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使用 Homebrew, Nix, scoop 安装 fabric-ai

查看 fabric-ai 的安装路径、可执行文件、元数据以及面向 AI 代理工作流的安全说明。

安装

其他安装命令

macOS

Homebrew已验证 · 100%
brew install fabric-ai

local Homebrew formula metadata

Linux

Nix已验证 · 92%
nix profile install nixpkgs#fabric-ai

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

Windows

Scoop已验证 · 92%
scoop install main/fabric-ai

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

概览

软件包摘要

Open-source framework for augmenting humans using AI

命令和别名

  • fabric-ai

历史

项目历史与用法

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

项目历史

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`.

采用历史

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.

使用方式

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.

为什么软件包爱好者会关心

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.

时间线

  • 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.

安全态势

风险级别:绿色

narrow executable package without higher-risk signals.

风险分类器

绿色 风险 · 低 置信度 · appliance

原因

  • narrow executable package without higher-risk signals

信号

  • metadata:no-higher-risk-signals

安装行为

  • 未记录 Homebrew bottle 元数据。

建议审查

在无人值守的代理使用前,请检查该工具是否读取明文凭据、写入远程状态、发布制品或调用插件。

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

可执行文件

已安装的可执行文件

命令类型暴露范围备注
fabric-ai可执行文件已索引可执行文件从本地可执行文件索引发现。

新鲜度

版本和新鲜度

这些信号区分页生成时间、软件包管理器活动和上游发布比较。只有存在证据 URL 和可比较版本时,才会提示版本落后。

页面生成时间2026-08-03
管理器版本1.4.468
管理器更新时间2026-08-03
本地数据未知
上游不可用
检测到的最新版本未检测到
  • OK没有生成新鲜度警告。

安装元数据

软件包元数据

软件包键brew:fabric-ai
版本1.4.468
软件包管理器Homebrew
主页https://github.com/danielmiessler/fabric
仓库https://github.com/danielmiessler/fabric
最后更新2026-08-03T03:15:03Z
Pulseupdated
Bottle未记录
服务未声明

源数据库匹配

其他软件包管理器记录

匹配项来自外部软件包管理器索引,并与本地 Automic Vault 软件包链接分开显示。

Nix95%

fabric-ai

nix profile install nixpkgs#fabric-ai
  • normalized package name match
  • 匹配方式: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
  • 匹配方式: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

来源线索

由仓库数据生成

此页面由 av-webscripts/generate-pkg-sqlite.py 生成的私有软件包 SQLite 工件提供。

使用的来源

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