Skip to main content

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

  1. A nightly GitHub Actions workflow (check_upstream.yml) compares the latest upstream tag with the published PyPI version.
  2. If they differ, it triggers build_and_publish.yml with the new tag.
  3. build_and_publish.yml calls build_wheels.py, which downloads each platform archive from GitHub Releases, verifies its SHA256 checksum, extracts the binary, and constructs a platform-tagged wheel for the llmfit package.
  4. 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


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

llmfit-0.9.10-py3-none-win_arm64.whl (2.8 MB view details)

Uploaded Python 3Windows ARM64

llmfit-0.9.10-py3-none-win_amd64.whl (2.9 MB view details)

Uploaded Python 3Windows x86-64

llmfit-0.9.10-py3-none-musllinux_1_2_x86_64.whl (3.7 MB view details)

Uploaded Python 3musllinux: musl 1.2+ x86-64

llmfit-0.9.10-py3-none-musllinux_1_2_aarch64.whl (3.6 MB view details)

Uploaded Python 3musllinux: musl 1.2+ ARM64

llmfit-0.9.10-py3-none-manylinux_2_17_x86_64.whl (3.6 MB view details)

Uploaded Python 3manylinux: glibc 2.17+ x86-64

llmfit-0.9.10-py3-none-manylinux_2_17_aarch64.whl (3.5 MB view details)

Uploaded Python 3manylinux: glibc 2.17+ ARM64

llmfit-0.9.10-py3-none-macosx_11_0_arm64.whl (3.2 MB view details)

Uploaded Python 3macOS 11.0+ ARM64

llmfit-0.9.10-py3-none-macosx_10_12_x86_64.whl (3.3 MB view details)

Uploaded Python 3macOS 10.12+ x86-64

File details

Details for the file llmfit-0.9.10-py3-none-win_arm64.whl.

File metadata

  • Download URL: llmfit-0.9.10-py3-none-win_arm64.whl
  • Upload date:
  • Size: 2.8 MB
  • Tags: Python 3, Windows ARM64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for llmfit-0.9.10-py3-none-win_arm64.whl
Algorithm Hash digest
SHA256 4048e211069868753b5770700621ee649ae39540b522e3a318b27478c95d7ee2
MD5 e070e578f10cf54a18a1bd17a25607e3
BLAKE2b-256 45c63c226d9c420ef4331b5738ec2117c0a23be99801ef1fc0191458a29542d5

See more details on using hashes here.

Provenance

The following attestation bundles were made for llmfit-0.9.10-py3-none-win_arm64.whl:

Publisher: build_and_publish.yml on JEHoctor/llmfit-pypi

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file llmfit-0.9.10-py3-none-win_amd64.whl.

File metadata

  • Download URL: llmfit-0.9.10-py3-none-win_amd64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: Python 3, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for llmfit-0.9.10-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 57345d05c6627f1c9d91135933fa0847562389c5aa52cfa0d1d5231d32d10b8d
MD5 baccdec96fe30b71859001dc91f4348c
BLAKE2b-256 bf277e7bc67088ad464586c14c45fe946b28eabb031ccee4c9f263f2db0bc9d9

See more details on using hashes here.

Provenance

The following attestation bundles were made for llmfit-0.9.10-py3-none-win_amd64.whl:

Publisher: build_and_publish.yml on JEHoctor/llmfit-pypi

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file llmfit-0.9.10-py3-none-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for llmfit-0.9.10-py3-none-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 38a662b2dd7151bb3d7c1236171fa02fe8f51b44bb7c71e9cc43d6ba3c6fe499
MD5 8c784435a070baae9b4dd848c79243a2
BLAKE2b-256 7d8c604d75ac63be27d871860e88f240f203e1811f985bbba99f2fdb6b0b1c07

See more details on using hashes here.

Provenance

The following attestation bundles were made for llmfit-0.9.10-py3-none-musllinux_1_2_x86_64.whl:

Publisher: build_and_publish.yml on JEHoctor/llmfit-pypi

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file llmfit-0.9.10-py3-none-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for llmfit-0.9.10-py3-none-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 05b36e994a4c9e3a388f872e97320faed8d0fbd92938927b14399939a9f1df10
MD5 7326bd290e6c7a8a5b3e25f39744ccf0
BLAKE2b-256 09f6e17093fb23d7cd3259ba24e77928d1b7fb2ca96dd23d3903264b5207a3b6

See more details on using hashes here.

Provenance

The following attestation bundles were made for llmfit-0.9.10-py3-none-musllinux_1_2_aarch64.whl:

Publisher: build_and_publish.yml on JEHoctor/llmfit-pypi

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file llmfit-0.9.10-py3-none-manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for llmfit-0.9.10-py3-none-manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 46831b955f8bb98a06163e520f5b4abf779538db7fa281da2c5a112d8b37aae2
MD5 31cb3b033e7d73470e21475887d58517
BLAKE2b-256 e920c20e56405e79ed18b378255791b64d22545191c17f2b6502cc308bea5ac1

See more details on using hashes here.

Provenance

The following attestation bundles were made for llmfit-0.9.10-py3-none-manylinux_2_17_x86_64.whl:

Publisher: build_and_publish.yml on JEHoctor/llmfit-pypi

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file llmfit-0.9.10-py3-none-manylinux_2_17_aarch64.whl.

File metadata

File hashes

Hashes for llmfit-0.9.10-py3-none-manylinux_2_17_aarch64.whl
Algorithm Hash digest
SHA256 c4a746db455e7eb32329d505f64d566cba44b6a241b675908b7e1b46a39ec4f6
MD5 fb73465a93180f2a2539d316071d61af
BLAKE2b-256 28f0d0cdeb56cbf35feb0b15a0988de0839b30bda67df39d18d85f654b7c04e2

See more details on using hashes here.

Provenance

The following attestation bundles were made for llmfit-0.9.10-py3-none-manylinux_2_17_aarch64.whl:

Publisher: build_and_publish.yml on JEHoctor/llmfit-pypi

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file llmfit-0.9.10-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for llmfit-0.9.10-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7dd1169f3793ef2442ccb81cc643c77c276ab166e9072a3543f045ad78346006
MD5 8bc7e3837c9935668b97facf59d69cbe
BLAKE2b-256 f8e49a165e4ad95dc3448c84e7d0289a8e3804cbb23ac6bfd31275d5c4686ef5

See more details on using hashes here.

Provenance

The following attestation bundles were made for llmfit-0.9.10-py3-none-macosx_11_0_arm64.whl:

Publisher: build_and_publish.yml on JEHoctor/llmfit-pypi

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file llmfit-0.9.10-py3-none-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for llmfit-0.9.10-py3-none-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 53e0e303a132b09cf11d2246db025779cfb6816f72532103894a9b1ecf4703fc
MD5 7e46b4dda53ae2eb0c58c50279989eb1
BLAKE2b-256 ef560c90a4a798f9aadc237b28b460682078f1825d4c19100dfaf64bec911c0d

See more details on using hashes here.

Provenance

The following attestation bundles were made for llmfit-0.9.10-py3-none-macosx_10_12_x86_64.whl:

Publisher: build_and_publish.yml on JEHoctor/llmfit-pypi

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page