Show HN: Hearth, an open-source local AI that runs your PC (files, apps, voice) Hearth, an open-source local AI assistant, launches as a framework that controls a user's Windows PC—opening apps, managing files, driving a browser, and responding via voice—without cloud dependency or telemetry. The project offers a full installer with a bundled GPU model server and a lite edition for existing endpoints, aiming to provide a persistent, private alternative to cloud-locked assistants. The local AI that actually runs your computer. It talks. It listens. It opens your apps, reads and writes your files, drives a real browser you can watch, and remembers you, all on your own machine. No account. No cloud required. No telemetry. The framework is Hearth. The assistant it ships with is named JARVIS, rename it to anything. The resident, and the house. The smartest AI in the world lives in someone else's cloud. It's brilliant, and it can't touch your computer, it forgets you the moment the tab closes, and the meter never stops. So you ran a model locally. Now what? Most "local AI" projects are one of three things: A chat UI around a model LibreChat, Open WebUI, big-AGI . Beautiful, but it's just chat. It can't open your files or do anything on your machine. A coding agent Aider, Cline, Continue, Open Interpreter . Powerful, but scoped to "write code in this folder," not "be the AI on my PC." A cloud-locked assistant ChatGPT, Claude, Gemini . Great, until they change the rules, deprecate your model, or you go offline. Hearth is the fourth thing. A local-first operator that runs on the model you already have, controls your actual Windows PC, files, shell, apps, browser, the desktop itself clicks and types , screenshots, voice, talks back, listens, and remembers you across sessions. Nothing ever leaves your machine except a web search, and only when you ask. And it keeps growing: skills are shareable. A skill is a folder that teaches Hearth a workflow "clean up my Downloads", "turn this folder of photos into a contact sheet" . Installing one someone else wrote is a single line, /skill install someone/their-repo , and writing your own is one command. Reach it however you work: a terminal CLI , a desktop/web app , a headless bridge , or an MCP server . v0.7-preview, the CLI and desktop app are the daily drivers. Voice and the bundled llama.cpp server work but are preview-quality see notes below . Windows is the supported platform; macOS/Linux run from source with most tools working. Where it's headed, grounded computer-use it watches the screen, points, and acts , a guided "walk me through this" mode, and Mac/Linux, is in the Roadmap . Disposable facts get archived, what matters builds a wall of memory | Built-in model manager, no LM Studio needed | Skills, reminders, your workspace | Grab the latest release https://github.com/0pen-sourcer/Hearth/releases/latest , no Python, no git, no setup. Two editions: Hearth Full ~1 GB bundles a GPU model server CUDA llama.cpp . It downloads and runs models for you, so there is nothing else to install. Hearth Lite ~500 MB skips the bundled server, for when you already run LM Studio, Ollama, or another OpenAI-compatible endpoint. Both install to your user folder, no admin needed. Started on Lite and want the built-in server later? Run the Full installer over it, your settings, memory, and chats stay exactly where they are. Needs Python 3.11+ . Windows has a one-line installer: git clone https://github.com/0pen-sourcer/Hearth.git cd Hearth .\install.ps1 bring your own server LM Studio / Ollama / vLLM / llama.cpp / a cloud key .\install.ps1 -BuiltinLLM cuda NVIDIA GPU: Hearth installs + runs its own llama.cpp server .\install.ps1 -BuiltinLLM cpu no GPU: same server, on CPU .\hearth.bat launch The installer is idempotent safe to re-run and has switches to skip optional pieces, voice, STT, MCP SDK, file readers, desktop window, browser control. Run Get-Help .\install.ps1 -Detailed for the full list. On macOS and Linux you clone and run with Python pip install -r requirements.txt , then python hearth cli.py , steps in the macOS / Linux section below. On first launch, a short onboarding flow asks which model brain to use, lets you pick a voice and rename the assistant to anything you want, and sets its tone. If you installed Full or ran install.ps1 -BuiltinLLM , Hearth has its own bundled llama.cpp server, open the Models tab, pick a model, and it downloads and runs it for you, no other app needed. Otherwise Hearth auto-detects a running LM Studio port 1234 , Ollama 11434 , or llama.cpp server 8080 at boot, no configuration needed. To use something else, set LOCAL API BASE to any OpenAI-compatible endpoint. A cloud key is optional. In the desktop app's Settings or via env vars , you can point the chat brain at Gemini, OpenAI, Grok, or OpenRouter and switch back to local at any time without restarting. Files, voice, and memory stay local regardless; only the prompt goes to the provider you choose. Any ~7B-or-larger model with OpenAI-style tool-calling works. On ~8GB VRAM, tool adherence is best on recent tool-trained models. Small local models handle everyday tasks well open this, read that, remember this but can fumble long multi-step chains; a built-in loop guard catches and breaks those spirals. For heavier reasoning deep web research, multi-page browser sessions a larger or cloud model helps. Hearth ships a tool-call parser that recognizes the formats emitted by Gemma, Hermes, Qwen 2.5/3, Llama 3.x, Mistral, Phi, Granite, and Cohere Command-R, plus a generic