v1.0.0 — First stable release, now on PyPI

eeANE 1.0.0 is the first stable release. eeANE is now published on PyPI, the documentation has been rewritten around it, and a launchd guide covers running the server as a proper macOS service. There are no functional changes to the server or the compiler since 0.10.0 — an existing setup keeps working as is.

Install from PyPI

uv tool install "eeane[compile]"

is now the whole install story: no git URL, no tag to pin. pipx and plain pip + venv work the same way (pipx install --python python3.12 "eeane[compile]"), the server-only lightweight variant remains, and installing from the GitHub repository is still documented for development snapshots and pinned revisions. If you installed 0.10.0 from a git URL, reinstall from PyPI once (uv tool install --force "eeane[compile]") and future upgrades are just uv tool upgrade eeane. From this release on, every tagged release is published to PyPI automatically by CI via trusted publishing.

Run eeANE as a service

docs/launchd.md is a step-by-step guide to running eeane serve as a macOS user LaunchAgent — start at login, restart on crash — with a ready-made plist template in the same directory. The whole flow (bootstrap, health check, on-demand model load, restart, boot out) is verified on real hardware. On-demand loading makes an always-on agent nearly free while idle.

Documentation overhaul

Both READMEs (English and Japanese) were rewritten for 1.0: a highlights section, PyPI-first installation, a quick start, a performance section with measurement conditions stated, troubleshooting, known limitations, and a compact changelog table that links here instead of narrating every version. The known-limitations section now says explicitly what is and is not verified: all published measurements come from an M2 Mac, other Apple Silicon generations are expected to work but unverified — the self-check summary that eeane compile prints doubles as a compatibility report, and reports from other machines are very welcome as issues.

Acknowledgments

eeANE exists because Infinity showed how convenient a self-hosted, API-compatible embedding and reranking server can be, and eeANE's /rerank API deliberately follows Infinity's schema. The two projects complement each other: eeANE is Apple-Neural-Engine-only by design — for serving on Linux, Windows, NVIDIA/AMD GPUs or CPUs, or for a much wider model catalogue, use Infinity.

Requires Python 3.11 or 3.12 (uv resolves one automatically; pipx and pip + venv need you to provide it), an Apple Silicon Mac on macOS 13+, and Xcode Command Line Tools for compiling models.

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