Unofficial PyPI distribution of llmfit – the LLM model management CLI
Project description
llmfit via PyPI
Unofficial PyPI distribution of llmfit — the LLM model management CLI.
This package downloads pre-built binaries from the upstream GitHub releases and
repackages them as Python wheels so you can install llmfit with pip or uv
without a Rust toolchain.
Installation
pip install llmfit
# or
uv add llmfit
After installation the llmfit command is available on your PATH.
llmfit --help
You can also use this package to install and update llmfit via uv tool:
uv tool install -U llmfit
Supported platforms
See Rust platform support for more information. Refer to the the upstream llmfit project for authoritative requirements.
| Platform | Architecture | Requirements |
|---|---|---|
| Linux (glibc) | x86_64 | kernel ≥ 3.2, glibc ≥ 2.17 |
| Linux (glibc) | aarch64 | kernel ≥ 4.1, glibc ≥ 2.17 |
| Linux (musl) | x86_64 | musl ≥ 1.2.5 |
| Linux (musl) | aarch64 | musl ≥ 1.2.5 |
| macOS | x86_64 (Intel) | macOS ≥ 10.12 |
| macOS | arm64 (Apple Silicon) | macOS ≥ 11.0 |
| Windows | x86_64 | Windows 10+ or Windows Server 2016+ |
| Windows | ARM64 |
Version correspondence
The version of this package always matches the upstream llmfit release tag
(with the leading v stripped). llmfit==0.8.6 contains v0.8.6 of the
upstream binary.
About this package
This is an unofficial redistribution. The llmfit binary is the work of
Alex Jones and contributors, released under
the MIT License. See LICENSE for details.
Source for this packaging wrapper: https://github.com/JEHoctor/llmfit-pypi
For maintainers of this repository
How it works
- A nightly GitHub Actions workflow (
check_upstream.yml) compares the latest upstream tag with the published PyPI version. - If they differ, it triggers
build_and_publish.ymlwith the new tag. build_and_publish.ymlcallsbuild_wheels.py, which downloads each platform archive from GitHub Releases, verifies its SHA256 checksum, extracts the binary, and constructs a platform-tagged wheel for thellmfitpackage.- All wheels are published to PyPI via OIDC Trusted Publisher (no API tokens stored in repository secrets).
You can also trigger a build manually from the Actions tab, providing the
version tag (e.g. v0.8.6).
Project details
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