Samantha

Meet Samantha.

A small AI that lives on your Mac. Free, private, and it runs itself through everything she can do while you watch.

Download for Mac
Samantha's Mac Vol 50
0 squares,

What she can do

Say it, type it, or watch the demo above run through all of it. Anything that writes, sends or deletes asks first.

Draw and paint

  • paint the mona lisaRebuilt from 30,000 squares.
  • draw a lighthouse at duskAn image model imagines it, she rebuilds it.
  • make me a logo for a surf schoolAn icon, never text.
  • paint cat.png as a mosaicSix styles: mosaic, dots, poster, sketch, glass, squares.

Run your Mac

  • open chrome and go to wikipedia.orgOpens it and goes there.
  • set the volume to 40Done.
  • play some musicPlays, pauses, skips.
  • take a screenshotSaved to your Desktop.
  • how much battery do i haveReads it off the Mac.
  • turn on dark modeFlips it.
  • make a shortcut that says good morningShows the steps, then the Shortcuts app asks you to add it. She never runs it for you.

Notes, reminders, calendar, mail

  • write a note to buy milkInto Notes.
  • remind me to call mom tomorrow at 9A real reminder, with the time.
  • what's on my calendar todayReads it out.
  • add dentist to my calendar tomorrow at 3Adds it.
  • email mom saying I'll be lateShows you the words first and sends only on a yes.

Files and documents

  • show me the files in ~/DocumentsLists them.
  • find budget.pdfSearches your Mac.
  • summarize ~/Desktop/report.pdfThree to five real sentences.
  • what's the deadline in proposal.pdfAnswers from the file.
  • transcribe the video ~/Desktop/clip.mp4Pulls the words out of any video or audio.

Words and numbers

  • translate good morning to frenchOffline.
  • define serendipityPlain meaning.
  • what is 17*23391.
  • convert 72 f to c22.2 C.
  • tip on a 42 dollar billThe tip and the total.
  • days until christmasCounts them.

Write code

  • write a python function that reverses a stringThe biggest model on your Mac writes it. It lands as a code box with a Copy button, in the app, on the phone and here.
  • write a Swift function that checks whether a string is a palindromeC, Rust, Swift, Go, JavaScript, bash: each one tested.
  • stats on sales.csvWrites a short script and runs it in a sandbox. Asks first.

Research and learning

  • research the history of the printing pressA short brief with a source after every sentence.
  • explain the nimble codebaseWalks you through a project.
  • teach me about tidesA short lesson and two quiz questions.
  • ask qwen what is a loraHands the hard ones to a bigger model on your Mac.

Her eyes and hands

  • what's on my screenReads it with the system's own text recognition.
  • what's in ~/Desktop/cat.pngA vision model looks and answers.
  • click Sign inShows each step and asks before it happens.
  • work on cleaning up my downloadsPlans in rounds and tells you what she couldn't do.
Every tool, and how she plugs in

Her Mac. Open apps and sites, search, read the current tab, screenshots, the clipboard, volume, battery, music, notes, reminders with a time ("remind me tomorrow at 9am to call mom"), the calendar, unread mail, timers, the weather, files: find one by name, what you just downloaded, how big a folder is, then move, copy, rename, zip, unzip or trash it, asking first.

Pictures. Draw anything you can name (an image model imagines it, she rebuilds it from squares), paint any photo out of squares or in a style ("paint the mona lisa as a mosaic": mosaic, dots, poster, sketch, stained glass), make a logo (the icon on this page is one she designed), remove a background, upscale, enhance, grayscale, rotate, flip, resize, crop, convert.

Math. Calculate, convert units, tips, primes and factors, roman numerals.

Documents. On a Mac she reads PDFs, Word files and plain text in your home folder, finds the passages that mention what you ask about, and answers questions about them, or about your screen, from the text alone: a number or name that is not in the text is declined. Nothing hidden, nothing outside home.

Video and audio. Say "transcribe the video ~/Desktop/clip.mp4" and she pulls the words out of any video or audio file in your home folder with the same Whisper pipeline her voice mode uses.

Real summaries. "Summarize ~/Desktop/report.pdf", "summarize this page" or "summarize my unread mail" hands the text to the biggest local model for three to five real sentences, not the one-line answer a lookup gives. Anything short enough to just read is read back instead.

Translates, offline. "Translate good morning to French", "how do you say thank you in Japanese", or "translate the page github.com into Spanish": the same local model does it.

Research. On a Mac, say "research the history of the printing press". She reads several sources, and a bigger model on the same Mac writes a short brief with a source after every sentence. A sentence she cannot back up is cut.

Eyes. On a Mac, say "look at my screen and tell me what's wrong with this chart" or "what's in ~/Desktop/cat.png". A small vision model on the Mac looks and answers. It asks first.

Hands on your screen. On a Mac, say "click Sign in", "type hello" or "press return". She reads the screen to find the words you named and clicks them, and she shows you each step and asks before it happens. Press Escape any time and she stops.

Camera. On a Mac, say "what am I holding" or "read this label". One frame from the Mac's own camera goes to the same vision model, and the frame is deleted right after the answer. It asks first.

Run code. On a Mac, say "stats on sales.csv" or "chart sales.csv". The biggest local model writes a short Python script from your request and the file's header, and it only runs in a sandbox: a fresh folder holding a copy of that one file, no network, a time and memory cap. A chart comes back as a real PNG. It asks first.

Long work. On a Mac, say "work on cleaning up my downloads". She plans in rounds: when a step fails she plans around it, still does the parts that can be done, and tells you at the end what she could not. Each new plan comes from your words and her own record, never from what she read. Every write still asks.

Asks which. Say "trash this file" or "crop that image" without naming it and she asks which one, instead of guessing or saying no.

What needs you. On a Mac, say "what needs my attention" for one ranked answer built from your unread mail, today's calendar and due reminders, or "am I free Thursday afternoon" for your calendar's open gaps that day or across the week. Both read only, and both say plainly when there is nothing. Say "good morning" for the same with the date on top, and the Mac app brings it to you by itself the first time it opens each morning.

Talk to her. On a Mac, python3 app/chat.py --voice and just speak. Whisper turns your voice into text on the Mac itself, she answers, and she says it out loud. Add an ElevenLabs key and she speaks in a real voice. Add --face and a window shows her face, idle while you talk and talking while she answers. Set it up. Anything that writes still asks first.

Cut her off. With voice on, anything new you send stops her mid-sentence, and "shh" or "stop" just silences her. In the Mac app your chat is saved after every answer and comes back when you reopen it; Cmd-N files it away and starts a clean one. Nothing leaves the Mac.

Joshua Tree. On a Mac, "Joshua Tree status" reports the OS's version, open pull requests and whether its test machine is running. "Boot Joshua Tree" starts it headless in qemu and "stop Joshua Tree" shuts that one process down; both ask first. "What did Joshua Tree say" reads the last lines of its serial log, and "type ls into Joshua Tree and press enter" sends it real keystrokes, asking first. On a Raspberry Pi she is an app on Joshua Tree itself: ask her to write hello world in C and save it as hello.c, and the code lands on the Pi's SD card. "Screenshot Joshua Tree" saves its screen to a file her eyes can read, and "what is Joshua Tree showing" does both in one go, asking first.

Her own library. On a Mac she keeps the lead of every one of Wikipedia's ~10,000 vital articles, anthropology to astronomy, plus a plain-words fieldbook of every science. When the web has nothing or is down she answers "what is" and "who was" questions from the page of that name, says which page, and declines the rest instead of guessing.

Ask any LLM, still local. Say "ask qwen", "ask llama" or "ask gemma" and a question too hard for her goes to that model on your Mac, found through oMLX or Ollama. Say "ask claude" or "ask gpt" and she uses the biggest one there. If you name one you do not have, she lists what you do. It asks first, needs no account or key, and the answer names the model that gave it.

Screen. On a Mac she reads what is on your screen with the system's own text recognition. It asks first.

Memory. Tell her "remember that my dog is called Biscuit" and she still knows next visit: on this page it lives in your own browser, on your Mac in a file only she reads. Recalling and forgetting are by name only, and remembering asks first. On your Mac, from 4.19, she also reads what she remembers back into her answers when it bears on the question: ask about your dog and she uses what you told her. If you ask, she keeps that file in your own iCloud Drive ("keep my memory in iCloud"), so your other devices can carry it; the phone app keeps its own copy and reads it back too.

Explain and teach. On a Mac, "explain the nimble codebase" walks you through a project from its README and folders, and "teach me about tides" gives a short lesson and two quiz questions. Neither changes anything.

Email. On a Mac, "email mom saying I'll be late" finds her in Contacts, shows you the address and the words, and sends only after you say yes.

Chrome. List your tabs, switch to one, read it as it is rendered (so pages built by JavaScript work), and close one, which asks first.

Time. The time in any big city, today's date, days until a date or a holiday.

Chance. Coin, dice, random numbers, passwords, UUIDs.

Text. SHA-256, base64, word count, reverse, capitals, morse, tidy JSON.

Shortcuts. List your Apple Shortcuts and run any one by name, so every automation you already built is one of her tools. She only runs one when you name it, never on her own.

Promises she keeps. Seven rules live in LAWS.md and are checked against every tool on every push: anything that writes or sends asks first, the tools with hidden side effects never reach a model, her hands stay in the home folder, every function is documented, and this page says the same words the Mac does.

Plugs into other assistants. She speaks MCP, the standard plug for AI tools, both ways: Claude Code or any other assistant can use her tools, and she can call theirs, asking first. A harness keeps the conversation, prints every tool call before it runs, and asks first before anything that writes or sends.

This Mac's vitals. Disk space, uptime, memory, processor load, IP address, Wi-Fi, system info, copy to clipboard, sleep the screen, show a file in Finder. These answer on a real Mac. The stand-in above has no disk to read, and says so.

Watch her work

Results

Loading results...
How she trained: the loss curve
Base: , Iterations: , Latest train loss: ,

Round six of the picker, the one she runs today. The line is training loss, the dots are validation loss. Lower is better. The first validation point, logged before training started, is left off so the real curve is readable.

About

How she was made

Samantha is a LoRA fine-tune of a small open base model, trained on the project's own Obsidian wiki and READMEs so it actually knows the codebase and writes in house voice. No from-scratch pretraining, that path was tried once (project code name Arthur) and produced gibberish. This time: small model, real data, short loop, iterate.

Where this is going

A small model on your own Mac cannot out-think a frontier model, and it does not try. It wins by staying private, free per question, and honest: it looks things up instead of guessing, and it asks before it acts. Next: whole jobs done end to end, not just single steps, still asking first at every one. See roadmap.md for the live plan.

Run it yourself

git clone https://github.com/nulljosh/turing
cd turing
python3 -m venv .venv && ./.venv/bin/pip install mlx-lm
./.venv/bin/python app/chat.py
# Linux
curl -fsSL https://raw.githubusercontent.com/nulljosh/turing/main/install/install.sh | sh

# Windows (PowerShell)
irm https://raw.githubusercontent.com/nulljosh/turing/main/install/install.ps1 | iex

Mac: the app, everything she can do. iPhone: her own app, in the repo under ios/: her exact tools and her models run on the phone, the Mac is optional and lends its bigger model and its hands. Build it with xcodegen today. The App Store version is on its way, $1. Windows, Linux and phones: press Install app (Chrome or Edge) for the portable half of her, offline: math, time, conversions, text, memory. Or run the one-line install above for her chat and tool picker (the GGUF is on Hugging Face). The parts that drive your screen and apps stay on the Mac. Joshua Tree: she ships as an app on Joshua Tree, an operating system built from scratch, with chat, voice and her face, and her model answers from the Mac.

Latest: - Release notes Her weights on Hugging Face

Questions

Is it really private?

Yes. She runs on your Mac. Your words, files and screen never go to a server. The demo on this page is a stand-in on Cloudflare, so type nothing you would not post.

What does it cost?

Nothing. No account, no key, no subscription, and no per-question fee. It runs on the chip you already paid for.

What do I need to run her?

A Mac with Apple silicon and a few gigabytes free. Download the app, open it once, and she sets herself up.

Can she break my stuff?

Not without asking. Anything that writes, sends or deletes asks first, and her hands stay in your home folder. Seven rules, checked on every push, keep it that way. Read them.

Is she as smart as ChatGPT or Claude?

No, and she does not pretend to be. She is small. She wins by being private, free per question, and honest: she looks things up and says "I don't know" instead of guessing. For a hard question she can hand it to a bigger model on your own Mac.

Does the demo here do everything?

It does the things a web page can: paint, draw, math, time, the stand-in Mac. Talking out loud, seeing your screen, researching and working your real apps need the Mac app.

Where is the source?

All of it is on GitHub, open and free to read.

Samantha