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@ -12,14 +12,13 @@ # MetaGPT: The Multi-Agent Framework
<a href="docs/README_CN.md"><img src="https://img.shields.io/badge/文档-中文版-blue.svg" alt="CN doc"></a>
<a href="README.md"><img src="https://img.shields.io/badge/document-English-blue.svg" alt="EN doc"></a>
<a href="docs/README_JA.md"><img src="https://img.shields.io/badge/ドキュメント-日本語-blue.svg" alt="JA doc"></a>
<a href="https://discord.gg/wCp6Q3fsAk"><img src="https://img.shields.io/badge/Discord-Join-blue?logo=discord&logoColor=white&color=blue" alt="Discord Follow"></a>
<a href="https://discord.gg/DYn29wFk9z"><img src="https://dcbadge.vercel.app/api/server/DYn29wFk9z?style=flat" alt="Discord Follow"></a>
<a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/License-MIT-blue.svg" alt="License: MIT"></a>
<a href="docs/ROADMAP.md"><img src="https://img.shields.io/badge/ROADMAP-路线图-blue" alt="roadmap"></a>
<a href="https://twitter.com/MetaGPT_"><img src="https://img.shields.io/twitter/follow/MetaGPT?style=social" alt="Twitter Follow"></a>
</p>
<p align="center">
<a href="https://airtable.com/appInfdG0eJ9J4NNL/shrEd9DrwVE3jX6oz"><img src="https://img.shields.io/badge/AgentStore-Waitlist-ffc107?logoColor=white" alt="AgentStore Waitlist"></a>
<a href="https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/geekan/MetaGPT"><img src="https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode" alt="Open in Dev Containers"></a>
<a href="https://codespaces.new/geekan/MetaGPT"><img src="https://img.shields.io/badge/Github_Codespace-Open-blue?logo=github" alt="Open in GitHub Codespaces"></a>
<a href="https://huggingface.co/spaces/deepwisdom/MetaGPT" target="_blank"><img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20-Hugging%20Face-blue?color=blue&logoColor=white" /></a>
@ -33,132 +32,38 @@ # MetaGPT: The Multi-Agent Framework
<p align="center">Software Company Multi-Role Schematic (Gradually Implementing)</p>
## MetaGPT's Abilities
https://github.com/geekan/MetaGPT/assets/34952977/34345016-5d13-489d-b9f9-b82ace413419
## Install
## Examples (fully generated by GPT-4)
For example, if you type `python startup.py "Design a RecSys like Toutiao"`, you would get many outputs, one of them is data & api design
![Jinri Toutiao Recsys Data & API Design](docs/resources/workspace/content_rec_sys/resources/data_api_design.png)
It costs approximately **$0.2** (in GPT-4 API fees) to generate one example with analysis and design, and around **$2.0** for a full project.
## Installation
### Installation Video Guide
- [Matthew Berman: How To Install MetaGPT - Build A Startup With One Prompt!!](https://youtu.be/uT75J_KG_aY)
### Traditional Installation
### Pip installation
```bash
# 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 official website to install Node.js https://nodejs.org/ and then you will have npm tool in your computer.)
# Step 1: Ensure that Python 3.9+ is installed on your system. You can check this by using:
# You can use conda to initialize a new python env
# conda create -n metagpt python=3.9
# conda activate metagpt
python3 --version
# Step 2: Clone the repository to your local machine for latest version, and install it.
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT
pip3 install -e. # or pip3 install metagpt # for stable version
# Step 3: run the startup.py
# setup your OPENAI_API_KEY in key.yaml copy from config.yaml
python3 startup.py "Write a cli snake game"
# Step 4 [Optional]: If you want to save the artifacts like diagrams such as quadrant chart, system designs, sequence flow in the workspace, you can execute the step before Step 3. By default, the framework is compatible, and the entire process can be run completely without executing this step.
# If executing, 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 official 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:**
detail installation please refer to [cli_install](https://docs.deepwisdom.ai/guide/get_started/installation.html#install-stable-version)
- If already have Chrome, Chromium, or MS Edge installed, you can skip downloading Chromium by setting the environment variable
`PUPPETEER_SKIP_CHROMIUM_DOWNLOAD` to `true`.
- Some people are [having issues](https://github.com/mermaidjs/mermaid.cli/issues/15) installing this tool globally. Installing it locally is an alternative solution,
```bash
npm install @mermaid-js/mermaid-cli
```
- don't forget to the configuration for mmdc in config.yml
```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 running `pip install -e. --user`
- To convert Mermaid charts to SVG, PNG, and PDF formats. In addition to the Node.js version of Mermaid-CLI, you now have the option to use Python version Playwright, pyppeteer or mermaid.ink for this task.
- Playwright
- **Install Playwright**
```bash
pip install playwright
```
- **Install the Required Browsers**
to support PDF conversion, please install Chrominum.
```bash
playwright install --with-deps chromium
```
- **modify `config.yaml`**
uncomment MERMAID_ENGINE from config.yaml and change it to `playwright`
```yaml
MERMAID_ENGINE: playwright
```
- pyppeteer
- **Install pyppeteer**
```bash
pip install pyppeteer
```
- **Use your own Browsers**
pyppeteer allows you use installed browsers, please set the following envirment
```bash
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
```bash
pyppeteer-install
```
- **modify `config.yaml`**
uncomment MERMAID_ENGINE from config.yaml and change it to `pyppeteer`
```yaml
MERMAID_ENGINE: pyppeteer
```
- mermaid.ink
- **modify `config.yaml`**
uncomment MERMAID_ENGINE from config.yaml and change it to `ink`
```yaml
MERMAID_ENGINE: ink
```
Note: this method does not support pdf export.
### Installation by Docker
### Docker installation
> Note: In the Windows, you need to replace "/opt/metagpt" with a directory that Docker has permission to create, such as "D:\Users\x\metagpt"
```bash
# Step 1: Download metagpt official image and prepare config.yaml
@ -174,141 +79,41 @@ # Step 2: Run metagpt demo with container
-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:
detail installation please refer to [docker_install](https://docs.deepwisdom.ai/guide/get_started/installation.html#install-with-docker)
- Run in privileged mode to have permission to run the browser
- Map host configure file `/opt/metagpt/config/key.yaml` to container `/app/metagpt/config/key.yaml`
- Map host directory `/opt/metagpt/workspace` to container `/app/metagpt/workspace`
- Execute the demo command `python startup.py "Write a cli snake game"`
### QuickStart & Demo Video
- Try it on [MetaGPT Huggingface Space](https://huggingface.co/spaces/deepwisdom/MetaGPT)
- [Matthew Berman: How To Install MetaGPT - Build A Startup With One Prompt!!](https://youtu.be/uT75J_KG_aY)
- [Official Demo Video](https://github.com/geekan/MetaGPT/assets/2707039/5e8c1062-8c35-440f-bb20-2b0320f8d27d)
### Build image by yourself
https://github.com/geekan/MetaGPT/assets/34952977/34345016-5d13-489d-b9f9-b82ace413419
```bash
# You can also build metagpt image by yourself.
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT && docker build -t metagpt:custom .
```
## Tutorial
## Configuration
- 🗒 [Online Document](https://docs.deepwisdom.ai/)
- 💻 [Usage](https://docs.deepwisdom.ai/guide/get_started/quickstart.html)
- 🔎 [What can MetaGPT do?](https://docs.deepwisdom.ai/guide/get_started/introduction.html)
- 🛠 How to build your own agents?
- [MetaGPT Usage & Development Guide | Agent 101](https://docs.deepwisdom.ai/guide/tutorials/agent_101.html)
- [MetaGPT Usage & Development Guide | MultiAgent 101](https://docs.deepwisdom.ai/guide/tutorials/multi_agent_101.html)
- 🧑‍💻 Contribution
- [Develop Roadmap](docs/ROADMAP.md)
- 🔖 Use Cases
- [Debate](https://docs.deepwisdom.ai/guide/use_cases/multi_agent/debate.html)
- [Researcher](https://docs.deepwisdom.ai/guide/use_cases/agent/researcher.html)
- [Recepit Assistant](https://docs.deepwisdom.ai/guide/use_cases/agent/receipt_assistant.html)
- ❓ [FAQs](https://docs.deepwisdom.ai/guide/faq.html)
- Configure your `OPENAI_API_KEY` in any of `config/key.yaml / config/config.yaml / env`
- Priority order: `config/key.yaml > config/config.yaml > env`
## Support
```bash
# Copy the configuration file and make the necessary modifications.
cp config/config.yaml config/key.yaml
```
### Discard Join US
📢 Join Our [Discord Channel](https://discord.gg/ZRHeExS6xv)!
| 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" |
Looking forward to seeing you there! 🎉
## Tutorial: Initiating a startup
```shell
# 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.
```shell
python startup.py "Write a cli snake game based on pygame"
```
### Usage
```
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
```
### Code walkthrough
```python
from metagpt.software_company import SoftwareCompany
from metagpt.roles import ProjectManager, ProductManager, Architect, Engineer
async def startup(idea: str, investment: float = 3.0, n_round: int = 5):
"""Run a startup. Be a boss."""
company = SoftwareCompany()
company.hire([ProductManager(), Architect(), ProjectManager(), Engineer()])
company.invest(investment)
company.start_project(idea)
await company.run(n_round=n_round)
```
You can check `examples` for more details on single role (with knowledge base) and LLM only examples.
## QuickStart
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.
- [MetaGPT quickstart](https://deepwisdom.feishu.cn/wiki/CyY9wdJc4iNqArku3Lncl4v8n2b)
Try it on Huggingface Space
- https://huggingface.co/spaces/deepwisdom/MetaGPT
## Citation
For now, cite the [Arxiv paper](https://arxiv.org/abs/2308.00352):
```bibtex
@misc{hong2023metagpt,
title={MetaGPT: Meta Programming for Multi-Agent Collaborative Framework},
author={Sirui Hong and Xiawu Zheng and Jonathan Chen and Yuheng Cheng and Jinlin Wang and Ceyao Zhang and Zili Wang and Steven Ka Shing Yau and Zijuan Lin and Liyang Zhou and Chenyu Ran and Lingfeng Xiao and Chenglin Wu},
year={2023},
eprint={2308.00352},
archivePrefix={arXiv},
primaryClass={cs.AI}
}
```
## Contact Information
### Contact Information
If you have any questions or feedback about this project, please feel free to contact us. We highly appreciate your suggestions!
@ -317,13 +122,17 @@ ## Contact Information
We will respond to all questions within 2-3 business days.
## Demo
## Citation
https://github.com/geekan/MetaGPT/assets/2707039/5e8c1062-8c35-440f-bb20-2b0320f8d27d
For now, cite the [arXiv paper](https://arxiv.org/abs/2308.00352):
## Join us
📢 Join Our Discord Channel!
https://discord.gg/ZRHeExS6xv
Looking forward to seeing you there! 🎉
```bibtex
@misc{hong2023metagpt,
title={MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework},
author={Sirui Hong and Mingchen Zhuge and Jonathan Chen and Xiawu Zheng and Yuheng Cheng and Ceyao Zhang and Jinlin Wang and Zili Wang and Steven Ka Shing Yau and Zijuan Lin and Liyang Zhou and Chenyu Ran and Lingfeng Xiao and Chenglin Wu and Jürgen Schmidhuber},
year={2023},
eprint={2308.00352},
archivePrefix={arXiv},
primaryClass={cs.AI}
}
```

9
config/config.yaml
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@ -7,9 +7,9 @@
## Or, you can configure OPENAI_PROXY to access official OPENAI_API_BASE.
OPENAI_API_BASE: "https://api.openai.com/v1"
#OPENAI_PROXY: "http://127.0.0.1:8118"
#OPENAI_API_KEY: "YOUR_API_KEY"
OPENAI_API_MODEL: "gpt-4"
MAX_TOKENS: 1500
#OPENAI_API_KEY: "YOUR_API_KEY" # set the value to sk-xxx if you host the openai interface for open llm model
OPENAI_API_MODEL: "gpt-4-1106-preview"
MAX_TOKENS: 4096
RPM: 10
#### if Spark
@ -31,6 +31,9 @@ RPM: 10
#DEPLOYMENT_NAME: "YOUR_DEPLOYMENT_NAME"
#DEPLOYMENT_ID: "YOUR_DEPLOYMENT_ID"
#### if zhipuai from `https://open.bigmodel.cn`. You can set here or export API_KEY="YOUR_API_KEY"
# ZHIPUAI_API_KEY: "YOUR_API_KEY"
#### for Search
## Supported values: serpapi/google/serper/ddg

215
docs/README_CN.md
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@ -12,14 +12,13 @@ # MetaGPT: 多智能体框架
<a href="docs/README_CN.md"><img src="https://img.shields.io/badge/文档-中文版-blue.svg" alt="CN doc"></a>
<a href="README.md"><img src="https://img.shields.io/badge/document-English-blue.svg" alt="EN doc"></a>
<a href="docs/README_JA.md"><img src="https://img.shields.io/badge/ドキュメント-日本語-blue.svg" alt="JA doc"></a>
<a href="https://discord.gg/wCp6Q3fsAk"><img src="https://img.shields.io/badge/Discord-Join-blue?logo=discord&logoColor=white&color=blue" alt="Discord Follow"></a>
<a href="https://discord.gg/DYn29wFk9z"><img src="https://dcbadge.vercel.app/api/server/DYn29wFk9z?style=flat" alt="Discord Follow"></a>
<a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/License-MIT-blue.svg" alt="License: MIT"></a>
<a href="docs/ROADMAP.md"><img src="https://img.shields.io/badge/ROADMAP-路线图-blue" alt="roadmap"></a>
<a href="https://twitter.com/MetaGPT_"><img src="https://img.shields.io/twitter/follow/MetaGPT?style=social" alt="Twitter Follow"></a>
</p>
<p align="center">
<a href="https://airtable.com/appInfdG0eJ9J4NNL/shrEd9DrwVE3jX6oz"><img src="https://img.shields.io/badge/AgentStore-Waitlist-ffc107?logoColor=white" alt="AgentStore Waitlist"></a>
<a href="https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/geekan/MetaGPT"><img src="https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode" alt="Open in Dev Containers"></a>
<a href="https://codespaces.new/geekan/MetaGPT"><img src="https://img.shields.io/badge/Github_Codespace-Open-blue?logo=github" alt="Open in GitHub Codespaces"></a>
<a href="https://huggingface.co/spaces/deepwisdom/MetaGPT" target="_blank"><img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20-Hugging%20Face-blue?color=blue&logoColor=white" /></a>
@ -33,57 +32,35 @@ # MetaGPT: 多智能体框架
<p align="center">软件公司多角色示意图（正在逐步实现）</p>
## MetaGPT 的能力
https://github.com/geekan/MetaGPT/assets/34952977/34345016-5d13-489d-b9f9-b82ace413419
## 示例（均由 GPT-4 生成）
例如，键入`python startup.py "写个类似今日头条的推荐系统"`并回车，你会获得一系列输出，其一是数据结构与API设计
![今日头条 Recsys 数据 & API 设计](resources/workspace/content_rec_sys/resources/data_api_design.png)
这需要大约**0.2美元**（GPT-4 API的费用）来生成一个带有分析和设计的示例，大约2.0美元用于一个完整的项目
## 安装
### 传统安装
### Pip安装
```bash
# 第 1 步：确保您的系统上安装了 NPM。并使用npm安装mermaid-js
# 第 1 步：确保您的系统上安装了 Python 3.9+。您可以使用以下命令进行检查：
# 可以使用conda来初始化新的python环境
# conda create -n metagpt python=3.9
# conda activate metagpt
python3 --version
# 第 2 步：克隆最新仓库到您的本地机器，并进行安装。
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT
pip3 install -e. # 或者 pip3 install metagpt # 安装稳定版本
# 第 3 步：执行startup.py
# 拷贝config.yaml为key.yaml，并设置你自己的OPENAI_API_KEY
python3 startup.py "Write a cli snake game"
# 第 4 步【可选的】：如果你想在执行过程中保存像象限图、系统设计、序列流程等图表这些产物，可以在第3步前执行该步骤。默认的，框架做了兼容，在不执行该步的情况下，也可以完整跑完整个流程。
# 如果执行，确保您的系统上安装了 NPM。并使用npm安装mermaid-js
npm --version
sudo npm install -g @mermaid-js/mermaid-cli
# 第 2 步：确保您的系统上安装了 Python 3.9+。您可以使用以下命令进行检查：
python --version
# 第 3 步：克隆仓库到您的本地机器，并进行安装。
git clone https://github.com/geekan/metagpt
cd metagpt
pip install -e.
```
**注意：**
- 如果已经安装了Chrome、Chromium或MS Edge，可以通过将环境变量`PUPPETEER_SKIP_CHROMIUM_DOWNLOAD`设置为`true`来跳过下载Chromium。
- 一些人在全局安装此工具时遇到问题。在本地安装是替代解决方案，
```bash
npm install @mermaid-js/mermaid-cli
```
- 不要忘记在config.yml中为mmdc配置配置，
```yml
PUPPETEER_CONFIG: "./config/puppeteer-config.json"
MMDC: "./node_modules/.bin/mmdc"
```
- 如果`pip install -e.`失败并显示错误`[Errno 13] Permission denied: '/usr/local/lib/python3.11/dist-packages/test-easy-install-13129.write-test'`，请尝试使用`pip install -e. --user`运行。
详细的安装请安装 [cli_install](https://docs.deepwisdom.ai/guide/get_started/installation.html#install-stable-version)
### Docker安装
> 注意：在Windows中，你需要将 "/opt/metagpt" 替换为Docker具有创建权限的目录，比如"D:\Users\x\metagpt"
```bash
# 步骤1: 下载metagpt官方镜像并准备好config.yaml
@ -99,121 +76,41 @@ # 步骤2: 使用容器运行metagpt演示
-v /opt/metagpt/workspace:/app/metagpt/workspace \
metagpt/metagpt:latest \
python startup.py "Write a cli snake game"
# 您也可以启动一个容器并在其中执行命令
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"
```
`docker run ...`做了以下事情:
详细的安装请安装 [docker_install](https://docs.deepwisdom.ai/zhcn/guide/get_started/installation.html#%E4%BD%BF%E7%94%A8docker%E5%AE%89%E8%A3%85)
- 以特权模式运行，有权限运行浏览器
- 将主机文件 `/opt/metagpt/config/key.yaml` 映射到容器文件 `/app/metagpt/config/key.yaml`
- 将主机目录 `/opt/metagpt/workspace` 映射到容器目录 `/app/metagpt/workspace`
- 执行示例命令 `python startup.py "Write a cli snake game"`
### 快速开始的演示视频
- 在 [MetaGPT Huggingface Space](https://huggingface.co/spaces/deepwisdom/MetaGPT) 上进行体验
- [Matthew Berman: How To Install MetaGPT - Build A Startup With One Prompt!!](https://youtu.be/uT75J_KG_aY)
- [官方演示视频](https://github.com/geekan/MetaGPT/assets/2707039/5e8c1062-8c35-440f-bb20-2b0320f8d27d)
### 自己构建镜像
https://github.com/geekan/MetaGPT/assets/34952977/34345016-5d13-489d-b9f9-b82ace413419
```bash
# 您也可以自己构建metagpt镜像
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT && docker build -t metagpt:custom .
```
## 教程
- 🗒 [在线文档](https://docs.deepwisdom.ai/zhcn/)
- 💻 [如何使用](https://docs.deepwisdom.ai/zhcn/guide/get_started/quickstart.html)
- 🔎 [MetaGPT的能力及应用场景](https://docs.deepwisdom.ai/zhcn/guide/get_started/introduction.html)
- 🛠 如何构建你自己的智能体？
- [MetaGPT的使用和开发教程 | 智能体入门](https://docs.deepwisdom.ai/zhcn/guide/tutorials/agent_101.html)
- [MetaGPT的使用和开发教程 | 多智能体入门](https://docs.deepwisdom.ai/zhcn/guide/tutorials/multi_agent_101.html)
- 🧑‍💻 贡献
- [开发路线图](ROADMAP.md)
- 🔖 示例
- [辩论](https://docs.deepwisdom.ai/zhcn/guide/use_cases/multi_agent/debate.html)
- [调研员](https://docs.deepwisdom.ai/zhcn/guide/use_cases/agent/researcher.html)
- [票据助手](https://docs.deepwisdom.ai/zhcn/guide/use_cases/agent/receipt_assistant.html)
- ❓ [常见问题解答](https://docs.deepwisdom.ai/zhcn/guide/faq.html)
## 配置
## 支持
- 在 `config/key.yaml / config/config.yaml / env` 中配置您的 `OPENAI_API_KEY`
- 优先级顺序：`config/key.yaml > config/config.yaml > env`
### 加入我们
```bash
# 复制配置文件并进行必要的修改
cp config/config.yaml config/key.yaml
```
📢 加入我们的[Discord频道](https://discord.gg/ZRHeExS6xv)！
| 变量名 | config/key.yaml | env |
| ----------------------------------- | ----------------------------------------- | ----------------------------------------------- |
| OPENAI_API_KEY # 用您自己的密钥替换 | OPENAI_API_KEY: "sk-..." | export OPENAI_API_KEY="sk-..." |
| OPENAI_API_BASE # 可选 | OPENAI_API_BASE: "https://<YOUR_SITE>/v1" | export OPENAI_API_BASE="https://<YOUR_SITE>/v1" |
期待在那里与您相见！🎉
## 示例：启动一个创业公司
```shell
python startup.py "写一个命令行贪吃蛇"
# 开启code review模式会花费更多的金钱, 但是会提升代码质量和成功率
python startup.py "写一个命令行贪吃蛇" --code_review True
```
运行脚本后，您可以在 `workspace/` 目录中找到您的新项目。
### 平台或工具的倾向性
可以在阐述需求时说明想要使用的平台或工具。
例如：
```shell
python startup.py "写一个基于pygame的命令行贪吃蛇"
```
### 使用
```
名称
startup.py - 我们是一家AI软件创业公司。通过投资我们，您将赋能一个充满无限可能的未来。
概要
startup.py IDEA <flags>
描述
我们是一家AI软件创业公司。通过投资我们，您将赋能一个充满无限可能的未来。
位置参数
IDEA
类型: str
您的创新想法，例如"写一个命令行贪吃蛇。"
标志
--investment=INVESTMENT
类型: float
默认值: 3.0
作为投资者，您有机会向这家AI公司投入一定的美元金额。
--n_round=N_ROUND
类型: int
默认值: 5
备注
您也可以用`标志`的语法，来处理`位置参数`
```
### 代码实现
```python
from metagpt.software_company import SoftwareCompany
from metagpt.roles import ProjectManager, ProductManager, Architect, Engineer
async def startup(idea: str, investment: float = 3.0, n_round: int = 5):
"""运行一个创业公司。做一个老板"""
company = SoftwareCompany()
company.hire([ProductManager(), Architect(), ProjectManager(), Engineer()])
company.invest(investment)
company.start_project(idea)
await company.run(n_round=n_round)
```
你可以查看`examples`，其中有单角色（带知识库）的使用例子与仅LLM的使用例子。
## 快速体验
对一些用户来说，安装配置本地环境是有困难的，下面这些教程能够让你快速体验到MetaGPT的魅力。
- [MetaGPT快速体验](https://deepwisdom.feishu.cn/wiki/Q8ycw6J9tiNXdHk66MRcIN8Pnlg)
可直接在Huggingface Space体验
- https://huggingface.co/spaces/deepwisdom/MetaGPT
## 联系信息
### 联系信息
如果您对这个项目有任何问题或反馈，欢迎联系我们。我们非常欢迎您的建议！
@ -222,13 +119,17 @@ ## 联系信息
我们会在2-3个工作日内回复所有问题。
## 演示
## 引用
https://github.com/geekan/MetaGPT/assets/2707039/5e8c1062-8c35-440f-bb20-2b0320f8d27d
引用 [arXiv paper](https://arxiv.org/abs/2308.00352):
## 加入我们
📢 加入我们的Discord频道！
https://discord.gg/ZRHeExS6xv
期待在那里与您相见！🎉
```bibtex
@misc{hong2023metagpt,
title={MetaGPT: Meta Programming for Multi-Agent Collaborative Framework},
author={Sirui Hong and Xiawu Zheng and Jonathan Chen and Yuheng Cheng and Jinlin Wang and Ceyao Zhang and Zili Wang and Steven Ka Shing Yau and Zijuan Lin and Liyang Zhou and Chenyu Ran and Lingfeng Xiao and Chenglin Wu},
year={2023},
eprint={2308.00352},
archivePrefix={arXiv},
primaryClass={cs.AI}
}
```

33
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View file

@ -19,7 +19,6 @@ # MetaGPT: マルチエージェントフレームワーク
</p>
<p align="center">
<a href="https://airtable.com/appInfdG0eJ9J4NNL/shrEd9DrwVE3jX6oz"><img src="https://img.shields.io/badge/AgentStore-Waitlist-ffc107?logoColor=white" alt="AgentStore Waitlist"></a>
<a href="https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/geekan/MetaGPT"><img src="https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode" alt="Open in Dev Containers"></a>
<a href="https://codespaces.new/geekan/MetaGPT"><img src="https://img.shields.io/badge/Github_Codespace-Open-blue?logo=github" alt="Open in GitHub Codespaces"></a>
<a href="https://huggingface.co/spaces/deepwisdom/MetaGPT" target="_blank"><img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20-Hugging%20Face-blue?color=blue&logoColor=white" /></a>
@ -60,17 +59,22 @@ ### インストールビデオガイド
### 伝統的なインストール
```bash
# ステップ 1: NPM がシステムにインストールされていることを確認してください。次に mermaid-js をインストールします。(お使いのコンピューターに npm がない場合は、Node.js 公式サイトで Node.js https://nodejs.org/ をインストールしてください。）
npm --version
sudo npm install -g @mermaid-js/mermaid-cli
# ステップ 2: Python 3.9+ がシステムにインストールされていることを確認してください。これを確認するには:
# ステップ 1: Python 3.9+ がシステムにインストールされていることを確認してください。これを確認するには:
python --version
# ステップ 3: リポジトリをローカルマシンにクローンし、インストールする。
git clone https://github.com/geekan/metagpt
cd metagpt
# ステップ 2: リポジトリをローカルマシンにクローンし、インストールする。
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT
pip install -e.
# ステップ 3: startup.py を実行する
# config.yaml を key.yaml にコピーし、独自の OPENAI_API_KEY を設定します
python3 startup.py "Write a cli snake game"
# ステップ 4 [オプション]: 実行中に PRD ファイルなどのアーティファクトを保存する場合は、ステップ 3 の前にこのステップを実行できます。デフォルトでは、フレームワークには互換性があり、この手順を実行しなくてもプロセス全体を完了できます。
# NPM がシステムにインストールされていることを確認してください。次に mermaid-js をインストールします。(お使いのコンピューターに npm がない場合は、Node.js 公式サイトで Node.js https://nodejs.org/ をインストールしてください。）
npm --version
sudo npm install -g @mermaid-js/mermaid-cli
```
**注:**
@ -159,6 +163,7 @@ # ステップ 3: リポジトリをローカルマシンにクローンし、
注: この方法は pdf エクスポートに対応していません。
### Docker によるインストール
> Windowsでは、"/opt/metagpt"をDockerが作成する権限を持つディレクトリに置き換える必要があります。例えば、"D:\Users\x\metagpt"などです。
```bash
# ステップ 1: metagpt 公式イメージをダウンロードし、config.yaml を準備する
@ -270,12 +275,12 @@ ### 使用方法
### コードウォークスルー
```python
from metagpt.software_company import SoftwareCompany
from metagpt.team import Team
from metagpt.roles import ProjectManager, ProductManager, Architect, Engineer
async def startup(idea: str, investment: float = 3.0, n_round: int = 5):
"""スタートアップを実行する。ボスになる。"""
company = SoftwareCompany()
company = Team()
company.hire([ProductManager(), Architect(), ProjectManager(), Engineer()])
company.invest(investment)
company.start_project(idea)
@ -295,12 +300,12 @@ ## クイックスタート
## 引用
現時点では、[Arxiv 論文](https://arxiv.org/abs/2308.00352)を引用してください:
現時点では、[arXiv 論文](https://arxiv.org/abs/2308.00352)を引用してください:
```bibtex
@misc{hong2023metagpt,
title={MetaGPT: Meta Programming for Multi-Agent Collaborative Framework},
author={Sirui Hong and Xiawu Zheng and Jonathan Chen and Yuheng Cheng and Jinlin Wang and Ceyao Zhang and Zili Wang and Steven Ka Shing Yau and Zijuan Lin and Liyang Zhou and Chenyu Ran and Lingfeng Xiao and Chenglin Wu},
title={MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework},
author={Sirui Hong and Mingchen Zhuge and Jonathan Chen and Xiawu Zheng and Yuheng Cheng and Ceyao Zhang and Jinlin Wang and Zili Wang and Steven Ka Shing Yau and Zijuan Lin and Liyang Zhou and Chenyu Ran and Lingfeng Xiao and Chenglin Wu and Jürgen Schmidhuber},
year={2023},
eprint={2308.00352},
archivePrefix={arXiv},

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@ -0,0 +1,109 @@
## Traditional Command Line Installation
### Support System and version
| System Version | Python Version | Supported |
| ---- | ---- | ----- |
| macOS 13.x | python 3.9 | Yes |
| Windows 11 | python 3.9 | Yes |
| Ubuntu 22.04 | python 3.9 | Yes |
### Detail Installation
```bash
# 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 official 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:
python3 --version
# Step 3: Clone the repository to your local machine, and install it.
git clone https://github.com/geekan/MetaGPT.git
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_DOWNLOAD` to `true`.
- Some people are [having issues](https://github.com/mermaidjs/mermaid.cli/issues/15) installing this tool globally. Installing it locally is an alternative solution,
```bash
npm install @mermaid-js/mermaid-cli
```
- don't forget to the configuration for mmdc in config.yml
```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 running `pip install -e. --user`
- To convert Mermaid charts to SVG, PNG, and PDF formats. In addition to the Node.js version of Mermaid-CLI, you now have the option to use Python version Playwright, pyppeteer or mermaid.ink for this task.
- Playwright
- **Install Playwright**
```bash
pip install playwright
```
- **Install the Required Browsers**
to support PDF conversion, please install Chrominum.
```bash
playwright install --with-deps chromium
```
- **modify `config.yaml`**
uncomment MERMAID_ENGINE from config.yaml and change it to `playwright`
```yaml
MERMAID_ENGINE: playwright
```
- pyppeteer
- **Install pyppeteer**
```bash
pip install pyppeteer
```
- **Use your own Browsers**
pyppeteer allows you use installed browsers, please set the following envirment
```bash
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
```bash
pyppeteer-install
```
- **modify `config.yaml`**
uncomment MERMAID_ENGINE from config.yaml and change it to `pyppeteer`
```yaml
MERMAID_ENGINE: pyppeteer
```
- mermaid.ink
- **modify `config.yaml`**
uncomment MERMAID_ENGINE from config.yaml and change it to `ink`
```yaml
MERMAID_ENGINE: ink
```
Note: this method does not support pdf export.

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@ -0,0 +1,43 @@
## 命令行安装
### 支持的系统和版本
| 系统版本 | Python 版本 | 是否支持 |
| ---- | ---- | ----- |
| macOS 13.x | python 3.9 | 是 |
| Windows 11 | python 3.9 | 是 |
| Ubuntu 22.04 | python 3.9 | 是 |
### 详细安装
```bash
# 第 1 步：确保您的系统上安装了 NPM。并使用npm安装mermaid-js
npm --version
sudo npm install -g @mermaid-js/mermaid-cli
# 第 2 步：确保您的系统上安装了 Python 3.9+。您可以使用以下命令进行检查：
python --version
# 第 3 步：克隆仓库到您的本地机器，并进行安装。
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT
pip install -e.
```
**注意：**
- 如果已经安装了Chrome、Chromium或MS Edge，可以通过将环境变量`PUPPETEER_SKIP_CHROMIUM_DOWNLOAD`设置为`true`来跳过下载Chromium。
- 一些人在全局安装此工具时遇到问题。在本地安装是替代解决方案，
```bash
npm install @mermaid-js/mermaid-cli
```
- 不要忘记在config.yml中为mmdc配置配置，
```yml
PUPPETEER_CONFIG: "./config/puppeteer-config.json"
MMDC: "./node_modules/.bin/mmdc"
```
- 如果`pip install -e.`失败并显示错误`[Errno 13] Permission denied: '/usr/local/lib/python3.11/dist-packages/test-easy-install-13129.write-test'`，请尝试使用`pip install -e. --user`运行。

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@ -0,0 +1,44 @@
## Docker Installation
### Use default MetaGPT image
```bash
# 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 \
python3 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
$ python3 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 configure file `/opt/metagpt/config/key.yaml` to container `/app/metagpt/config/key.yaml`
- Map host directory `/opt/metagpt/workspace` to container `/app/metagpt/workspace`
- Execute the demo command `python3 startup.py "Write a cli snake game"`
### Build image by yourself
```bash
# You can also build metagpt image by yourself.
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT && docker build -t metagpt:custom .
```

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@ -0,0 +1,44 @@
## Docker安装
### 使用MetaGPT镜像
```bash
# 步骤1: 下载metagpt官方镜像并准备好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 # 修改配置文件
# 步骤2: 使用容器运行metagpt演示
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"
# 您也可以启动一个容器并在其中执行命令
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"
```
`docker run ...`做了以下事情:
- 以特权模式运行，有权限运行浏览器
- 将主机文件 `/opt/metagpt/config/key.yaml` 映射到容器文件 `/app/metagpt/config/key.yaml`
- 将主机目录 `/opt/metagpt/workspace` 映射到容器目录 `/app/metagpt/workspace`
- 执行示例命令 `python startup.py "Write a cli snake game"`
### 自己构建镜像
```bash
# 您也可以自己构建metagpt镜像
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT && docker build -t metagpt:custom .
```

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@ -0,0 +1,67 @@
## MetaGPT Usage
### Configuration
- Configure your `OPENAI_API_KEY` in any of `config/key.yaml / config/config.yaml / env`
- Priority order: `config/key.yaml > config/config.yaml > env`
```bash
# 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" |
### Initiating a startup
```shell
# 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.
```shell
python startup.py "Write a cli snake game based on pygame"
```
### Usage
```
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
```

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@ -0,0 +1,63 @@
## MetaGPT 使用
### 配置
- 在 `config/key.yaml / config/config.yaml / env` 中配置您的 `OPENAI_API_KEY`
- 优先级顺序：`config/key.yaml > config/config.yaml > env`
```bash
# 复制配置文件并进行必要的修改
cp config/config.yaml config/key.yaml
```
| 变量名 | config/key.yaml | env |
| ----------------------------------- | ----------------------------------------- | ----------------------------------------------- |
| OPENAI_API_KEY # 用您自己的密钥替换 | OPENAI_API_KEY: "sk-..." | export OPENAI_API_KEY="sk-..." |
| OPENAI_API_BASE # 可选 | OPENAI_API_BASE: "https://<YOUR_SITE>/v1" | export OPENAI_API_BASE="https://<YOUR_SITE>/v1" |
### 示例：启动一个创业公司
```shell
python startup.py "写一个命令行贪吃蛇"
# 开启code review模式会花费更多的金钱, 但是会提升代码质量和成功率
python startup.py "写一个命令行贪吃蛇" --code_review True
```
运行脚本后，您可以在 `workspace/` 目录中找到您的新项目。
### 平台或工具的倾向性
可以在阐述需求时说明想要使用的平台或工具。
例如：
```shell
python startup.py "写一个基于pygame的命令行贪吃蛇"
```
### 使用
```
名称
startup.py - 我们是一家AI软件创业公司。通过投资我们，您将赋能一个充满无限可能的未来。
概要
startup.py IDEA <flags>
描述
我们是一家AI软件创业公司。通过投资我们，您将赋能一个充满无限可能的未来。
位置参数
IDEA
类型: str
您的创新想法，例如"写一个命令行贪吃蛇。"
标志
--investment=INVESTMENT
类型: float
默认值: 3.0
作为投资者，您有机会向这家AI公司投入一定的美元金额。
--n_round=N_ROUND
类型: int
默认值: 5
备注
您也可以用`标志`的语法，来处理`位置参数`
```

7
examples/agent_creator.py
View file

@ -6,12 +6,13 @@ Author: garylin2099
import re
from metagpt.actions import Action
from metagpt.const import PROJECT_ROOT, WORKSPACE_ROOT
from metagpt.config import CONFIG
from metagpt.const import METAGPT_ROOT
from metagpt.logs import logger
from metagpt.roles import Role
from metagpt.schema import Message
with open(PROJECT_ROOT / "examples/build_customized_agent.py", "r") as f:
with open(METAGPT_ROOT / "examples/build_customized_agent.py", "r") as f:
# use official example script to guide AgentCreator
MULTI_ACTION_AGENT_CODE_EXAMPLE = f.read()
@ -48,7 +49,7 @@ class CreateAgent(Action):
pattern = r"```python(.*)```"
match = re.search(pattern, rsp, re.DOTALL)
code_text = match.group(1) if match else ""
with open(WORKSPACE_ROOT / "agent_created_agent.py", "w") as f:
with open(CONFIG.workspace_path / "agent_created_agent.py", "w") as f:
f.write(code_text)
return code_text

59
examples/build_customized_agent.py
View file

@ -10,6 +10,7 @@ import subprocess
import fire
from metagpt.actions import Action
from metagpt.llm import LLM
from metagpt.logs import logger
from metagpt.roles import Role
from metagpt.schema import Message
@ -19,19 +20,10 @@ class SimpleWriteCode(Action):
PROMPT_TEMPLATE = """
Write a python function that can {instruction} and provide two runnnable test cases.
Return ```python your_code_here ``` with NO other texts,
example:
```python
# function
def add(a, b):
return a + b
# test cases
print(add(1, 2))
print(add(3, 4))
```
your code:
"""
def __init__(self, name="SimpleWriteCode", context=None, llm=None):
def __init__(self, name: str = "SimpleWriteCode", context=None, llm: LLM = None):
super().__init__(name, context, llm)
async def run(self, instruction: str):
@ -52,7 +44,7 @@ class SimpleWriteCode(Action):
class SimpleRunCode(Action):
def __init__(self, name="SimpleRunCode", context=None, llm=None):
def __init__(self, name: str = "SimpleRunCode", context=None, llm: LLM = None):
super().__init__(name, context, llm)
async def run(self, code_text: str):
@ -74,13 +66,11 @@ class SimpleCoder(Role):
async def _act(self) -> Message:
logger.info(f"{self._setting}: ready to {self._rc.todo}")
todo = self._rc.todo
todo = self._rc.todo # todo will be SimpleWriteCode()
msg = self._rc.memory.get()[-1] # retrieve the latest memory
instruction = msg.content
code_text = await SimpleWriteCode().run(instruction)
msg = Message(content=code_text, role=self.profile, cause_by=todo)
msg = self.get_memories(k=1)[0] # find the most recent messages
code_text = await todo.run(msg.content)
msg = Message(content=code_text, role=self.profile, cause_by=type(todo))
return msg
@ -94,44 +84,23 @@ class RunnableCoder(Role):
):
super().__init__(name, profile, **kwargs)
self._init_actions([SimpleWriteCode, SimpleRunCode])
async def _think(self) -> None:
if self._rc.todo is None:
self._set_state(0)
return
if self._rc.state + 1 < len(self._states):
self._set_state(self._rc.state + 1)
else:
self._rc.todo = None
self._set_react_mode(react_mode="by_order")
async def _act(self) -> Message:
logger.info(f"{self._setting}: ready to {self._rc.todo}")
# By choosing the Action by order under the hood
# todo will be first SimpleWriteCode() then SimpleRunCode()
todo = self._rc.todo
msg = self._rc.memory.get()[-1]
if isinstance(todo, SimpleWriteCode):
instruction = msg.content
result = await SimpleWriteCode().run(instruction)
msg = self.get_memories(k=1)[0] # find the most k recent messages
result = await todo.run(msg.content)
elif isinstance(todo, SimpleRunCode):
code_text = msg.content
result = await SimpleRunCode().run(code_text)
msg = Message(content=result, role=self.profile, cause_by=todo)
msg = Message(content=result, role=self.profile, cause_by=type(todo))
self._rc.memory.add(msg)
return msg
async def _react(self) -> Message:
while True:
await self._think()
if self._rc.todo is None:
break
await self._act()
return Message(content="All job done", role=self.profile)
def main(msg="write a function that calculates the sum of a list"):
def main(msg="write a function that calculates the product of a list and run it"):
# role = SimpleCoder()
role = RunnableCoder()
logger.info(msg)

155
examples/build_customized_multi_agents.py Normal file
View file

@ -0,0 +1,155 @@
"""
Filename: MetaGPT/examples/build_customized_multi_agents.py
Created Date: Wednesday, November 15th 2023, 7:12:39 pm
Author: garylin2099
"""
import re
import fire
from metagpt.actions import Action, UserRequirement
from metagpt.llm import LLM
from metagpt.logs import logger
from metagpt.roles import Role
from metagpt.schema import Message
from metagpt.team import Team
def parse_code(rsp):
pattern = r"```python(.*)```"
match = re.search(pattern, rsp, re.DOTALL)
code_text = match.group(1) if match else rsp
return code_text
class SimpleWriteCode(Action):
PROMPT_TEMPLATE = """
Write a python function that can {instruction}.
Return ```python your_code_here ``` with NO other texts,
your code:
"""
def __init__(self, name: str = "SimpleWriteCode", context=None, llm: LLM = None):
super().__init__(name, context, llm)
async def run(self, instruction: str):
prompt = self.PROMPT_TEMPLATE.format(instruction=instruction)
rsp = await self._aask(prompt)
code_text = parse_code(rsp)
return code_text
class SimpleCoder(Role):
def __init__(
self,
name: str = "Alice",
profile: str = "SimpleCoder",
**kwargs,
):
super().__init__(name, profile, **kwargs)
self._watch([UserRequirement])
self._init_actions([SimpleWriteCode])
class SimpleWriteTest(Action):
PROMPT_TEMPLATE = """
Context: {context}
Write {k} unit tests using pytest for the given function, assuming you have imported it.
Return ```python your_code_here ``` with NO other texts,
your code:
"""
def __init__(self, name: str = "SimpleWriteTest", context=None, llm: LLM = None):
super().__init__(name, context, llm)
async def run(self, context: str, k: int = 3):
prompt = self.PROMPT_TEMPLATE.format(context=context, k=k)
rsp = await self._aask(prompt)
code_text = parse_code(rsp)
return code_text
class SimpleTester(Role):
def __init__(
self,
name: str = "Bob",
profile: str = "SimpleTester",
**kwargs,
):
super().__init__(name, profile, **kwargs)
self._init_actions([SimpleWriteTest])
# self._watch([SimpleWriteCode])
self._watch([SimpleWriteCode, SimpleWriteReview]) # feel free to try this too
async def _act(self) -> Message:
logger.info(f"{self._setting}: ready to {self._rc.todo}")
todo = self._rc.todo
# context = self.get_memories(k=1)[0].content # use the most recent memory as context
context = self.get_memories() # use all memories as context
code_text = await todo.run(context, k=5) # specify arguments
msg = Message(content=code_text, role=self.profile, cause_by=type(todo))
return msg
class SimpleWriteReview(Action):
PROMPT_TEMPLATE = """
Context: {context}
Review the test cases and provide one critical comments:
"""
def __init__(self, name: str = "SimpleWriteReview", context=None, llm: LLM = None):
super().__init__(name, context, llm)
async def run(self, context: str):
prompt = self.PROMPT_TEMPLATE.format(context=context)
rsp = await self._aask(prompt)
return rsp
class SimpleReviewer(Role):
def __init__(
self,
name: str = "Charlie",
profile: str = "SimpleReviewer",
**kwargs,
):
super().__init__(name, profile, **kwargs)
self._init_actions([SimpleWriteReview])
self._watch([SimpleWriteTest])
async def main(
idea: str = "write a function that calculates the product of a list",
investment: float = 3.0,
n_round: int = 5,
add_human: bool = False,
):
logger.info(idea)
team = Team()
team.hire(
[
SimpleCoder(),
SimpleTester(),
SimpleReviewer(is_human=add_human),
]
)
team.invest(investment=investment)
team.start_project(idea)
await team.run(n_round=n_round)
if __name__ == "__main__":
fire.Fire(main)

104
examples/debate.py
View file

@ -10,16 +10,15 @@ import platform
import fire
from metagpt.actions import Action, BossRequirement
from metagpt.actions import Action, UserRequirement
from metagpt.logs import logger
from metagpt.roles import Role
from metagpt.schema import Message
from metagpt.software_company import SoftwareCompany
from metagpt.utils.common import any_to_str
from metagpt.team import Team
class ShoutOut(Action):
"""Action: Shout out loudly in a debate (quarrel)"""
class SpeakAloud(Action):
"""Action: Speak out aloud in a debate (quarrel)"""
PROMPT_TEMPLATE = """
## BACKGROUND
@ -32,7 +31,7 @@ class ShoutOut(Action):
craft a strong and emotional response in 80 words, in {name}'s rhetoric and viewpoints, your will argue:
"""
def __init__(self, name="ShoutOut", context=None, llm=None):
def __init__(self, name="SpeakAloud", context=None, llm=None):
super().__init__(name, context, llm)
async def run(self, context: str, name: str, opponent_name: str):
@ -44,18 +43,18 @@ class ShoutOut(Action):
return rsp
class Trump(Role):
class Debator(Role):
def __init__(
self,
name: str = "Trump",
profile: str = "Republican",
name: str,
profile: str,
opponent_name: str,
**kwargs,
):
super().__init__(name, profile, **kwargs)
self._init_actions([ShoutOut])
self._watch([ShoutOut])
self.name = "Trump"
self.opponent_name = "Biden"
self._init_actions([SpeakAloud])
self._watch([UserRequirement, SpeakAloud])
self.opponent_name = opponent_name
async def _observe(self) -> int:
await super()._observe()
@ -65,80 +64,35 @@ class Trump(Role):
async def _act(self) -> Message:
logger.info(f"{self._setting}: ready to {self._rc.todo}")
todo = self._rc.todo # An instance of SpeakAloud
msg_history = self._rc.memory.get_by_actions([ShoutOut])
context = []
for m in msg_history:
context.append(str(m))
context = "\n".join(context)
memories = self.get_memories()
context = "\n".join(f"{msg.sent_from}: {msg.content}" for msg in memories)
# print(context)
rsp = await ShoutOut().run(context=context, name=self.name, opponent_name=self.opponent_name)
rsp = await todo.run(context=context, name=self.name, opponent_name=self.opponent_name)
msg = Message(
content=rsp,
role=self.profile,
cause_by=ShoutOut,
cause_by=type(todo),
sent_from=self.name,
send_to=self.opponent_name,
)
self._rc.memory.add(msg)
return msg
class Biden(Role):
def __init__(
self,
name: str = "Biden",
profile: str = "Democrat",
**kwargs,
):
super().__init__(name, profile, **kwargs)
self._init_actions([ShoutOut])
self._watch([BossRequirement, ShoutOut])
self.name = "Biden"
self.opponent_name = "Trump"
async def _observe(self) -> int:
await super()._observe()
# accept the very first human instruction (the debate topic) or messages sent (from opponent) to self,
# disregard own messages from the last round
self._rc.news = [
msg for msg in self._rc.news if msg.cause_by == any_to_str(BossRequirement) or msg.send_to == {self.name}
]
return len(self._rc.news)
async def _act(self) -> Message:
logger.info(f"{self._setting}: ready to {self._rc.todo}")
msg_history = self._rc.memory.get_by_actions([BossRequirement, ShoutOut])
context = []
for m in msg_history:
context.append(str(m))
context = "\n".join(context)
rsp = await ShoutOut().run(context=context, name=self.name, opponent_name=self.opponent_name)
msg = Message(
content=rsp,
role=self.profile,
cause_by=ShoutOut,
sent_from=self.name,
send_to=self.opponent_name,
)
return msg
async def startup(
idea: str, investment: float = 3.0, n_round: int = 5, code_review: bool = False, run_tests: bool = False
):
"""We reuse the startup paradigm for roles to interact with each other.
Now we run a startup of presidents and watch they quarrel. :)"""
company = SoftwareCompany()
company.hire([Biden(), Trump()])
company.invest(investment)
company.start_project(idea)
await company.run(n_round=n_round)
async def debate(idea: str, investment: float = 3.0, n_round: int = 5):
"""Run a team of presidents and watch they quarrel. :)"""
Biden = Debator(name="Biden", profile="Democrat", opponent_name="Trump")
Trump = Debator(name="Trump", profile="Republican", opponent_name="Biden")
team = Team()
team.hire([Biden, Trump])
team.invest(investment)
team.run_project(idea, send_to="Biden") # send debate topic to Biden and let him speak first
await team.run(n_round=n_round)
def main(idea: str, investment: float = 3.0, n_round: int = 10):
@ -151,7 +105,7 @@ def main(idea: str, investment: float = 3.0, n_round: int = 10):
"""
if platform.system() == "Windows":
asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
asyncio.run(startup(idea, investment, n_round))
asyncio.run(debate(idea, investment, n_round))
if __name__ == "__main__":

10
examples/sk_agent.py
View file

@ -13,7 +13,7 @@ from semantic_kernel.planning import SequentialPlanner
# from semantic_kernel.planning import SequentialPlanner
from semantic_kernel.planning.action_planner.action_planner import ActionPlanner
from metagpt.actions import BossRequirement
from metagpt.actions import UserRequirement
from metagpt.const import SKILL_DIRECTORY
from metagpt.roles.sk_agent import SkAgent
from metagpt.schema import Message
@ -39,7 +39,7 @@ async def basic_planner_example():
role.import_semantic_skill_from_directory(SKILL_DIRECTORY, "WriterSkill")
role.import_skill(TextSkill(), "TextSkill")
# using BasicPlanner
await role.run(Message(content=task, cause_by=BossRequirement))
await role.run(Message(content=task, cause_by=UserRequirement))
async def sequential_planner_example():
@ -53,7 +53,7 @@ async def sequential_planner_example():
role.import_semantic_skill_from_directory(SKILL_DIRECTORY, "WriterSkill")
role.import_skill(TextSkill(), "TextSkill")
# using BasicPlanner
await role.run(Message(content=task, cause_by=BossRequirement))
await role.run(Message(content=task, cause_by=UserRequirement))
async def basic_planner_web_search_example():
@ -64,7 +64,7 @@ async def basic_planner_web_search_example():
role.import_skill(SkSearchEngine(), "WebSearchSkill")
# role.import_semantic_skill_from_directory(skills_directory, "QASkill")
await role.run(Message(content=task, cause_by=BossRequirement))
await role.run(Message(content=task, cause_by=UserRequirement))
async def action_planner_example():
@ -75,7 +75,7 @@ async def action_planner_example():
role.import_skill(TimeSkill(), "time")
role.import_skill(TextSkill(), "text")
task = "What is the sum of 110 and 990?"
await role.run(Message(content=task, cause_by=BossRequirement)) # it will choose mathskill.Add
await role.run(Message(content=task, cause_by=UserRequirement)) # it will choose mathskill.Add
if __name__ == "__main__":

4
metagpt/actions/__init__.py
View file

@ -9,7 +9,7 @@ from enum import Enum
from metagpt.actions.action import Action
from metagpt.actions.action_output import ActionOutput
from metagpt.actions.add_requirement import BossRequirement
from metagpt.actions.add_requirement import UserRequirement
from metagpt.actions.debug_error import DebugError
from metagpt.actions.design_api import WriteDesign
from metagpt.actions.design_api_review import DesignReview
@ -28,7 +28,7 @@ from metagpt.actions.write_test import WriteTest
class ActionType(Enum):
"""All types of Actions, used for indexing."""
ADD_REQUIREMENT = BossRequirement
ADD_REQUIREMENT = UserRequirement
WRITE_PRD = WritePRD
WRITE_PRD_REVIEW = WritePRDReview
WRITE_DESIGN = WriteDesign

4
metagpt/actions/action.py
View file

@ -30,6 +30,10 @@ class Action(ABC):
self.desc = ""
self.content = ""
self.instruct_content = None
self.env = None
def set_env(self, env):
self.env = env
def set_prefix(self, prefix, profile):
"""Set prefix for later usage"""

4
metagpt/actions/add_requirement.py
View file

@ -8,8 +8,8 @@
from metagpt.actions import Action
class BossRequirement(Action):
"""Boss Requirement without any implementation details"""
class UserRequirement(Action):
"""User Requirement without any implementation details"""
async def run(self, *args, **kwargs):
raise NotImplementedError

12
metagpt/actions/debug_error.py
View file

@ -51,7 +51,9 @@ class DebugError(Action):
super().__init__(name, context, llm)
async def run(self, *args, **kwargs) -> str:
output_doc = await FileRepository.get_file(filename=self.context.output_filename, relative_path=TEST_OUTPUTS_FILE_REPO)
output_doc = await FileRepository.get_file(
filename=self.context.output_filename, relative_path=TEST_OUTPUTS_FILE_REPO
)
if not output_doc:
return ""
output_detail = RunCodeResult.loads(output_doc.content)
@ -61,10 +63,14 @@ class DebugError(Action):
return ""
logger.info(f"Debug and rewrite {self.context.code_filename}")
code_doc = await FileRepository.get_file(filename=self.context.code_filename, relative_path=CONFIG.src_workspace)
code_doc = await FileRepository.get_file(
filename=self.context.code_filename, relative_path=CONFIG.src_workspace
)
if not code_doc:
return ""
test_doc = await FileRepository.get_file(filename=self.context.test_filename, relative_path=TEST_CODES_FILE_REPO)
test_doc = await FileRepository.get_file(
filename=self.context.test_filename, relative_path=TEST_CODES_FILE_REPO
)
if not test_doc:
return ""
prompt = PROMPT_TEMPLATE.format(code=code_doc.content, test_code=test_doc.content, logs=output_detail.stderr)

117
metagpt/actions/design_api.py
View file

@ -37,21 +37,21 @@ templates = {
## Format example
{format_example}
-----
Role: You are an architect; the goal is to design a SOTA PEP8-compliant python system; make the best use of good open source tools
Role: You are an architect; the goal is to design a SOTA PEP8-compliant python system
Language: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.
Requirement: Fill in the following missing information based on the context, each section name is a key in json
Max Output: 8192 chars or 2048 tokens. Try to use them up.
## Implementation approach: Provide as Plain text. Analyze the difficult points of the requirements, select the appropriate open-source framework.
## Implementation approach: Provide as Plain text. Analyze the difficult points of the requirements, select appropriate open-source frameworks.
## Python package name: Provide as Python str with python triple quoto, concise and clear, characters only use a combination of all lowercase and underscores
## project_name: Provide as Plain text, concise and clear, characters only use a combination of all lowercase and underscores
## File list: Provided as Python list[str], the list of ONLY REQUIRED files needed to write the program(LESS IS MORE!). Only need relative paths, comply with PEP8 standards. ALWAYS write a main.py or app.py here
## File list: Provided as Python list[str], the list of files needed (including HTML & CSS IF NEEDED) to write the program. Only need relative paths. ALWAYS write a main.py or app.py here
## Data structures and interface definitions: Use mermaid classDiagram code syntax, including classes (INCLUDING __init__ method) and functions (with type annotations), CLEARLY MARK the RELATIONSHIPS between classes, and comply with PEP8 standards. The data structures SHOULD BE VERY DETAILED and the API should be comprehensive with a complete design.
## Data structures and interfaces: Use mermaid classDiagram code syntax, including classes (INCLUDING __init__ method) and functions (with type annotations), CLEARLY MARK the RELATIONSHIPS between classes, and comply with PEP8 standards. The data structures SHOULD BE VERY DETAILED and the API should be comprehensive with a complete design.
## Program call flow: Use sequenceDiagram code syntax, COMPLETE and VERY DETAILED, using CLASSES AND API DEFINED ABOVE accurately, covering the CRUD AND INIT of each object, SYNTAX MUST BE CORRECT.
## Anything UNCLEAR: Provide as Plain text. Make clear here.
## Anything UNCLEAR: Provide as Plain text. Try to clarify it.
output a properly formatted JSON, wrapped inside [CONTENT][/CONTENT] like format example,
and only output the json inside this tag, nothing else
@ -60,9 +60,9 @@ and only output the json inside this tag, nothing else
[CONTENT]
{
"Implementation approach": "We will ...",
"Python package name": "snake_game",
"project_name": "snake_game",
"File list": ["main.py"],
"Data structures and interface definitions": '
"Data structures and interfaces": '
classDiagram
class Game{
+int score
@ -90,21 +90,21 @@ and only output the json inside this tag, nothing else
{format_example}
-----
Role: You are an architect; the goal is to design a SOTA PEP8-compliant python system; make the best use of good open source tools
Language: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.
Requirement: Fill in the following missing information based on the context, note that all sections are response with code form separately
Max Output: 8192 chars or 2048 tokens. Try to use them up.
Attention: Use '##' to split sections, not '#', and '## <SECTION_NAME>' SHOULD WRITE BEFORE the code and triple quote.
ATTENTION: Output carefully referenced "Format example" in format.
## Implementation approach: Provide as Plain text. Analyze the difficult points of the requirements, select the appropriate open-source framework.
## Python package name: Provide as Python str with python triple quoto, concise and clear, characters only use a combination of all lowercase and underscores
## project_name: Provide as Plain text, concise and clear, characters only use a combination of all lowercase and underscores
## File list: Provided as Python list[str], the list of ONLY REQUIRED files needed to write the program(LESS IS MORE!). Only need relative paths, comply with PEP8 standards. ALWAYS write a main.py or app.py here
## File list: Provided as Python list[str], the list of code files (including HTML & CSS IF NEEDED) to write the program. Only need relative paths. ALWAYS write a main.py or app.py here
## Data structures and interface definitions: Use mermaid classDiagram code syntax, including classes (INCLUDING __init__ method) and functions (with type annotations), CLEARLY MARK the RELATIONSHIPS between classes, and comply with PEP8 standards. The data structures SHOULD BE VERY DETAILED and the API should be comprehensive with a complete design.
## Data structures and interfaces: Use mermaid classDiagram code syntax, including classes (INCLUDING __init__ method) and functions (with type annotations), CLEARLY MARK the RELATIONSHIPS between classes, and comply with PEP8 standards. The data structures SHOULD BE VERY DETAILED and the API should be comprehensive with a complete design.
## Program call flow: Use sequenceDiagram code syntax, COMPLETE and VERY DETAILED, using CLASSES AND API DEFINED ABOVE accurately, covering the CRUD AND INIT of each object, SYNTAX MUST BE CORRECT.
## Anything UNCLEAR: Provide as Plain text. Make clear here.
## Anything UNCLEAR: Provide as Plain text. Try to clarify it.
""",
"FORMAT_EXAMPLE": """
@ -112,7 +112,7 @@ Attention: Use '##' to split sections, not '#', and '## <SECTION_NAME>' SHOULD W
## Implementation approach
We will ...
## Python package name
## project_name
```python
"snake_game"
```
@ -124,7 +124,7 @@ We will ...
]
```
## Data structures and interface definitions
## Data structures and interfaces
```mermaid
classDiagram
class Game{
@ -151,9 +151,9 @@ The requirement is clear to me.
OUTPUT_MAPPING = {
"Implementation approach": (str, ...),
"Python package name": (str, ...),
"project_name": (str, ...),
"File list": (List[str], ...),
"Data structures and interface definitions": (str, ...),
"Data structures and interfaces": (str, ...),
"Program call flow": (str, ...),
"Anything UNCLEAR": (str, ...),
}
@ -226,19 +226,76 @@ class WriteDesign(Action):
# leaving room for global optimization in subsequent steps.
return ActionOutput(content=changed_files.json(), instruct_content=changed_files)
# =======
# def recreate_workspace(self, workspace: Path):
# try:
# shutil.rmtree(workspace)
# except FileNotFoundError:
# pass # Folder does not exist, but we don't care
# workspace.mkdir(parents=True, exist_ok=True)
# async def _save_prd(self, docs_path, resources_path, context):
# prd_file = docs_path / "prd.md"
# if context[-1].instruct_content and context[-1].instruct_content.dict()["Competitive Quadrant Chart"]:
# quadrant_chart = context[-1].instruct_content.dict()["Competitive Quadrant Chart"]
# await mermaid_to_file(quadrant_chart, resources_path / "competitive_analysis")
#
# if context[-1].instruct_content:
# logger.info(f"Saving PRD to {prd_file}")
# prd_file.write_text(context[-1].instruct_content.json(ensure_ascii=False), encoding='utf-8')
# async def _save_system_design(self, docs_path, resources_path, system_design):
# data_api_design = system_design.instruct_content.dict()[
# "Data structures and interfaces"
# ] # CodeParser.parse_code(block="Data structures and interfaces", text=content)
# seq_flow = system_design.instruct_content.dict()[
# "Program call flow"
# ] # CodeParser.parse_code(block="Program call flow", text=content)
# await mermaid_to_file(data_api_design, resources_path / "data_api_design")
# await mermaid_to_file(seq_flow, resources_path / "seq_flow")
# system_design_file = docs_path / "system_design.md"
# logger.info(f"Saving System Designs to {system_design_file}")
# system_design_file.write_text(system_design.instruct_content.json(ensure_ascii=False), encoding='utf-8')
# async def _save(self, context, system_design):
# if isinstance(system_design, ActionOutput):
# project_name = system_design.instruct_content.dict()["project_name"]
# else:
# project_name = CodeParser.parse_str(block="project_name", text=system_design)
# workspace = CONFIG.workspace_path / project_name
# self.recreate_workspace(workspace)
# docs_path = workspace / "docs"
# resources_path = workspace / "resources"
# docs_path.mkdir(parents=True, exist_ok=True)
# resources_path.mkdir(parents=True, exist_ok=True)
# await self._save_prd(docs_path, resources_path, context)
# await self._save_system_design(docs_path, resources_path, system_design)
# async def run(self, context, format=CONFIG.prompt_format):
async def _new_system_design(self, context, format=CONFIG.prompt_format):
prompt_template, format_example = get_template(templates, format)
prompt = prompt_template.format(context=context, format_example=format_example)
# system_design = await self._aask(prompt)
system_design = await self._aask_v1(prompt, "system_design", OUTPUT_MAPPING, format=format)
# fix Python package name, we can't system_design.instruct_content.python_package_name = "xxx" since "Python
# package name" contain space, have to use setattr
# fix project_name, we can't system_design.instruct_content.python_package_name = "xxx" since "project_name"
# contain space, have to use setattr
setattr(
system_design.instruct_content,
"Python package name",
system_design.instruct_content.dict()["Python package name"].strip().strip("'").strip('"'),
"project_name",
system_design.instruct_content.dict()["project_name"].strip().strip("'").strip('"'),
)
await self._rename_workspace(system_design)
# =======
# # fix project_name, we can't system_design.instruct_content.python_package_name = "xxx" since "project_name" contain space, have to use setattr
# # setattr(
# # system_design.instruct_content,
# # "project_name",
# # system_design.instruct_content.dict()["project_name"].strip().strip("'").strip('"'),
# # )
# await self._save(context, system_design)
# >>>>>>> feature/geekan_cli_etc
return system_design
async def _merge(self, prd_doc, system_design_doc, format=CONFIG.prompt_format):
@ -248,10 +305,10 @@ class WriteDesign(Action):
# package name" contain space, have to use setattr
setattr(
system_design.instruct_content,
"Python package name",
system_design.instruct_content.dict()["Python package name"].strip().strip("'").strip('"'),
"project_name",
system_design.instruct_content.dict()["project_name"].strip().strip("'").strip('"'),
)
system_design_doc.content = system_design.instruct_content.json()
system_design_doc.content = system_design.instruct_content.json(ensure_ascii=False)
return system_design_doc
@staticmethod
@ -260,9 +317,9 @@ class WriteDesign(Action):
return
if isinstance(system_design, ActionOutput):
ws_name = system_design.instruct_content.dict()["Python package name"]
ws_name = system_design.instruct_content.dict()["project_name"]
else:
ws_name = CodeParser.parse_str(block="Python package name", text=system_design)
ws_name = CodeParser.parse_str(block="project_name", text=system_design)
CONFIG.git_repo.rename_root(ws_name)
async def _update_system_design(self, filename, prds_file_repo, system_design_file_repo) -> Document:
@ -271,7 +328,9 @@ class WriteDesign(Action):
if not old_system_design_doc:
system_design = await self._new_system_design(context=prd.content)
doc = Document(
root_path=SYSTEM_DESIGN_FILE_REPO, filename=filename, content=system_design.instruct_content.json()
root_path=SYSTEM_DESIGN_FILE_REPO,
filename=filename,
content=system_design.instruct_content.json(ensure_ascii=False),
)
else:
doc = await self._merge(prd_doc=prd, system_design_doc=old_system_design_doc)

65
metagpt/actions/project_management.py
View file

@ -15,7 +15,12 @@ from typing import List
from metagpt.actions import ActionOutput
from metagpt.actions.action import Action
from metagpt.config import CONFIG
from metagpt.const import SYSTEM_DESIGN_FILE_REPO, TASK_FILE_REPO, TASK_PDF_FILE_REPO, PACKAGE_REQUIREMENTS_FILENAME
from metagpt.const import (
PACKAGE_REQUIREMENTS_FILENAME,
SYSTEM_DESIGN_FILE_REPO,
TASK_FILE_REPO,
TASK_PDF_FILE_REPO,
)
from metagpt.logs import logger
from metagpt.schema import Document, Documents
from metagpt.utils.file_repository import FileRepository
@ -31,22 +36,23 @@ templates = {
{format_example}
-----
Role: You are a project manager; the goal is to break down tasks according to PRD/technical design, give a task list, and analyze task dependencies to start with the prerequisite modules
Language: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.
Requirements: Based on the context, fill in the following missing information, each section name is a key in json. Here the granularity of the task is a file, if there are any missing files, you can supplement them
Attention: Use '##' to split sections, not '#', and '## <SECTION_NAME>' SHOULD WRITE BEFORE the code and triple quote.
ATTENTION: Output carefully referenced "Format example" in format.
## Required Python third-party packages: Provided in requirements.txt format
## Required Python third-party packages: Provide Python list[str] in requirements.txt format
## Required Other language third-party packages: Provided in requirements.txt format
## Full API spec: Use OpenAPI 3.0. Describe all APIs that may be used by both frontend and backend.
## Required Other language third-party packages: Provide Python list[str] in requirements.txt format
## Logic Analysis: Provided as a Python list[list[str]. the first is filename, the second is class/method/function should be implemented in this file. Analyze the dependencies between the files, which work should be done first
## Task list: Provided as Python list[str]. Each str is a filename, the more at the beginning, the more it is a prerequisite dependency, should be done first
## Full API spec: Use OpenAPI 3.0. Describe all APIs that may be used by both frontend and backend.
## Shared Knowledge: Anything that should be public like utils' functions, config's variables details that should make clear first.
## Anything UNCLEAR: Provide as Plain text. Make clear here. For example, don't forget a main entry. don't forget to init 3rd party libs.
## Anything UNCLEAR: Provide as Plain text. Try to clarify it. For example, don't forget a main entry. don't forget to init 3rd party libs.
output a properly formatted JSON, wrapped inside [CONTENT][/CONTENT] like format example,
and only output the json inside this tag, nothing else
@ -60,17 +66,17 @@ and only output the json inside this tag, nothing else
"Required Other language third-party packages": [
"No third-party ..."
],
"Logic Analysis": [
["game.py", "Contains..."]
],
"Task list": [
"game.py"
],
"Full API spec": """
openapi: 3.0.0
...
description: A JSON object ...
""",
"Logic Analysis": [
["game.py","Contains..."]
],
"Task list": [
"game.py"
],
"Shared Knowledge": """
'game.py' contains ...
""",
@ -94,15 +100,15 @@ Attention: Use '##' to split sections, not '#', and '## <SECTION_NAME>' SHOULD W
## Required Other language third-party packages: Provided in requirements.txt format
## Full API spec: Use OpenAPI 3.0. Describe all APIs that may be used by both frontend and backend.
## Logic Analysis: Provided as a Python list[list[str]. the first is filename, the second is class/method/function should be implemented in this file. Analyze the dependencies between the files, which work should be done first
## Task list: Provided as Python list[str]. Each str is a filename, the more at the beginning, the more it is a prerequisite dependency, should be done first
## Full API spec: Use OpenAPI 3.0. Describe all APIs that may be used by both frontend and backend.
## Shared Knowledge: Anything that should be public like utils' functions, config's variables details that should make clear first.
## Anything UNCLEAR: Provide as Plain text. Make clear here. For example, don't forget a main entry. don't forget to init 3rd party libs.
## Anything UNCLEAR: Provide as Plain text. Try to clarify it. For example, don't forget a main entry. don't forget to init 3rd party libs.
""",
"FORMAT_EXAMPLE": '''
@ -134,14 +140,16 @@ description: A JSON object ...
## Logic Analysis
```python
[
["game.py", "Contains ..."],
["index.js", "Contains ..."],
["main.py", "Contains ..."],
]
```
## Task list
```python
[
"game.py",
"index.js",
"main.py",
]
```
@ -239,7 +247,9 @@ class WriteTasks(Action):
task_doc = await self._merge(system_design_doc=system_design_doc, task_doc=task_doc)
else:
rsp = await self._run_new_tasks(context=system_design_doc.content)
task_doc = Document(root_path=TASK_FILE_REPO, filename=filename, content=rsp.instruct_content.json())
task_doc = Document(
root_path=TASK_FILE_REPO, filename=filename, content=rsp.instruct_content.json(ensure_ascii=False)
)
await tasks_file_repo.save(
filename=filename, content=task_doc.content, dependencies={system_design_doc.root_relative_path}
)
@ -248,6 +258,21 @@ class WriteTasks(Action):
return task_doc
async def _run_new_tasks(self, context, format=CONFIG.prompt_format):
# =======
# def _save(self, context, rsp):
# if context[-1].instruct_content:
# ws_name = context[-1].instruct_content.dict()["project_name"]
# else:
# ws_name = CodeParser.parse_str(block="project_name", text=context[-1].content)
# file_path = CONFIG.workspace_path / ws_name / "docs/api_spec_and_tasks.md"
# file_path.write_text(rsp.instruct_content.json(ensure_ascii=False))
#
# # Write requirements.txt
# requirements_path = CONFIG.workspace_path / ws_name / "requirements.txt"
# requirements_path.write_text("\n".join(rsp.instruct_content.dict().get("Required Python third-party packages")))
#
# async def run(self, context, format=CONFIG.prompt_format):
# >>>>>>> feature/geekan_cli_etc
prompt_template, format_example = get_template(templates, format)
prompt = prompt_template.format(context=context, format_example=format_example)
rsp = await self._aask_v1(prompt, "task", OUTPUT_MAPPING, format=format)
@ -256,7 +281,7 @@ class WriteTasks(Action):
async def _merge(self, system_design_doc, task_doc, format=CONFIG.prompt_format) -> Document:
prompt = MERGE_PROMPT.format(context=system_design_doc.content, old_tasks=task_doc.content)
rsp = await self._aask_v1(prompt, "task", OUTPUT_MAPPING, format=format)
task_doc.content = rsp.instruct_content.json()
task_doc.content = rsp.instruct_content.json(ensure_ascii=False)
return task_doc
@staticmethod

115
metagpt/actions/summarize_code.py Normal file
View file

@ -0,0 +1,115 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Author : alexanderwu
@File : summarize_code.py
"""
from tenacity import retry, stop_after_attempt, wait_fixed
from metagpt.actions.action import Action
from metagpt.config import CONFIG
from metagpt.logs import logger
from metagpt.utils.file_repository import FileRepository
PROMPT_TEMPLATE = """
NOTICE
Role: You are a professional software engineer, and your main task is to review the code.
Language: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.
ATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced "Format example".
-----
# System Design
```text
{system_design}
```
-----
# Tasks
```text
{tasks}
```
-----
{code_blocks}
## Code Review All: 请你对历史所有文件进行阅读，在文件中找到可能的bug，如函数未实现、调用错误、未引用等
## Call flow: mermaid代码，根据实现的函数，使用mermaid绘制完整的调用链
## Summary: 根据历史文件的实现情况进行总结
## TODOs: Python dict[str, str]，这里写出需要修改的文件列表与理由，我们会在之后进行修改
"""
FORMAT_EXAMPLE = """
## Code Review All
### a.py
- 它少实现了xxx需求...
- 字段yyy没有给出...
- ...
### b.py
...
### c.py
...
## Call flow
```mermaid
flowchart TB
c1-->a2
subgraph one
a1-->a2
end
subgraph two
b1-->b2
end
subgraph three
c1-->c2
end
```
## Summary
- a.py:...
- b.py:...
- c.py:...
- ...
## TODOs
{
"a.py": "implement requirement xxx...",
}
"""
class SummarizeCode(Action):
def __init__(self, name="SummarizeCode", context=None, llm=None):
super().__init__(name, context, llm)
@retry(stop=stop_after_attempt(2), wait=wait_fixed(1))
async def summarize_code(self, prompt):
code_rsp = await self._aask(prompt)
return code_rsp
async def run(self):
design_doc = await FileRepository.get_file(self.context.design_filename)
task_doc = await FileRepository.get_file(self.context.task_filename)
src_file_repo = CONFIG.git_repo.new_file_repository(relative_path=CONFIG.src_workspace)
code_blocks = []
for filename in self.context.codes_filenames:
code_doc = await src_file_repo.get(filename)
code_block = f"```python\n{code_doc.content}\n```\n-----"
code_blocks.append(code_block)
format_example = FORMAT_EXAMPLE
prompt = PROMPT_TEMPLATE.format(
system_design=design_doc.content,
tasks=task_doc.content,
code_blocks="\n".join(code_blocks),
format_example=format_example,
)
logger.info("Summarize code..")
rsp = await self.summarize_code(prompt)
return rsp

42
metagpt/actions/write_code.py
View file

@ -15,10 +15,10 @@
RunCodeResult to standardize and unify parameter passing between WriteCode, RunCode, and DebugError.
"""
from tenacity import retry, stop_after_attempt, wait_fixed
from metagpt.actions.action import Action
from metagpt.config import CONFIG
from metagpt.const import TEST_OUTPUTS_FILE_REPO
from metagpt.logs import logger
from metagpt.schema import CodingContext, RunCodeResult
@ -28,16 +28,24 @@ from metagpt.utils.file_repository import FileRepository
PROMPT_TEMPLATE = """
NOTICE
Role: You are a professional engineer; the main goal is to write PEP8 compliant, elegant, modular, easy to read and maintain Python 3.9 code (but you can also use other programming language)
Language: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.
ATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced "Format example".
-----
# Context
{context}
-----
## Code: {filename} Write code with triple quoto, based on the following list and context.
1. Do your best to implement THIS ONLY ONE FILE. ONLY USE EXISTING API. IF NO API, IMPLEMENT IT.
2. Requirement: Based on the context, implement one following code file, note to return only in code form, your code will be part of the entire project, so please implement complete, reliable, reusable code snippets
3. Attention1: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE.
4. Attention2: YOU MUST FOLLOW "Data structures and interface definitions". DONT CHANGE ANY DESIGN.
3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE.
4. Follow design: YOU MUST FOLLOW "Data structures and interfaces". DONT CHANGE ANY DESIGN.
5. Think before writing: What should be implemented and provided in this document?
6. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.
7. Do not use public member functions that do not exist in your design.
8. Before using a variable, make sure you reference it first
9. Write out EVERY DETAIL, DON'T LEAVE TODO.
-----
# Design
@ -75,6 +83,29 @@ class WriteCode(Action):
def __init__(self, name="WriteCode", context=None, llm=None):
super().__init__(name, context, llm)
# <<<<<<< HEAD
# =======
# def _is_invalid(self, filename):
# return any(i in filename for i in ["mp3", "wav"])
#
# def _save(self, context, filename, code):
# # logger.info(filename)
# # logger.info(code_rsp)
# if self._is_invalid(filename):
# return
#
# design = [i for i in context if i.cause_by == WriteDesign][0]
#
# ws_name = CodeParser.parse_str(block="project_name", text=design.content)
# ws_path = CONFIG.workspace_path / ws_name
# if f"{ws_name}/" not in filename and all(i not in filename for i in ["requirements.txt", ".md"]):
# ws_path = ws_path / ws_name
# code_path = ws_path / filename
# code_path.parent.mkdir(parents=True, exist_ok=True)
# code_path.write_text(code)
# logger.info(f"Saving Code to {code_path}")
#
# >>>>>>> feature/geekan_cli_etc
@retry(stop=stop_after_attempt(2), wait=wait_fixed(1))
async def write_code(self, prompt) -> str:
code_rsp = await self._aask(prompt)
@ -83,8 +114,9 @@ class WriteCode(Action):
async def run(self, *args, **kwargs) -> CodingContext:
coding_context = CodingContext.loads(self.context.content)
test_doc = await FileRepository.get_file(filename="test_" + coding_context.filename + ".json",
relative_path=TEST_OUTPUTS_FILE_REPO)
test_doc = await FileRepository.get_file(
filename="test_" + coding_context.filename + ".json", relative_path=TEST_OUTPUTS_FILE_REPO
)
logs = ""
if test_doc:
test_detail = RunCodeResult.loads(test_doc.content)

127
metagpt/actions/write_code_review.py
View file

@ -11,6 +11,7 @@
from tenacity import retry, stop_after_attempt, wait_fixed
from metagpt.actions.action import Action
from metagpt.config import CONFIG
from metagpt.logs import logger
from metagpt.schema import CodingContext
from metagpt.utils.common import CodeParser
@ -18,49 +19,74 @@ from metagpt.utils.common import CodeParser
PROMPT_TEMPLATE = """
NOTICE
Role: You are a professional software engineer, and your main task is to review the code. You need to ensure that the code conforms to the PEP8 standards, is elegantly designed and modularized, easy to read and maintain, and is written in Python 3.9 (or in another programming language).
Language: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.
ATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced "Format example".
## Code Review: Based on the following context and code, and following the check list, Provide key, clear, concise, and specific code modification suggestions, up to 5.
```
1. Check 0: Is the code implemented as per the requirements?
2. Check 1: Are there any issues with the code logic?
3. Check 2: Does the existing code follow the "Data structures and interface definitions"?
4. Check 3: Is there a function in the code that is omitted or not fully implemented that needs to be implemented?
5. Check 4: Does the code have unnecessary or lack dependencies?
```
## Rewrite Code: {filename} Base on "Code Review" and the source code, rewrite code with triple quotes. Do your utmost to optimize THIS SINGLE FILE.
-----
# Context
{context}
## Code: {filename}
## Code to be Reviewed: {filename}
```
{code}
```
-----
## Code Review: Based on the "Code to be Reviewed", provide key, clear, concise, and specific code modification suggestions, up to 5.
1. Is the code implemented as per the requirements? If not, how to achieve it? Analyse it step by step.
2. Is the code logic completely correct? If there are errors, please indicate how to correct them.
3. Does the existing code follow the "Data structures and interfaces"?
4. Are all functions implemented? If there is no implementation, please indicate how to achieve it step by step.
5. Have all necessary pre-dependencies been imported? If not, indicate which ones need to be imported
6. Is the code implemented concisely enough? Are methods from other files being reused correctly?
## Code Review Result: If the code doesn't have bugs, we don't need to rewrite it, so answer LGTM and stop. ONLY ANSWER LGTM/LBTM.
LGTM/LBTM
## Rewrite Code: if it still has some bugs, rewrite {filename} based on "Code Review" with triple quotes, try to get LGTM. Do your utmost to optimize THIS SINGLE FILE. Implement ALL TODO. RETURN ALL CODE, NEVER OMIT ANYTHING. 以任何方式省略代码都是不允许的。
```
```
## Format example
-----
{format_example}
-----
"""
FORMAT_EXAMPLE = """
## Code Review
1. The code ...
-----
# EXAMPLE 1
## Code Review: {filename}
1. No, we should add the logic of ...
2. ...
3. ...
4. ...
5. ...
6. ...
## Code Review Result: {filename}
LBTM
## Rewrite Code: {filename}
```python
## {filename}
...
```
-----
# EXAMPLE 2
## Code Review: {filename}
1. Yes.
2. Yes.
3. Yes.
4. Yes.
5. Yes.
6. Yes.
## Code Review Result: {filename}
LGTM
## Rewrite Code: {filename}
pass
-----
"""
@ -69,23 +95,60 @@ class WriteCodeReview(Action):
super().__init__(name, context, llm)
@retry(stop=stop_after_attempt(2), wait=wait_fixed(1))
async def write_code(self, prompt):
async def write_code_review_and_rewrite(self, prompt):
code_rsp = await self._aask(prompt)
result = CodeParser.parse_block("Code Review Result", code_rsp)
if "LGTM" in result:
return result, None
code = CodeParser.parse_code(block="", text=code_rsp)
return code
return result, code
# <<<<<<< HEAD
# async def run(self, *args, **kwargs) -> CodingContext:
# format_example = FORMAT_EXAMPLE.format(filename=self.context.code_doc.filename)
# context = "\n----------\n".join(
# [self.context.design_doc.content, self.context.task_doc.content, self.context.code_doc.content]
# )
# prompt = PROMPT_TEMPLATE.format(
# context=context,
# code=self.context.code_doc.content,
# filename=self.context.code_doc.filename,
# format_example=format_example,
# )
# logger.info(f"Code review {self.context.code_doc.filename}..")
# code = await self.write_code(prompt)
# self.context.code_doc.content = code
# return self.context
# =======
async def run(self, *args, **kwargs) -> CodingContext:
format_example = FORMAT_EXAMPLE.format(filename=self.context.code_doc.filename)
context = "\n".join(
[self.context.design_doc.content, self.context.task_doc.content, self.context.code_doc.content]
)
prompt = PROMPT_TEMPLATE.format(
context=context,
code=self.context.code_doc.content,
filename=self.context.code_doc.filename,
format_example=format_example,
)
logger.info(f"Code review {self.context.code_doc.filename}..")
code = await self.write_code(prompt)
self.context.code_doc.content = code
iterative_code = self.context.code_doc.content
k = CONFIG.code_review_k_times or 1
for i in range(k):
format_example = FORMAT_EXAMPLE.format(filename=self.context.code_doc.filename)
context = "\n----------\n".join(
[
"```text\n" + self.context.design_doc.content + "```\n",
"```text\n" + self.context.task_doc.content + "```\n",
"```python\n" + self.context.code_doc.content + "```\n",
]
)
prompt = PROMPT_TEMPLATE.format(
context=context,
code=iterative_code,
filename=self.context.code_doc.filename,
format_example=format_example,
)
logger.info(
f"Code review and rewrite {self.context.code_doc.filename,}: {i+1}/{k} | {len(iterative_code)=}, {len(self.context.code_doc.content)=}"
)
result, rewrited_code = await self.write_code_review_and_rewrite(prompt)
if "LBTM" in result:
iterative_code = rewrited_code
elif "LGTM" in result:
self.context.code_doc.content = iterative_code
return self.context
# code_rsp = await self._aask_v1(prompt, "code_rsp", OUTPUT_MAPPING)
# self._save(context, filename, code)
# 如果rewrited_code是None（原code perfect），那么直接返回code
self.context.code_doc.content = iterative_code
return self.context

105
metagpt/actions/write_prd.py
View file

@ -35,53 +35,50 @@ templates = {
"json": {
"PROMPT_TEMPLATE": """
# Context
## Original Requirements
{requirements}
## Search Information
{search_information}
## mermaid quadrantChart code syntax example. DONT USE QUOTO IN CODE DUE TO INVALID SYNTAX. Replace the <Campain X> with REAL COMPETITOR NAME
```mermaid
quadrantChart
title Reach and engagement of campaigns
x-axis Low Reach --> High Reach
y-axis Low Engagement --> High Engagement
quadrant-1 We should expand
quadrant-2 Need to promote
quadrant-3 Re-evaluate
quadrant-4 May be improved
"Campaign: A": [0.3, 0.6]
"Campaign B": [0.45, 0.23]
"Campaign C": [0.57, 0.69]
"Campaign D": [0.78, 0.34]
"Campaign E": [0.40, 0.34]
"Campaign F": [0.35, 0.78]
"Our Target Product": [0.5, 0.6]
```
{{
"Original Requirements": "{requirements}",
"Search Information": ""
}}
## Format example
{format_example}
-----
Role: You are a professional product manager; the goal is to design a concise, usable, efficient product
Requirements: According to the context, fill in the following missing information, each section name is a key in json ,If the requirements are unclear, ensure minimum viability and avoid excessive design
Language: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.
Requirements: According to the context, fill in the following missing information, note that each sections are returned in Python code triple quote form seperatedly.
ATTENTION: Output carefully referenced "Format example" in format.
## Original Requirements: Provide as Plain text, place the polished complete original requirements here
## YOU NEED TO FULFILL THE BELOW JSON DOC
## Product Goals: Provided as Python list[str], up to 3 clear, orthogonal product goals. If the requirement itself is simple, the goal should also be simple
## User Stories: Provided as Python list[str], up to 5 scenario-based user stories, If the requirement itself is simple, the user stories should also be less
## Competitive Analysis: Provided as Python list[str], up to 7 competitive product analyses, consider as similar competitors as possible
## Competitive Quadrant Chart: Use mermaid quadrantChart code syntax. up to 14 competitive products. Translation: Distribute these competitor scores evenly between 0 and 1, trying to conform to a normal distribution centered around 0.5 as much as possible.
## Requirement Analysis: Provide as Plain text. Be simple. LESS IS MORE. Make your requirements less dumb. Delete the parts unnessasery.
## Requirement Pool: Provided as Python list[list[str], the parameters are requirement description, priority(P0/P1/P2), respectively, comply with PEP standards; no more than 5 requirements and consider to make its difficulty lower
## UI Design draft: Provide as Plain text. Be simple. Describe the elements and functions, also provide a simple style description and layout description.
## Anything UNCLEAR: Provide as Plain text. Make clear here.
{{
"Language": "", # str, use the same language as the user requirement. en_us / zh_cn etc.
"Original Requirements": "", # str, place the polished complete original requirements here
"project_name": "", # str, name it like game_2048 / web_2048 / simple_crm etc.
"Search Information": "",
"Requirements": "",
"Product Goals": [], # Provided as Python list[str], up to 3 clear, orthogonal product goals.
"User Stories": [], # Provided as Python list[str], up to 5 scenario-based user stories
"Competitive Analysis": [], # Provided as Python list[str], up to 8 competitive product analyses
# Use mermaid quadrantChart code syntax. up to 14 competitive products. Translation: Distribute these competitor scores evenly between 0 and 1, trying to conform to a normal distribution centered around 0.5 as much as possible.
"Competitive Quadrant Chart": "quadrantChart
title Reach and engagement of campaigns
x-axis Low Reach --> High Reach
y-axis Low Engagement --> High Engagement
quadrant-1 We should expand
quadrant-2 Need to promote
quadrant-3 Re-evaluate
quadrant-4 May be improved
Campaign A: [0.3, 0.6]
Campaign B: [0.45, 0.23]
Campaign C: [0.57, 0.69]
Campaign D: [0.78, 0.34]
Campaign E: [0.40, 0.34]
Campaign F: [0.35, 0.78]",
"Requirement Analysis": "", # Provide as Plain text.
"Requirement Pool": [["P0","P0 requirement"],["P1","P1 requirement"]], # Provided as Python list[list[str], the parameters are requirement description, priority(P0/P1/P2), respectively, comply with PEP standards
"UI Design draft": "", # Provide as Plain text. Be simple. Describe the elements and functions, also provide a simple style description and layout description.
"Anything UNCLEAR": "", # Provide as Plain text. Try to clarify it.
}}
output a properly formatted JSON, wrapped inside [CONTENT][/CONTENT] like format example,
and only output the json inside this tag, nothing else
@ -89,6 +86,7 @@ and only output the json inside this tag, nothing else
"FORMAT_EXAMPLE": """
[CONTENT]
{
"Language": "",
"Original Requirements": "",
"Search Information": "",
"Requirements": "",
@ -149,30 +147,33 @@ quadrantChart
{format_example}
-----
Role: You are a professional product manager; the goal is to design a concise, usable, efficient product
Requirements: According to the context, fill in the following missing information, note that each sections are returned in Python code triple quote form seperatedly. If the requirements are unclear, ensure minimum viability and avoid excessive design
Language: Please use the same language as the user requirement to answer, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.
Requirements: According to the context, fill in the following missing information, note that each sections are returned in Python code triple quote form seperatedly.
ATTENTION: Use '##' to SPLIT SECTIONS, not '#'. AND '## <SECTION_NAME>' SHOULD WRITE BEFORE the code and triple quote. Output carefully referenced "Format example" in format.
## Language: Provide as Plain text, use the same language as the user requirement.
## Original Requirements: Provide as Plain text, place the polished complete original requirements here
## Product Goals: Provided as Python list[str], up to 3 clear, orthogonal product goals. If the requirement itself is simple, the goal should also be simple
## Product Goals: Provided as Python list[str], up to 3 clear, orthogonal product goals.
## User Stories: Provided as Python list[str], up to 5 scenario-based user stories, If the requirement itself is simple, the user stories should also be less
## User Stories: Provided as Python list[str], up to 5 scenario-based user stories
## Competitive Analysis: Provided as Python list[str], up to 7 competitive product analyses, consider as similar competitors as possible
## Competitive Quadrant Chart: Use mermaid quadrantChart code syntax. up to 14 competitive products. Translation: Distribute these competitor scores evenly between 0 and 1, trying to conform to a normal distribution centered around 0.5 as much as possible.
## Requirement Analysis: Provide as Plain text. Be simple. LESS IS MORE. Make your requirements less dumb. Delete the parts unnessasery.
## Requirement Analysis: Provide as Plain text.
## Requirement Pool: Provided as Python list[list[str], the parameters are requirement description, priority(P0/P1/P2), respectively, comply with PEP standards; no more than 5 requirements and consider to make its difficulty lower
## Requirement Pool: Provided as Python list[list[str], the parameters are requirement description, priority(P0/P1/P2), respectively, comply with PEP standards
## UI Design draft: Provide as Plain text. Be simple. Describe the elements and functions, also provide a simple style description and layout description.
## Anything UNCLEAR: Provide as Plain text. Make clear here.
## Anything UNCLEAR: Provide as Plain text. Try to clarify it.
""",
"FORMAT_EXAMPLE": """
---
## Original Requirements
The boss ...
The user ...
## Product Goals
```python
@ -225,6 +226,7 @@ There are no unclear points.
OUTPUT_MAPPING = {
"Language": (str, ...),
"Original Requirements": (str, ...),
"Product Goals": (List[str], ...),
"User Stories": (List[str], ...),
@ -322,11 +324,14 @@ class WritePRD(Action):
logger.info(sas.result)
logger.info(rsp)
# logger.info(format)
prompt_template, format_example = get_template(templates, format)
# logger.info(prompt_template)
# logger.info(format_example)
prompt = prompt_template.format(
requirements=requirements, search_information=info, format_example=format_example
)
logger.debug(prompt)
# logger.info(prompt)
# prd = await self._aask_v1(prompt, "prd", OUTPUT_MAPPING)
prd = await self._aask_v1(prompt, "prd", OUTPUT_MAPPING, format=format)
return prd
@ -346,7 +351,7 @@ class WritePRD(Action):
async def _merge(self, new_requirement_doc, prd_doc, format=CONFIG.prompt_format) -> Document:
prompt = MERGE_PROMPT.format(requirements=new_requirement_doc.content, old_prd=prd_doc.content)
prd = await self._aask_v1(prompt, "prd", OUTPUT_MAPPING, format=format)
prd_doc.content = prd.instruct_content.json()
prd_doc.content = prd.instruct_content.json(ensure_ascii=False)
return prd_doc
async def _update_prd(self, requirement_doc, prd_doc, prds_file_repo, *args, **kwargs) -> Document | None:
@ -355,7 +360,7 @@ class WritePRD(Action):
new_prd_doc = Document(
root_path=PRDS_FILE_REPO,
filename=FileRepository.new_filename() + ".json",
content=prd.instruct_content.json(),
content=prd.instruct_content.json(ensure_ascii=False),
)
elif await self._is_relative_to(requirement_doc, prd_doc):
new_prd_doc = await self._merge(requirement_doc, prd_doc)

4
metagpt/actions/write_test.py
View file

@ -3,7 +3,7 @@
"""
@Time : 2023/5/11 22:12
@Author : alexanderwu
@File : environment.py
@File : write_test.py
@Modified By: mashenquan, 2023-11-27. Following the think-act principle, solidify the task parameters when creating the
WriteTest object, rather than passing them in when calling the run function.
"""
@ -19,7 +19,7 @@ NOTICE
2. Requirement: Based on the context, develop a comprehensive test suite that adequately covers all relevant aspects of the code file under review. Your test suite will be part of the overall project QA, so please develop complete, robust, and reusable test cases.
3. Attention1: Use '##' to split sections, not '#', and '## <SECTION_NAME>' SHOULD WRITE BEFORE the test case or script.
4. Attention2: If there are any settings in your tests, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE.
5. Attention3: YOU MUST FOLLOW "Data structures and interface definitions". DO NOT CHANGE ANY DESIGN. Make sure your tests respect the existing design and ensure its validity.
5. Attention3: YOU MUST FOLLOW "Data structures and interfaces". DO NOT CHANGE ANY DESIGN. Make sure your tests respect the existing design and ensure its validity.
6. Think before writing: What should be tested and validated in this document? What edge cases could exist? What might fail?
7. CAREFULLY CHECK THAT YOU DON'T MISS ANY NECESSARY TEST CASES/SCRIPTS IN THIS FILE.
Attention: Use '##' to split sections, not '#', and '## <SECTION_NAME>' SHOULD WRITE BEFORE the test case or script and triple quotes.

33
metagpt/config.py
View file

@ -8,12 +8,12 @@ Provide configuration, singleton
"""
import os
from copy import deepcopy
from pathlib import Path
from typing import Any
import openai
import yaml
from metagpt.const import OPTIONS, PROJECT_ROOT
from metagpt.const import DEFAULT_WORKSPACE_ROOT, METAGPT_ROOT, OPTIONS
from metagpt.logs import logger
from metagpt.tools import SearchEngineType, WebBrowserEngineType
from metagpt.utils.singleton import Singleton
@ -40,8 +40,9 @@ class Config(metaclass=Singleton):
"""
_instance = None
key_yaml_file = PROJECT_ROOT / "config/key.yaml"
default_yaml_file = PROJECT_ROOT / "config/config.yaml"
home_yaml_file = Path.home() / ".metagpt/config.yaml"
key_yaml_file = METAGPT_ROOT / "config/key.yaml"
default_yaml_file = METAGPT_ROOT / "config/config.yaml"
def __init__(self, yaml_file=default_yaml_file):
self._init_with_config_files_and_env(yaml_file)
@ -49,18 +50,19 @@ class Config(metaclass=Singleton):
self._update()
def _update(self):
# logger.info("Config loading done.")
self.global_proxy = self._get("GLOBAL_PROXY")
self.openai_api_key = self._get("OPENAI_API_KEY")
self.anthropic_api_key = self._get("Anthropic_API_KEY")
if (not self.openai_api_key or "YOUR_API_KEY" == self.openai_api_key) and (
not self.anthropic_api_key or "YOUR_API_KEY" == self.anthropic_api_key
self.zhipuai_api_key = self._get("ZHIPUAI_API_KEY")
if (
(not self.openai_api_key or "YOUR_API_KEY" == self.openai_api_key)
and (not self.anthropic_api_key or "YOUR_API_KEY" == self.anthropic_api_key)
and (not self.zhipuai_api_key or "YOUR_API_KEY" == self.zhipuai_api_key)
):
raise NotConfiguredException("Set OPENAI_API_KEY or Anthropic_API_KEY first")
raise NotConfiguredException("Set OPENAI_API_KEY or Anthropic_API_KEY or ZHIPUAI_API_KEY first")
self.openai_api_base = self._get("OPENAI_API_BASE")
openai_proxy = self._get("OPENAI_PROXY") or self.global_proxy
if openai_proxy:
openai.proxy = openai_proxy
openai.api_base = self.openai_api_base
self.openai_proxy = self._get("OPENAI_PROXY") or self.global_proxy
self.openai_api_type = self._get("OPENAI_API_TYPE")
self.openai_api_version = self._get("OPENAI_API_VERSION")
self.openai_api_rpm = self._get("RPM", 3)
@ -90,6 +92,7 @@ class Config(metaclass=Singleton):
logger.warning("LONG_TERM_MEMORY is True")
self.max_budget = self._get("MAX_BUDGET", 10.0)
self.total_cost = 0.0
self.code_review_k_times = 2
self.puppeteer_config = self._get("PUPPETEER_CONFIG", "")
self.mmdc = self._get("MMDC", "mmdc")
@ -100,12 +103,18 @@ class Config(metaclass=Singleton):
self.pyppeteer_executable_path = self._get("PYPPETEER_EXECUTABLE_PATH", "")
self.prompt_format = self._get("PROMPT_FORMAT", "markdown")
self.workspace_path = Path(self._get("WORKSPACE_PATH", DEFAULT_WORKSPACE_ROOT))
self._ensure_workspace_exists()
def _ensure_workspace_exists(self):
self.workspace_path.mkdir(parents=True, exist_ok=True)
logger.info(f"WORKSPACE_PATH set to {self.workspace_path}")
def _init_with_config_files_and_env(self, yaml_file):
"""Load from config/key.yaml, config/config.yaml, and env in decreasing order of priority"""
configs = dict(os.environ)
for _yaml_file in [yaml_file, self.key_yaml_file]:
for _yaml_file in [yaml_file, self.key_yaml_file, self.home_yaml_file]:
if not _yaml_file.exists():
continue

99
metagpt/const.py
View file

@ -9,45 +9,90 @@
@Modified By: mashenquan, 2023-11-27. Defines file repository paths according to Section 2.2.3.4 of RFC 135.
"""
import contextvars
import os
from pathlib import Path
from loguru import logger
def get_project_root():
"""Search upwards to find the project root directory."""
current_path = Path.cwd()
while True:
if (
(current_path / ".git").exists()
or (current_path / ".project_root").exists()
or (current_path / ".gitignore").exists()
):
return current_path
parent_path = current_path.parent
if parent_path == current_path:
raise Exception("Project root not found.")
current_path = parent_path
import metagpt
OPTIONS = contextvars.ContextVar("OPTIONS")
PROJECT_ROOT = get_project_root()
DATA_PATH = PROJECT_ROOT / "data"
WORKSPACE_ROOT = PROJECT_ROOT / "workspace"
PROMPT_PATH = PROJECT_ROOT / "metagpt/prompts"
UT_PATH = PROJECT_ROOT / "data/ut"
SWAGGER_PATH = UT_PATH / "files/api/"
UT_PY_PATH = UT_PATH / "files/ut/"
API_QUESTIONS_PATH = UT_PATH / "files/question/"
YAPI_URL = "http://yapi.deepwisdomai.com/"
TMP = PROJECT_ROOT / "tmp"
# <<<<<<< HEAD
# def get_project_root():
# """Search upwards to find the project root directory."""
# current_path = Path.cwd()
# while True:
# if (
# (current_path / ".git").exists()
# or (current_path / ".project_root").exists()
# or (current_path / ".gitignore").exists()
# ):
# return current_path
# parent_path = current_path.parent
# if parent_path == current_path:
# raise Exception("Project root not found.")
# current_path = parent_path
#
#
# PROJECT_ROOT = get_project_root()
# DATA_PATH = PROJECT_ROOT / "data"
# WORKSPACE_ROOT = PROJECT_ROOT / "workspace"
# PROMPT_PATH = PROJECT_ROOT / "metagpt/prompts"
# UT_PATH = PROJECT_ROOT / "data/ut"
# SWAGGER_PATH = UT_PATH / "files/api/"
# UT_PY_PATH = UT_PATH / "files/ut/"
# API_QUESTIONS_PATH = UT_PATH / "files/question/"
# YAPI_URL = "http://yapi.deepwisdomai.com/"
# TMP = PROJECT_ROOT / "tmp"
# =======
def get_metagpt_package_root():
"""Get the root directory of the installed package."""
package_root = Path(metagpt.__file__).parent.parent
logger.info(f"Package root set to {str(package_root)}")
return package_root
def get_metagpt_root():
"""Get the project root directory."""
# Check if a project root is specified in the environment variable
project_root_env = os.getenv("METAGPT_PROJECT_ROOT")
if project_root_env:
project_root = Path(project_root_env)
logger.info(f"PROJECT_ROOT set from environment variable to {str(project_root)}")
else:
# Fallback to package root if no environment variable is set
project_root = get_metagpt_package_root()
return project_root
# METAGPT PROJECT ROOT AND VARS
METAGPT_ROOT = get_metagpt_root()
DEFAULT_WORKSPACE_ROOT = METAGPT_ROOT / "workspace"
DATA_PATH = METAGPT_ROOT / "data"
RESEARCH_PATH = DATA_PATH / "research"
TUTORIAL_PATH = DATA_PATH / "tutorial_docx"
INVOICE_OCR_TABLE_PATH = DATA_PATH / "invoice_table"
UT_PATH = DATA_PATH / "ut"
SWAGGER_PATH = UT_PATH / "files/api/"
UT_PY_PATH = UT_PATH / "files/ut/"
API_QUESTIONS_PATH = UT_PATH / "files/question/"
SKILL_DIRECTORY = PROJECT_ROOT / "metagpt/skills"
TMP = METAGPT_ROOT / "tmp"
SOURCE_ROOT = METAGPT_ROOT / "metagpt"
PROMPT_PATH = SOURCE_ROOT / "prompts"
SKILL_DIRECTORY = SOURCE_ROOT / "skills"
# REAL CONSTS
MEM_TTL = 24 * 30 * 3600
MESSAGE_ROUTE_FROM = "sent_from"
MESSAGE_ROUTE_TO = "send_to"
MESSAGE_ROUTE_CAUSE_BY = "cause_by"
@ -70,3 +115,5 @@ PRD_PDF_FILE_REPO = "resources/prd"
TASK_PDF_FILE_REPO = "resources/api_spec_and_tasks"
TEST_CODES_FILE_REPO = "tests"
TEST_OUTPUTS_FILE_REPO = "test_outputs"
YAPI_URL = "http://yapi.deepwisdomai.com/"

255
metagpt/document.py Normal file
View file

@ -0,0 +1,255 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Time : 2023/6/8 14:03
@Author : alexanderwu
@File : document.py
"""
from enum import Enum
from pathlib import Path
from typing import Optional, Union
import pandas as pd
from langchain.document_loaders import (
TextLoader,
UnstructuredPDFLoader,
UnstructuredWordDocumentLoader,
)
from langchain.text_splitter import CharacterTextSplitter
from pydantic import BaseModel, Field
from tqdm import tqdm
from metagpt.config import CONFIG
from metagpt.logs import logger
from metagpt.repo_parser import RepoParser
def validate_cols(content_col: str, df: pd.DataFrame):
if content_col not in df.columns:
raise ValueError("Content column not found in DataFrame.")
def read_data(data_path: Path):
suffix = data_path.suffix
if ".xlsx" == suffix:
data = pd.read_excel(data_path)
elif ".csv" == suffix:
data = pd.read_csv(data_path)
elif ".json" == suffix:
data = pd.read_json(data_path)
elif suffix in (".docx", ".doc"):
data = UnstructuredWordDocumentLoader(str(data_path), mode="elements").load()
elif ".txt" == suffix:
data = TextLoader(str(data_path)).load()
text_splitter = CharacterTextSplitter(separator="\n", chunk_size=256, chunk_overlap=0)
texts = text_splitter.split_documents(data)
data = texts
elif ".pdf" == suffix:
data = UnstructuredPDFLoader(str(data_path), mode="elements").load()
else:
raise NotImplementedError("File format not supported.")
return data
class DocumentStatus(Enum):
"""Indicates document status, a mechanism similar to RFC/PEP"""
DRAFT = "draft"
UNDERREVIEW = "underreview"
APPROVED = "approved"
DONE = "done"
class Document(BaseModel):
"""
Document: Handles operations related to document files.
"""
path: Path = Field(default=None)
name: str = Field(default="")
content: str = Field(default="")
# metadata? in content perhaps.
author: str = Field(default="")
status: DocumentStatus = Field(default=DocumentStatus.DRAFT)
reviews: list = Field(default_factory=list)
@classmethod
def from_path(cls, path: Path):
"""
Create a Document instance from a file path.
"""
if not path.exists():
raise FileNotFoundError(f"File {path} not found.")
content = path.read_text()
return cls(content=content, path=path)
@classmethod
def from_text(cls, text: str, path: Optional[Path] = None):
"""
Create a Document from a text string.
"""
return cls(content=text, path=path)
def to_path(self, path: Optional[Path] = None):
"""
Save content to the specified file path.
"""
if path is not None:
self.path = path
if self.path is None:
raise ValueError("File path is not set.")
self.path.parent.mkdir(parents=True, exist_ok=True)
self.path.write_text(self.content, encoding="utf-8")
def persist(self):
"""
Persist document to disk.
"""
return self.to_path()
class IndexableDocument(Document):
"""
Advanced document handling: For vector databases or search engines.
"""
data: Union[pd.DataFrame, list]
content_col: Optional[str] = Field(default="")
meta_col: Optional[str] = Field(default="")
class Config:
arbitrary_types_allowed = True
@classmethod
def from_path(cls, data_path: Path, content_col="content", meta_col="metadata"):
if not data_path.exists():
raise FileNotFoundError(f"File {data_path} not found.")
data = read_data(data_path)
content = data_path.read_text()
if isinstance(data, pd.DataFrame):
validate_cols(content_col, data)
return cls(data=data, content=content, content_col=content_col, meta_col=meta_col)
def _get_docs_and_metadatas_by_df(self) -> (list, list):
df = self.data
docs = []
metadatas = []
for i in tqdm(range(len(df))):
docs.append(df[self.content_col].iloc[i])
if self.meta_col:
metadatas.append({self.meta_col: df[self.meta_col].iloc[i]})
else:
metadatas.append({})
return docs, metadatas
def _get_docs_and_metadatas_by_langchain(self) -> (list, list):
data = self.data
docs = [i.page_content for i in data]
metadatas = [i.metadata for i in data]
return docs, metadatas
def get_docs_and_metadatas(self) -> (list, list):
if isinstance(self.data, pd.DataFrame):
return self._get_docs_and_metadatas_by_df()
elif isinstance(self.data, list):
return self._get_docs_and_metadatas_by_langchain()
else:
raise NotImplementedError("Data type not supported for metadata extraction.")
class RepoMetadata(BaseModel):
name: str = Field(default="")
n_docs: int = Field(default=0)
n_chars: int = Field(default=0)
symbols: list = Field(default_factory=list)
class Repo(BaseModel):
# Name of this repo.
name: str = Field(default="")
# metadata: RepoMetadata = Field(default=RepoMetadata)
docs: dict[Path, Document] = Field(default_factory=dict)
codes: dict[Path, Document] = Field(default_factory=dict)
assets: dict[Path, Document] = Field(default_factory=dict)
path: Path = Field(default=None)
def _path(self, filename):
return self.path / filename
@classmethod
def from_path(cls, path: Path):
"""Load documents, code, and assets from a repository path."""
path.mkdir(parents=True, exist_ok=True)
repo = Repo(path=path, name=path.name)
for file_path in path.rglob("*"):
# FIXME: These judgments are difficult to support multiple programming languages and need to be more general
if file_path.is_file() and file_path.suffix in [".json", ".txt", ".md", ".py", ".js", ".css", ".html"]:
repo._set(file_path.read_text(), file_path)
return repo
def to_path(self):
"""Persist all documents, code, and assets to the given repository path."""
for doc in self.docs.values():
doc.to_path()
for code in self.codes.values():
code.to_path()
for asset in self.assets.values():
asset.to_path()
def _set(self, content: str, path: Path):
"""Add a document to the appropriate category based on its file extension."""
suffix = path.suffix
doc = Document(content=content, path=path, name=str(path.relative_to(self.path)))
# FIXME: These judgments are difficult to support multiple programming languages and need to be more general
if suffix.lower() == ".md":
self.docs[path] = doc
elif suffix.lower() in [".py", ".js", ".css", ".html"]:
self.codes[path] = doc
else:
self.assets[path] = doc
return doc
def set(self, content: str, filename: str):
"""Set a document and persist it to disk."""
path = self._path(filename)
doc = self._set(content, path)
doc.to_path()
def get(self, filename: str) -> Optional[Document]:
"""Get a document by its filename."""
path = self._path(filename)
return self.docs.get(path) or self.codes.get(path) or self.assets.get(path)
def get_text_documents(self) -> list[Document]:
return list(self.docs.values()) + list(self.codes.values())
def eda(self) -> RepoMetadata:
n_docs = sum(len(i) for i in [self.docs, self.codes, self.assets])
n_chars = sum(sum(len(j.content) for j in i.values()) for i in [self.docs, self.codes, self.assets])
symbols = RepoParser(base_directory=self.path).generate_symbols()
return RepoMetadata(name=self.name, n_docs=n_docs, n_chars=n_chars, symbols=symbols)
def set_existing_repo(path=CONFIG.workspace_path / "t1"):
repo1 = Repo.from_path(path)
repo1.set("wtf content", "doc/wtf_file.md")
repo1.set("wtf code", "code/wtf_file.py")
logger.info(repo1) # check doc
def load_existing_repo(path=CONFIG.workspace_path / "web_tetris"):
repo = Repo.from_path(path)
logger.info(repo)
logger.info(repo.eda())
def main():
load_existing_repo()
if __name__ == "__main__":
main()

10
metagpt/document_store/base_store.py
View file

@ -28,20 +28,20 @@ class BaseStore(ABC):
class LocalStore(BaseStore, ABC):
def __init__(self, raw_data: Path, cache_dir: Path = None):
if not raw_data:
def __init__(self, raw_data_path: Path, cache_dir: Path = None):
if not raw_data_path:
raise FileNotFoundError
self.config = Config()
self.raw_data = raw_data
self.raw_data_path = raw_data_path
if not cache_dir:
cache_dir = raw_data.parent
cache_dir = raw_data_path.parent
self.cache_dir = cache_dir
self.store = self._load()
if not self.store:
self.store = self.write()
def _get_index_and_store_fname(self):
fname = self.raw_data.name.split(".")[0]
fname = self.raw_data_path.name.split(".")[0]
index_file = self.cache_dir / f"{fname}.index"
store_file = self.cache_dir / f"{fname}.pkl"
return index_file, store_file

10
metagpt/document_store/faiss_store.py
View file

@ -14,16 +14,16 @@ from langchain.embeddings import OpenAIEmbeddings
from langchain.vectorstores import FAISS
from metagpt.const import DATA_PATH
from metagpt.document import IndexableDocument
from metagpt.document_store.base_store import LocalStore
from metagpt.document_store.document import Document
from metagpt.logs import logger
class FaissStore(LocalStore):
def __init__(self, raw_data: Path, cache_dir=None, meta_col="source", content_col="output"):
def __init__(self, raw_data_path: Path, cache_dir=None, meta_col="source", content_col="output"):
self.meta_col = meta_col
self.content_col = content_col
super().__init__(raw_data, cache_dir)
super().__init__(raw_data_path, cache_dir)
def _load(self) -> Optional["FaissStore"]:
index_file, store_file = self._get_index_and_store_fname()
@ -60,9 +60,9 @@ class FaissStore(LocalStore):
def write(self):
"""Initialize the index and library based on the Document (JSON / XLSX, etc.) file provided by the user."""
if not self.raw_data.exists():
if not self.raw_data_path.exists():
raise FileNotFoundError
doc = Document(self.raw_data, self.content_col, self.meta_col)
doc = IndexableDocument.from_path(self.raw_data_path, self.content_col, self.meta_col)
docs, metadatas = doc.get_docs_and_metadatas()
self.store = self._write(docs, metadatas)

44
metagpt/environment.py
View file

@ -23,6 +23,7 @@ from metagpt.utils.common import is_subscribed
class Environment(BaseModel):
# <<<<<<< HEAD
"""环境，承载一批角色，角色可以向环境发布消息，可以被其他角色观察到
Environment, hosting a batch of roles, roles can publish messages to the environment, and can be observed by other roles
@ -31,6 +32,17 @@ class Environment(BaseModel):
roles: dict[str, Role] = Field(default_factory=dict)
members: dict[Role, Set] = Field(default_factory=dict)
history: str = Field(default="") # For debug
# =======
# """
# Environment, hosting a batch of roles, roles can publish messages to the environment, and can be observed by other roles
# """
#
# roles: dict[str, Role] = Field(default_factory=dict)
# memory: Memory = Field(default_factory=Memory) # 已经私有化
# history: str = Field(default='')
# repo: Repo = Field(default_factory=Repo) # 在CONFIG里
# kv: dict = Field(default_factory=dict) # 在CONFIG里
# >>>>>>> feature/geekan_cli_etc
class Config:
arbitrary_types_allowed = True
@ -71,6 +83,38 @@ class Environment(BaseModel):
return True
# # Replaced by FileRepository.set_file
# def set_doc(self, content: str, filename: str):
# """向当前环境发布文档（包括代码）"""
# return self.repo.set(content, filename)
#
# # Replaced by FileRepository.get_file
# def get_doc(self, filename: str):
# return self.repo.get(filename)
#
# # Replaced by CONFIG.xx
# def set(self, k: str, v: str):
# self.kv[k] = v
#
# # Replaced by CONFIG.xx
# def get(self, k: str):
# return self.kv.get(k, None)
# Replaced By 增量变更流程
# def load_existing_repo(self, path: Path, inc: bool):
# self.repo = Repo.from_path(path)
# logger.info(self.repo.eda())
#
# # Incremental mode: publish all docs to messages. Then roles can read the docs.
# if inc:
# docs = self.repo.get_text_documents()
# for doc in docs:
# msg = Message(content=doc.content)
# self.publish_message(msg)
# logger.info(f"Message from existing doc {doc.path}: {msg}")
# logger.info(f"Load {len(docs)} docs from existing repo.")
# raise NotImplementedError
async def run(self, k=1):
"""处理一次所有信息的运行
Process all Role runs at once

28
metagpt/llm.py
View file

@ -6,15 +6,25 @@
@File : llm.py
"""
from metagpt.config import CONFIG
from metagpt.provider.anthropic_api import Claude2 as Claude
from metagpt.provider.openai_api import OpenAIGPTAPI as LLM
DEFAULT_LLM = LLM()
CLAUDE_LLM = Claude()
from metagpt.provider.openai_api import OpenAIGPTAPI
from metagpt.provider.spark_api import SparkAPI
from metagpt.provider.zhipuai_api import ZhiPuAIGPTAPI
async def ai_func(prompt):
"""使用LLM进行QA
QA with LLMs
"""
return await DEFAULT_LLM.aask(prompt)
def LLM() -> "BaseGPTAPI":
"""initialize different LLM instance according to the key field existence"""
# TODO a little trick, can use registry to initialize LLM instance further
if CONFIG.openai_api_key:
llm = OpenAIGPTAPI()
elif CONFIG.claude_api_key:
llm = Claude()
elif CONFIG.spark_api_key:
llm = SparkAPI()
elif CONFIG.zhipuai_api_key:
llm = ZhiPuAIGPTAPI()
else:
raise RuntimeError("You should config a LLM configuration first")
return llm

8
metagpt/logs.py
View file

@ -10,16 +10,14 @@ import sys
from loguru import logger as _logger
from metagpt.const import PROJECT_ROOT
from metagpt.const import METAGPT_ROOT
def define_log_level(print_level="INFO", logfile_level="DEBUG"):
"""调整日志级别到level之上
Adjust the log level to above level
"""
"""Adjust the log level to above level"""
_logger.remove()
_logger.add(sys.stderr, level=print_level)
_logger.add(PROJECT_ROOT / "logs/log.txt", level=logfile_level)
_logger.add(METAGPT_ROOT / "logs/log.txt", level=logfile_level)
return _logger

2
metagpt/manager.py
View file

@ -14,7 +14,7 @@ class Manager:
def __init__(self, llm: LLM = LLM()):
self.llm = llm # Large Language Model
self.role_directions = {
"BOSS": "Product Manager",
"User": "Product Manager",
"Product Manager": "Architect",
"Architect": "Engineer",
"Engineer": "QA Engineer",

5
metagpt/memory/__init__.py
View file

@ -7,10 +7,11 @@
"""
from metagpt.memory.memory import Memory
from metagpt.memory.longterm_memory import LongTermMemory
# from metagpt.memory.longterm_memory import LongTermMemory
__all__ = [
"Memory",
"LongTermMemory",
# "LongTermMemory",
]

2
metagpt/memory/longterm_memory.py
View file

@ -30,7 +30,7 @@ class LongTermMemory(Memory):
logger.warning(f"It may the first time to run Agent {role_id}, the long-term memory is empty")
else:
logger.warning(
f"Agent {role_id} has existed memory storage with {len(messages)} messages " f"and has recovered them."
f"Agent {role_id} has existing memory storage with {len(messages)} messages " f"and has recovered them."
)
self.msg_from_recover = True
self.add_batch(messages)

1
metagpt/provider/base_chatbot.py
View file

@ -14,6 +14,7 @@ class BaseChatbot(ABC):
"""Abstract GPT class"""
mode: str = "API"
use_system_prompt: bool = True
@abstractmethod
def ask(self, msg: str) -> str:

53
metagpt/provider/base_gpt_api.py
View file

@ -5,6 +5,7 @@
@Author : alexanderwu
@File : base_gpt_api.py
"""
import json
from abc import abstractmethod
from typing import Optional
@ -33,15 +34,21 @@ class BaseGPTAPI(BaseChatbot):
return self._system_msg(self.system_prompt)
def ask(self, msg: str) -> str:
message = [self._default_system_msg(), self._user_msg(msg)]
message = [self._default_system_msg(), self._user_msg(msg)] if self.use_system_prompt else [self._user_msg(msg)]
rsp = self.completion(message)
return self.get_choice_text(rsp)
async def aask(self, msg: str, system_msgs: Optional[list[str]] = None) -> str:
if system_msgs:
message = self._system_msgs(system_msgs) + [self._user_msg(msg)]
message = (
self._system_msgs(system_msgs) + [self._user_msg(msg)]
if self.use_system_prompt
else [self._user_msg(msg)]
)
else:
message = [self._default_system_msg(), self._user_msg(msg)]
message = (
[self._default_system_msg(), self._user_msg(msg)] if self.use_system_prompt else [self._user_msg(msg)]
)
rsp = await self.acompletion_text(message, stream=True)
logger.debug(message)
# logger.debug(rsp)
@ -109,6 +116,46 @@ class BaseGPTAPI(BaseChatbot):
"""Required to provide the first text of choice"""
return rsp.get("choices")[0]["message"]["content"]
def get_choice_function(self, rsp: dict) -> dict:
"""Required to provide the first function of choice
:param dict rsp: OpenAI chat.comletion respond JSON, Note "message" must include "tool_calls",
and "tool_calls" must include "function", for example:
{...
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": null,
"tool_calls": [
{
"id": "call_Y5r6Ddr2Qc2ZrqgfwzPX5l72",
"type": "function",
"function": {
"name": "execute",
"arguments": "{\n \"language\": \"python\",\n \"code\": \"print('Hello, World!')\"\n}"
}
}
]
},
"finish_reason": "stop"
}
],
...}
:return dict: return first function of choice, for exmaple,
{'name': 'execute', 'arguments': '{\n "language": "python",\n "code": "print(\'Hello, World!\')"\n}'}
"""
return rsp.get("choices")[0]["message"]["tool_calls"][0]["function"].to_dict()
def get_choice_function_arguments(self, rsp: dict) -> dict:
"""Required to provide the first function arguments of choice.
:param dict rsp: same as in self.get_choice_function(rsp)
:return dict: return the first function arguments of choice, for example,
{'language': 'python', 'code': "print('Hello, World!')"}
"""
return json.loads(self.get_choice_function(rsp)["arguments"])
def messages_to_prompt(self, messages: list[dict]):
"""[{"role": "user", "content": msg}] to user: <msg> etc."""
return "\n".join([f"{i['role']}: {i['content']}" for i in messages])

30
metagpt/provider/constant.py Normal file
View file

@ -0,0 +1,30 @@
# function in tools, https://platform.openai.com/docs/api-reference/chat/create#chat-create-tools
# Reference: https://github.com/KillianLucas/open-interpreter/blob/v0.1.14/interpreter/llm/setup_openai_coding_llm.py
GENERAL_FUNCTION_SCHEMA = {
"name": "execute",
"description": "Executes code on the user's machine, **in the users local environment**, and returns the output",
"parameters": {
"type": "object",
"properties": {
"language": {
"type": "string",
"description": "The programming language (required parameter to the `execute` function)",
"enum": [
"python",
"R",
"shell",
"applescript",
"javascript",
"html",
"powershell",
],
},
"code": {"type": "string", "description": "The code to execute (required)"},
},
"required": ["language", "code"],
},
}
# tool_choice value for general_function_schema
# https://platform.openai.com/docs/api-reference/chat/create#chat-create-tool_choice
GENERAL_TOOL_CHOICE = {"type": "function", "function": {"name": "execute"}}

58
metagpt/provider/general_api_requestor.py Normal file
View file

@ -0,0 +1,58 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Desc : General Async API for http-based LLM model
import asyncio
from typing import AsyncGenerator, Tuple, Union
import aiohttp
from openai.api_requestor import APIRequestor
from metagpt.logs import logger
class GeneralAPIRequestor(APIRequestor):
"""
usage
# full_url = "{api_base}{url}"
requester = GeneralAPIRequestor(api_base=api_base)
result, _, api_key = await requester.arequest(
method=method,
url=url,
headers=headers,
stream=stream,
params=kwargs,
request_timeout=120
)
"""
def _interpret_response_line(self, rbody: str, rcode: int, rheaders, stream: bool) -> str:
# just do nothing to meet the APIRequestor process and return the raw data
# due to the openai sdk will convert the data into OpenAIResponse which we don't need in general cases.
return rbody
async def _interpret_async_response(
self, result: aiohttp.ClientResponse, stream: bool
) -> Tuple[Union[str, AsyncGenerator[str, None]], bool]:
if stream and "text/event-stream" in result.headers.get("Content-Type", ""):
return (
self._interpret_response_line(line, result.status, result.headers, stream=True)
async for line in result.content
), True
else:
try:
await result.read()
except (aiohttp.ServerTimeoutError, asyncio.TimeoutError) as e:
raise TimeoutError("Request timed out") from e
except aiohttp.ClientError as exp:
logger.warning(f"response: {result.content}, exp: {exp}")
return (
self._interpret_response_line(
await result.read(), # let the caller to decode the msg
result.status,
result.headers,
stream=False,
),
False,
)

37
metagpt/provider/human_provider.py Normal file
View file

@ -0,0 +1,37 @@
"""
Filename: MetaGPT/metagpt/provider/human_provider.py
Created Date: Wednesday, November 8th 2023, 11:55:46 pm
Author: garylin2099
"""
from typing import Optional
from metagpt.logs import logger
from metagpt.provider.base_gpt_api import BaseGPTAPI
class HumanProvider(BaseGPTAPI):
"""Humans provide themselves as a 'model', which actually takes in human input as its response.
This enables replacing LLM anywhere in the framework with a human, thus introducing human interaction
"""
def ask(self, msg: str) -> str:
logger.info("It's your turn, please type in your response. You may also refer to the context below")
rsp = input(msg)
if rsp in ["exit", "quit"]:
exit()
return rsp
async def aask(self, msg: str, system_msgs: Optional[list[str]] = None) -> str:
return self.ask(msg)
def completion(self, messages: list[dict]):
"""dummy implementation of abstract method in base"""
return []
async def acompletion(self, messages: list[dict]):
"""dummy implementation of abstract method in base"""
return []
async def acompletion_text(self, messages: list[dict], stream=False) -> str:
"""dummy implementation of abstract method in base"""
return []

84
metagpt/provider/openai_api.py
View file

@ -21,6 +21,8 @@ from tenacity import (
from metagpt.config import CONFIG
from metagpt.logs import logger
from metagpt.provider.base_gpt_api import BaseGPTAPI
from metagpt.provider.constant import GENERAL_FUNCTION_SCHEMA, GENERAL_TOOL_CHOICE
from metagpt.schema import Message
from metagpt.utils.singleton import Singleton
from metagpt.utils.token_counter import (
TOKEN_COSTS,
@ -155,6 +157,8 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
if config.openai_api_type:
openai.api_type = config.openai_api_type
openai.api_version = config.openai_api_version
if config.openai_proxy:
openai.proxy = config.openai_proxy
self.rpm = int(config.get("RPM", 10))
async def _achat_completion_stream(self, messages: list[dict]) -> str:
@ -179,7 +183,7 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
self._update_costs(usage)
return full_reply_content
def _cons_kwargs(self, messages: list[dict]) -> dict:
def _cons_kwargs(self, messages: list[dict], **configs) -> dict:
kwargs = {
"messages": messages,
"max_tokens": self.get_max_tokens(messages),
@ -188,6 +192,9 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
"temperature": 0.3,
"timeout": 3,
}
if configs:
kwargs.update(configs)
if CONFIG.openai_api_type == "azure":
if CONFIG.deployment_name and CONFIG.deployment_id:
raise ValueError("You can only use one of the `deployment_id` or `deployment_name` model")
@ -237,6 +244,81 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
rsp = await self._achat_completion(messages)
return self.get_choice_text(rsp)
def _func_configs(self, messages: list[dict], **kwargs) -> dict:
"""
Note: Keep kwargs consistent with the parameters in the https://platform.openai.com/docs/api-reference/chat/create
"""
if "tools" not in kwargs:
configs = {
"tools": [{"type": "function", "function": GENERAL_FUNCTION_SCHEMA}],
"tool_choice": GENERAL_TOOL_CHOICE,
}
kwargs.update(configs)
return self._cons_kwargs(messages, **kwargs)
def _chat_completion_function(self, messages: list[dict], **kwargs) -> dict:
rsp = self.llm.ChatCompletion.create(**self._func_configs(messages, **kwargs))
self._update_costs(rsp.get("usage"))
return rsp
async def _achat_completion_function(self, messages: list[dict], **chat_configs) -> dict:
rsp = await self.llm.ChatCompletion.acreate(**self._func_configs(messages, **chat_configs))
self._update_costs(rsp.get("usage"))
return rsp
def _process_message(self, messages: Union[str, Message, list[dict], list[Message], list[str]]) -> list[dict]:
"""convert messages to list[dict]."""
if isinstance(messages, list):
messages = [Message(msg) if isinstance(msg, str) else msg for msg in messages]
return [msg if isinstance(msg, dict) else msg.to_dict() for msg in messages]
if isinstance(messages, Message):
messages = [messages.to_dict()]
elif isinstance(messages, str):
messages = [{"role": "user", "content": messages}]
else:
raise ValueError(
f"Only support messages type are: str, Message, list[dict], but got {type(messages).__name__}!"
)
return messages
def ask_code(self, messages: Union[str, Message, list[dict]], **kwargs) -> dict:
"""Use function of tools to ask a code.
Note: Keep kwargs consistent with the parameters in the https://platform.openai.com/docs/api-reference/chat/create
Examples:
>>> llm = OpenAIGPTAPI()
>>> llm.ask_code("Write a python hello world code.")
{'language': 'python', 'code': "print('Hello, World!')"}
>>> msg = [{'role': 'user', 'content': "Write a python hello world code."}]
>>> llm.ask_code(msg)
{'language': 'python', 'code': "print('Hello, World!')"}
"""
messages = self._process_message(messages)
rsp = self._chat_completion_function(messages, **kwargs)
return self.get_choice_function_arguments(rsp)
async def aask_code(self, messages: Union[str, Message, list[dict]], **kwargs) -> dict:
"""Use function of tools to ask a code.
Note: Keep kwargs consistent with the parameters in the https://platform.openai.com/docs/api-reference/chat/create
Examples:
>>> llm = OpenAIGPTAPI()
>>> rsp = await llm.ask_code("Write a python hello world code.")
>>> rsp
{'language': 'python', 'code': "print('Hello, World!')"}
>>> msg = [{'role': 'user', 'content': "Write a python hello world code."}]
>>> rsp = await llm.aask_code(msg) # -> {'language': 'python', 'code': "print('Hello, World!')"}
"""
messages = self._process_message(messages)
rsp = await self._achat_completion_function(messages, **kwargs)
return self.get_choice_function_arguments(rsp)
def _calc_usage(self, messages: list[dict], rsp: str) -> dict:
usage = {}
if CONFIG.calc_usage:

3
metagpt/provider/zhipuai/__init__.py Normal file
View file

@ -0,0 +1,3 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Desc :

75
metagpt/provider/zhipuai/async_sse_client.py Normal file
View file

@ -0,0 +1,75 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Desc : async_sse_client to make keep the use of Event to access response
# refs to `https://github.com/zhipuai/zhipuai-sdk-python/blob/main/zhipuai/utils/sse_client.py`
from zhipuai.utils.sse_client import _FIELD_SEPARATOR, Event, SSEClient
class AsyncSSEClient(SSEClient):
async def _aread(self):
data = b""
async for chunk in self._event_source:
for line in chunk.splitlines(True):
data += line
if data.endswith((b"\r\r", b"\n\n", b"\r\n\r\n")):
yield data
data = b""
if data:
yield data
async def async_events(self):
async for chunk in self._aread():
event = Event()
# Split before decoding so splitlines() only uses \r and \n
for line in chunk.splitlines():
# Decode the line.
line = line.decode(self._char_enc)
# Lines starting with a separator are comments and are to be
# ignored.
if not line.strip() or line.startswith(_FIELD_SEPARATOR):
continue
data = line.split(_FIELD_SEPARATOR, 1)
field = data[0]
# Ignore unknown fields.
if field not in event.__dict__:
self._logger.debug("Saw invalid field %s while parsing " "Server Side Event", field)
continue
if len(data) > 1:
# From the spec:
# "If value starts with a single U+0020 SPACE character,
# remove it from value."
if data[1].startswith(" "):
value = data[1][1:]
else:
value = data[1]
else:
# If no value is present after the separator,
# assume an empty value.
value = ""
# The data field may come over multiple lines and their values
# are concatenated with each other.
if field == "data":
event.__dict__[field] += value + "\n"
else:
event.__dict__[field] = value
# Events with no data are not dispatched.
if not event.data:
continue
# If the data field ends with a newline, remove it.
if event.data.endswith("\n"):
event.data = event.data[0:-1]
# Empty event names default to 'message'
event.event = event.event or "message"
# Dispatch the event
self._logger.debug("Dispatching %s...", event)
yield event

72
metagpt/provider/zhipuai/zhipu_model_api.py Normal file
View file

@ -0,0 +1,72 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Desc : zhipu model api to support sync & async for invoke & sse_invoke
import zhipuai
from zhipuai.model_api.api import InvokeType, ModelAPI
from zhipuai.utils.http_client import headers as zhipuai_default_headers
from metagpt.provider.general_api_requestor import GeneralAPIRequestor
from metagpt.provider.zhipuai.async_sse_client import AsyncSSEClient
class ZhiPuModelAPI(ModelAPI):
@classmethod
def get_header(cls) -> dict:
token = cls._generate_token()
zhipuai_default_headers.update({"Authorization": token})
return zhipuai_default_headers
@classmethod
def get_sse_header(cls) -> dict:
token = cls._generate_token()
headers = {"Authorization": token}
return headers
@classmethod
def split_zhipu_api_url(cls, invoke_type: InvokeType, kwargs):
# use this method to prevent zhipu api upgrading to different version.
# and follow the GeneralAPIRequestor implemented based on openai sdk
zhipu_api_url = cls._build_api_url(kwargs, invoke_type)
"""
example:
zhipu_api_url: https://open.bigmodel.cn/api/paas/v3/model-api/{model}/{invoke_method}
"""
arr = zhipu_api_url.split("/api/")
# ("https://open.bigmodel.cn/api/" , "/paas/v3/model-api/chatglm_turbo/invoke")
return f"{arr[0]}/api", f"/{arr[1]}"
@classmethod
async def arequest(cls, invoke_type: InvokeType, stream: bool, method: str, headers: dict, kwargs):
# TODO to make the async request to be more generic for models in http mode.
assert method in ["post", "get"]
api_base, url = cls.split_zhipu_api_url(invoke_type, kwargs)
requester = GeneralAPIRequestor(api_base=api_base)
result, _, api_key = await requester.arequest(
method=method,
url=url,
headers=headers,
stream=stream,
params=kwargs,
request_timeout=zhipuai.api_timeout_seconds,
)
return result
@classmethod
async def ainvoke(cls, **kwargs) -> dict:
"""async invoke different from raw method `async_invoke` which get the final result by task_id"""
headers = cls.get_header()
resp = await cls.arequest(
invoke_type=InvokeType.SYNC, stream=False, method="post", headers=headers, kwargs=kwargs
)
return resp
@classmethod
async def asse_invoke(cls, **kwargs) -> AsyncSSEClient:
"""async sse_invoke"""
headers = cls.get_sse_header()
return AsyncSSEClient(
await cls.arequest(invoke_type=InvokeType.SSE, stream=True, method="post", headers=headers, kwargs=kwargs)
)

135
metagpt/provider/zhipuai_api.py Normal file
View file

@ -0,0 +1,135 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Desc : zhipuai LLM from https://open.bigmodel.cn/dev/api#sdk
import json
from enum import Enum
import openai
import zhipuai
from requests import ConnectionError
from tenacity import (
after_log,
retry,
retry_if_exception_type,
stop_after_attempt,
wait_fixed,
)
from metagpt.config import CONFIG
from metagpt.logs import logger
from metagpt.provider.base_gpt_api import BaseGPTAPI
from metagpt.provider.openai_api import CostManager, log_and_reraise
from metagpt.provider.zhipuai.zhipu_model_api import ZhiPuModelAPI
class ZhiPuEvent(Enum):
ADD = "add"
ERROR = "error"
INTERRUPTED = "interrupted"
FINISH = "finish"
class ZhiPuAIGPTAPI(BaseGPTAPI):
"""
Refs to `https://open.bigmodel.cn/dev/api#chatglm_turbo`
From now, there is only one model named `chatglm_turbo`
"""
use_system_prompt: bool = False # zhipuai has no system prompt when use api
def __init__(self):
self.__init_zhipuai(CONFIG)
self.llm = ZhiPuModelAPI
self.model = "chatglm_turbo" # so far only one model, just use it
self._cost_manager = CostManager()
def __init_zhipuai(self, config: CONFIG):
assert config.zhipuai_api_key
zhipuai.api_key = config.zhipuai_api_key
openai.api_key = zhipuai.api_key # due to use openai sdk, set the api_key but it will't be used.
def _const_kwargs(self, messages: list[dict]) -> dict:
kwargs = {"model": self.model, "prompt": messages, "temperature": 0.3}
return kwargs
def _update_costs(self, usage: dict):
"""update each request's token cost"""
if CONFIG.calc_usage:
try:
prompt_tokens = int(usage.get("prompt_tokens", 0))
completion_tokens = int(usage.get("completion_tokens", 0))
self._cost_manager.update_cost(prompt_tokens, completion_tokens, self.model)
except Exception as e:
logger.error("zhipuai updats costs failed!", e)
def get_choice_text(self, resp: dict) -> str:
"""get the first text of choice from llm response"""
assist_msg = resp.get("data", {}).get("choices", [{"role": "error"}])[-1]
assert assist_msg["role"] == "assistant"
return assist_msg.get("content")
def completion(self, messages: list[dict]) -> dict:
resp = self.llm.invoke(**self._const_kwargs(messages))
usage = resp.get("data").get("usage")
self._update_costs(usage)
return resp
async def _achat_completion(self, messages: list[dict]) -> dict:
resp = await self.llm.ainvoke(**self._const_kwargs(messages))
usage = resp.get("data").get("usage")
self._update_costs(usage)
return resp
async def acompletion(self, messages: list[dict]) -> dict:
return await self._achat_completion(messages)
async def _achat_completion_stream(self, messages: list[dict]) -> str:
response = await self.llm.asse_invoke(**self._const_kwargs(messages))
collected_content = []
usage = {}
async for event in response.async_events():
if event.event == ZhiPuEvent.ADD.value:
content = event.data
collected_content.append(content)
print(content, end="")
elif event.event == ZhiPuEvent.ERROR.value or event.event == ZhiPuEvent.INTERRUPTED.value:
content = event.data
logger.error(f"event error: {content}", end="")
collected_content.append([content])
elif event.event == ZhiPuEvent.FINISH.value:
"""
event.meta
{
"task_status":"SUCCESS",
"usage":{
"completion_tokens":351,
"prompt_tokens":595,
"total_tokens":946
},
"task_id":"xx",
"request_id":"xxx"
}
"""
meta = json.loads(event.meta)
usage = meta.get("usage")
else:
print(f"zhipuapi else event: {event.data}", end="")
self._update_costs(usage)
full_content = "".join(collected_content)
return full_content
@retry(
stop=stop_after_attempt(3),
wait=wait_fixed(1),
after=after_log(logger, logger.level("WARNING").name),
retry=retry_if_exception_type(ConnectionError),
retry_error_callback=log_and_reraise,
)
async def acompletion_text(self, messages: list[dict], stream=False) -> str:
"""response in async with stream or non-stream mode"""
if stream:
return await self._achat_completion_stream(messages)
resp = await self._achat_completion(messages)
return self.get_choice_text(resp)

94
metagpt/repo_parser.py Normal file
View file

@ -0,0 +1,94 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Time : 2023/11/17 17:58
@Author : alexanderwu
@File : repo_parser.py
"""
import ast
import json
from pathlib import Path
from pprint import pformat
import pandas as pd
from pydantic import BaseModel, Field
from metagpt.config import CONFIG
from metagpt.logs import logger
class RepoParser(BaseModel):
base_directory: Path = Field(default=None)
def parse_file(self, file_path):
"""Parse a Python file in the repository."""
try:
return ast.parse(file_path.read_text()).body
except:
return []
def extract_class_and_function_info(self, tree, file_path):
"""Extract class, function, and global variable information from the AST."""
file_info = {
"file": str(file_path.relative_to(self.base_directory)),
"classes": [],
"functions": [],
"globals": [],
}
for node in tree:
if isinstance(node, ast.ClassDef):
class_methods = [m.name for m in node.body if is_func(m)]
file_info["classes"].append({"name": node.name, "methods": class_methods})
elif is_func(node):
file_info["functions"].append(node.name)
elif isinstance(node, (ast.Assign, ast.AnnAssign)):
for target in node.targets if isinstance(node, ast.Assign) else [node.target]:
if isinstance(target, ast.Name):
file_info["globals"].append(target.id)
return file_info
def generate_symbols(self):
files_classes = []
directory = self.base_directory
for path in directory.rglob("*.py"):
tree = self.parse_file(path)
file_info = self.extract_class_and_function_info(tree, path)
files_classes.append(file_info)
return files_classes
def generate_json_structure(self, output_path):
"""Generate a JSON file documenting the repository structure."""
files_classes = self.generate_symbols()
output_path.write_text(json.dumps(files_classes, indent=4))
def generate_dataframe_structure(self, output_path):
"""Generate a DataFrame documenting the repository structure and save as CSV."""
files_classes = self.generate_symbols()
df = pd.DataFrame(files_classes)
df.to_csv(output_path, index=False)
def generate_structure(self, output_path=None, mode="json"):
"""Generate the structure of the repository as a specified format."""
output_file = self.base_directory / f"{self.base_directory.name}-structure.{mode}"
output_path = Path(output_path) if output_path else output_file
if mode == "json":
self.generate_json_structure(output_path)
elif mode == "csv":
self.generate_dataframe_structure(output_path)
def is_func(node):
return isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef))
def main():
repo_parser = RepoParser(base_directory=CONFIG.workspace_path / "web_2048")
symbols = repo_parser.generate_symbols()
logger.info(pformat(symbols))
if __name__ == "__main__":
main()

269
metagpt/roles/engineer.py
View file

@ -21,11 +21,18 @@ from pathlib import Path
from typing import Set
from metagpt.actions import Action, WriteCode, WriteCodeReview, WriteTasks
from metagpt.actions.summarize_code import SummarizeCode
from metagpt.config import CONFIG
from metagpt.const import SYSTEM_DESIGN_FILE_REPO, TASK_FILE_REPO
from metagpt.const import MESSAGE_ROUTE_TO_NONE, SYSTEM_DESIGN_FILE_REPO, TASK_FILE_REPO
from metagpt.logs import logger
from metagpt.roles import Role
from metagpt.schema import CodingContext, Document, Documents, Message
from metagpt.schema import (
CodeSummarizeContext,
CodingContext,
Document,
Documents,
Message,
)
class Engineer(Role):
@ -39,7 +46,6 @@ class Engineer(Role):
constraints (str): Constraints for the engineer.
n_borg (int): Number of borgs.
use_code_review (bool): Whether to use code review.
todos (list): List of tasks.
"""
def __init__(
@ -55,7 +61,8 @@ class Engineer(Role):
super().__init__(name, profile, goal, constraints)
self.use_code_review = use_code_review
self._watch([WriteTasks])
self.todos = []
self.code_todos = []
self.summarize_todos = []
self.n_borg = n_borg
@staticmethod
@ -63,10 +70,100 @@ class Engineer(Role):
m = json.loads(task_msg.content)
return m.get("Task list")
async def _act_sp_precision(self, review=False) -> Set[str]:
# @classmethod
# def parse_tasks(cls, task_msg: Message) -> list[str]:
# if task_msg.instruct_content:
# return task_msg.instruct_content.dict().get("Task list")
# return CodeParser.parse_file_list(block="Task list", text=task_msg.content)
#
# @classmethod
# def parse_code(cls, code_text: str) -> str:
# return CodeParser.parse_code(block="", text=code_text)
#
# @classmethod
# def parse_workspace(cls, system_design_msg: Message) -> str:
# if system_design_msg.instruct_content:
# return system_design_msg.instruct_content.dict().get("project_name").strip().strip("'").strip('"')
# return CodeParser.parse_str(block="project_name", text=system_design_msg.content)
#
# def get_workspace(self) -> Path:
# msg = self._rc.memory.get_by_action(WriteDesign)[-1]
# if not msg:
# return CONFIG.workspace_path / "src"
# workspace = self.parse_workspace(msg)
# # Codes are written in workspace/{package_name}/{package_name}
# return CONFIG.workspace_path / workspace / workspace
#
# def recreate_workspace(self):
# workspace = self.get_workspace()
# try:
# shutil.rmtree(workspace)
# except FileNotFoundError:
# pass # The folder does not exist, but we don't care
# workspace.mkdir(parents=True, exist_ok=True)
#
# def write_file(self, filename: str, code: str):
# workspace = self.get_workspace()
# filename = filename.replace('"', "").replace("\n", "")
# file = workspace / filename
# file.parent.mkdir(parents=True, exist_ok=True)
# file.write_text(code)
# return file
#
# def recv(self, message: Message) -> None:
# self._rc.memory.add(message)
# if message in self._rc.important_memory:
# self.todos = self.parse_tasks(message)
#
# async def _act_mp(self) -> Message:
# # self.recreate_workspace()
# todo_coros = []
# for todo in self.todos:
# todo_coro = WriteCode().run(
# context=self._rc.memory.get_by_actions([WriteTasks, WriteDesign]), filename=todo
# )
# todo_coros.append(todo_coro)
#
# rsps = await gather_ordered_k(todo_coros, self.n_borg)
# for todo, code_rsp in zip(self.todos, rsps):
# _ = self.parse_code(code_rsp)
# logger.info(todo)
# logger.info(code_rsp)
# # self.write_file(todo, code)
# msg = Message(content=code_rsp, role=self.profile, cause_by=type(self._rc.todo))
# self._rc.memory.add(msg)
# del self.todos[0]
#
# logger.info(f"Done {self.get_workspace()} generating.")
# msg = Message(content="all done.", role=self.profile, cause_by=type(self._rc.todo))
# return msg
#
# async def _act_sp(self) -> Message:
# code_msg_all = [] # gather all code info, will pass to qa_engineer for tests later
# for todo in self.todos:
# code = await WriteCode().run(context=self._rc.history, filename=todo)
# # logger.info(todo)
# # logger.info(code_rsp)
# # code = self.parse_code(code_rsp)
# file_path = self.write_file(todo, code)
# msg = Message(content=code, role=self.profile, cause_by=type(self._rc.todo))
# self._rc.memory.add(msg)
#
# code_msg = todo + FILENAME_CODE_SEP + str(file_path)
# code_msg_all.append(code_msg)
#
# logger.info(f"Done {self.get_workspace()} generating.")
# msg = Message(
# content=MSG_SEP.join(code_msg_all), role=self.profile, cause_by=type(self._rc.todo), send_to="QaEngineer"
# )
# return msg
# async def _act_sp_with_cr(self) -> Message:
# code_msg_all = [] # gather all code info, will pass to qa_engineer for tests later
async def _act_sp_with_cr(self, review=False) -> Set[str]:
changed_files = set()
src_file_repo = CONFIG.git_repo.new_file_repository(CONFIG.src_workspace)
for todo in self.todos:
for todo in self.code_todos:
"""
# Select essential information from the historical data to reduce the length of the prompt (summarized from human experience):
1. All from Architect
@ -77,11 +174,7 @@ class Engineer(Role):
coding_context = await todo.run()
# Code review
if review:
try:
coding_context = await WriteCodeReview(context=coding_context, llm=self._llm).run()
except Exception as e:
logger.error("code review failed!", e)
pass
coding_context = await WriteCodeReview(context=coding_context, llm=self._llm).run()
await src_file_repo.save(
coding_context.filename,
dependencies={coding_context.design_doc.root_relative_path, coding_context.task_doc.root_relative_path},
@ -90,6 +183,24 @@ class Engineer(Role):
msg = Message(
content=coding_context.json(), instruct_content=coding_context, role=self.profile, cause_by=WriteCode
)
# =======
# context = []
# msg = self._rc.memory.get_by_actions([WriteDesign, WriteTasks, WriteCode])
# for m in msg:
# context.append(m.content)
# context_str = "\n----------\n".join(context)
# # Write code
# code = await WriteCode().run(context=context_str, filename=todo)
# # Code review
# if self.use_code_review:
# # try:
# rewrite_code = await WriteCodeReview().run(context=context_str, code=code, filename=todo)
# code = rewrite_code
# # except Exception as e:
# # logger.error("code review failed!", e)
# file_path = self.write_file(todo, code)
# msg = Message(content=code, role=self.profile, cause_by=WriteCode)
# >>>>>>> feature/geekan_cli_etc
self._rc.memory.add(msg)
changed_files.add(coding_context.code_doc.filename)
@ -97,26 +208,81 @@ class Engineer(Role):
logger.info("Nothing has changed.")
return changed_files
async def _act(self) -> Message:
async def _act(self) -> Message | None:
"""Determines the mode of action based on whether code review is used."""
changed_files = await self._act_sp_precision(review=self.use_code_review)
# Unit tests only.
if CONFIG.REQA_FILENAME and CONFIG.REQA_FILENAME not in changed_files:
changed_files.add(CONFIG.REQA_FILENAME)
from metagpt.roles import QaEngineer # Avoid circular references.
msg = Message(
content="\n".join(changed_files),
role=self.profile,
cause_by=WriteCodeReview if self.use_code_review else WriteCode,
send_to=QaEngineer,
)
return msg
if self._rc.todo is None:
return None
if isinstance(self._rc.todo, WriteCode):
changed_files = await self._act_sp_with_cr(review=self.use_code_review)
# Unit tests only.
if CONFIG.REQA_FILENAME and CONFIG.REQA_FILENAME not in changed_files:
changed_files.add(CONFIG.REQA_FILENAME)
return Message(
content="\n".join(changed_files),
role=self.profile,
cause_by=WriteCodeReview if self.use_code_review else WriteCode,
send_to="Edward", # The name of QaEngineer
)
if isinstance(self._rc.todo, SummarizeCode):
summaries = []
for todo in self.summarize_todos:
summary = await todo.run()
summaries.append(summary.json(ensure_ascii=False))
return Message(
content="\n".join(summaries),
role=self.profile,
cause_by=SummarizeCode,
send_to=MESSAGE_ROUTE_TO_NONE,
)
return None
async def _think(self) -> Action | None:
if not CONFIG.src_workspace:
CONFIG.src_workspace = CONFIG.git_repo.workdir / CONFIG.git_repo.workdir.name
if not self.code_todos:
await self._new_code_actions()
elif not self.summarize_todos:
await self._new_summarize_actions()
else:
return None
return self._rc.todo # For agent store
@staticmethod
async def _new_coding_context(
filename, src_file_repo, task_file_repo, design_file_repo, dependency
) -> CodingContext:
old_code_doc = await src_file_repo.get(filename)
if not old_code_doc:
old_code_doc = Document(root_path=str(src_file_repo.root_path), filename=filename, content="")
dependencies = {Path(i) for i in await dependency.get(old_code_doc.root_relative_path)}
task_doc = None
design_doc = None
for i in dependencies:
if str(i.parent) == TASK_FILE_REPO:
task_doc = task_file_repo.get(i.filename)
elif str(i.parent) == SYSTEM_DESIGN_FILE_REPO:
design_doc = design_file_repo.get(i.filename)
context = CodingContext(filename=filename, design_doc=design_doc, task_doc=task_doc, code_doc=old_code_doc)
return context
@staticmethod
async def _new_coding_doc(filename, src_file_repo, task_file_repo, design_file_repo, dependency):
context = await Engineer._new_coding_context(
filename, src_file_repo, task_file_repo, design_file_repo, dependency
)
coding_doc = Document(root_path=str(src_file_repo.root_path), filename=filename, content=context.json())
return coding_doc
# =======
# async def _act(self) -> Message:
# """Determines the mode of action based on whether code review is used."""
# logger.info(f"{self._setting}: ready to WriteCode")
# if self.use_code_review:
# return await self._act_sp_with_cr()
# return await self._act_sp()
# >>>>>>> feature/geekan_cli_etc
async def _new_code_actions(self):
# Prepare file repos
src_file_repo = CONFIG.git_repo.new_file_repository(CONFIG.src_workspace)
changed_src_files = src_file_repo.changed_files
@ -146,7 +312,7 @@ class Engineer(Role):
f"{changed_files.docs[task_filename].json()}"
)
changed_files.docs[task_filename] = coding_doc
self.todos = [WriteCode(context=i, llm=self._llm) for i in changed_files.docs.values()]
self.code_todos = [WriteCode(context=i, llm=self._llm) for i in changed_files.docs.values()]
# Code directly modified by the user.
dependency = await CONFIG.git_repo.get_dependency()
for filename in changed_src_files:
@ -160,34 +326,25 @@ class Engineer(Role):
dependency=dependency,
)
changed_files.docs[filename] = coding_doc
self.todos.append(WriteCode(context=coding_doc, llm=self._llm))
self.code_todos.append(WriteCode(context=coding_doc, llm=self._llm))
if self.todos:
self._rc.todo = self.todos[0]
return self._rc.todo # For agent store
if self.code_todos:
self._rc.todo = self.code_todos[0]
@staticmethod
async def _new_coding_context(
filename, src_file_repo, task_file_repo, design_file_repo, dependency
) -> CodingContext:
old_code_doc = await src_file_repo.get(filename)
if not old_code_doc:
old_code_doc = Document(root_path=str(src_file_repo.root_path), filename=filename, content="")
dependencies = {Path(i) for i in await dependency.get(old_code_doc.root_relative_path)}
task_doc = None
design_doc = None
for i in dependencies:
if str(i.parent) == TASK_FILE_REPO:
task_doc = task_file_repo.get(i.filename)
elif str(i.parent) == SYSTEM_DESIGN_FILE_REPO:
design_doc = design_file_repo.get(i.filename)
context = CodingContext(filename=filename, design_doc=design_doc, task_doc=task_doc, code_doc=old_code_doc)
return context
@staticmethod
async def _new_coding_doc(filename, src_file_repo, task_file_repo, design_file_repo, dependency):
context = await Engineer._new_coding_context(
filename, src_file_repo, task_file_repo, design_file_repo, dependency
)
coding_doc = Document(root_path=str(src_file_repo.root_path), filename=filename, content=context.json())
return coding_doc
async def _new_summarize_actions(self):
src_file_repo = CONFIG.git_repo.new_file_repository(CONFIG.src_workspace)
changed_src_files = src_file_repo.changed_files
# Generate a SummarizeCode action for each pair of (system_design_doc, task_doc).
summerizations = {}
for filename in changed_src_files:
depenencies = src_file_repo.get_dependency(filename=filename)
ctx = CodeSummarizeContext.loads(filenames=depenencies)
if ctx not in summerizations:
summerizations[ctx] = set()
srcs = summerizations.get(ctx)
srcs.add(filename)
for ctx, filenames in summerizations.items():
ctx.codes_filenames = filenames
self.summarize_todos.append(SummarizeCode(context=ctx, llm=self._llm))
if self.summarize_todos:
self._rc.todo = self.summarize_todos[0]

25
metagpt/roles/invoice_ocr_assistant.py
View file

@ -42,17 +42,7 @@ class InvoiceOCRAssistant(Role):
self.filename = ""
self.origin_query = ""
self.orc_data = None
async def _think(self) -> None:
"""Determine the next action to be taken by the role."""
if self._rc.todo is None:
self._set_state(0)
return
if self._rc.state + 1 < len(self._states):
self._set_state(self._rc.state + 1)
else:
self._rc.todo = None
self._set_react_mode(react_mode="by_order")
async def _act(self) -> Message:
"""Perform an action as determined by the role.
@ -94,16 +84,3 @@ class InvoiceOCRAssistant(Role):
msg = Message(content=content, instruct_content=resp)
self._rc.memory.add(msg)
return msg
async def _react(self) -> Message:
"""Execute the invoice ocr assistant's think and actions.
Returns:
A message containing the final result of the assistant's actions.
"""
while True:
await self._think()
if self._rc.todo is None:
break
msg = await self._act()
return msg

6
metagpt/roles/product_manager.py
View file

@ -6,7 +6,8 @@
@File : product_manager.py
@Modified By: mashenquan, 2023/11/27. Add `PrepareDocuments` action according to Section 2.2.3.5.1 of RFC 135.
"""
from metagpt.actions import BossRequirement, WritePRD
from metagpt.actions import UserRequirement, WritePRD
from metagpt.actions.prepare_documents import PrepareDocuments
from metagpt.config import CONFIG
from metagpt.roles import Role
@ -40,8 +41,9 @@ class ProductManager(Role):
constraints (str): Constraints or limitations for the product manager.
"""
super().__init__(name, profile, goal, constraints)
self._init_actions([PrepareDocuments, WritePRD])
self._watch([BossRequirement, PrepareDocuments])
self._watch([UserRequirement, PrepareDocuments])
async def _think(self) -> None:
"""Decide what to do"""

28
metagpt/roles/qa_engineer.py
View file

@ -13,6 +13,8 @@
to using file references.
"""
from metagpt.actions import DebugError, RunCode, WriteCode, WriteCodeReview, WriteTest
# from metagpt.const import WORKSPACE_ROOT
from metagpt.config import CONFIG
from metagpt.const import (
MESSAGE_ROUTE_TO_NONE,
@ -42,6 +44,32 @@ class QaEngineer(Role):
self.test_round = 0
self.test_round_allowed = test_round_allowed
# <<<<<<< HEAD
# =======
# @classmethod
# def parse_workspace(cls, system_design_msg: Message) -> str:
# if system_design_msg.instruct_content:
# return system_design_msg.instruct_content.dict().get("project_name")
# return CodeParser.parse_str(block="project_name", text=system_design_msg.content)
#
# def get_workspace(self, return_proj_dir=True) -> Path:
# msg = self._rc.memory.get_by_action(WriteDesign)[-1]
# if not msg:
# return CONFIG.workspace_path / "src"
# workspace = self.parse_workspace(msg)
# # project directory: workspace/{package_name}, which contains package source code folder, tests folder, resources folder, etc.
# if return_proj_dir:
# return CONFIG.workspace_path / workspace
# # development codes directory: workspace/{package_name}/{package_name}
# return CONFIG.workspace_path / workspace / workspace
#
# def write_file(self, filename: str, code: str):
# workspace = self.get_workspace() / "tests"
# file = workspace / filename
# file.parent.mkdir(parents=True, exist_ok=True)
# file.write_text(code)
#
# >>>>>>> feature/geekan_cli_etc
async def _write_test(self, message: Message) -> None:
changed_files = message.content.splitlines()
src_file_repo = CONFIG.git_repo.new_file_repository(CONFIG.src_workspace)

19
metagpt/roles/researcher.py
View file

@ -36,20 +36,11 @@ class Researcher(Role):
):
super().__init__(name, profile, goal, constraints, **kwargs)
self._init_actions([CollectLinks(name), WebBrowseAndSummarize(name), ConductResearch(name)])
self._set_react_mode(react_mode="by_order")
self.language = language
if language not in ("en-us", "zh-cn"):
logger.warning(f"The language `{language}` has not been tested, it may not work.")
async def _think(self) -> None:
if self._rc.todo is None:
self._set_state(0)
return
if self._rc.state + 1 < len(self._states):
self._set_state(self._rc.state + 1)
else:
self._rc.todo = None
async def _act(self) -> Message:
logger.info(f"{self._setting}: ready to {self._rc.todo}")
todo = self._rc.todo
@ -78,12 +69,8 @@ class Researcher(Role):
self._rc.memory.add(ret)
return ret
async def _react(self) -> Message:
while True:
await self._think()
if self._rc.todo is None:
break
msg = await self._act()
async def react(self) -> Message:
msg = await super().react()
report = msg.instruct_content
self.write_report(report.topic, report.content)
return msg

171
metagpt/roles/role.py
View file

@ -20,15 +20,18 @@
"""
from __future__ import annotations
from enum import Enum
from typing import Iterable, Set, Type
from pydantic import BaseModel, Field
from metagpt.actions import Action, ActionOutput
from metagpt.config import CONFIG
from metagpt.llm import LLM
from metagpt.llm import LLM, HumanProvider
from metagpt.logs import logger
from metagpt.memory import LongTermMemory, Memory
from metagpt.memory import Memory
# from metagpt.memory import LongTermMemory
from metagpt.schema import Message, MessageQueue
from metagpt.utils.common import any_to_str
@ -40,12 +43,14 @@ Please note that only the text between the first and second "===" is information
{history}
===
You can now choose one of the following stages to decide the stage you need to go in the next step:
Your previous stage: {previous_state}
Now choose one of the following stages you need to go to in the next step:
{states}
Just answer a number between 0-{n_states}, choose the most suitable stage according to the understanding of the conversation.
Please note that the answer only needs a number, no need to add any other text.
If there is no conversation record, choose 0.
If you think you have completed your goal and don't need to go to any of the stages, return -1.
Do not answer anything else, and do not add any other information in your answer.
"""
@ -60,6 +65,16 @@ ROLE_TEMPLATE = """Your response should be based on the previous conversation hi
"""
class RoleReactMode(str, Enum):
REACT = "react"
BY_ORDER = "by_order"
PLAN_AND_ACT = "plan_and_act"
@classmethod
def values(cls):
return [item.value for item in cls]
class RoleSetting(BaseModel):
"""Role Settings"""
@ -68,6 +83,7 @@ class RoleSetting(BaseModel):
goal: str
constraints: str
desc: str
is_human: bool
def __str__(self):
return f"{self.name}({self.profile})"
@ -82,11 +98,15 @@ class RoleContext(BaseModel):
env: "Environment" = Field(default=None)
msg_buffer: MessageQueue = Field(default_factory=MessageQueue) # Message Buffer with Asynchronous Updates
memory: Memory = Field(default_factory=Memory)
long_term_memory: LongTermMemory = Field(default_factory=LongTermMemory)
state: int = Field(default=0)
# long_term_memory: LongTermMemory = Field(default_factory=LongTermMemory)
state: int = Field(default=-1) # -1 indicates initial or termination state where todo is None
todo: Action = Field(default=None)
watch: set[str] = Field(default_factory=set)
news: list[Type[Message]] = Field(default=[])
react_mode: RoleReactMode = (
RoleReactMode.REACT
) # see `Role._set_react_mode` for definitions of the following two attributes
max_react_loop: int = 1
class Config:
arbitrary_types_allowed = True
@ -109,9 +129,11 @@ class RoleContext(BaseModel):
class Role:
"""Role/Agent"""
def __init__(self, name="", profile="", goal="", constraints="", desc=""):
self._llm = LLM()
self._setting = RoleSetting(name=name, profile=profile, goal=goal, constraints=constraints, desc=desc)
def __init__(self, name="", profile="", goal="", constraints="", desc="", is_human=False):
self._llm = LLM() if not is_human else HumanProvider()
self._setting = RoleSetting(
name=name, profile=profile, goal=goal, constraints=constraints, desc=desc, is_human=is_human
)
self._states = []
self._actions = []
self._role_id = str(self._setting)
@ -126,13 +148,40 @@ class Role:
self._reset()
for idx, action in enumerate(actions):
if not isinstance(action, Action):
i = action("")
i = action("", llm=self._llm)
else:
if self._setting.is_human and not isinstance(action.llm, HumanProvider):
logger.warning(
f"is_human attribute does not take effect,"
f"as Role's {str(action)} was initialized using LLM, try passing in Action classes instead of initialized instances"
)
i = action
i.set_env(self._rc.env)
i.set_prefix(self._get_prefix(), self.profile)
self._actions.append(i)
self._states.append(f"{idx}. {action}")
def _set_react_mode(self, react_mode: str, max_react_loop: int = 1):
"""Set strategy of the Role reacting to observed Message. Variation lies in how
this Role elects action to perform during the _think stage, especially if it is capable of multiple Actions.
Args:
react_mode (str): Mode for choosing action during the _think stage, can be one of:
"react": standard think-act loop in the ReAct paper, alternating thinking and acting to solve the task, i.e. _think -> _act -> _think -> _act -> ...
Use llm to select actions in _think dynamically;
"by_order": switch action each time by order defined in _init_actions, i.e. _act (Action1) -> _act (Action2) -> ...;
"plan_and_act": first plan, then execute an action sequence, i.e. _think (of a plan) -> _act -> _act -> ...
Use llm to come up with the plan dynamically.
Defaults to "react".
max_react_loop (int): Maximum react cycles to execute, used to prevent the agent from reacting forever.
Take effect only when react_mode is react, in which we use llm to choose actions, including termination.
Defaults to 1, i.e. _think -> _act (-> return result and end)
"""
assert react_mode in RoleReactMode.values(), f"react_mode must be one of {RoleReactMode.values()}"
self._rc.react_mode = react_mode
if react_mode == RoleReactMode.REACT:
self._rc.max_react_loop = max_react_loop
def _watch(self, actions: Iterable[Type[Action]]):
"""Watch Actions of interest. Role will select Messages caused by these Actions from its personal message
buffer during _observe.
@ -151,11 +200,11 @@ class Role:
if self._rc.env: # According to the routing feature plan in Chapter 2.2.3.2 of RFC 113
self._rc.env.set_subscription(self, self._subscription)
def _set_state(self, state):
def _set_state(self, state: int):
"""Update the current state."""
self._rc.state = state
logger.debug(self._actions)
self._rc.todo = self._actions[self._rc.state]
self._rc.todo = self._actions[self._rc.state] if state >= 0 else None
def set_env(self, env: "Environment"):
"""Set the environment in which the role works. The role can talk to the environment and can also receive
@ -164,6 +213,22 @@ class Role:
if env:
env.set_subscription(self, self._subscription)
# # Replaced by FileRepository.set_file
# def set_doc(self, content: str, filename: str):
# return self._rc.env.set_doc(content, filename)
#
# # Replaced by FileRepository.get_file
# def get_doc(self, filename: str):
# return self._rc.env.get_doc(filename)
#
# # Replaced by CONFIG.xx
# def set(self, k, v):
# return self._rc.env.set(k, v)
#
# # Replaced by CONFIG.xx
# def get(self, k):
# return self._rc.env.get(k)
@property
def profile(self):
"""Get the role description (position)"""
@ -193,14 +258,22 @@ class Role:
return
prompt = self._get_prefix()
prompt += STATE_TEMPLATE.format(
history=self._rc.history, states="\n".join(self._states), n_states=len(self._states) - 1
history=self._rc.history,
states="\n".join(self._states),
n_states=len(self._states) - 1,
previous_state=self._rc.state,
)
# print(prompt)
next_state = await self._llm.aask(prompt)
logger.debug(f"{prompt=}")
if not next_state.isdigit() or int(next_state) not in range(len(self._states)):
logger.warning(f"Invalid answer of state, {next_state=}")
next_state = "0"
self._set_state(int(next_state))
if (not next_state.isdigit() and next_state != "-1") or int(next_state) not in range(-1, len(self._states)):
logger.warning(f"Invalid answer of state, {next_state=}, will be set to -1")
next_state = -1
else:
next_state = int(next_state)
if next_state == -1:
logger.info(f"End actions with {next_state=}")
self._set_state(next_state)
async def _act(self) -> Message:
logger.info(f"{self._setting}: ready to {self._rc.todo}")
@ -250,10 +323,66 @@ class Role:
self._rc.msg_buffer.push(message)
async def _react(self) -> Message:
"""Think first, then act"""
await self._think()
logger.debug(f"{self._setting}: {self._rc.state=}, will do {self._rc.todo}")
return await self._act()
"""Think first, then act, until the Role _think it is time to stop and requires no more todo.
This is the standard think-act loop in the ReAct paper, which alternates thinking and acting in task solving, i.e. _think -> _act -> _think -> _act -> ...
Use llm to select actions in _think dynamically
"""
actions_taken = 0
rsp = Message("No actions taken yet") # will be overwritten after Role _act
while actions_taken < self._rc.max_react_loop:
# think
await self._think()
if self._rc.todo is None:
break
# act
logger.debug(f"{self._setting}: {self._rc.state=}, will do {self._rc.todo}")
rsp = await self._act() # 这个rsp是否需要publish_message？
actions_taken += 1
return rsp # return output from the last action
async def _act_by_order(self) -> Message:
"""switch action each time by order defined in _init_actions, i.e. _act (Action1) -> _act (Action2) -> ..."""
for i in range(len(self._states)):
self._set_state(i)
rsp = await self._act()
return rsp # return output from the last action
async def _plan_and_act(self) -> Message:
"""first plan, then execute an action sequence, i.e. _think (of a plan) -> _act -> _act -> ... Use llm to come up with the plan dynamically."""
# TODO: to be implemented
return Message("")
async def react(self) -> Message:
"""Entry to one of three strategies by which Role reacts to the observed Message"""
if self._rc.react_mode == RoleReactMode.REACT:
rsp = await self._react()
elif self._rc.react_mode == RoleReactMode.BY_ORDER:
rsp = await self._act_by_order()
elif self._rc.react_mode == RoleReactMode.PLAN_AND_ACT:
rsp = await self._plan_and_act()
self._set_state(state=-1) # current reaction is complete, reset state to -1 and todo back to None
return rsp
# # Replaced by run()
# def recv(self, message: Message) -> None:
# """add message to history."""
# # self._history += f"\n{message}"
# # self._context = self._history
# if message in self._rc.memory.get():
# return
# self._rc.memory.add(message)
# # Replaced by run()
# async def handle(self, message: Message) -> Message:
# """Receive information and reply with actions"""
# # logger.debug(f"{self.name=}, {self.profile=}, {message.role=}")
# self.recv(message)
#
# return await self._react()
def get_memories(self, k=0) -> list[Message]:
"""A wrapper to return the most recent k memories of this role, return all when k=0"""
return self._rc.memory.get(k=k)
async def run(self, with_message=None):
"""Observe, and think and act based on the results of the observation"""

4
metagpt/roles/sk_agent.py
View file

@ -11,7 +11,7 @@ from semantic_kernel.planning import SequentialPlanner
from semantic_kernel.planning.action_planner.action_planner import ActionPlanner
from semantic_kernel.planning.basic_planner import BasicPlanner
from metagpt.actions import BossRequirement
from metagpt.actions import UserRequirement
from metagpt.actions.execute_task import ExecuteTask
from metagpt.logs import logger
from metagpt.roles import Role
@ -41,7 +41,7 @@ class SkAgent(Role):
"""Initializes the Engineer role with given attributes."""
super().__init__(name, profile, goal, constraints)
self._init_actions([ExecuteTask()])
self._watch([BossRequirement])
self._watch([UserRequirement])
self.kernel = make_sk_kernel()
# how funny the interface is inconsistent

21
metagpt/schema.py
View file

@ -18,6 +18,7 @@ import json
import os.path
from asyncio import Queue, QueueEmpty, wait_for
from json import JSONDecodeError
from pathlib import Path
from typing import Dict, List, Optional, Set, TypedDict
from pydantic import BaseModel, Field
@ -28,6 +29,8 @@ from metagpt.const import (
MESSAGE_ROUTE_FROM,
MESSAGE_ROUTE_TO,
MESSAGE_ROUTE_TO_ALL,
SYSTEM_DESIGN_FILE_REPO,
TASK_FILE_REPO,
)
from metagpt.logs import logger
from metagpt.utils.common import any_to_str, any_to_str_set
@ -312,3 +315,21 @@ class RunCodeResult(BaseModel):
return RunCodeResult(**m)
except Exception:
return None
class CodeSummarizeContext(BaseModel):
design_filename: str = ""
task_filename: str = ""
codes_filenames: Set[str] = Field(default_factory=set)
@staticmethod
def loads(filenames: Set) -> CodeSummarizeContext:
ctx = CodeSummarizeContext()
for filename in filenames:
if Path(filename).is_relative_to(SYSTEM_DESIGN_FILE_REPO):
ctx.design_filename = str(filename)
continue
if Path(filename).is_relative_to(TASK_FILE_REPO):
ctx.task_filename = str(filename)
continue
return ctx

52
metagpt/startup.py Normal file
View file

@ -0,0 +1,52 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import asyncio
import typer
app = typer.Typer()
@app.command()
def startup(
idea: str = typer.Argument(..., help="Your innovative idea, such as 'Create a 2048 game.'"),
investment: float = typer.Option(3.0, help="Dollar amount to invest in the AI company."),
n_round: int = typer.Option(5, help="Number of rounds for the simulation."),
code_review: bool = typer.Option(True, help="Whether to use code review."),
run_tests: bool = typer.Option(False, help="Whether to enable QA for adding & running tests."),
implement: bool = typer.Option(True, help="Enable or disable code implementation."),
project_name: str = typer.Option("", help="Unique project name, such as 'game_2048'."),
inc: bool = typer.Option(False, help="Incremental mode. Use it to coop with existing repo."),
):
"""Run a startup. Be a boss."""
from metagpt.roles import (
Architect,
Engineer,
ProductManager,
ProjectManager,
QaEngineer,
)
from metagpt.team import Team
company = Team()
company.hire(
[
ProductManager(),
Architect(),
ProjectManager(),
]
)
if implement or code_review:
company.hire([Engineer(n_borg=5, use_code_review=code_review)])
if run_tests:
company.hire([QaEngineer()])
company.invest(investment)
company.run_project(idea, project_name=project_name, inc=inc)
asyncio.run(company.run(n_round=n_round))
if __name__ == "__main__":
startup(idea="Make a 2048 game.")

30
metagpt/software_company.py → metagpt/team.py
View file

@ -9,7 +9,7 @@
"""
from pydantic import BaseModel, Field
from metagpt.actions import BossRequirement
from metagpt.actions import UserRequirement
from metagpt.config import CONFIG
from metagpt.environment import Environment
from metagpt.logs import logger
@ -18,13 +18,13 @@ from metagpt.schema import Message
from metagpt.utils.common import NoMoneyException
class SoftwareCompany(BaseModel):
class Team(BaseModel):
"""
Software Company: Possesses a team, SOP (Standard Operating Procedures), and a platform for instant messaging,
dedicated to writing executable code.
Team: Possesses one or more roles (agents), SOP (Standard Operating Procedures), and a platform for instant messaging,
dedicated to perform any multi-agent activity, such as collaboratively writing executable code.
"""
environment: Environment = Field(default_factory=Environment)
env: Environment = Field(default_factory=Environment)
investment: float = Field(default=10.0)
idea: str = Field(default="")
@ -33,7 +33,7 @@ class SoftwareCompany(BaseModel):
def hire(self, roles: list[Role]):
"""Hire roles to cooperate"""
self.environment.add_roles(roles)
self.env.add_roles(roles)
def invest(self, investment: float):
"""Invest company. raise NoMoneyException when exceed max_budget."""
@ -45,13 +45,19 @@ class SoftwareCompany(BaseModel):
if CONFIG.total_cost > CONFIG.max_budget:
raise NoMoneyException(CONFIG.total_cost, f"Insufficient funds: {CONFIG.max_budget}")
def start_project(self, idea):
"""Start a project from publishing boss requirement."""
def run_project(self, idea, send_to: str = "", project_name: str = "", inc: bool = False):
"""Start a project from publishing user requirement."""
self.idea = idea
self.environment.publish_message(Message(role="BOSS", content=idea, cause_by=BossRequirement))
# If user set project_name, then use it.
if project_name:
path = CONFIG.workspace_path / project_name
self.env.load_existing_repo(path, inc=inc)
# Human requirement.
self.env.publish_message(Message(role="Human", content=idea, cause_by=UserRequirement, send_to=send_to))
def _save(self):
logger.info(self.json())
logger.info(self.json(ensure_ascii=False))
async def run(self, n_round=3):
"""Run company until target round or no money"""
@ -60,7 +66,7 @@ class SoftwareCompany(BaseModel):
n_round -= 1
logger.debug(f"{n_round=}")
self._check_balance()
await self.environment.run()
await self.env.run()
if CONFIG.git_repo:
CONFIG.git_repo.archive()
return self.environment.history
return self.env.history

14
metagpt/tools/sd_engine.py
View file

@ -13,11 +13,10 @@ from typing import List
from aiohttp import ClientSession
from PIL import Image, PngImagePlugin
from metagpt.config import Config
from metagpt.const import WORKSPACE_ROOT
from metagpt.logs import logger
from metagpt.config import CONFIG
config = Config()
# from metagpt.const import WORKSPACE_ROOT
from metagpt.logs import logger
payload = {
"prompt": "",
@ -56,9 +55,8 @@ default_negative_prompt = "(easynegative:0.8),black, dark,Low resolution"
class SDEngine:
def __init__(self):
# Initialize the SDEngine with configuration
self.config = Config()
self.sd_url = self.config.get("SD_URL")
self.sd_t2i_url = f"{self.sd_url}{self.config.get('SD_T2I_API')}"
self.sd_url = CONFIG.get("SD_URL")
self.sd_t2i_url = f"{self.sd_url}{CONFIG.get('SD_T2I_API')}"
# Define default payload settings for SD API
self.payload = payload
logger.info(self.sd_t2i_url)
@ -81,7 +79,7 @@ class SDEngine:
return self.payload
def _save(self, imgs, save_name=""):
save_dir = WORKSPACE_ROOT / "resources" / "SD_Output"
save_dir = CONFIG.workspace_path / "resources" / "SD_Output"
if not os.path.exists(save_dir):
os.makedirs(save_dir, exist_ok=True)
batch_decode_base64_to_image(imgs, save_dir, save_name=save_name)

2
metagpt/utils/common.py
View file

@ -9,6 +9,8 @@
@Modified By: mashenquan, 2023/11/27. Bug fix: `parse_recipient` failed to parse the recipient in certain GPT-3.5
responses.
"""
from __future__ import annotations
import ast
import contextlib
import inspect

10
metagpt/utils/file_repository.py
View file

@ -54,7 +54,7 @@ class FileRepository:
"""
pathname = self.workdir / filename
pathname.parent.mkdir(parents=True, exist_ok=True)
async with aiofiles.open(str(pathname), mode="w") as writer:
async with aiofiles.open(str(pathname), mode="wb") as writer:
await writer.write(content)
logger.info(f"save to: {str(pathname)}")
@ -98,7 +98,7 @@ class FileRepository:
if not path_name.exists():
return None
try:
async with aiofiles.open(str(path_name), mode="r") as reader:
async with aiofiles.open(str(path_name), mode="rb") as reader:
doc.content = await reader.read()
except FileNotFoundError as e:
logger.info(f"open {str(path_name)} failed:{e}")
@ -178,7 +178,7 @@ class FileRepository:
# guid_suffix = str(uuid.uuid4())[:8]
# return f"{current_time}x{guid_suffix}"
async def save_doc(self, doc: Document, with_suffix:str = None, dependencies: List[str] = None):
async def save_doc(self, doc: Document, with_suffix: str = None, dependencies: List[str] = None):
"""Save a Document instance as a PDF file.
This method converts the content of the Document instance to Markdown,
@ -238,7 +238,9 @@ class FileRepository:
return await file_repo.save(filename=filename, content=content, dependencies=dependencies)
@staticmethod
async def save_as(doc:Document, with_suffix:str = None, dependencies: List[str] = None, relative_path: Path | str = "."):
async def save_as(
doc: Document, with_suffix: str = None, dependencies: List[str] = None, relative_path: Path | str = "."
):
"""Save a Document instance with optional modifications.
This static method creates a new FileRepository, saves the Document instance

13
metagpt/utils/mermaid.py
View file

@ -10,7 +10,7 @@ import os
from pathlib import Path
from metagpt.config import CONFIG
from metagpt.const import PROJECT_ROOT
from metagpt.const import METAGPT_ROOT
from metagpt.logs import logger
from metagpt.utils.common import check_cmd_exists
@ -34,7 +34,10 @@ async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048,
engine = CONFIG.mermaid_engine.lower()
if engine == "nodejs":
if check_cmd_exists(CONFIG.mmdc) != 0:
logger.warning("RUN `npm install -g @mermaid-js/mermaid-cli` to install mmdc")
logger.warning(
"RUN `npm install -g @mermaid-js/mermaid-cli` to install mmdc,"
"or consider changing MERMAID_ENGINE to `playwright`, `pyppeteer`, or `ink`."
)
return -1
for suffix in ["pdf", "svg", "png"]:
@ -66,7 +69,7 @@ async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048,
if stdout:
logger.info(stdout.decode())
if stderr:
logger.error(stderr.decode())
logger.warning(stderr.decode())
else:
if engine == "playwright":
from metagpt.utils.mmdc_playwright import mermaid_to_file
@ -138,6 +141,6 @@ MMC2 = """sequenceDiagram
if __name__ == "__main__":
loop = asyncio.new_event_loop()
result = loop.run_until_complete(mermaid_to_file(MMC1, PROJECT_ROOT / f"{CONFIG.mermaid_engine}/1"))
result = loop.run_until_complete(mermaid_to_file(MMC2, PROJECT_ROOT / f"{CONFIG.mermaid_engine}/1"))
result = loop.run_until_complete(mermaid_to_file(MMC1, METAGPT_ROOT / f"{CONFIG.mermaid_engine}/1"))
result = loop.run_until_complete(mermaid_to_file(MMC2, METAGPT_ROOT / f"{CONFIG.mermaid_engine}/1"))
loop.close()

13
metagpt/utils/token_counter.py
View file

@ -21,7 +21,9 @@ TOKEN_COSTS = {
"gpt-4-32k": {"prompt": 0.06, "completion": 0.12},
"gpt-4-32k-0314": {"prompt": 0.06, "completion": 0.12},
"gpt-4-0613": {"prompt": 0.06, "completion": 0.12},
"gpt-4-1106-preview": {"prompt": 0.01, "completion": 0.03},
"text-embedding-ada-002": {"prompt": 0.0004, "completion": 0.0},
"chatglm_turbo": {"prompt": 0.0, "completion": 0.00069}, # 32k version, prompt + completion tokens=0.005￥/k-tokens
}
@ -36,7 +38,9 @@ TOKEN_MAX = {
"gpt-4-32k": 32768,
"gpt-4-32k-0314": 32768,
"gpt-4-0613": 8192,
"gpt-4-1106-preview": 128000,
"text-embedding-ada-002": 8192,
"chatglm_turbo": 32768,
}
@ -54,21 +58,24 @@ def count_message_tokens(messages, model="gpt-3.5-turbo-0613"):
"gpt-4-32k-0314",
"gpt-4-0613",
"gpt-4-32k-0613",
"gpt-4-1106-preview",
}:
tokens_per_message = 3
tokens_per_name = 1
elif model == "gpt-3.5-turbo-0301":
tokens_per_message = 4 # every message follows <|start|>{role/name}\n{content}<|end|>\n
tokens_per_name = -1 # if there's a name, the role is omitted
elif "gpt-3.5-turbo" in model:
elif "gpt-3.5-turbo" == model:
print("Warning: gpt-3.5-turbo may update over time. Returning num tokens assuming gpt-3.5-turbo-0613.")
return count_message_tokens(messages, model="gpt-3.5-turbo-0613")
elif "gpt-4" in model:
elif "gpt-4" == model:
print("Warning: gpt-4 may update over time. Returning num tokens assuming gpt-4-0613.")
return count_message_tokens(messages, model="gpt-4-0613")
else:
raise NotImplementedError(
f"""num_tokens_from_messages() is not implemented for model {model}. See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens."""
f"num_tokens_from_messages() is not implemented for model {model}. "
f"See https://github.com/openai/openai-python/blob/main/chatml.md "
f"for information on how messages are converted to tokens."
)
num_tokens = 0
for message in messages:

9
requirements.txt
View file

@ -6,7 +6,8 @@ channels==4.0.0
# docx==0.2.4
#faiss==1.5.3
faiss_cpu==1.7.4
fire==0.4.0
# fire==0.4.0
typer
# godot==0.1.1
# google_api_python_client==2.93.0
lancedb==0.1.16
@ -14,7 +15,7 @@ langchain==0.0.231
loguru==0.6.0
meilisearch==0.21.0
numpy==1.24.3
openai==0.28.1
openai>=0.28.1
openpyxl
beautifulsoup4==4.12.2
pandas==2.0.3
@ -45,4 +46,6 @@ semantic-kernel==0.3.13.dev0
wrapt==1.15.0
websocket-client==0.58.0
aiofiles==23.2.1
gitpython==3.1.40
gitpython==3.1.40
zhipuai==1.0.7

17
setup.py
View file

@ -30,16 +30,16 @@ with open(path.join(here, "requirements.txt"), encoding="utf-8") as f:
setup(
name="metagpt",
version="0.1",
description="The Multi-Role Meta Programming Framework",
version="0.3.0",
description="The Multi-Agent Framework",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://gitlab.deepwisdomai.com/pub/metagpt",
url="https://github.com/geekan/MetaGPT",
author="Alexander Wu",
author_email="alexanderwu@fuzhi.ai",
license="Apache 2.0",
keywords="metagpt multi-role multi-agent programming gpt llm",
packages=find_packages(exclude=["contrib", "docs", "examples"]),
license="MIT",
keywords="metagpt multi-role multi-agent programming gpt llm metaprogramming",
packages=find_packages(exclude=["contrib", "docs", "examples", "tests*"]),
python_requires=">=3.9",
install_requires=requirements,
extras_require={
@ -52,4 +52,9 @@ setup(
cmdclass={
"install_mermaid": InstallMermaidCLI,
},
entry_points={
"console_scripts": [
"metagpt=metagpt.startup:app",
],
},
)

6
tests/metagpt/actions/mock.py
View file

@ -90,7 +90,7 @@ Python's in-built data structures like lists and dictionaries will be used exten
For testing, we can use the PyTest framework. This is a mature full-featured Python testing tool that helps you write better programs.
## Python package name:
## project_name:
```python
"adventure_game"
```
@ -100,7 +100,7 @@ For testing, we can use the PyTest framework. This is a mature full-featured Pyt
file_list = ["main.py", "room.py", "player.py", "game.py", "object.py", "puzzle.py", "test_game.py"]
```
## Data structures and interface definitions:
## Data structures and interfaces:
```mermaid
classDiagram
class Room{
@ -209,7 +209,7 @@ Shared knowledge for this project includes understanding the basic principles of
"""
```
## Anything UNCLEAR: Provide as Plain text. Make clear here. For example, don't forget a main entry. don't forget to init 3rd party libs.
## Anything UNCLEAR: Provide as Plain text. Try to clarify it. For example, don't forget a main entry. don't forget to init 3rd party libs.
```python
"""
The original requirements did not specify whether the game should have a save/load feature, multiplayer support, or any specific graphical user interface. More information on these aspects could help in further refining the product design and requirements.

4
tests/metagpt/actions/test_write_prd.py
View file

@ -8,7 +8,7 @@
"""
import pytest
from metagpt.actions import BossRequirement
from metagpt.actions import UserRequirement
from metagpt.logs import logger
from metagpt.roles.product_manager import ProductManager
from metagpt.schema import Message
@ -18,7 +18,7 @@ from metagpt.schema import Message
async def test_write_prd():
product_manager = ProductManager()
requirements = "开发一个基于大语言模型与私有知识库的搜索引擎，希望可以基于大语言模型进行搜索总结"
prd = await product_manager.run(Message(content=requirements, cause_by=BossRequirement))
prd = await product_manager.run(Message(content=requirements, cause_by=UserRequirement))
logger.info(requirements)
logger.info(prd)

16
tests/metagpt/document_store/test_document.py
View file

@ -7,22 +7,22 @@
"""
import pytest
from metagpt.const import DATA_PATH
from metagpt.document_store.document import Document
from metagpt.const import METAGPT_ROOT
from metagpt.document import IndexableDocument
CASES = [
("st/faq.xlsx", "Question", "Answer", 1),
("cases/faq.csv", "Question", "Answer", 1),
("requirements.txt", None, None, 0),
# ("cases/faq.csv", "Question", "Answer", 1),
# ("cases/faq.json", "Question", "Answer", 1),
("docx/faq.docx", None, None, 1),
("cases/faq.pdf", None, None, 0), # 这是因为pdf默认没有分割段落
("cases/faq.txt", None, None, 0), # 这是因为txt按照256分割段落
# ("docx/faq.docx", None, None, 1),
# ("cases/faq.pdf", None, None, 0), # 这是因为pdf默认没有分割段落
# ("cases/faq.txt", None, None, 0), # 这是因为txt按照256分割段落
]
@pytest.mark.parametrize("relative_path, content_col, meta_col, threshold", CASES)
def test_document(relative_path, content_col, meta_col, threshold):
doc = Document(DATA_PATH / relative_path, content_col, meta_col)
doc = IndexableDocument.from_path(METAGPT_ROOT / relative_path, content_col, meta_col)
rsp = doc.get_docs_and_metadatas()
assert len(rsp[0]) > threshold
assert len(rsp[1]) > threshold

12
tests/metagpt/memory/test_longterm_memory.py
View file

@ -4,7 +4,7 @@
@Desc : unittest of `metagpt/memory/longterm_memory.py`
"""
from metagpt.actions import BossRequirement
from metagpt.actions import UserRequirement
from metagpt.config import CONFIG
from metagpt.memory import LongTermMemory
from metagpt.roles.role import RoleContext
@ -17,24 +17,24 @@ def test_ltm_search():
assert len(openai_api_key) > 20
role_id = "UTUserLtm(Product Manager)"
rc = RoleContext(watch=[BossRequirement])
rc = RoleContext(watch=[UserRequirement])
ltm = LongTermMemory()
ltm.recover_memory(role_id, rc)
idea = "Write a cli snake game"
message = Message(role="BOSS", content=idea, cause_by=BossRequirement)
message = Message(role="User", content=idea, cause_by=UserRequirement)
news = ltm.find_news([message])
assert len(news) == 1
ltm.add(message)
sim_idea = "Write a game of cli snake"
sim_message = Message(role="BOSS", content=sim_idea, cause_by=BossRequirement)
sim_message = Message(role="User", content=sim_idea, cause_by=UserRequirement)
news = ltm.find_news([sim_message])
assert len(news) == 0
ltm.add(sim_message)
new_idea = "Write a 2048 web game"
new_message = Message(role="BOSS", content=new_idea, cause_by=BossRequirement)
new_message = Message(role="User", content=new_idea, cause_by=UserRequirement)
news = ltm.find_news([new_message])
assert len(news) == 1
ltm.add(new_message)
@ -50,7 +50,7 @@ def test_ltm_search():
assert len(news) == 0
new_idea = "Write a Battle City"
new_message = Message(role="BOSS", content=new_idea, cause_by=BossRequirement)
new_message = Message(role="User", content=new_idea, cause_by=UserRequirement)
news = ltm_new.find_news([new_message])
assert len(news) == 1

10
tests/metagpt/memory/test_memory_storage.py
View file

@ -7,7 +7,7 @@
from typing import List
from metagpt.actions import BossRequirement, WritePRD
from metagpt.actions import UserRequirement, WritePRD
from metagpt.actions.action_output import ActionOutput
from metagpt.memory.memory_storage import MemoryStorage
from metagpt.schema import Message
@ -16,7 +16,7 @@ from metagpt.schema import Message
def test_idea_message():
idea = "Write a cli snake game"
role_id = "UTUser1(Product Manager)"
message = Message(role="BOSS", content=idea, cause_by=BossRequirement)
message = Message(role="User", content=idea, cause_by=UserRequirement)
memory_storage: MemoryStorage = MemoryStorage()
messages = memory_storage.recover_memory(role_id)
@ -26,12 +26,12 @@ def test_idea_message():
assert memory_storage.is_initialized is True
sim_idea = "Write a game of cli snake"
sim_message = Message(role="BOSS", content=sim_idea, cause_by=BossRequirement)
sim_message = Message(role="User", content=sim_idea, cause_by=UserRequirement)
new_messages = memory_storage.search(sim_message)
assert len(new_messages) == 0 # similar, return []
new_idea = "Write a 2048 web game"
new_message = Message(role="BOSS", content=new_idea, cause_by=BossRequirement)
new_message = Message(role="User", content=new_idea, cause_by=UserRequirement)
new_messages = memory_storage.search(new_message)
assert new_messages[0].content == message.content
@ -45,7 +45,7 @@ def test_actionout_message():
ic_obj = ActionOutput.create_model_class("prd", out_mapping)
role_id = "UTUser2(Architect)"
content = "The boss has requested the creation of a command-line interface (CLI) snake game"
content = "The user has requested the creation of a command-line interface (CLI) snake game"
message = Message(
content=content, instruct_content=ic_obj(**out_data), role="user", cause_by=WritePRD
) # WritePRD as test action

5
tests/metagpt/planner/test_action_planner.py
View file

@ -11,7 +11,7 @@ import pytest
from semantic_kernel.core_skills import FileIOSkill, MathSkill, TextSkill, TimeSkill
from semantic_kernel.planning.action_planner.action_planner import ActionPlanner
from metagpt.actions import BossRequirement
from metagpt.actions import UserRequirement
from metagpt.roles.sk_agent import SkAgent
from metagpt.schema import Message
@ -25,7 +25,8 @@ async def test_action_planner():
role.import_skill(TimeSkill(), "time")
role.import_skill(TextSkill(), "text")
task = "What is the sum of 110 and 990?"
role.put_message(Message(content=task, cause_by=BossRequirement))
role.put_message(Message(content=task, cause_by=UserRequirement))
await role._observe()
await role._think() # it will choose mathskill.Add
assert "1100" == (await role._act()).content

4
tests/metagpt/planner/test_basic_planner.py
View file

@ -10,7 +10,7 @@
import pytest
from semantic_kernel.core_skills import TextSkill
from metagpt.actions import BossRequirement
from metagpt.actions import UserRequirement
from metagpt.const import SKILL_DIRECTORY
from metagpt.roles.sk_agent import SkAgent
from metagpt.schema import Message
@ -28,7 +28,7 @@ async def test_basic_planner():
role.import_semantic_skill_from_directory(SKILL_DIRECTORY, "WriterSkill")
role.import_skill(TextSkill(), "TextSkill")
# using BasicPlanner
role.put_message(Message(content=task, cause_by=BossRequirement))
role.put_message(Message(content=task, cause_by=UserRequirement))
await role._observe()
await role._think()
# assuming sk_agent will think he needs WriterSkill.Brainstorm and WriterSkill.Translate

80
tests/metagpt/provider/test_openai.py Normal file
View file

@ -0,0 +1,80 @@
import pytest
from metagpt.provider.openai_api import OpenAIGPTAPI
from metagpt.schema import UserMessage
@pytest.mark.asyncio
async def test_aask_code():
llm = OpenAIGPTAPI()
msg = [{"role": "user", "content": "Write a python hello world code."}]
rsp = await llm.aask_code(msg) # -> {'language': 'python', 'code': "print('Hello, World!')"}
assert "language" in rsp
assert "code" in rsp
assert len(rsp["code"]) > 0
@pytest.mark.asyncio
async def test_aask_code_str():
llm = OpenAIGPTAPI()
msg = "Write a python hello world code."
rsp = await llm.aask_code(msg) # -> {'language': 'python', 'code': "print('Hello, World!')"}
assert "language" in rsp
assert "code" in rsp
assert len(rsp["code"]) > 0
@pytest.mark.asyncio
async def test_aask_code_Message():
llm = OpenAIGPTAPI()
msg = UserMessage("Write a python hello world code.")
rsp = await llm.aask_code(msg) # -> {'language': 'python', 'code': "print('Hello, World!')"}
assert "language" in rsp
assert "code" in rsp
assert len(rsp["code"]) > 0
def test_ask_code():
llm = OpenAIGPTAPI()
msg = [{"role": "user", "content": "Write a python hello world code."}]
rsp = llm.ask_code(msg) # -> {'language': 'python', 'code': "print('Hello, World!')"}
assert "language" in rsp
assert "code" in rsp
assert len(rsp["code"]) > 0
def test_ask_code_str():
llm = OpenAIGPTAPI()
msg = "Write a python hello world code."
rsp = llm.ask_code(msg) # -> {'language': 'python', 'code': "print('Hello, World!')"}
assert "language" in rsp
assert "code" in rsp
assert len(rsp["code"]) > 0
def test_ask_code_Message():
llm = OpenAIGPTAPI()
msg = UserMessage("Write a python hello world code.")
rsp = llm.ask_code(msg) # -> {'language': 'python', 'code': "print('Hello, World!')"}
assert "language" in rsp
assert "code" in rsp
assert len(rsp["code"]) > 0
def test_ask_code_list_Message():
llm = OpenAIGPTAPI()
msg = [UserMessage("a=[1,2,5,10,-10]"), UserMessage("写出求a中最大值的代码python")]
rsp = llm.ask_code(msg) # -> {'language': 'python', 'code': 'max_value = max(a)\nmax_value'}
assert "language" in rsp
assert "code" in rsp
assert len(rsp["code"]) > 0
def test_ask_code_list_str():
llm = OpenAIGPTAPI()
msg = ["a=[1,2,5,10,-10]", "写出求a中最大值的代码python"]
rsp = llm.ask_code(msg) # -> {'language': 'python', 'code': 'max_value = max(a)\nmax_value'}
print(rsp)
assert "language" in rsp
assert "code" in rsp
assert len(rsp["code"]) > 0

37
tests/metagpt/provider/test_zhipuai_api.py Normal file
View file

@ -0,0 +1,37 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Desc : the unittest of ZhiPuAIGPTAPI
import pytest
from metagpt.provider.zhipuai_api import ZhiPuAIGPTAPI
default_resp = {"code": 200, "data": {"choices": [{"role": "assistant", "content": "I'm chatglm-turbo"}]}}
messages = [{"role": "user", "content": "who are you"}]
def mock_llm_ask(self, messages: list[dict]) -> dict:
return default_resp
def test_zhipuai_completion(mocker):
mocker.patch("metagpt.provider.zhipuai_api.ZhiPuAIGPTAPI.completion", mock_llm_ask)
resp = ZhiPuAIGPTAPI().completion(messages)
assert resp["code"] == 200
assert "chatglm-turbo" in resp["data"]["choices"][0]["content"]
async def mock_llm_aask(self, messgaes: list[dict], stream: bool = False) -> dict:
return default_resp
@pytest.mark.asyncio
async def test_zhipuai_acompletion(mocker):
mocker.patch("metagpt.provider.zhipuai_api.ZhiPuAIGPTAPI.acompletion_text", mock_llm_aask)
resp = await ZhiPuAIGPTAPI().acompletion_text(messages, stream=False)
assert resp["code"] == 200
assert "chatglm-turbo" in resp["data"]["choices"][0]["content"]

10
tests/metagpt/roles/mock.py
View file

@ -5,10 +5,10 @@
@Author : alexanderwu
@File : mock.py
"""
from metagpt.actions import BossRequirement, WriteDesign, WritePRD, WriteTasks
from metagpt.actions import UserRequirement, WriteDesign, WritePRD, WriteTasks
from metagpt.schema import Message
BOSS_REQUIREMENT = """开发一个基于大语言模型与私有知识库的搜索引擎，希望可以基于大语言模型进行搜索总结"""
USER_REQUIREMENT = """开发一个基于大语言模型与私有知识库的搜索引擎，希望可以基于大语言模型进行搜索总结"""
DETAIL_REQUIREMENT = """需求：开发一个基于LLM（大语言模型）与私有知识库的搜索引擎，希望有几点能力
1. 用户可以在私有知识库进行搜索，再根据大语言模型进行总结，输出的结果包括了总结
@ -71,7 +71,7 @@ PRD = '''## 原始需求
```
'''
SYSTEM_DESIGN = """## Python package name
SYSTEM_DESIGN = """## project_name
```python
"smart_search_engine"
```
@ -94,7 +94,7 @@ SYSTEM_DESIGN = """## Python package name
]
```
## Data structures and interface definitions
## Data structures and interfaces
```mermaid
classDiagram
class Main {
@ -252,7 +252,7 @@ a = 'a'
class MockMessages:
req = Message(role="Boss", content=BOSS_REQUIREMENT, cause_by=BossRequirement)
req = Message(role="User", content=USER_REQUIREMENT, cause_by=UserRequirement)
prd = Message(role="Product Manager", content=PRD, cause_by=WritePRD)
system_design = Message(role="Architect", content=SYSTEM_DESIGN, cause_by=WriteDesign)
tasks = Message(role="Project Manager", content=TASKS, cause_by=WriteTasks)

6
tests/metagpt/roles/test_ui.py
View file

@ -3,7 +3,7 @@
# @Author : stellahong (stellahong@fuzhi.ai)
#
from metagpt.roles import ProductManager
from metagpt.software_company import SoftwareCompany
from metagpt.team import Team
from tests.metagpt.roles.ui_role import UI
@ -14,8 +14,8 @@ def test_add_ui():
async def test_ui_role(idea: str, investment: float = 3.0, n_round: int = 5):
"""Run a startup. Be a boss."""
company = SoftwareCompany()
company = Team()
company.hire([ProductManager(), UI()])
company.invest(investment)
company.start_project(idea)
company.run_project(idea)
await company.run(n_round=n_round)

8
tests/metagpt/roles/ui_role.py
View file

@ -8,7 +8,9 @@ from functools import wraps
from importlib import import_module
from metagpt.actions import Action, ActionOutput, WritePRD
from metagpt.const import WORKSPACE_ROOT
# from metagpt.const import WORKSPACE_ROOT
from metagpt.config import CONFIG
from metagpt.logs import logger
from metagpt.roles import Role
from metagpt.schema import Message
@ -29,7 +31,7 @@ Attention: Use '##' to split sections, not '#', and '## <SECTION_NAME>' SHOULD W
## Selected Elements:Provide as Plain text, up to 5 specified elements, clear and simple
## HTML Layout:Provide as Plain text, use standard HTML code
## CSS Styles (styles.css):Provide as Plain text,use standard css code
## Anything UNCLEAR:Provide as Plain text. Make clear here.
## Anything UNCLEAR:Provide as Plain text. Try to clarify it.
"""
@ -214,7 +216,7 @@ class UIDesign(Action):
logger.info("Finish icon design using StableDiffusion API")
async def _save(self, css_content, html_content):
save_dir = WORKSPACE_ROOT / "resources" / "codes"
save_dir = CONFIG.workspace_path / "resources" / "codes"
if not os.path.exists(save_dir):
os.makedirs(save_dir, exist_ok=True)
# Save CSS and HTML content to files

4
tests/metagpt/test_environment.py
View file

@ -8,7 +8,7 @@
import pytest
from metagpt.actions import BossRequirement
from metagpt.actions import UserRequirement
from metagpt.environment import Environment
from metagpt.logs import logger
from metagpt.manager import Manager
@ -49,7 +49,7 @@ async def test_publish_and_process_message(env: Environment):
env.add_roles([product_manager, architect])
env.set_manager(Manager())
env.publish_message(Message(role="BOSS", content="需要一个基于LLM做总结的搜索引擎", cause_by=BossRequirement))
env.publish_message(Message(role="User", content="需要一个基于LLM做总结的搜索引擎", cause_by=UserRequirement))
await env.run(k=2)
logger.info(f"{env.history=}")

19
tests/metagpt/test_software_company.py
View file

@ -1,19 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Time : 2023/5/15 11:40
@Author : alexanderwu
@File : test_software_company.py
"""
import pytest
from metagpt.logs import logger
from metagpt.software_company import SoftwareCompany
@pytest.mark.asyncio
async def test_software_company():
company = SoftwareCompany()
company.start_project("做一个基础搜索引擎，可以支持知识库")
history = await company.run(n_round=5)
logger.info(history)

27
tests/metagpt/test_startup.py Normal file
View file

@ -0,0 +1,27 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Time : 2023/5/15 11:40
@Author : alexanderwu
@File : test_startup.py
"""
import pytest
from typer.testing import CliRunner
from metagpt.logs import logger
from metagpt.team import Team
runner = CliRunner()
@pytest.mark.asyncio
async def test_team():
company = Team()
company.run_project("做一个基础搜索引擎，可以支持知识库")
history = await company.run(n_round=5)
logger.info(history)
# def test_startup():
# args = ["Make a 2048 game"]
# result = runner.invoke(app, args)

7
tests/metagpt/tools/test_sd_tool.py
View file

@ -4,7 +4,8 @@
#
import os
from metagpt.tools.sd_engine import WORKSPACE_ROOT, SDEngine
from metagpt.config import CONFIG
from metagpt.tools.sd_engine import SDEngine
def test_sd_engine_init():
@ -21,5 +22,5 @@ def test_sd_engine_generate_prompt():
async def test_sd_engine_run_t2i():
sd_engine = SDEngine()
await sd_engine.run_t2i(prompts=["test"])
img_path = WORKSPACE_ROOT / "resources" / "SD_Output" / "output_0.png"
assert os.path.exists(img_path) == True
img_path = CONFIG.workspace_path / "resources" / "SD_Output" / "output_0.png"
assert os.path.exists(img_path)

8
tests/metagpt/utils/test_common.py
View file

@ -14,7 +14,7 @@ import pytest
from pydantic import BaseModel
from metagpt.actions import RunCode
from metagpt.const import get_project_root
from metagpt.const import get_metagpt_root
from metagpt.roles.tutorial_assistant import TutorialAssistant
from metagpt.schema import Message
from metagpt.utils.common import any_to_str, any_to_str_set
@ -27,13 +27,13 @@ class TestGetProjectRoot:
os.chdir(abs_root)
def test_get_project_root(self):
project_root = get_project_root()
assert project_root.name == "MetaGPT"
project_root = get_metagpt_root()
assert project_root.name == "metagpt"
def test_get_root_exception(self):
with pytest.raises(Exception) as exc_info:
self.change_etc_dir()
get_project_root()
get_metagpt_root()
assert str(exc_info.value) == "Project root not found."
def test_any_to_str(self):

2
tests/metagpt/utils/test_output_parser.py
View file

@ -220,7 +220,7 @@ We need clarification on how the high score should be stored. Should it persist
}
t_text1 = """## Original Requirements:
The boss wants to create a web-based version of the game "Fly Bird".
The user wants to create a web-based version of the game "Fly Bird".
## Product Goals:

4
tests/metagpt/utils/test_read_docx.py
View file

@ -6,12 +6,12 @@
@File : test_read_docx.py
"""
from metagpt.const import PROJECT_ROOT
from metagpt.const import METAGPT_ROOT
from metagpt.utils.read_document import read_docx
class TestReadDocx:
def test_read_docx(self):
docx_sample = PROJECT_ROOT / "tests/data/docx_for_test.docx"
docx_sample = METAGPT_ROOT / "tests/data/docx_for_test.docx"
docx = read_docx(docx_sample)
assert len(docx) == 6