AutoGPT：构建、部署和运行 AI 代理

Deutsch | Español | français | 日本語 | 한국어 | Português | Русский | 中文

AutoGPT 是一个强大的平台，可以创建、部署和管理持续运行的 AI 代理，以自动化复杂工作流。

• 自行下载并自托管（免费！）
• 加入等候名单 获取云托管测试版（封闭测试 - 公开版即将推出！）

如何自托管 AutoGPT 平台

注意：自行设置和托管 AutoGPT 平台属于技术性操作。如果您更希望直接使用，我们建议 加入等候名单 获取云托管测试版。

在开始安装之前，请确保系统满足以下要求：

• CPU：建议 4 核以上

• 内存：最低 8GB，建议 16GB

• 存储：至少 10GB 可用空间

• 操作系统：

  • Linux（建议 Ubuntu 20.04 或更新版本）
  • macOS（10.15 或更新版本）
  • Windows 10/11 并启用 WSL2

• 必备软件（含最低版本要求）：

  • Docker Engine（20.10.0 或更新版本）
  • Docker Compose（2.0.0 或更新版本）
  • Git（2.30 或更新版本）
  • Node.js（16.x 或更新版本）
  • npm（8.x 或更新版本）
  • VSCode（1.60 或更新版本）或其他现代代码编辑器

• 稳定的互联网连接

• 可访问所需端口（将在 Docker 中配置）

• 能够发起出站 HTTPS 连接

更新后的安装说明：

我们已迁移到全面维护并定期更新的文档站点。

👉 在此处查看官方自托管指南

本教程假定您已安装 Docker、VSCode、git 和 npm。

---

⚡ 使用一行脚本快速安装（推荐用于本地托管）

跳过手动步骤，使用我们的自动安装脚本几分钟即可开始。

适用于 macOS/Linux：

curl -fsSL https://setup.agpt.co/install.sh -o install.sh && bash install.sh

适用于 Windows（PowerShell）：

powershell -c "iwr https://setup.agpt.co/install.bat -o install.bat; ./install.bat"

该脚本将一次性安装依赖项、配置 Docker 并启动本地实例。

AutoGPT 前端是用户与我们强大的 AI 自动化平台交互的地方。它提供多种方式使用和利用 AI 代理。这个界面正是您将 AI 自动化想法变为现实的地方：

Agent 构建器：对于那些想要自定义的用户，我们直观的低代码界面可让您设计并配置自己的 AI 代理。

工作流管理：轻松构建、修改和优化您的自动化工作流。通过连接各个操作块来构建代理，每个块执行单一动作。

部署控制：管理代理的整个生命周期，从测试到生产。

即用型代理：不想自己构建？只需从我们的预配置代理库中选择，即可立即投入工作。

代理交互：无论您是自己构建还是使用预配置代理，都可以通过我们友好的用户界面轻松运行并与之互动。

监控与分析：跟踪代理的性能并获得洞察，持续改进自动化流程。

阅读本指南 学习如何构建自定义块。

AutoGPT 服务器是我们平台的核心动力。您的代理就是在这里运行。一旦部署，代理可以被外部源触发并持续运行。它包含了使 AutoGPT 顺利运行的所有关键组件。

源代码：驱动代理和自动化流程的核心逻辑。

基础设施：确保可靠且可扩展性能的健壮系统。

市场：一个综合性的市场，您可以在此找到并部署各种预构建代理。

以下是通过 AutoGPT 可以实现的两个示例：

1. 根据热门话题生成病毒式视频

   • 该代理读取 Reddit 上的话题。
   • 识别当前热门话题。
   • 然后根据内容自动创建一条短视频。

2. 从视频中识别热门引言用于社交媒体

   • 该代理订阅您的 YouTube 频道。
   • 当您发布新视频时，它会进行转录。
   • 利用 AI 识别最具影响力的引言以生成摘要。
   • 接着撰写帖子，自动发布到您的社交媒体。

这些示例仅是一瞥，您可以用 AutoGPT 实现更多！可以创建自定义工作流，为任何用例构建代理。

---

🛡️ Polyform Shield 许可证：autogpt_platform 文件夹内的所有代码和内容均依据 Polyform Shield 许可证授权。这个新项目是我们正在开发中、用于构建、部署和管理代理的平台。 阅读有关此项努力的更多信息

🦉 MIT 许可证：AutoGPT 仓库的所有其他部分（即 autogpt_platform 文件夹之外的所有内容）依据 MIT 许可证授权。这包括最初的独立 AutoGPT Agent，以及诸如 Forge、agbenchmark 和 AutoGPT Classic GUI 等项目。 我们还在其他仓库中按 MIT 许可证发布额外作品，例如为 AutoGPT 平台开发并用于该平台的 GravitasML。另请参阅我们 MIT 许可的 Code Ability 项目。

---

我们的使命是提供工具，让您可以专注于重要的事情：

• 🏗️ 构建 - 奠定非凡事物的基础。
• 🧪 测试 - 将代理微调至完美。
• 🤝 委托 - 让 AI 为您工作，让想法变为现实。

加入这场革命！AutoGPT 将一直存在，站在 AI 创新的最前沿。

📖 文档 | 🚀 贡献

---

以下信息关于经典版 AutoGPT。

🛠️ 构建您自己的 Agent - 快速入门

锻造您自己的代理！ – Forge 是一个开箱即用的工具包，用于构建您自己的代理应用。它处理了大部分样板代码，让您将全部创造力集中在让 您的 代理与众不同的地方。所有教程位于 此处。来自 forge 的组件也可以单独使用，以加速开发并减少代理项目中的样板代码。

🚀 Forge 入门指南 – 本指南将带您了解创建自己的代理并使用基准测试和用户界面的整个过程。

📘 了解更多 关于 Forge

测量代理的性能！ agbenchmark 可用于任何支持代理协议的代理，并且与项目 CLI 的集成使其更易于与 AutoGPT 和基于 Forge 的代理一起使用。基准测试提供了严格的测试环境。我们的框架允许自主、客观的性能评估，确保您的代理已为现实世界行动做好准备。

📦 agbenchmark 在 Pypi 上 | 📘 了解更多 关于基准测试

让代理易于使用！ frontend 为您提供用户友好的界面来控制和监控代理。它通过代理协议连接代理，确保与生态内外的众多代理兼容。

前端开箱即用地支持仓库中的所有代理。只需使用 CLI 运行您选择的代理！

📘 了解更多 关于前端

为了方便地使用仓库提供的所有工具，仓库根目录包含一个 CLI：

$ ./run
Usage: cli.py [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  agent      Commands to create, start and stop agents
  benchmark  Commands to start the benchmark and list tests and categories
  setup      Installs dependencies needed for your system.

只需克隆仓库，通过 ./run setup 安装依赖，即可开始使用！

🤔 有问题？建议？

要报告错误或请求功能，请创建 GitHub Issue。请确保没有其他人已为同一主题创建 Issue。

为了保持统一标准并确保与众多当前和未来应用的无缝兼容，AutoGPT 采用了 AI Engineer Foundation 的 代理协议 标准。这标准化了代理到前端和基准测试的通信路径。

---

AutoGPT: Build, Deploy, and Run AI Agents

Deutsch | Español | français | 日本語 | 한국어 | Português | Русский | 中文

AutoGPT is a powerful platform that allows you to create, deploy, and manage continuous AI agents that automate complex workflows.

• Download to self-host (Free!)
• Join the Waitlist for the cloud-hosted beta (Closed Beta - Public release Coming Soon!)

How to Self-Host the AutoGPT Platform

Note

Setting up and hosting the AutoGPT Platform yourself is a technical process. If you'd rather something that just works, we recommend joining the waitlist for the cloud-hosted beta.

Before proceeding with the installation, ensure your system meets the following requirements:

• CPU: 4+ cores recommended

• RAM: Minimum 8GB, 16GB recommended

• Storage: At least 10GB of free space

• Operating Systems:

  • Linux (Ubuntu 20.04 or newer recommended)
  • macOS (10.15 or newer)
  • Windows 10/11 with WSL2

• Required Software (with minimum versions):

  • Docker Engine (20.10.0 or newer)
  • Docker Compose (2.0.0 or newer)
  • Git (2.30 or newer)
  • Node.js (16.x or newer)
  • npm (8.x or newer)
  • VSCode (1.60 or newer) or any modern code editor

• Stable internet connection

• Access to required ports (will be configured in Docker)

• Ability to make outbound HTTPS connections

Updated Setup Instructions:

We've moved to a fully maintained and regularly updated documentation site.

👉 Follow the official self-hosting guide here

This tutorial assumes you have Docker, VSCode, git and npm installed.

---

⚡ Quick Setup with One-Line Script (Recommended for Local Hosting)

Skip the manual steps and get started in minutes using our automatic setup script.

For macOS/Linux:

curl -fsSL https://setup.agpt.co/install.sh -o install.sh && bash install.sh

For Windows (PowerShell):

powershell -c "iwr https://setup.agpt.co/install.bat -o install.bat; ./install.bat"

This will install dependencies, configure Docker, and launch your local instance — all in one go.

The AutoGPT frontend is where users interact with our powerful AI automation platform. It offers multiple ways to engage with and leverage our AI agents. This is the interface where you'll bring your AI automation ideas to life:

Agent Builder: For those who want to customize, our intuitive, low-code interface allows you to design and configure your own AI agents.

Workflow Management: Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block performs a single action.

Deployment Controls: Manage the lifecycle of your agents, from testing to production.

Ready-to-Use Agents: Don't want to build? Simply select from our library of pre-configured agents and put them to work immediately.

Agent Interaction: Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly interface.

Monitoring and Analytics: Keep track of your agents' performance and gain insights to continually improve your automation processes.

Read this guide to learn how to build your own custom blocks.

The AutoGPT Server is the powerhouse of our platform This is where your agents run. Once deployed, agents can be triggered by external sources and can operate continuously. It contains all the essential components that make AutoGPT run smoothly.

Source Code: The core logic that drives our agents and automation processes.

Infrastructure: Robust systems that ensure reliable and scalable performance.

Marketplace: A comprehensive marketplace where you can find and deploy a wide range of pre-built agents.

Here are two examples of what you can do with AutoGPT:

1. Generate Viral Videos from Trending Topics

   • This agent reads topics on Reddit.
   • It identifies trending topics.
   • It then automatically creates a short-form video based on the content.

2. Identify Top Quotes from Videos for Social Media

   • This agent subscribes to your YouTube channel.
   • When you post a new video, it transcribes it.
   • It uses AI to identify the most impactful quotes to generate a summary.
   • Then, it writes a post to automatically publish to your social media.

These examples show just a glimpse of what you can achieve with AutoGPT! You can create customized workflows to build agents for any use case.

---

🛡️ Polyform Shield License: All code and content within the autogpt_platform folder is licensed under the Polyform Shield License. This new project is our in-developlemt platform for building, deploying and managing agents.
Read more about this effort

🦉 MIT License: All other portions of the AutoGPT repository (i.e., everything outside the autogpt_platform folder) are licensed under the MIT License. This includes the original stand-alone AutoGPT Agent, along with projects such as Forge, agbenchmark and the AutoGPT Classic GUI.
We also publish additional work under the MIT Licence in other repositories, such as GravitasML which is developed for and used in the AutoGPT Platform. See also our MIT Licenced Code Ability project.

---

Our mission is to provide the tools, so that you can focus on what matters:

• 🏗️ Building - Lay the foundation for something amazing.
• 🧪 Testing - Fine-tune your agent to perfection.
• 🤝 Delegating - Let AI work for you, and have your ideas come to life.

Be part of the revolution! AutoGPT is here to stay, at the forefront of AI innovation.

📖Documentation | 🚀Contributing

---

Below is information about the classic version of AutoGPT.

🛠️Build your own Agent - Quickstart

Forge your own agent! – Forge is a ready-to-go toolkit to build your own agent application. It handles most of the boilerplate code, letting you channel all your creativity into the things that set your agent apart. All tutorials are located here. Components from forge can also be used individually to speed up development and reduce boilerplate in your agent project.

🚀 Getting Started with Forge – This guide will walk you through the process of creating your own agent and using the benchmark and user interface.

📘 Learn More about Forge

Measure your agent's performance! The agbenchmark can be used with any agent that supports the agent protocol, and the integration with the project's CLI makes it even easier to use with AutoGPT and forge-based agents. The benchmark offers a stringent testing environment. Our framework allows for autonomous, objective performance evaluations, ensuring your agents are primed for real-world action.

📦 agbenchmark on Pypi | 📘 Learn More about the Benchmark

Makes agents easy to use! The frontend gives you a user-friendly interface to control and monitor your agents. It connects to agents through the agent protocol, ensuring compatibility with many agents from both inside and outside of our ecosystem.

The frontend works out-of-the-box with all agents in the repo. Just use the CLI to run your agent of choice!

📘 Learn More about the Frontend

To make it as easy as possible to use all of the tools offered by the repository, a CLI is included at the root of the repo:

$ ./run
Usage: cli.py [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  agent      Commands to create, start and stop agents
  benchmark  Commands to start the benchmark and list tests and categories
  setup      Installs dependencies needed for your system.

Just clone the repo, install dependencies with ./run setup, and you should be good to go!

🤔 Questions? Problems? Suggestions?

To report a bug or request a feature, create a GitHub Issue. Please ensure someone else hasn't created an issue for the same topic.

To maintain a uniform standard and ensure seamless compatibility with many current and future applications, AutoGPT employs the agent protocol standard by the AI Engineer Foundation. This standardizes the communication pathways from your agent to the frontend and benchmark.

---