to ensure your automated agents are completely reproducible before they ever touch live financial data.

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📦 joeseesun/qiaomu-cut-skill

Qiaomu Cut Skill

You can now transform a single spoken prompt into a complete, ready-to-render video project using Qiaomu Cut Skill. This agent-native video director builds structure out of chaos by taking your simple prompt and generating a fully realized video timeline complete with shot lists, background music, and professional three-layer bilingual subtitles. Instead of promising magic, it coordinates actual engineering tasks, searching free stock sites, generating speech overlays, applying precise cinematic transitions, and organizing everything into structured files. It even includes a three-tiered rendering pipeline so you can quickly preview drafts before exporting your final high-quality master copy. It makes automated video editing structured and fully verifiable.

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📦 nexu-io/codex-slides

Codex Slides

Turn a prompt, a repository, or a folder of local files into a beautiful, presentation-ready slide deck without ever leaving your coding workspace. codex-slides is an open-source, image-native slide studio built for coding agents that serves as a self-hosted alternative to standard AI presentation tools. Instead of waiting for a hidden background task, you can watch the entire process live as the agent conducts research, builds an outline, and styles your project. The absolute best part is fast mode, which renders over ten slides in parallel in just four minutes. When you are done, you can edit pages on a live canvas and export your work as a PowerPoint or...

📰 https://news.ycombinator.com/item?id=49031776

🆔 @hackernewsgithubprojects

📦 saddam213/amuseai

Amuse AI Local Generator

You can now run massive artificial intelligence pipelines locally on your machine without dealing with broken Python dependencies. Amuse AI acts as a smart interface for the Tensor Stack software development kit, giving you a smooth desktop app to generate images, edit videos, and translate speech entirely on your own hardware. The coolest part is how it handles different hardware by automatically launching isolated Python environments for each specific graphics card or pipeline. This means your Nvidia and AMD setups will never clash, and you can even shrink massive models down using built-in quantization to fit them onto budget graphics cards without running out of memory.

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📦 joeyvansommeren/journey-mapper

Journey Mapper

You can now instantly turn any codebase into a beautiful, interactive customer journey map without doing a single pixel of manual design work. Journey-mapper is an automated tool that scans your routes, components, and API calls to map out exactly how users move through your application. It acts like a service designer, automatically building a single, browser-ready HTML file that combines a customer journey with a service blueprint. The tool maps out what the user does, what they see on the frontstage, and what the code triggers backstage, while marking its emotional and cognitive insights as assumptions for you to validate later. It is the easiest way to bridge the...

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📦 ailinone/collective-intelligence

Collective Intelligence

Collective Intelligence is the open source engine that lets over seventy-six thousand AI models collaborate inside a single system rather than routing requests to just one place. Instead of relying on a single model that acts as a single point of failure and training bias, this project coordinates thousands of models across dozens of strategies, like blind debates, expert panels, and consensus pools. By testing models against each other and using deterministic verifiers, it achieves an outstanding ninety-seven percent accuracy on verifiable tasks, beating major standalone frontier models. It is the ultimate way to build resilient, self-healing, and highly auditable AI applications.

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📦 maomao-2001/whispera

whispera

You can now run a fully local, real-time voice assistant directly on your Windows PC without sending a single byte of your conversations to the cloud. A clever open-source desktop app called whispera orchestrates everything right on your machine. It ties together a local language model, smart voice activity detection, and incredibly fast speech-to-text to let you have natural, spoken conversations. When you speak, it listens and can even be interrupted mid-sentence just like a real person. It generates streaming audio replies locally, and you can even plug in long-term memory so it actually remembers your past chats.

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📦 tencent/workbuddy-bench

WorkBuddy Bench

Drop your coding agents directly into a simulated office environment to see how they handle realistic corporate workloads. Rather than testing simple code snippets, workbuddy-bench runs your agent inside a local Docker sandbox to tackle complex, multi-step tasks reverse engineered from actual professional roles, like developers, product managers, and security analysts. It evaluates how effectively these agents edit real repositories, fix security vulnerabilities, modify front-end web interfaces, and manipulate messy office spreadsheet files. The system runs the agent, captures its step-by-step behavior, and scores the results automatically. It is the perfect way to pressure-test your artificial intelligence on messy, real-world tasks before letting it loose on your production code.

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📦 lexsi-labs/circuitkit

CircuitKit

CircuitKit is the mechanistic interpretability framework that lets you directly edit and export task-specialized transformer models. Most AI interpretability tools stop at showing you a colorful graph of which attention heads are active. This clever tool goes much further by finding the exact minimal circuit of neurons driving a specific behavior, letting you prune or steer that pathway, and then exporting a fully functional Hugging Face checkpoint of your newly optimized model. It makes deep model surgery accessible to anyone wanting to patch hallucinations, steer behaviors, or aggressively compress neural networks. Grab this tool and start dissecting your AI models today.

🆔 @hackernewsgithubprojects

📦 decodingai-magazine/building-a-coding-agent-from-scratch-course

building-a-coding-agent-from-scratch-course

Build a fully capable AI coding agent from the ground up without relying on complex, pre-made frameworks that hide all the magic. This repository gives you a free eight-lesson course where you construct a terminal coding assistant called decode in Python. You will go beyond the basic text generator loop to construct the actual harness that controls the model. It guides you through designing strict permission gates, running untrusted code in secure sandboxes, compressing conversation history, and even launching parallel teams of subagents to solve tasks. It is the ultimate hands-on guide to mastering how real-world AI coding tools actually operate.

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📦 role1776/netmon

Netmon

Your self-hosted network monitor can now roast your internet connection using artificial intelligence. Netmon is a brilliant little Python tool that silently watches your home network, runs hourly speed tests, and scans your local Wi-Fi to count connected devices. Every four hours, it bundles this data into a beautiful custom graph and sends it straight to your Telegram app. But the best part is the commentary. Netmon feeds your actual bandwidth metrics to an AI model, generating hilariously sarcastic, cynical status updates blaming your local network freeloaders or questionable internet provider for any sudden slowdowns. It is the perfect, highly entertaining way to keep tabs on your home connection.

📰 https://news.ycombinator.com/item?id=49012930

🆔 @hackernewsgithubprojects