MyPaiOS runs entirely on your machine. Chat, research, write code, analyse video, triage email, generate images — powered by any of 35+ open-source models. No subscription. No data leaving. No lock-in.
Scroll to see each real-world workflow in action — most run themselves as you scroll.
Every Ollama-compatible model works in MyPaiOS. Filter by what you need — then pull and go.
Any Ollama-compatible model works — including custom GGUF files, Hugging Face imports, or any OpenAI-compatible API endpoint.
Fan the same prompt out to two, three, or four local models and watch them stream side-by-side. Vote for the answer you'd actually use. Over time that becomes a leaderboard built from your tasks — not someone else's benchmark suite.
Every model streams at once. You see who is fast, who is thorough, and who rambles — on the exact task in front of you.
When the answers land, pick the one you'd ship. One click. No scoring rubric, no eval harness to configure.
Picks add up per model. After a week the arena tells you which model earns your default slot — with receipts.
Chat is just the front door. Research, code, video, email, images, voice — all of it runs on your hardware, against your models.
Multi-round web search with a local reasoning loop. Pi plans the queries, reads what it finds, and writes the report itself.
An agent that works in your codebase, not a snippet generator.
Keyframes plus a Whisper transcript. Chat with any video by timestamp.
IMAP triage with local spam and threat scoring.
Image generation plus a full layer-based editor.
Kokoro TTS, Whisper STT. Spoken conversation, fully local.
Everything you write, indexed for RAG search.
Pi learns your context. Teach it new skills.
AES-GCM storage for keys, tokens, and secrets.
Same prompt, multiple models, side by side.
Also in the box: Calendar & Contacts with CalDAV sync, a Prompt Cookbook, an MCP client for external tools, and multi-agent Crews.
A realistic Tuesday with Pi — triage, research, a background refactor, a meeting recording, a model bake-off, and a ping from your phone. Every token generated on your own hardware.
MailGuard worked through 41 overnight emails and flagged the 2 that actually mattered. The rest never reached your attention.
MailGuard“Battery chemistries for home storage.” Four rounds of Deep Research, 23 sources, one cited report waiting by the time the coffee is gone.
Deep ResearchThe Coding Agent reworked a FastAPI service as a detached job while you sat in a meeting. The job kept running after you closed the tab.
Coding AgentDropped in a meeting recording. Minutes later: a full transcript with timestamps, ready to search and question.
Video AnalysisSame refactor prompt, three models, side by side in the Compare arena. You picked the winner on the evidence.
Compare ArenaAsked Pi to summarise the day over the Telegram gateway. Your laptop composed the answer. Nothing ever left it.
Telegram GatewayMyPaiOS ships a hardware-fit scorer. It reads your GPU, RAM and CPU, then rates all 35+ models from 0 to 100 for the box you actually own — so you never pull a model that will not fit.
On first run, Pi reads your GPU, unified or system RAM, and CPU core count. Locally, like everything else.
Every model in the catalog gets a fit score from 0 to 100 — for your machine, not a spec-sheet average.
Download what scores well. Skip what doesn't. No wasted disk, no model that loads once and swaps forever.
Works on any Mac, Linux, or Windows box. No dedicated GPU? CPU-only machines run the small models fine — the scorer points you straight to them.
Ollama manages local LLMs on Mac, Linux, and Windows. Pull any model you want — or all of them.
One script creates the virtual environment, installs dependencies, and starts the server.
Navigate to localhost:7860. Switch models from the picker. Your data never leaves this machine — even offline.
Once models are pulled, MyPaiOS needs zero internet. Airplane mode AI — no calls home, ever.
Conversations, notes, memory, embeddings — SQLite + ChromaDB on your disk. Nothing synced.
No sign-up. No telemetry. Admin panel is local-only, protected by a key you set.
Every line is on GitHub, MIT-licensed, with all third-party notices carried. Read it, fork it, modify it — no black boxes.
Everything runs on your machine — and still talks to the outside world over standard protocols. Six doors, all of them yours to open or close.
Connect any Model Context Protocol server and Pi picks up its tools. OAuth flows handled.
MCP · stdio/SSE/HTTP
Point at any server: llama.cpp, vLLM, LM Studio. Or a cloud key — only if you choose.
API · /v1 compatible
Push events to anything with a URL. Your other systems find out the moment Pi does.
HTTP · outbound POST
Chat with Pi from your phone. Same assistant, smaller screen.
Telegram · bot API
Calendar sync over the open standard. Works with the calendar you already have.
CalDAV · RFC 4791
Put MyPaiOS in your dock or on your home screen. Feels native, stays local.
PWA · installable
The connections are yours: keys live in an AES-GCM vault on YOUR disk.
Every feature is documented inside MyPaiOS — reachable from the /help panel. Exportable to PDF. Here's a live preview.
We turned MyPaiOS's own codebase into a queryable knowledge graph — every file, every cross-reference, traced locally with tree-sitter AST parsing. No LLM calls, no vector store, nothing left the machine. Explore it yourself below.
Graphs built locally, zero API cost: domain & file maps with Graphify (tree-sitter AST, Apache-2.0) — 15,471 symbols · 34,652 relationships · 817 communities; the call graph with CodeGraph (Rust kernel, MIT) — 21,652 symbols · 84,716 edges, dynamic dispatch resolved.
No borrowed quotes, no vanity graphs. These numbers come from the repository itself — clone it and count them yourself.
The Architecture section below is generated from the repo's own AST graph — 15,471 nodes parsed straight from source. The code describes the code.
parse source → build graph → render pageNot just a claim — every one of those 108 features is cited against the exact file and line that implements it →
Traffic, stars, and forks — refreshed automatically every day by this workflow →
The version number is an ordinary build tag — major.minor.patch.build, incremented commit by commit like any other piece of software. It wasn't chosen for what follows. But read as four numbers instead of one version string, each segment happens to land on a figure Hindu tradition has returned to for centuries, and that felt worth a moment's honesty rather than a marketing footnote.
"Ekam Sat Vipra Bahudha Vadanti" — "Truth is one; the wise call it by many names" (Rig Veda 1.164.46). The Vedas' oldest articulation of unity within apparent multiplicity, later given its fullest philosophical form in the Upanishads' teaching that Brahman is "one, without a second" (Chandogya Upanishad 6.2.1).
The 13th day of every lunar fortnight — twice each month — is held sacred to Shiva. Pradosh Vrat is observed at pradosh kaal, the twilight window tradition holds to be his most benevolent hour.
51 is the most widely cited count of the Shakti Peethas — sites across the subcontinent where, in the Daksha Yajna legend, parts of the goddess Sati's body are said to have fallen. Other Puranas name 7, 18, 42, 64, or 108 instead; devotion, like scripture, rarely settles on one number.
108 beads on a japa mala. 108 Upanishads in the Muktika Upanishad's own canonical list. A deity's Ashtottara Shatanamavali — literally "108 names." 108 Divya Desams of Vaishnavism. 108 karanas of classical dance, linked to Shiva's cosmic dance. No single reason is agreed on for why — that plurality is itself part of the tradition.
None of this was engineered — it was noticed after the fact, the same week this project's dedication to Swarajya was written below. Some numbers, it turns out, were already carrying weight before anyone thought to look.
The things people want to know before they run the install script. Short answers, no fine print.
data/ folder on your disk. You can copy it, back it up, or delete it. It never leaves your machine.launchd background service. Linux and Windows run fine via Python.data/ folder. That is the whole migration.MIT License. Fork it, self-host it, run it on your Mac, Linux box, or homelab. No telemetry, no premium tier, no rug-pull.
Commercial use, forks, modifications — no strings.
Runs anywhere Python and Ollama run.
Free website, free HTTPS, zero domain cost.
Starts at login on macOS — always there when you need it.
Stars are how open source travels. They are the only currency this project asks for — no account, no invoice, nothing tracked. One click, if it earned it.
Something broke on your machine? File it with your OS and the model you ran. Clear reproductions get fixed first.
Open an issue →Discussions is where the roadmap starts. Pitch an idea, or add weight to one somebody already argued for.
Start a discussion →MIT-licensed, notices and all. The Architecture section above maps all 1,041 files — pick a folder and start reading.
Browse the source →