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brew

llm mit Homebrew, apt, Nix installieren

Prüfe Installationswege, Executables, Metadaten und Sicherheitshinweise für llm in AI-Agent-Workflows.

Installation

Weitere Installationsbefehle

macOS

Homebrewverifiziert · 100%
brew install llm

local Homebrew formula metadata

Linux

Debian aptverifiziert · 92%
sudo apt install llm

Debian stable package indexes · llm · Quelle: deb.debian.org

Nixverifiziert · 92%
nix profile install nixpkgs#llm

nixpkgs package indexes · pkgs/by-name/ll/llm/package.nix · Quelle: api.github.com

Überblick

Paketzusammenfassung

Access large language models from the command-line

Verlauf

Projektgeschichte und Nutzung

LLM is Simon Willison's command-line tool and Python library for working with large language models. It started as an OpenAI-focused CLI in 2023 and evolved into a plugin-based interface for remote APIs, local models, embeddings, prompt templates, logging, attachments, schemas, and tool use.

Projektgeschichte

The changelog records version 0.1 on April 1, 2023 as the initial prototype release. Version 0.5 on July 12, 2023 added a plugin mechanism for additional language models, a key change that moved LLM beyond a single-provider OpenAI wrapper.

During 2023 and 2024, LLM added chat, embeddings, templates, SQLite logging and search, model aliases, attachments, async models, and broader provider support. In May 2025, version 0.26 added tool support, letting models execute Python functions through the CLI and Python API.

Adoptionsgeschichte

LLM became part of the Datasette-adjacent command-line culture around small composable tools, SQLite-backed logs, and plugin systems. Homebrew, Debian, and Nix packaging made it easy to install as a normal developer utility rather than only as a Python package.

Its adoption expanded with the growth of provider-specific plugins and local-model integrations, giving users one command-line interface across OpenAI, Anthropic, Gemini, Ollama-backed models, and many community plugins.

Wie es verwendet wird

Common uses include running one-off prompts from the shell, piping files into a model, starting interactive chats, storing API keys, saving prompt templates, logging responses to SQLite, generating embeddings, and calling models from Python code.

The documented configuration paths and keys.json locations matter to package users because Homebrew installs the executable, while user-specific model keys, templates, logs, and extra model definitions live outside the package prefix.

Warum Paket-Nerds sich dafür interessieren

LLM is package-nerd significant because it turns rapidly changing AI APIs into a stable Unix-style command with plugins. The packaging story is unusually important: users want a single binary-ish command in PATH, but the real extension surface is Python plugins and user configuration.

It is also a useful example of modern CLI state management: credentials, templates, provider models, logs, and tool definitions are intentionally external to the package, so upgrades can move the application forward without overwriting user data.

Zeitleiste

  • 2023-04-01: LLM 0.1 initial prototype release.
  • 2023-07-12: LLM 0.5 added the plugin mechanism for additional language models.
  • 2024-10-29: LLM 0.17 added attachment support for multimodal models.
  • 2025-05-27: LLM 0.26 added tool support.
  • 2026-06-09: LLM 0.32a3 appeared in the changelog with tool-call and human-in-the-loop improvements.

Related projects

  • Datasette is related through the broader Simon Willison/Datasette tooling ecosystem and the io.datasette.llm application data namespace.
  • LLM plugins such as provider adapters and local-model integrations are central to the project's architecture.
  • SQLite is related through LLM's prompt and response logging features.

Sicherheitslage

Noch keine Protected-Tool-Abdeckung gefunden

Für llm wurde kein passendes lokales Secret-Handling-Manifest gefunden. Nucleus-Paketmetadaten bleiben hier veröffentlicht, damit künftige Abdeckung eine stabile Paket-URL hat.

Installationsverhalten

  • In den Formelmetadaten ist kein Homebrew-Post-install-Hook erfasst.
  • Homebrew-Bottle-Metadaten sind für 6 Plattformziele verfügbar.
  • Installiert mit 4 Laufzeitabhängigkeiten.
  • Build-Metadaten listen 1 Build-Abhängigkeiten.

Empfohlene Prüfung

Prüfe vor unbeaufsichtigter Agent-Nutzung, ob das Tool Klartext-Credentials liest, Remote-Zustand schreibt, Artefakte veröffentlicht oder Plugins ausführt.

local files

Configuration and credential file locations

These source-backed paths show where this package keeps local settings or durable credentials. Automic Vault can use them as review targets for secret scanning, migration, and command approval.

Configuration files

Config paths the tool may read or write during local use.

Linux
~/.config/io.datasette.llm/~/.config/io.datasette.llm/templates/*.yaml~/.config/io.datasette.llm/extra-openai-models.yaml
macOS
~/Library/Application Support/io.datasette.llm/~/Library/Application Support/io.datasette.llm/templates/*.yaml~/Library/Application Support/io.datasette.llm/extra-openai-models.yaml

Credential files

Credential-bearing paths to review before unattended agent runs.

Linux
~/.config/io.datasette.llm/keys.json
macOS
~/Library/Application Support/io.datasette.llm/keys.json

Executables

Installierte Executables

BefehlArtSichtbarkeitHinweis
llmcliglobales Executable

Aktualität

Version und Aktualität

Diese Signale trennen das Alter der Seitengenerierung, Aktivität des Paketmanagers und Upstream-Release-Vergleich. Versionsrückstand wird nur gemeldet, wenn eine Evidenz-URL und vergleichbare Versionen vorhanden sind.

Seite generiert2026-07-25
Manager-Version0.31.1
Manager aktualisiert2026-07-10
lokale DatenOK
Upstreamnot checked
neueste erkannte Versionnicht erkannt

https://llm.datasette.io/

Installationsmetadaten

Paketmetadaten

Paketschlüsselbrew:llm
Version0.31.1
PaketmanagerHomebrew
Paketmanager-Seitehttps://formulae.brew.sh/formula/llm
Homepagehttps://llm.datasette.io/
Repositoryhttps://github.com/simonw/llm
Upstream-Dokumentationhttps://llm.datasette.io/en/stable
LizenzApache-2.0
Quellarchivhttps://files.pythonhosted.org/packages/02/2a/ac37d94f6ac91d501475d80a0a1d8fb6bce392f9d7b483bf87257342e0b7/llm-0.31.1.tar.gz
Zuletzt aktualisiert2026-07-10T19:29:48Z
Pulseupdated
Abhängigkeitencertifi, libyaml, pydantic, python@3.14
Build-Abhängigkeitenrust
Bottleverfügbar (auf arm64_linux, arm64_sequoia, arm64_sonoma, arm64_tahoe, sonoma, x86_64_linux)
Homebrew post-installnicht definiert
Dienstkeiner deklariert

Registry-Fakten

Details aus der Quelldatenbank

Source DatabaseHomebrew formula API
Taphomebrew/core
Full Namellm
Version Scheme0
Revision0
Bottle Stable Root URLhttps://ghcr.io/v2/homebrew/core
Deprecatedno
Disabledno
Keg Onlyno
URL Keys
  • stable

Source-Datenbank-Treffer

Andere Paketmanager-Einträge

Treffer stammen aus externen Paketmanager-Indizes und bleiben von lokalen Automic-Vault-Paketlinks getrennt.

Debian apt95%

llm 0.23-1

CLI utility and Python library for interacting with Large Language Models

https://github.com/simonw/llm

sudo apt install llm
  • Section: contrib/science
  • Architecture: all
  • 14 Abhängigkeiten
  • normalized package name match
  • Abgeglichen nach: Llm
Debian stable package indexes · deb.debian.org · Debian stable package indexes: llm from https://deb.debian.org/debian/dists/stable/contrib/binary-amd64/Packages.xz
Nix95%

llm

nix profile install nixpkgs#llm
  • normalized package name match
  • Abgeglichen nach: Llm
nixpkgs package indexes · api.github.com · nixpkgs package indexes: pkgs/by-name/ll/llm/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1

Quellspur

Aus Repository-Daten generiert

Diese Seite wird von av-web aus dem privaten Paket-SQLite-Artefakt bereitgestellt, das scripts/generate-pkg-sqlite.py erstellt.

Verwendete Quellen

  • Geiger risk classifier
  • Nucleus package database
  • av.db category and tag curation
  • cross-ecosystem install command graph
  • curated configuration and credential file locations
  • curated package history
  • external package-manager database matches
  • package relationship graph
  • package version freshness
  • package-page enrichment