Hearth gives the model you already run a body, and meets you everywhere: a terminal, a desktop app, your phone, MCP server, or a scriptable headless bridge. It runs your files, shell, apps, a real browser, and the desktop itself.
desktop_snapshot reads a window's real controls as a list, then desktop_click and desktop_type act on them by name. You watch the cursor move.
Ask for a frontend, a backend and an architect — Hearth spawns each as a sub-agent in its own live terminal pane. You watch them work side by side.
Around 100 tools exist, but the model never sees them all. A core set loads by default; the rest sit behind a load_tools call it makes on demand. The prompt stays small.
HEARTH_ALL_TOOLS=1 loads everything up front, if you want.Search Hugging Face and pull a GGUF without leaving the app, or let Hearth auto-detect a running LM Studio, Ollama or llama.cpp. Then tune each model once — GPU layers, context, KV-cache quant — and it remembers. Switch brains without a restart; files, voice and memory stay local either way.
Ask in plain English. Hearth generates on your own GPU through Forge, or routes to a cloud model — and the picture develops right there in the chat.
From opening a file to driving a browser to writing itself a new tool when it hits a gap.
soul.md identity that persistscreate_plugin: writes its own toolsPer-fact notes that persist across sessions. The most relevant fold into context automatically; cold facts archive and warm back when recalled.
Leave continuous listen on and just talk, or set a wake word — your assistant's name, so it changes when you rename it — to open the overlay even when Hearth isn't focused. Speech streams out; barge-in cuts it off mid-sentence.
A skill is a folder that teaches a workflow. Install one someone else wrote with a single line, publish yours by pushing to GitHub.
A skill is just a folder that teaches a workflow. Publish yours by pushing to GitHub, install anyone else's with a single line. The library grows as people ship more.
No account, no telemetry, no analytics, no server the author runs. Your files, prompts and memory stay on your machine. The only things that ever leave are ones you turn on.
JARVIS_LOCKDOWN=1 confines reads too.Windows 10/11. One installer, no admin needed, nothing to configure. Prefer source? The tabs below cover it.
# clone and enter git clone https://github.com/0pen-sourcer/hearth.git cd hearth # bring your own server (LM Studio / Ollama / vLLM / llama.cpp / a cloud key) .\install.ps1 # launch .\hearth.bat
# Hearth installs and runs its own llama.cpp server on your GPU .\install.ps1 -BuiltinLLM cuda .\hearth.bat
# same bundled server, no GPU required .\install.ps1 -BuiltinLLM cpu .\hearth.bat
# CLI, web UI and most POSIX tools work. See docs/INSTALL_LINUX_MAC.md
git clone https://github.com/0pen-sourcer/hearth.git
cd hearth
pip install -r requirements.txt
python hearth_cli.py
Hearth collects nothing — no account, no telemetry, no server the author runs. The only things that ever leave are ones you turn on: web search / fetch (DuckDuckGo), a cloud model if you pick one, or ntfy / Telegram. All off by default.
Yes, to anything. It ships as JARVIS, but /name ATHENA (or Friday, Cortana, whatever you like) renames the avatar, persona and workspace folder. The framework is Hearth; the character is yours — personas, voices and models are all swappable.
No. Anything OpenAI-compatible works — Ollama, vLLM, llama.cpp, LocalAI — or the bundled llama.cpp server via -BuiltinLLM.
Writes are confined to the workspace by default, and risky tools prompt for permission the first time per session. JARVIS_AUTO_APPROVE=1 removes the prompts; JARVIS_LOCKDOWN=1 confines reads too.
Yes, except web search / fetch. Run against a local model with nothing else configured and Hearth is fully offline.
Any ~7B-or-larger model with OpenAI-style tool-calling. On ~8GB VRAM, recent tool-trained models do best. A built-in loop guard catches and breaks runaway multi-step spirals on smaller models.
Free, MIT-licensed, built by one developer. Runs on your machine, collects nothing, and grows with the community.
If it's useful, a ⭐ is the biggest help — it's how other people find the project.