MetaGPT( The Multi-Agent Framework):颠覆AI开发的革命性多智能体元编程框架
"MetaGPT( The Multi-Agent Framework):颠覆AI开发的革命性多智能体元编程框架"
一个多智能体元编程框架,给定一行需求,它可以返回产品文档、架构设计、任务列表和代码。这个项目提供了一种创新的方式来管理和执行项目,将需求转化为具体的文档和任务列表,使项目管理变得高效而智能。对于需要进行规划和协调的项目,这个框架提供了强大的支持.
MetaGPT's 能力展示
https://github.com/geekan/MetaGPT/assets/34952977/34345016-5d13-489d-b9f9-b82ace413419
例如,如果你输入' python startup.py ' ' Design a RecSys like今日头条' ',你会得到很多输出,其中之一是data & api Design
生成一个分析和设计示例的成本约为0.2美元(在GPT-4 API费用中),而生成一个完整项目的成本约为2.0美元。
1.安装
1.1 安装视频指南
- 常规安装
#Step 1: Ensure that NPM is installed on your system. Then install mermaid-js. (If you don't have npm in your computer, please go to the Node.js offical website to install Node.js https://nodejs.org/ and then you will have npm tool in your computer.)
npm --version
sudo npm install -g @mermaid-js/mermaid-cli
#Step 2: Ensure that Python 3.9+ is installed on your system. You can check this by using:
python --version
#Step 3: Clone the repository to your local machine, and install it.
git clone https://github.com/geekan/metagpt
cd metagpt
pip install -e.
Note:
If already have Chrome, Chromium, or MS Edge installed, you can skip downloading Chromium by setting the environment variable
PUPPETEER_SKIP_CHROMIUM_DOWNLOADtotrue.Some people are having issues installing this tool globally. Installing it locally is an alternative solution,
npm install @mermaid-js/mermaid-cli
don't forget to the configuration for mmdc in config.yml
PUPPETEER_CONFIG: "./config/puppeteer-config.json"
MMDC: "./node_modules/.bin/mmdc"
if
pip install -e.fails with error[Errno 13] Permission denied: '/usr/local/lib/python3.11/dist-packages/test-easy-install-13129.write-test', try instead runningpip install -e. --user将Mermaid图表转换为SVG、PNG和PDF格式。除了Node.js版本的mermaid - cli之外,你现在还可以选择使用Python版本的剧作家、pyppeteer或mermaid。
Playwright
- Install Playwright
pip install playwright
- Install the Required Browsers
to support PDF conversion, please install Chrominum.
playwright install --with-deps chromium
- modify
config.yaml
uncomment MERMAID_ENGINE from config.yaml and change it to
playwrightMERMAID_ENGINE: playwright
pyppeteer
- Install pyppeteer
pip install pyppeteer
- Use your own Browsers
pyppeteer alow you use installed browsers, please set the following envirment
export PUPPETEER_EXECUTABLE_PATH = /path/to/your/chromium or edge or chrome
please do not use this command to install browser, it is too old
pyppeteer-install
- modify
config.yaml
uncomment MERMAID_ENGINE from config.yaml and change it to
pyppeteerMERMAID_ENGINE: pyppeteer
mermaid.ink
- modify
config.yaml
uncomment MERMAID_ENGINE from config.yaml and change it to
inkMERMAID_ENGINE: ink
Note: this method does not support pdf export.
- modify
1.2 Docker安装指南
#Step 1: Download metagpt official image and prepare config.yaml
docker pull metagpt/metagpt:latest
mkdir -p /opt/metagpt/{config,workspace}
docker run --rm metagpt/metagpt:latest cat /app/metagpt/config/config.yaml > /opt/metagpt/config/key.yaml
vim /opt/metagpt/config/key.yaml # Change the config
#Step 2: Run metagpt demo with container
docker run --rm \
--privileged \
-v /opt/metagpt/config/key.yaml:/app/metagpt/config/key.yaml \
-v /opt/metagpt/workspace:/app/metagpt/workspace \
metagpt/metagpt:latest \
python startup.py "Write a cli snake game"
#You can also start a container and execute commands in it
docker run --name metagpt -d \
--privileged \
-v /opt/metagpt/config/key.yaml:/app/metagpt/config/key.yaml \
-v /opt/metagpt/workspace:/app/metagpt/workspace \
metagpt/metagpt:latest
docker exec -it metagpt /bin/bash
$ python startup.py "Write a cli snake game"
The command docker run ... do the following things:
- Run in privileged mode to have permission to run the browser
- Map host directory
/opt/metagpt/configto container directory/app/metagpt/config - Map host directory
/opt/metagpt/workspaceto container directory/app/metagpt/workspace - Execute the demo command
python startup.py "Write a cli snake game"
1.3 构造自定义
#You can also build metagpt image by yourself.
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT && docker build -t metagpt:custom .
1.4 相关配置
- Configure your
OPENAI_API_KEYin any ofconfig/key.yaml / config/config.yaml / env - Priority order:
config/key.yaml > config/config.yaml > env
#Copy the configuration file and make the necessary modifications.
cp config/config.yaml config/key.yaml
| Variable Name | config/key.yaml | env |
|---|---|---|
| OPENAI_API_KEY # Replace with your own key | OPENAI_API_KEY: "sk-..." | export OPENAI_API_KEY="sk-..." |
| OPENAI_API_BASE # Optional | OPENAI_API_BASE: "https://<YOUR_SITE>/v1" | export OPENAI_API_BASE="https://<YOUR_SITE>/v1" |
2.相关教程
#Run the script
python startup.py "Write a cli snake game"
#Do not hire an engineer to implement the project
python startup.py "Write a cli snake game" --implement False
#Hire an engineer and perform code reviews
python startup.py "Write a cli snake game" --code_review True
After running the script, you can find your new project in the workspace/ directory.
- Preference of Platform or Tool
You can tell which platform or tool you want to use when stating your requirements.
python startup.py "Write a cli snake game based on pygame"
- 使用指南
NAME
startup.py - We are a software startup comprised of AI. By investing in us, you are empowering a future filled with limitless possibilities.
SYNOPSIS
startup.py IDEA <flags>
DESCRIPTION
We are a software startup comprised of AI. By investing in us, you are empowering a future filled with limitless possibilities.
POSITIONAL ARGUMENTS
IDEA
Type: str
Your innovative idea, such as "Creating a snake game."
FLAGS
--investment=INVESTMENT
Type: float
Default: 3.0
As an investor, you have the opportunity to contribute a certain dollar amount to this AI company.
--n_round=N_ROUND
Type: int
Default: 5
NOTES
You can also use flags syntax for POSITIONAL ARGUMENTS
2.1 快速开始
It is difficult to install and configure the local environment for some users. The following tutorials will allow you to quickly experience the charm of MetaGPT.
Try it on Huggingface Space
- 相关链接
https://github.com/geekan/MetaGPT/assets/2707039/5e8c1062-8c35-440f-bb20-2b0320f8d27d
3.更多推荐:终端LLM AI模型:mlc-llm
大型语言模型的机器学习编译(MLC LLM)是一种高性能的通用部署解决方案,允许使用带有编译器加速的本机api来本地部署任何大型语言模型。这个项目的使命是让每个人都能使用ML编译技术在每个人的设备上开发、优化和部署人工智能模型。
项目链接:https://github.com/mlc-ai/mlc-llm
更多优质内容请关注公号:汀丶人工智能;会提供一些相关的资源和优质文章,免费获取阅读。
MetaGPT( The Multi-Agent Framework):颠覆AI开发的革命性多智能体元编程框架的更多相关文章
- AI开发利器:HiLens Studio技术解读
摘要:传统的AI应用开发和部署意味着高成本和高门槛,借助HiLens Studio,AI应用开发和部署仅需要三步. 曾几何时, 在我们青春年少时, 当我们看到某篇AI的技术文章时, 心中总不免想要在一 ...
- 整整十年 - Agent Framework for TypeScript 2.0
十年前,我发布了 Agent Framework for .NET 2.0 今天,Agent 又开始了新的旅程, 这次支持的语言是 TypeScript 2.0 上需求:init函数只能被调用一次 废 ...
- 关于Eclipse Modeling Framework 实现模型驱动开发,第一部分
======================================EMF第二篇文章========================= 用 Eclipse Modeling Framework ...
- [转]Net Framework引路蜂地图开发示例
From:http://www.2cto.com/kf/201207/140421.html 引路蜂地图也提供对.Net Framework平台的支持,可以开发桌面地图应用,由于Mono C#的跨平台 ...
- 微软Connect(); 2017大会梳理:Azure、数据、AI开发工具
在今天召开的 Connect(); 2017 开发者大会上,微软宣布了 Azure.数据.AI 开发工具的内容.这是第一天的 Connect(); 2017 的主题演讲. 在开场视频中霍金又来了.你记 ...
- [AI开发]将深度学习技术应用到实际项目
本文介绍如何将基于深度学习的目标检测算法应用到具体的项目开发中,体现深度学习技术在实际生产中的价值,算是AI算法的一个落地实现.本文算法部分可以参见前面几篇博客: [AI开发]Python+Tenso ...
- [AI开发]centOS7.5上基于keras/tensorflow深度学习环境搭建
这篇文章详细介绍在centOS7.5上搭建基于keras/tensorflow的深度学习环境,该环境可用于实际生产.本人现在非常熟练linux(Ubuntu/centOS/openSUSE).wind ...
- [AI开发]Python+Tensorflow打造自己的计算机视觉API服务
"与其停留在概念理论层面,不如动手去实现一个简单demo ." ——鲁迅 没有源码都是耍流氓github 前言 目前提供AI开发相关API接口的公司有很多,国外如微软. ...
- java通过百度AI开发平台提取身份证图片中的文字信息
废话不多说,直接上代码... IdCardDemo.java package com.wulss.baidubce; import java.io.BufferedReader; import jav ...
- 干货分享:五大最适合学习AI开发的编程语言
AI(人工智能)为应用开发者开创了一个全新的可能性.通过利用机器学习或深度学习,您可以生成更好的用户配置文件.个性化设置和推荐,或者整合更智能的搜索.语音界面或智能助手,或者以其他数种方式改进您的应用 ...
随机推荐
- 在DataGrid中实现Button Command绑定
在DataGrid中实现Button Command绑定 Command="{Binding editCommand}" 会默认查找UserList中对象的属性,而你的UserLi ...
- python+requests+unittest+htmltestrunner+Excel生成接口自动化的测试框架
Python+Requests+Unittest+Excel+HtmltestRunner生成自动化测试框架 流程 1.接口文档 2.读取接口文档 3.封装request的类 4.unittest类 ...
- Spark面试题(六)——Spark资源调优
Spark系列面试题 Spark面试题(一) Spark面试题(二) Spark面试题(三) Spark面试题(四) Spark面试题(五)--数据倾斜调优 Spark面试题(六)--Spark资源调 ...
- 从 AI 绘画到 ChatGPT,聊聊生成式 AI
我们小时候经常有幻想,未来不用再去上班了,在工厂工作的都是机器人.在家也不用打扫卫生,机器人可以包揽一切.不知不觉间,我们小时候的幻想已经慢慢变成现实,工厂里有了多种型号的机械臂,代替了部分流水线功能 ...
- 领域驱动设计(DDD)实践之路(二):事件驱动与CQRS
本文首发于 vivo互联网技术 微信公众号 链接: https://mp.weixin.qq.com/s/Z3uJhxJGDif3qN5OlE_woA作者:wenbo zhang [领域驱动设计实践之 ...
- node开发概述
一.Node开发概述 1. 为什么要学习服务器端开发 能够与后端程序员更加紧密的配合 网站业务逻辑前置,学习前端技术需要后端技术支撑(ajax) 扩宽知识视野,能够站在更高的角度审视整个项目 2. 服 ...
- C# 排序算法5:归并排序
归并排序,是将两个(或两个以上)有序表合并成一个新的有序表,即把待排序序列分为若干个有序的子序列,再把有序的子序列合并为整体有序序列.该算法是采用分治法. 原理: 1.申请空间,使其大小为两个已经排序 ...
- 简化 libevent 编译
在 CMakePresets.json 的 cacheVariables 字段加入 { "EVENT__DISABLE_OPENSSL": "ON", &quo ...
- Java开发者的Golang进修指南:从0->1带你实现协程池
在Java编程中,为了降低开销和优化程序的效率,我们常常使用线程池来管理线程的创建和销毁,并尽量复用已创建的对象.这样做不仅可以提高程序的运行效率,还能减少垃圾回收器对对象的回收次数. 在Golang ...
- Meta AI新发布的超大规模语言模型-OPT-175B
Meta AI在2022年5月3日新发布的OPT-175B模型,该模型是现阶段第一个模型参数超过千亿级别的开放模型,其次该模型与GPT-3相比,更加开放及便于访问. 具体开放性表现在如下几个方面: ...