PI-Desktop

A local-first desktop app for AI coding agents.

Bring your own models. Keep your code, your keys, and your conversations on your machine.

Download · Getting started · Highlights · How it works · Development · 简体中文

What is PI-Desktop?

PI-Desktop puts an AI coding agent in a native desktop app. Point it at a project, describe what you want — explore and understand code, build a feature, review changes, fix a failing test — and watch it work, with every file edit and shell command surfaced for your approval.

There is no account, no subscription, and no cloud in the middle: you connect the model provider you already use, and everything else — sessions, settings, API keys — stays local.

Highlights

• Any model, your keys. Anthropic, OpenAI, or anything that speaks an OpenAI-compatible API — hosted relays as well as local gateways like Ollama or LM Studio. Model IDs are free-form (no hardcoded allowlist), with per-model context window, output limit, temperature, and thinking-mode controls.
• Agent and Chat modes. Agent mode reads, edits, and runs commands to get things done. Chat mode is strictly read-only — safe for asking questions about an unfamiliar codebase.
• You approve every change. File writes and shell commands ask first, with session-scoped grants and a configurable default policy. Unanswered prompts deny by default.
• A real workbench. Review the agent's edits as diffs, open a terminal, preview in a browser, and browse project files — all in a side panel, without leaving the conversation.
• Projects and sessions. Sessions are grouped by project in a multi-project sidebar, with pinning, archiving, sorting, and throwaway scratch sessions.
• Local-first and private. Transcripts live on disk as plain JSONL with a SQLite index — easy to back up, grep, or delete. API keys go into the OS keychain. Logs stay local; there is no telemetry.
• Extensible with plugins. Install .piplug packages (or load a folder in dev mode) to add commands, panels, agent tools, and skills. Plugins run out-of-process and are default-deny.
• Comfortable to live in. English and 简体中文, light/dark/system themes, command palette, onboarding checklist, and update notifications for packaged builds.

Bring your own provider — any OpenAI-compatible endpoint, keys stored in the OS keychain	Language, theme, default mode, and the permission policy the agent must follow

Download

Grab the latest build from the Releases page.

macOS note: builds are not yet code-signed or notarized. If macOS refuses to open the app, right-click it and choose Open, or clear the quarantine flag:

xattr -cr /Applications/PI-Desktop.app

Packaged builds check GitHub Releases for new versions and show an in-app update banner.

Getting started

1. Add a model provider. Open Settings → Models → Add provider: pick the API style, paste the base URL and your API key, then choose or type a model ID. The key is stored in your OS keychain and never shown again.
2. Open a project. Add a project folder from the sidebar — sessions, tools, and permissions are scoped to it.
3. Describe the task. Start in Agent mode to make changes or Chat mode to explore read-only. Approve edits and commands as they come up, and check the result in the Review diff panel before you commit anything.

How it works

PI-Desktop keeps privileged work out of the UI process:

• Electron shell — a sandboxed React renderer plus a thin main process that only orchestrates.
• Rust host core — owns SQLite, secrets, permissions, and workspace access, over stdio JSON-RPC.
• pi agent sidecar — a Node process running the pi agent engine (pi-ai + pi-agent-core) for the actual agent loop.

The full picture lives in the architecture spec.

Status & roadmap

PI-Desktop is an early preview under active development. Shipped so far: the app shell, streaming chat runtime, workspace agent tools with the permission system, the plugin foundation, and macOS packaging with update checks.

Up next: signed and notarized macOS builds, and the plugin marketplace protocol. See the milestones and the project board.

Development

Prerequisites: Node.js (LTS) with pnpm, and a stable Rust toolchain.

# build the Rust host core
cargo build -p host-core

# install JS dependencies and build packages + app
pnpm install
pnpm -r --if-present build

# run in dev mode
pnpm dev

# protocol e2e smoke test
PI_DESKTOP_TEST_API_KEY=... pnpm test:e2e

CI runs JS build / typecheck / lint / unit tests plus cargo test on every PR. Releases are cut by tag:

node scripts/release.mjs 0.2.0 --tag   # bump versions + commit + tag v0.2.0
git push origin main v0.2.0            # Release workflow builds & publishes

Documentation

• Spec index — start here
• Baseline decisions
• Architecture
• Plugin system
• ADRs · Milestones · Agent guide

License

TBD — a license will be finalized before the first stable release.