Mario Zechner 827fe1e2c4 feat(ai): ImagesModels collections mirroring the chat-side design
createImagesModels()/ImagesProvider/createImagesProvider() give image
generation the same shape as chat: sync model reads, explicit async
refresh(provider?) with in-flight dedupe, provider-resolved auth, and
never-rejecting generateImages() (failures return AssistantImages with
stopReason error). Auth resolution is shared with the chat side via the
free-standing resolveProviderAuth() in auth/resolve.ts, which also owns
ModelsError; both collections pass their store/context as arguments.

The OpenRouter implementation moves to api/openrouter-images.ts with a
lazy wrapper; openrouterImagesProvider() factory plus
builtinImagesProviders()/builtinImagesModels() land in providers/all.
The ImagesProvider id type alias is renamed to ImagesProviderId
(mirror of Provider -> ProviderId). The old global image API
(getImageModel*, generateImages, registerImagesApiProvider) stays on
/compat, its registration shim repointed at the moved implementation.

README: Quick Start uses builtinModels(), the full streaming event
switch, image generation and the development checklist are restored in
full, image generation documents the new collections with compat noted
for the old API, plus the review fixes (builtinModels options,
credential-store mention for browsers, ImagesModels notes).
827fe1e2c4 · 2026-06-11 00:27:43 +02:00
4,519 Commits
2026-05-20 15:57:41 +02:00
2026-05-05 17:10:35 +02:00
2026-05-20 15:57:41 +02:00
2026-06-03 23:15:15 -05:00
2026-05-18 00:55:01 +02:00
2026-05-20 15:55:31 +02:00

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Pi Agent Harness Mono Repo

This is the home of the pi agent harness project including our self extensible coding agent.

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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:

All Packages

Package Description
@earendil-works/pi-ai Unified multi-provider LLM API (OpenAI, Anthropic, Google, etc.)
@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.

Permissions & Containerization

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:

  • OpenShell: run the whole pi process in a policy-controlled sandbox.
  • Gondolin extension: keep pi and provider auth on the host while routing built-in tools and ! commands into a local Linux micro-VM.
  • Plain Docker: run the whole pi process in a local container for simple isolation.

Contributing

See CONTRIBUTING.md for contribution guidelines and AGENTS.md for project-specific rules (for both humans and agents).

Development

npm install --ignore-scripts  # Install all dependencies without running lifecycle scripts
npm run build        # Build all packages
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)

Supply-chain hardening

We treat npm dependency changes as reviewed code changes.

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License

MIT

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