# Installer mlkit avec Homebrew, Nix

Consultez les chemins d'installation, exécutables, métadonnées et notes de sécurité de mlkit pour les workflows d'agents IA.

## installation

```sh
sudo av install brew:mlkit
```

Commandes d'installation supplémentaires:

### macOS

- Homebrew (100%):

```sh
brew install mlkit
```

  Preuve: local Homebrew formula metadata

### Linux

- Nix (92%):

```sh
nix profile install nixpkgs#mlkit
```

  Preuve: nixpkgs package indexes: pkgs/by-name/ml/mlkit/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1

## Faits du paquet

- **Clé du paquet:** brew:mlkit
- **Gestionnaire de paquets:** Homebrew
- **Version:** 4.7.22
- **Résumé source:** Compiler for the Standard ML programming language
- **Page d'accueil:** <https://melsman.github.io/mlkit>
- **Dépôt:** <https://github.com/melsman/mlkit>
- **Dernière mise à jour:** 2026-08-02T08:56:40Z
- **Généré:** 2026-08-03T19:37:03+00:00

## exécutables

- kittester (alias)
- mlkit (alias)
- mlkit-mllex (alias)
- mlkit-mlyacc (alias)
- reml (alias)
- rp2ps (alias)

## Comportement d'installation

- Bouteille: non disponible

## Version et fraîcheur

- page générée: 2026-08-03
- version du gestionnaire: 4.7.22
## Historique du projet et usages

MLKit descends from The ML Kit, Version 1, announced by Mads Tofte on 1993-03-12 and attributed there to Nick Rothwell, David N. Turner, Mads Tofte, and Lars Birkedal at Edinburgh and Copenhagen Universities. That early release was distributed with about 100 pages of documentation explaining how to build, run, read, and modify the Kit, making it both a Standard ML implementation and a compiler-hacking vehicle.

### Historique du projet

The later MLKit project became a compiler toolkit for Standard ML with two main compiler paths sharing a frontend and compilation-management scheme: MLKit with Regions, with a native x64 backend based on region inference, and SMLtoJs, a JavaScript backend for browser-targeted Standard ML. Its documentation says it covers all of Standard ML from the 1997 Definition and most of the Standard ML Basis Library.

### Modes d'utilisation

MLKit's distinctive technical role is region-based memory management for ML. The project documentation describes compiler-inferred allocation and deallocation directives, region profiling, C interoperation, and optional reference-tracing garbage collection on top of region inference. In practice it is used both as an SML compiler and as a research/development tool for region inference, SML-to-JavaScript compilation, bootstrapping, ML Basis files, and compatibility work alongside tools such as MLton and smlpkg.

### Sources

- <https://elsman.com/mlkit/papers>
- <https://elsman.com/mlkit/pdf/kit.pdf>
- <https://formulae.brew.sh/formula/mlkit>
- <https://github.com/melsman/mlkit>
- <https://groups.google.com/g/comp.compilers/c/my2OjNZxT20>
- <https://raw.githubusercontent.com/melsman/mlkit/master/README.md>


## Notes de sécurité

generalized runtime or code generation signal.

- **Risque Geiger:** yellow / moyen
- generalized runtime or code generation signal

## Autres enregistrements de gestionnaires de paquets

- Nix - mlkit: normalized package name match | nixpkgs package indexes: pkgs/by-name/ml/mlkit/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1


## Combined YAML source

View the package source record on GitHub. [combined/mlkit.yml](https://github.com/mxcl/pkgdb/blob/main/combined/mlkit.yml)


## Sources

- pkg.so package database
- Geiger risk classifier
- curated package history
- pkgdb category and tag curation
- external package-manager database matches
- cross-ecosystem install command graph