AI agent toolkit: unified LLM API, agent loop, TUI, coding agent CLI
在 DeepSeek Harness 终端运行:
dsh plugin --profile web add earendil-works/piNew issues and PRs from new contributors are auto-closed by default. Maintainers review auto-closed issues daily. See CONTRIBUTING.md.
Pi is a minimal, extensible agent harness that you can make your own.
Adapt Pi to your workflows, not the other way around. Customize Pi with extensions, skills, prompt templates, and themes. Bundle them as Pi packages and share via npm or git.
Pi ships with powerful defaults but skips features like sub-agents and plan mode. Ask Pi to build what you want, or install a package that does it your way.
Use Pi interactively, automate it in print or JSON mode, control it over RPC, or build apps with the Pi TypeScript SDK. See OpenClaw for a real-world integration.
Install the command-line interface:
curl -fsSL https://pi.dev/install.sh | sh
On Windows:
powershell -c "irm https://pi.dev/install.ps1 | iex"
The installer pins all dependencies and updates Pi with pi update. Alternatively, install directly with npm, which does not pin transitive dependencies:
npm install -g --ignore-scripts @earendil-works/pi-coding-agent
Pi requires Node.js 22.19 or newer. The macOS, Linux, and Windows installers can install it if needed. Pi does not require dependency lifecycle scripts for a normal npm installation.
Start Pi in the directory where you want it to work:
cd /path/to/project
pi
For a built-in AI provider, run /login inside Pi to connect a subscription or API key. Then give Pi a task.
See the documentation for full setup and usage instructions, or visit pi.dev for demos.
nix run github:earendil-works/pi/stable
stable points at the latest release. Install it with nix profile add github:earendil-works/pi/stable and update with nix profile upgrade pi. Use a release tag such as github:earendil-works/pi/v1.0.0 to pin a version, or github:earendil-works/pi for unreleased changes on main. Nix builds Pi from source.
Supports ARM64 and x86-64 on Linux and macOS. Use nix build . or nix run . to build or run your checkout.
Nix builds are offline, so the bundled model data comes from a pi.dev model catalog revision pinned in nix/model-catalog.json. At runtime, Pi still overlays newer catalog data from pi.dev as usual. The Nix workflow replaces the pin on main when it no longer matches the checkout, for example after a provider is added or gains a new model type. To refresh it by hand:
npm run update:model-catalog-pin
This monorepo contains the Pi CLI and its supporting libraries.
| Package | Description |
|---|---|
| @earendil-works/chord | Standalone application-composition runtime for services, replicated state, RPC, and plugins |
| @earendil-works/pi-telemetry | Vendor-neutral telemetry contracts, reference adapter, conformance tests, and typed schemas |
| @earendil-works/pi-ai | Unified multi-provider LLM API (OpenAI, Anthropic, Google, etc.) |
| @earendil-works/pi-durable | Durable conversation, task, and document runtime |
| @earendil-works/pi-agent-core | Agent runtime with tool calling and state management |
| @earendil-works/pi-coding-agent | Interactive coding agent CLI |
| @earendil-works/pi-tui | Terminal UI library with differential rendering |
For Slack/chat automation and workflows see earendil-works/pi-chat.
Pi does not include a built-in permission system for restricting filesystem, process, network, or credential access. By default, it runs with the permissions of the user and process that launched it.
If you need stronger boundaries, containerize or sandbox Pi. See packages/coding-agent/docs/containerization.md for three patterns:
pi and provider auth on the host while routing built-in tools and ! commands into a local Linux micro-VM.pi process in a local container for simple isolation.pi process in a policy-controlled sandbox.See CONTRIBUTING.md for contribution guidelines and AGENTS.md for project-specific rules (for both humans and agents). Longer term plans for Pi can also be found in RFCs.
npm install --ignore-scripts # Install all dependencies without running lifecycle scripts
npm run build # Refresh model data, then build all packages
npm run build:offline # Rebuild using existing model data without network access
npm run check # Lint, format, and type check
./test.sh # Run tests (skips LLM-dependent tests without API keys)
./pi-test.sh # Run pi from sources (can be run from any directory)
Build every public package into one coherent local artifact set:
npm run pack:packages -- --out .artifacts/pi-packages
This refreshes model data before building pi-ai. To avoid network access when
model data is already hydrated, pass --offline-model-data.
Then configure an external project to consume one package and resolve all of
its Pi dependencies from the same artifact set. npm is the default:
node scripts/use-local-packages.mjs \
--manifest .artifacts/pi-packages/manifest.json \
--consumer ../my-project \
--package @earendil-works/pi-durable \
--package @earendil-works/pi-agent-core
cd ../my-project
npm install --ignore-scripts
For a pnpm project, point --consumer at the workspace root:
node scripts/use-local-packages.mjs \
--manifest .artifacts/pi-packages/manifest.json \
--consumer ../my-project \
--package @earendil-works/pi-agent-core \
--package-manager pnpm
cd ../my-project
pnpm install --ignore-scripts
Repeat --package for each direct dependency. The command updates the
consumer's package.json with content-addressed local file: references. It
writes transitive overrides to package.json for npm or pnpm-workspace.yaml
for pnpm. Keep the artifact directory available while installing or updating
the consumer. Re-run both commands after changing Pi source.
GitHub releases include a versioned source archive covered by the release's SHA256SUMS file. Extract it and run the same build script used for the official standalone binaries:
VERSION="<release-version>"
tar -xzf "pi-${VERSION}-source.tar.gz"
cd "pi-${VERSION}"
./scripts/build-binaries.sh --offline-model-data --platform linux-x64 --out "$PWD/out"
The archive includes release model data and native prebuilds. --offline-model-data uses that model data without refreshing provider catalogs. The script installs dependencies and builds the executable with its runtime assets; pass --skip-install if dependencies are already provided.
We treat npm dependency changes as reviewed code changes.
.npmrc sets save-exact=true and min-release-age=2 to avoid same-day dependency releases during npm resolution.package-lock.json is the dependency ground truth. Pre-commit blocks accidental lockfile commits unless PI_ALLOW_LOCKFILE_CHANGE=1 is set.npm run check verifies pinned direct deps, native TypeScript import compatibility, and the generated coding-agent install lock.packages/coding-agent/install-lock/, generated from the root lockfile, to pin transitive deps. The npm package does not pin transitive deps.pi update --self use --ignore-scripts where supported.npm ci --ignore-scripts, and a scheduled GitHub workflow runs npm audit --omit=dev plus npm audit signatures --omit=dev.If you use Pi or other coding agents for open source work, please share your sessions.
Public OSS session data helps improve coding agents with real-world tasks, tool use, failures, and fixes instead of toy benchmarks.
For the full explanation, see this post on X.
To publish sessions, use badlogic/pi-share-hf. Read its README.md for setup instructions. All you need is a Hugging Face account, the Hugging Face CLI, and pi-share-hf.
You can also watch this video, where I show how I publish my pi-mono sessions.
I regularly publish my own pi-mono work sessions here:
MIT
登录后即可为该插件评分和评价。
还没有人评价这个插件,来抢个沙发吧!