# llm を Homebrew, apt, Nix でインストール

llm のインストール経路、実行ファイル、メタデータ、AI エージェント向けセキュリティノートを確認します。

## インストール

```sh
sudo av install brew:llm
```

追加のインストールコマンド:

### macOS

- Homebrew (100%):

```sh
brew install llm
```

  証拠: local Homebrew formula metadata

### Linux

- Debian apt (92%):

```sh
sudo apt install llm
```

  証拠: Debian stable package indexes: llm from https://deb.debian.org/debian/dists/stable/contrib/binary-amd64/Packages.xz

- Nix (92%):

```sh
nix profile install nixpkgs#llm
```

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

## パッケージ情報

- **パッケージキー:** brew:llm
- **パッケージマネージャ:** Homebrew
- **バージョン:** 0.31.1
- **ソース概要:** Access large language models from the command-line
- **ホームページ:** <https://llm.datasette.io/>
- **最終更新:** 2026-07-10T19:29:48Z
- **生成日時:** 2026-08-03T19:37:03+00:00

## 実行可能ファイル

- llm (エイリアス)

## インストール挙動

- Bottle: 利用不可

## バージョンと鮮度

- ページ生成日: 2026-08-03
- マネージャ版: 0.31.1
## プロジェクトの歴史と使われ方

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.

### プロジェクトの歴史

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.

### 採用の歴史

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.

### 使われ方

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.

### パッケージ好きにとっての重要性

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.

### タイムライン

- 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.

### ソース

- <https://formulae.brew.sh/formula/llm>
- <https://github.com/simonw/llm>
- <https://github.com/simonw/llm/releases/tag/0.1>
- <https://llm.datasette.io/>
- <https://llm.datasette.io/en/stable/changelog.html>
- <https://llm.datasette.io/en/stable/setup.html>


## セキュリティノート

llm に一致するローカルシークレット処理マニフェストは見つかりませんでした。将来の対応で安定したパッケージ URL を使えるよう、Nucleus パッケージメタデータはここに公開されています。



## 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

- 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

- Linux: ~/.config/io.datasette.llm/keys.json
- macOS: ~/Library/Application Support/io.datasette.llm/keys.json
## 他のパッケージマネージャ記録

- Debian apt - llm - 0.23-1: normalized package name match | Debian stable package indexes: llm from https://deb.debian.org/debian/dists/stable/contrib/binary-amd64/Packages.xz | CLI utility and Python library for interacting with Large Language Models | https://github.com/simonw/llm
- Nix - llm: normalized package name match | nixpkgs package indexes: pkgs/by-name/ll/llm/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/llm.yml](https://github.com/mxcl/pkgdb/blob/main/combined/llm.yml)


## ソース

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