Automic VaultAutomic Vault

brew

Installer fabric-ai avec Homebrew, Nix, scoop

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

installation

Commandes d'installation supplémentaires

macOS

Homebrewvérifié · 100%
brew install fabric-ai

local Homebrew formula metadata

Linux

Nixvérifié · 92%
nix profile install nixpkgs#fabric-ai

nixpkgs package indexes · pkgs/by-name/fa/fabric-ai/package.nix · Source: api.github.com

Windows

Scoopvérifié · 92%
scoop install main/fabric-ai

Scoop official bucket manifest trees · bucket/fabric-ai.json · Source: api.github.com

aperçu

Résumé du paquet

Open-source framework for augmenting humans using AI

Commandes et alias

  • fabric-ai

historique

Historique du projet et usages

Fabric is Daniel Miessler's open-source framework for organizing reusable AI prompts, called patterns, and running them from a CLI or related interfaces.

Historique du projet

Fabric was created after the late-2022 surge in modern AI tools. Its README argues that AI had an integration problem rather than a capabilities problem, and presents Fabric as a way to organize prompts by real-world task so they can be reused across workflows.

The project started publicly in early 2024 and grew rapidly around the idea that prompt collections could be packaged like command-line tools. The README describes Fabric as both a pattern library and, for command-line-focused users, an interface for running those patterns directly.

The current project is implemented and distributed as a fast-moving CLI with release binaries, shell completions, a REST API server, provider integrations, and package-manager installs. Its README notes that Homebrew and Arch Linux package the executable as `fabric-ai`, with an alias suggested for users who want to type `fabric`.

Historique d'adoption

Fabric's adoption followed the broader CLI-and-LLM trend: users wanted prompt workflows they could pipe text into, version in Git, and invoke from shells instead of only using web chat interfaces. The README points to intro videos and a large set of patterns for summarization, paper analysis, code explanation, social posts, and other repeatable tasks.

The project has kept widening provider support. The README update log lists additions for OpenAI Codex, Azure AI Gateway, Microsoft 365 Copilot, DigitalOcean GenAI, GitHub Models, Venice AI, Z AI, Abacus, Anthropic model updates, internationalization, Windows ARM and Linux ARM binaries, and Swagger API docs.

Modes d'utilisation

The core usage model is to select a pattern and feed it content. Users can run Fabric from the CLI, install or update patterns, create custom patterns, map patterns to models, add shell aliases, or run its REST API server for local integrations.

Because Fabric treats prompts as named assets, it behaves like a package of workflows rather than a single chatbot. That makes it useful for people who want repeatable LLM operations in shell pipelines, note-taking systems, coding workflows, or personal knowledge processes.

Pourquoi les passionnés de paquets s'y intéressent

Fabric is package-nerd significant because it turns prompts into installable, inspectable command-line artifacts. It is part of the 2024-2026 wave of LLM tooling where package managers distribute not only compilers and CLIs, but also opinionated prompt workflows.

The `fabric-ai` Homebrew naming detail is also notable: it avoids colliding with the older Python `fabric` package while preserving the upstream tool's identity through a recommended alias.

Chronologie

  • 2024: The Fabric repository is created.
  • 2025: Releases add new binary targets, provider integrations, internationalization, and REST API documentation.
  • 2026: README update log lists Microsoft 365 Copilot, Azure AI Gateway, OpenAI Codex backend, and Anthropic model support updates.

Related projects

  • Fabric integrates with LLM providers and backends such as OpenAI, Anthropic, Azure OpenAI, Google Vertex AI, AWS Bedrock, Ollama, GitHub Models, and others.
  • The Homebrew package is named `fabric-ai` to distinguish it from Python Fabric.

posture de sécurité

Niveau de risque : vert

narrow executable package without higher-risk signals.

Classificateur de risque

risque vert · confiance faible · appliance

Pourquoi

  • narrow executable package without higher-risk signals

Signaux

  • metadata:no-higher-risk-signals

Comportement d'installation

  • Aucun hook post-install Homebrew n’est enregistré dans les métadonnées de formule.
  • Les métadonnées de bottle Homebrew sont disponibles pour 6 plateformes.
  • Les métadonnées de compilation listent 1 dépendances de compilation.

Revue recommandée

Avant une utilisation sans surveillance par un agent, vérifiez si l'outil lit des identifiants en clair, écrit un état distant, publie des artefacts ou lance des plugins.

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.

Unix
~/.config/fabric/config.yaml

Credential files

Credential-bearing paths to review before unattended agent runs.

Unix
~/.config/fabric/.env

exécutables

Exécutables installés

CommandeTypeExpositionNote
fabric-aicliexécutable global

fraîcheur

Version et fraîcheur

Ces signaux séparent l'âge de génération de la page, l'activité du gestionnaire de paquets et la comparaison avec les versions amont. Un retard de version n'est signalé que lorsqu'une URL de preuve et des versions comparables sont présentes.

page générée2026-07-25
version du gestionnaire1.4.460
gestionnaire mis à jour2026-07-24
données localesOK
amontà jour
dernière version détectéev1.4.460

https://github.com/danielmiessler/fabric

  • OKAucun avertissement de fraîcheur n'a été généré.

métadonnées d'installation

Métadonnées du paquet

Clé du paquetbrew:fabric-ai
Version1.4.460
Gestionnaire de paquetsHomebrew
Page du gestionnaire de paquetshttps://formulae.brew.sh/formula/fabric-ai
Page d'accueilhttps://github.com/danielmiessler/fabric
Dépôthttps://github.com/danielmiessler/fabric
Docs amonthttps://github.com/danielmiessler/fabric#readme
LicenceMIT
Archive sourcehttps://github.com/danielmiessler/fabric/archive/refs/tags/v1.4.460.tar.gz
Dernière mise à jour2026-07-24T20:54:01Z
Pulseupdated
Dépendances de compilationgo
Bouteilledisponible (sur arm64_linux, arm64_sequoia, arm64_sonoma, arm64_tahoe, sonoma, x86_64_linux)
post-install Homebrewnon défini
Serviceaucun déclaré

faits du registre

Détails de la base source

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

correspondances dans les bases sources

Autres enregistrements de gestionnaires de paquets

Les correspondances proviennent d’index externes de gestionnaires de paquets et restent séparées des liens de paquets Automic Vault locaux.

Nix95%

fabric-ai

nix profile install nixpkgs#fabric-ai
  • normalized package name match
  • Correspondance par : Fabric Ai
nixpkgs package indexes · api.github.com · nixpkgs package indexes: pkgs/by-name/fa/fabric-ai/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1
Scoop95%

main/fabric-ai

scoop install main/fabric-ai
  • normalized package name match
  • Correspondance par : Fabric Ai
Scoop official bucket manifest trees · api.github.com · Scoop official bucket manifest trees: bucket/fabric-ai.json from https://api.github.com/repos/ScoopInstaller/Main/git/trees/master?recursive=1

piste source

Généré depuis les données du dépôt

Cette page est servie par av-web depuis l'artéfact SQLite privé des paquets généré par scripts/generate-pkg-sqlite.py.

Sources utilisées

  • 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