apunkt/MetaGPT
1
0
Fork 0
mirror of https://github.com/FoundationAgents/MetaGPT.git synced 2026-06-08 15:05:17 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Merge branch 'dev' into code_intepreter

Browse source
This commit is contained in:
yzlin 2024-02-01 16:27:20 +08:00
commit afb702c3f3
38 changed files with 537 additions and 366 deletions
Download patch file Download diff file Expand all files Collapse all files

61
.github/workflows/auto-unittest.yaml vendored Normal file
View file

@ -0,0 +1,61 @@
name: Auto Unit Tests
on:
pull_request_target:
push:
branches:
- 'main'
- 'dev'
- '*-release'
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
# python-version: ['3.9', '3.10', '3.11']
python-version: ['3.9']
steps:
- uses: actions/checkout@v4
with:
ref: ${{ github.event.pull_request.head.sha }}
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
cache: 'pip'
- name: Install dependencies
run: |
sh tests/scripts/run_install_deps.sh
- name: Test with pytest
run: |
export ALLOW_OPENAI_API_CALL=0
mkdir -p ~/.metagpt && cp tests/config2.yaml ~/.metagpt/config2.yaml && cp tests/spark.yaml ~/.metagpt/spark.yaml
pytest tests/ --doctest-modules --cov=./metagpt/ --cov-report=xml:cov.xml --cov-report=html:htmlcov --durations=20 | tee unittest.txt
- name: Show coverage report
run: |
coverage report -m
- name: Show failed tests and overall summary
run: |
grep -E "FAILED tests|ERROR tests|[0-9]+ passed," unittest.txt
failed_count=$(grep -E "FAILED|ERROR" unittest.txt | wc -l)
if [[ "$failed_count" -gt 0 ]]; then
echo "$failed_count failed lines found! Task failed."
exit 1
fi
- name: Upload pytest test results
uses: actions/upload-artifact@v3
with:
name: pytest-results-${{ matrix.python-version }}
path: |
./unittest.txt
./htmlcov/
./tests/data/rsp_cache_new.json
retention-days: 3
if: ${{ always() }}
- name: Upload coverage reports to Codecov
uses: codecov/codecov-action@v3
env:
CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
if: ${{ always() }}

4
.github/workflows/unittest.yaml vendored
View file

@ -5,6 +5,9 @@ on:
pull_request_target:
push:
branches:
- 'main'
- 'dev'
- '*-release'
- '*-debugger'
jobs:
@ -51,6 +54,7 @@ jobs:
export ALLOW_OPENAI_API_CALL=0
echo "${{ secrets.METAGPT_KEY_YAML }}" | base64 -d > config/key.yaml
mkdir -p ~/.metagpt && echo "${{ secrets.METAGPT_CONFIG2_YAML }}" | base64 -d > ~/.metagpt/config2.yaml
echo "${{ secrets.SPARK_YAML }}" | base64 -d > ~/.metagpt/spark.yaml
pytest tests/ --doctest-modules --cov=./metagpt/ --cov-report=xml:cov.xml --cov-report=html:htmlcov --durations=20 | tee unittest.txt
- name: Show coverage report
run: |

35
README.md
View file

@ -55,30 +55,21 @@ ## Install
### Pip installation
> Ensure that Python 3.9+ is installed on your system. You can check this by using: `python --version`.
> You can use conda like this: `conda create -n metagpt python=3.9 && conda activate metagpt`
```bash
# 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
pip install metagpt
metagpt --init-config # create ~/.metagpt/config2.yaml, modify it to your own config
metagpt "Create a 2048 game" # this will create a repo in ./workspace
```
# 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
or you can use it as library
# Step 3: setup your LLM key in the config2.yaml file
mkdir ~/.metagpt
cp config/config2.yaml ~/.metagpt/config2.yaml
vim ~/.metagpt/config2.yaml
# Step 4: run metagpt cli
metagpt "Create a 2048 game in python"
# Step 5 [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
```python
from metagpt.software_company import generate_repo, ProjectRepo
repo: ProjectRepo = generate_repo("Create a 2048 game") # or ProjectRepo("<path>")
print(repo) # it will print the repo structure with files
```
detail installation please refer to [cli_install](https://docs.deepwisdom.ai/main/en/guide/get_started/installation.html#install-stable-version)
@ -99,7 +90,7 @@ # Step 2: Run metagpt demo with container
-v /opt/metagpt/config/config2.yaml:/app/metagpt/config/config2.yaml \
-v /opt/metagpt/workspace:/app/metagpt/workspace \
metagpt/metagpt:latest \
metagpt "Write a cli snake game"
metagpt "Create a 2048 game"
```
detail installation please refer to [docker_install](https://docs.deepwisdom.ai/main/en/guide/get_started/installation.html#install-with-docker)

14
config/config2.yaml.example
View file

@ -29,11 +29,13 @@ s3:
bucket: "test"
AZURE_TTS_SUBSCRIPTION_KEY: "YOUR_SUBSCRIPTION_KEY"
AZURE_TTS_REGION: "eastus"
azure_tts_subscription_key: "YOUR_SUBSCRIPTION_KEY"
azure_tts_region: "eastus"
IFLYTEK_APP_ID: "YOUR_APP_ID"
IFLYTEK_API_KEY: "YOUR_API_KEY"
IFLYTEK_API_SECRET: "YOUR_API_SECRET"
iflytek_api_id: "YOUR_APP_ID"
iflytek_api_key: "YOUR_API_KEY"
iflytek_api_secret: "YOUR_API_SECRET"
METAGPT_TEXT_TO_IMAGE_MODEL_URL: "YOUR_MODEL_URL"
metagpt_tti_url: "YOUR_MODEL_URL"
repair_llm_output: true

18
docs/.well-known/metagpt_oas3_api.yaml
View file

@ -14,16 +14,16 @@ paths:
/tts/azsure:
x-prerequisite:
configurations:
AZURE_TTS_SUBSCRIPTION_KEY:
azure_tts_subscription_key:
type: string
description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
AZURE_TTS_REGION:
azure_tts_region:
type: string
description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
required:
allOf:
- AZURE_TTS_SUBSCRIPTION_KEY
- AZURE_TTS_REGION
- azure_tts_subscription_key
- azure_tts_region
post:
summary: "Convert Text to Base64-encoded .wav File Stream"
description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
@ -94,9 +94,9 @@ paths:
description: "WebAPI argument, see: `https://console.xfyun.cn/services/tts`"
required:
allOf:
- IFLYTEK_APP_ID
- IFLYTEK_API_KEY
- IFLYTEK_API_SECRET
- iflytek_app_id
- iflytek_api_key
- iflytek_api_secret
post:
summary: "Convert Text to Base64-encoded .mp3 File Stream"
description: "For more details, check out: [iFlyTek](https://console.xfyun.cn/services/tts)"
@ -242,12 +242,12 @@ paths:
/txt2image/metagpt:
x-prerequisite:
configurations:
METAGPT_TEXT_TO_IMAGE_MODEL_URL:
metagpt_tti_url:
type: string
description: "Model url."
required:
allOf:
- METAGPT_TEXT_TO_IMAGE_MODEL_URL
- metagpt_tti_url
post:
summary: "Text to Image"
description: "Generate an image from the provided text using the MetaGPT Text-to-Image API."

18
docs/.well-known/skills.yaml
View file

@ -14,10 +14,10 @@ entities:
id: text_to_speech.text_to_speech
x-prerequisite:
configurations:
AZURE_TTS_SUBSCRIPTION_KEY:
azure_tts_subscription_key:
type: string
description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
AZURE_TTS_REGION:
azure_tts_region:
type: string
description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
IFLYTEK_APP_ID:
@ -32,12 +32,12 @@ entities:
required:
oneOf:
- allOf:
- AZURE_TTS_SUBSCRIPTION_KEY
- AZURE_TTS_REGION
- azure_tts_subscription_key
- azure_tts_region
- allOf:
- IFLYTEK_APP_ID
- IFLYTEK_API_KEY
- IFLYTEK_API_SECRET
- iflytek_app_id
- iflytek_api_key
- iflytek_api_secret
parameters:
text:
description: 'The text used for voice conversion.'
@ -103,13 +103,13 @@ entities:
OPENAI_API_KEY:
type: string
description: "OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`"
METAGPT_TEXT_TO_IMAGE_MODEL_URL:
metagpt_tti_url:
type: string
description: "Model url."
required:
oneOf:
- OPENAI_API_KEY
- METAGPT_TEXT_TO_IMAGE_MODEL_URL
- metagpt_tti_url
parameters:
text:
description: 'The text used for image conversion.'

174
docs/FAQ-EN.md
View file

@ -1,161 +1,93 @@
Our vision is to [extend human life](https://github.com/geekan/HowToLiveLonger) and [reduce working hours](https://github.com/geekan/MetaGPT/).
1. ### Convenient Link for Sharing this Document:
### Convenient Link for Sharing this Document:
```
- MetaGPT-Index/FAQ https://deepwisdom.feishu.cn/wiki/MsGnwQBjiif9c3koSJNcYaoSnu4
- MetaGPT-Index/FAQ-EN https://github.com/geekan/MetaGPT/blob/main/docs/FAQ-EN.md
- MetaGPT-Index/FAQ-CN https://deepwisdom.feishu.cn/wiki/MsGnwQBjiif9c3koSJNcYaoSnu4
```
2. ### Link
<!---->
### Link
1. Code：https://github.com/geekan/MetaGPT
1. Roadmap：https://github.com/geekan/MetaGPT/blob/main/docs/ROADMAP.md
1. EN
1. Demo Video: [MetaGPT: Multi-Agent AI Programming Framework](https://www.youtube.com/watch?v=8RNzxZBTW8M)
2. Roadmap：https://github.com/geekan/MetaGPT/blob/main/docs/ROADMAP.md
3. EN
1. Demo Video: [MetaGPT: Multi-Agent AI Programming Framework](https://www.youtube.com/watch?v=8RNzxZBTW8M)
2. Tutorial: [MetaGPT: Deploy POWERFUL Autonomous Ai Agents BETTER Than SUPERAGI!](https://www.youtube.com/watch?v=q16Gi9pTG_M&t=659s)
3. Author's thoughts video(EN): [MetaGPT Matthew Berman](https://youtu.be/uT75J_KG_aY?si=EgbfQNAwD8F5Y1Ak)
4. CN
1. Demo Video: [MetaGPT：一行代码搭建你的虚拟公司_哔哩哔哩_bilibili](https://www.bilibili.com/video/BV1NP411C7GW/?spm_id_from=333.999.0.0&vd_source=735773c218b47da1b4bd1b98a33c5c77)
1. Tutorial: [一个提示词写游戏 Flappy bird, 比AutoGPT强10倍的MetaGPT，最接近AGI的AI项目](https://youtu.be/Bp95b8yIH5c)
2. Author's thoughts video(CN): [MetaGPT作者深度解析直播回放_哔哩哔哩_bilibili](https://www.bilibili.com/video/BV1Ru411V7XL/?spm_id_from=333.337.search-card.all.click)
1. CN
1. Demo Video: [MetaGPT：一行代码搭建你的虚拟公司_哔哩哔哩_bilibili](https://www.bilibili.com/video/BV1NP411C7GW/?spm_id_from=333.999.0.0&vd_source=735773c218b47da1b4bd1b98a33c5c77)
1. Tutorial: [一个提示词写游戏 Flappy bird, 比AutoGPT强10倍的MetaGPT，最接近AGI的AI项目](https://youtu.be/Bp95b8yIH5c)
2. Author's thoughts video(CN): [MetaGPT作者深度解析直播回放_哔哩哔哩_bilibili](https://www.bilibili.com/video/BV1Ru411V7XL/?spm_id_from=333.337.search-card.all.click)
<!---->
3. ### How to become a contributor?
<!---->
### How to become a contributor?
1. Choose a task from the Roadmap (or you can propose one). By submitting a PR, you can become a contributor and join the dev team.
1. Current contributors come from backgrounds including ByteDance AI Lab/DingDong/Didi/Xiaohongshu, Tencent/Baidu/MSRA/TikTok/BloomGPT Infra/Bilibili/CUHK/HKUST/CMU/UCB
2. Current contributors come from backgrounds including ByteDance AI Lab/DingDong/Didi/Xiaohongshu, Tencent/Baidu/MSRA/TikTok/BloomGPT Infra/Bilibili/CUHK/HKUST/CMU/UCB
<!---->
4. ### Chief Evangelist (Monthly Rotation)
### Chief Evangelist (Monthly Rotation)
MetaGPT Community - The position of Chief Evangelist rotates on a monthly basis. The primary responsibilities include:
1. Maintaining community FAQ documents, announcements, and Github resources/READMEs.
1. Responding to, answering, and distributing community questions within an average of 30 minutes, including on platforms like Github Issues, Discord and WeChat.
1. Upholding a community atmosphere that is enthusiastic, genuine, and friendly.
1. Encouraging everyone to become contributors and participate in projects that are closely related to achieving AGI (Artificial General Intelligence).
1. (Optional) Organizing small-scale events, such as hackathons.
2. Responding to, answering, and distributing community questions within an average of 30 minutes, including on platforms like Github Issues, Discord and WeChat.
3. Upholding a community atmosphere that is enthusiastic, genuine, and friendly.
4. Encouraging everyone to become contributors and participate in projects that are closely related to achieving AGI (Artificial General Intelligence).
5. (Optional) Organizing small-scale events, such as hackathons.
<!---->
5. ### FAQ
<!---->
1. Experience with the generated repo code:
1. https://github.com/geekan/MetaGPT/releases/tag/v0.1.0
### FAQ
1. Code truncation/ Parsing failure:
1. Check if it's due to exceeding length. Consider using the gpt-3.5-turbo-16k or other long token versions.
1. Success rate:
1. There hasn't been a quantitative analysis yet, but the success rate of code generated by GPT-4 is significantly higher than that of gpt-3.5-turbo.
1. Support for incremental, differential updates (if you wish to continue a half-done task):
1. Several prerequisite tasks are listed on the ROADMAP.
1. Can existing code be loaded?
1. It's not on the ROADMAP yet, but there are plans in place. It just requires some time.
1. Support for multiple programming languages and natural languages?
1. It's listed on ROADMAP.
1. Want to join the contributor team? How to proceed?
1. Check if it's due to exceeding length. Consider using the gpt-4-turbo-preview or other long token versions.
2. Success rate:
1. There hasn't been a quantitative analysis yet, but the success rate of code generated by gpt-4-turbo-preview is significantly higher than that of gpt-3.5-turbo.
3. Support for incremental, differential updates (if you wish to continue a half-done task):
1. There is now an experimental version. Specify `--inc --project-path "<path>"` or `--inc --project-name "<name>"` on the command line and enter the corresponding requirements to try it.
4. Can existing code be loaded?
1. We are doing this, but it is very difficult, especially when the project is large, it is very difficult to achieve a high success rate.
5. Support for multiple programming languages and natural languages?
1. It is now supported, but it is still in experimental version
6. Want to join the contributor team? How to proceed?
1. Merging a PR will get you into the contributor's team. The main ongoing tasks are all listed on the ROADMAP.
1. PRD stuck / unable to access/ connection interrupted
7. PRD stuck / unable to access/ connection interrupted
1. The official openai base_url address is `https://api.openai.com/v1`
1. If the official openai base_url address is inaccessible in your environment (this can be verified with curl), it's recommended to configure using the reverse proxy openai base_url provided by libraries such as openai-forward. For instance, `openai base_url: "``https://api.openai-forward.com/v1``"`
1. If the official openai base_url address is inaccessible in your environment (again, verifiable via curl), another option is to configure the llm.proxy parameter. This way, you can access the official openai base_url via a local proxy. If you don't need to access via a proxy, please do not enable this configuration; if accessing through a proxy is required, modify it to the correct proxy address. Note that when llm.proxy is enabled, don't set openai base_url.
1. Note: OpenAI's default API design ends with a v1. An example of the correct configuration is: `openai base_url: "``https://api.openai.com/v1``"`
1. Absolutely! How can I assist you today?
2. If the official openai base_url address is inaccessible in your environment (this can be verified with curl), it's recommended to configure using base_url to other "reverse-proxy" provider such as openai-forward. For instance, `openai base_url: "``https://api.openai-forward.com/v1``"`
3. If the official openai base_url address is inaccessible in your environment (again, verifiable via curl), another option is to configure the llm.proxy in the `config2.yaml`. This way, you can access the official openai base_url via a local proxy. If you don't need to access via a proxy, please do not enable this configuration; if accessing through a proxy is required, modify it to the correct proxy address.
4. Note: OpenAI's default API design ends with a v1. An example of the correct configuration is: `base_url: "https://api.openai.com/v1"
8. Get reply: "Absolutely! How can I assist you today?"
1. Did you use Chi or a similar service? These services are prone to errors, and it seems that the error rate is higher when consuming 3.5k-4k tokens in GPT-4
1. What does Max token mean?
9. What does Max token mean?
1. It's a configuration for OpenAI's maximum response length. If the response exceeds the max token, it will be truncated.
1. How to change the investment amount?
10. How to change the investment amount?
1. You can view all commands by typing `metagpt --help`
1. Which version of Python is more stable?
11. Which version of Python is more stable?
1. python3.9 / python3.10
1. Can't use GPT-4, getting the error "The model gpt-4 does not exist."
12. Can't use GPT-4, getting the error "The model gpt-4 does not exist."
1. OpenAI's official requirement: You can use GPT-4 only after spending $1 on OpenAI.
1. Tip: Run some data with gpt-3.5-turbo (consume the free quota and $1), and then you should be able to use gpt-4.
1. Can games whose code has never been seen before be written?
13. Can games whose code has never been seen before be written?
1. Refer to the README. The recommendation system of Toutiao is one of the most complex systems in the world currently. Although it's not on GitHub, many discussions about it exist online. If it can visualize these, it suggests it can also summarize these discussions and convert them into code. The prompt would be something like "write a recommendation system similar to Toutiao". Note: this was approached in earlier versions of the software. The SOP of those versions was different; the current one adopts Elon Musk's five-step work method, emphasizing trimming down requirements as much as possible.
1. Under what circumstances would there typically be errors?
14. Under what circumstances would there typically be errors?
1. More than 500 lines of code: some function implementations may be left blank.
1. When using a database, it often gets the implementation wrong — since the SQL database initialization process is usually not in the code.
1. With more lines of code, there's a higher chance of false impressions, leading to calls to non-existent APIs.
1. An error occurred during installation: "Another program is using this file...egg".
2. When using a database, it often gets the implementation wrong — since the SQL database initialization process is usually not in the code.
3. With more lines of code, there's a higher chance of false impressions, leading to calls to non-existent APIs.
15. An error occurred during installation: "Another program is using this file...egg".
1. Delete the file and try again.
1. Or manually execute`pip install -r requirements.txt`
1. The origin of the name MetaGPT？
2. Or manually execute`pip install -r requirements.txt`
16. The origin of the name MetaGPT？
1. The name was derived after iterating with GPT-4 over a dozen rounds. GPT-4 scored and suggested it.
1. Is there a more step-by-step installation tutorial?
1. Youtube（CN）：[一个提示词写游戏 Flappy bird, 比AutoGPT强10倍的MetaGPT，最接近AGI的AI项目=一个软件公司产品经理+程序员](https://youtu.be/Bp95b8yIH5c)
1. Youtube（EN）https://www.youtube.com/watch?v=q16Gi9pTG_M&t=659s
2. video(EN): [MetaGPT Matthew Berman](https://youtu.be/uT75J_KG_aY?si=EgbfQNAwD8F5Y1Ak)
1. openai.error.RateLimitError: You exceeded your current quota, please check your plan and billing details
17. openai.error.RateLimitError: You exceeded your current quota, please check your plan and billing details
1. If you haven't exhausted your free quota, set RPM to 3 or lower in the settings.
1. If your free quota is used up, consider adding funds to your account.
1. What does "borg" mean in n_borg?
2. If your free quota is used up, consider adding funds to your account.
18. What does "borg" mean in n_borg?
1. [Wikipedia borg meaning ](https://en.wikipedia.org/wiki/Borg)
1. The Borg civilization operates based on a hive or collective mentality, known as "the Collective." Every Borg individual is connected to the collective via a sophisticated subspace network, ensuring continuous oversight and guidance for every member. This collective consciousness allows them to not only "share the same thoughts" but also to adapt swiftly to new strategies. While individual members of the collective rarely communicate, the collective "voice" sometimes transmits aboard ships.
1. How to use the Claude API？
2. The Borg civilization operates based on a hive or collective mentality, known as "the Collective." Every Borg individual is connected to the collective via a sophisticated subspace network, ensuring continuous oversight and guidance for every member. This collective consciousness allows them to not only "share the same thoughts" but also to adapt swiftly to new strategies. While individual members of the collective rarely communicate, the collective "voice" sometimes transmits aboard ships.
19. How to use the Claude API？
1. The full implementation of the Claude API is not provided in the current code.
1. You can use the Claude API through third-party API conversion projects like: https://github.com/jtsang4/claude-to-chatgpt
1. Is Llama2 supported？
20. Is Llama2 supported？
1. On the day Llama2 was released, some of the community members began experiments and found that output can be generated based on MetaGPT's structure. However, Llama2's context is too short to generate a complete project. Before regularly using Llama2, it's necessary to expand the context window to at least 8k. If anyone has good recommendations for expansion models or methods, please leave a comment.
1. `mermaid-cli getElementsByTagName SyntaxError: Unexpected token '.'`
21. `mermaid-cli getElementsByTagName SyntaxError: Unexpected token '.'`
1. Upgrade node to version 14.x or above:
1. `npm install -g n`
1. `n stable` to install the stable version of node（v18.x）
2. `n stable` to install the stable version of node（v18.x）

37
docs/README_CN.md
View file

@ -35,29 +35,24 @@ # MetaGPT: 多智能体框架
## 安装
### Pip安装
> 确保您的系统已安装 Python 3.9 或更高版本。您可以使用以下命令来检查：`python --version`。
> 您可以这样使用 conda：`conda create -n metagpt python=3.9 && conda activate metagpt`
```bash
# 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metagpt
# 拷贝config2.yaml为~/.metagpt/config2.yaml，并设置你自己的api_key
metagpt "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
pip install metagpt
metagpt --init-config # 创建 ~/.metagpt/config2.yaml，根据您的需求修改它
metagpt "创建一个 2048 游戏" # 这将在 ./workspace 创建一个仓库
```
详细的安装请安装 [cli_install](https://docs.deepwisdom.ai/guide/get_started/installation.html#install-stable-version)
或者您可以将其作为库使用
```python
from metagpt.software_company import generate_repo, ProjectRepo
repo: ProjectRepo = generate_repo("创建一个 2048 游戏") # 或 ProjectRepo("<路径>")
print(repo) # 它将打印出仓库结构及其文件
```
详细的安装请参考 [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"
@ -78,7 +73,7 @@ # 步骤2: 使用容器运行metagpt演示
metagpt "Write a cli snake game"
```
详细的安装请安装 [docker_install](https://docs.deepwisdom.ai/main/zh/guide/get_started/installation.html#%E4%BD%BF%E7%94%A8docker%E5%AE%89%E8%A3%85)
详细的安装请参考 [docker_install](https://docs.deepwisdom.ai/main/zh/guide/get_started/installation.html#%E4%BD%BF%E7%94%A8docker%E5%AE%89%E8%A3%85)
### 快速开始的演示视频
- 在 [MetaGPT Huggingface Space](https://huggingface.co/spaces/deepwisdom/MetaGPT) 上进行体验

25
docs/README_JA.md
View file

@ -57,24 +57,21 @@ ### インストールビデオガイド
- [Matthew Berman: How To Install MetaGPT - Build A Startup With One Prompt!!](https://youtu.be/uT75J_KG_aY)
### 伝統的なインストール
> Python 3.9 以上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。これは `python --version` を使ってチェックできます。
> 以下のようにcondaを使うことができます：`conda create -n metagpt python=3.9 && conda activate metagpt`
```bash
# 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:
python3 --version
pip install metagpt
metagpt --init-config # ~/.metagpt/config2.yaml を作成し、自分の設定に合わせて変更してください
metagpt "2048ゲームを作成する" # これにより ./workspace にリポジトリが作成されます
```
# 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.
または、ライブラリとして使用することもできます
# ステップ 3: metagpt を実行する
# config/config2.yaml を ~/.metagpt/config2.yaml にコピーし、独自の api_key を設定します
metagpt "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
```python
from metagpt.software_company import generate_repo, ProjectRepo
repo: ProjectRepo = generate_repo("2048ゲームを作成する") # または ProjectRepo("<パス>")
print(repo) # リポジトリの構造とファイルを出力します
```
**注:**

45
docs/install/cli_install.md
View file

@ -9,17 +9,29 @@ ### Support System and version
### 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:
# 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 3: Clone the repository to your local machine, and install it.
# 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
pip install -e.
pip3 install -e . # or pip3 install metagpt # for stable version
# Step 3: setup your LLM key in the config2.yaml file
mkdir ~/.metagpt
cp config/config2.yaml ~/.metagpt/config2.yaml
vim ~/.metagpt/config2.yaml
# Step 4: run metagpt cli
metagpt "Create a 2048 game in python"
# Step 5 [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
```
**Note:**
@ -33,11 +45,12 @@ # Step 3: Clone the repository to your local machine, and install it.
npm install @mermaid-js/mermaid-cli
```
- don't forget to the configuration for mmdc in config.yml
- don't forget to the configuration for mmdc path in config.yml
```yml
puppeteer_config: "./config/puppeteer-config.json"
path: "./node_modules/.bin/mmdc"
```yaml
mermaid:
puppeteer_config: "./config/puppeteer-config.json"
path: "./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`
@ -61,7 +74,7 @@ # Step 3: Clone the repository to your local machine, and install it.
- **modify `config2.yaml`**
uncomment mermaid.engine from config2.yaml and change it to `playwright`
change mermaid.engine to `playwright`
```yaml
mermaid:
@ -91,7 +104,7 @@ # Step 3: Clone the repository to your local machine, and install it.
- **modify `config2.yaml`**
uncomment mermaid.engine from config2.yaml and change it to `pyppeteer`
change mermaid.engine to `pyppeteer`
```yaml
mermaid:
@ -100,8 +113,8 @@ # Step 3: Clone the repository to your local machine, and install it.
- mermaid.ink
- **modify `config2.yaml`**
uncomment mermaid.engine from config2.yaml and change it to `ink`
change mermaid.engine to `ink`
```yaml
mermaid:
@ -109,4 +122,4 @@ # Step 3: Clone the repository to your local machine, and install it.
```
Note: this method does not support pdf export.

33
docs/install/cli_install_cn.md
View file

@ -10,17 +10,29 @@ ### 支持的系统和版本
### 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：
# 步骤 1: 确保您的系统安装了 Python 3.9 或更高版本。您可以使用以下命令来检查:
# 您可以使用 conda 来初始化一个新的 Python 环境
# conda create -n metagpt python=3.9
# conda activate metagpt
python3 --version
# 第 3 步：克隆仓库到您的本地机器，并进行安装。
# 步骤 2: 克隆仓库到您的本地机器以获取最新版本，并安装它。
git clone https://github.com/geekan/MetaGPT.git
cd MetaGPT
pip install -e.
pip3 install -e . # 或 pip3 install metagpt # 用于稳定版本
# 步骤 3: 在 config2.yaml 文件中设置您的 LLM 密钥
mkdir ~/.metagpt
cp config/config2.yaml ~/.metagpt/config2.yaml
vim ~/.metagpt/config2.yaml
# 步骤 4: 运行 metagpt 命令行界面
metagpt "用 python 创建一个 2048 游戏"
# 步骤 5 [可选]: 如果您想保存诸如象限图、系统设计、序列流等图表作为工作空间的工件，您可以在执行步骤 3 之前执行此步骤。默认情况下，该框架是兼容的，整个过程可以完全不执行此步骤而运行。
# 如果执行此步骤，请确保您的系统上安装了 NPM。然后安装 mermaid-js。（如果您的计算机中没有 npm，请访问 Node.js 官方网站 https://nodejs.org/ 安装 Node.js，然后您将在计算机中拥有 npm 工具。）
npm --version
sudo npm install -g @mermaid-js/mermaid-cli
```
**注意：**
@ -33,11 +45,12 @@ # 第 3 步：克隆仓库到您的本地机器，并进行安装。
npm install @mermaid-js/mermaid-cli
```
- 不要忘记在config.yml中为mmdc配置配置，
- 不要忘记在config.yml中为mmdc配置
```yml
puppeteer_config: "./config/puppeteer-config.json"
path: "./node_modules/.bin/mmdc"
mermaid:
puppeteer_config: "./config/puppeteer-config.json"
path: "./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。

51
docs/tutorial/usage.md
View file

@ -2,7 +2,7 @@ ## MetaGPT Usage
### Configuration
- Configure your `key` in any of `~/.metagpt/config2.yaml / config/config2.yaml`
- Configure your `api_key` in any of `~/.metagpt/config2.yaml / config/config2.yaml`
- Priority order: `~/.metagpt/config2.yaml > config/config2.yaml`
```bash
@ -34,29 +34,28 @@ ### Preference of Platform or Tool
### Usage
```
NAME
metagpt - We are a software startup comprised of AI. By investing in us, you are empowering a future filled with limitless possibilities.
SYNOPSIS
metagpt 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
Usage: metagpt [OPTIONS] [IDEA]
Start a new project.
╭─ Arguments ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ idea [IDEA] Your innovative idea, such as 'Create a 2048 game.' [default: None] │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Options ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --investment FLOAT Dollar amount to invest in the AI company. [default: 3.0] │
│ --n-round INTEGER Number of rounds for the simulation. [default: 5] │
│ --code-review --no-code-review Whether to use code review. [default: code-review] │
│ --run-tests --no-run-tests Whether to enable QA for adding & running tests. [default: no-run-tests] │
│ --implement --no-implement Enable or disable code implementation. [default: implement] │
│ --project-name TEXT Unique project name, such as 'game_2048'. │
│ --inc --no-inc Incremental mode. Use it to coop with existing repo. [default: no-inc] │
│ --project-path TEXT Specify the directory path of the old version project to fulfill the incremental requirements. │
│ --reqa-file TEXT Specify the source file name for rewriting the quality assurance code. │
│ --max-auto-summarize-code INTEGER The maximum number of times the 'SummarizeCode' action is automatically invoked, with -1 indicating unlimited. This parameter is used for debugging the │
│ workflow. │
│ [default: 0] │
│ --recover-path TEXT recover the project from existing serialized storage [default: None] │
│ --init-config --no-init-config Initialize the configuration file for MetaGPT. [default: no-init-config] │
│ --help Show this message and exit. │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
```

51
docs/tutorial/usage_cn.md
View file

@ -2,7 +2,7 @@ ## MetaGPT 使用
### 配置
- 在 `~/.metagpt/config2.yaml / config/config2.yaml` 中配置您的 `key`
- 在 `~/.metagpt/config2.yaml / config/config2.yaml` 中配置您的 `api_key`
- 优先级顺序：`~/.metagpt/config2.yaml > config/config2.yaml`
```bash
@ -30,29 +30,28 @@ ### 平台或工具的倾向性
### 使用
```
名称
metagpt - 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
metagpt 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`
Usage: metagpt [OPTIONS] [IDEA]
Start a new project.
╭─ Arguments ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ idea [IDEA] Your innovative idea, such as 'Create a 2048 game.' [default: None] │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Options ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --investment FLOAT Dollar amount to invest in the AI company. [default: 3.0] │
│ --n-round INTEGER Number of rounds for the simulation. [default: 5] │
│ --code-review --no-code-review Whether to use code review. [default: code-review] │
│ --run-tests --no-run-tests Whether to enable QA for adding & running tests. [default: no-run-tests] │
│ --implement --no-implement Enable or disable code implementation. [default: implement] │
│ --project-name TEXT Unique project name, such as 'game_2048'. │
│ --inc --no-inc Incremental mode. Use it to coop with existing repo. [default: no-inc] │
│ --project-path TEXT Specify the directory path of the old version project to fulfill the incremental requirements. │
│ --reqa-file TEXT Specify the source file name for rewriting the quality assurance code. │
│ --max-auto-summarize-code INTEGER The maximum number of times the 'SummarizeCode' action is automatically invoked, with -1 indicating unlimited. This parameter is used for debugging the │
│ workflow. │
│ [default: 0] │
│ --recover-path TEXT recover the project from existing serialized storage [default: None] │
│ --init-config --no-init-config Initialize the configuration file for MetaGPT. [default: no-init-config] │
│ --help Show this message and exit. │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
```

49
examples/write_novel.py Normal file
View file

@ -0,0 +1,49 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Time : 2024/2/1 12:01
@Author : alexanderwu
@File : write_novel.py
"""
import asyncio
from typing import List
from pydantic import BaseModel, Field
from metagpt.actions.action_node import ActionNode
from metagpt.llm import LLM
class Novel(BaseModel):
name: str = Field(default="The Lord of the Rings", description="The name of the novel.")
user_group: str = Field(default="...", description="The user group of the novel.")
outlines: List[str] = Field(
default=["Chapter 1: ...", "Chapter 2: ...", "Chapter 3: ..."],
description="The outlines of the novel. No more than 10 chapters.",
)
background: str = Field(default="...", description="The background of the novel.")
character_names: List[str] = Field(default=["Frodo", "Gandalf", "Sauron"], description="The characters.")
conflict: str = Field(default="...", description="The conflict of the characters.")
plot: str = Field(default="...", description="The plot of the novel.")
ending: str = Field(default="...", description="The ending of the novel.")
class Chapter(BaseModel):
name: str = Field(default="Chapter 1", description="The name of the chapter.")
content: str = Field(default="...", description="The content of the chapter. No more than 1000 words.")
async def generate_novel():
instruction = (
"Write a novel named 'Harry Potter in The Lord of the Rings'. "
"Fill the empty nodes with your own ideas. Be creative! Use your own words!"
"I will tip you $100,000 if you write a good novel."
)
novel_node = await ActionNode.from_pydantic(Novel).fill(context=instruction, llm=LLM())
chap_node = await ActionNode.from_pydantic(Chapter).fill(
context=f"### instruction\n{instruction}\n### novel\n{novel_node.content}", llm=LLM()
)
print(chap_node.content)
asyncio.run(generate_novel())

4
metagpt/actions/run_code.py
View file

@ -42,8 +42,8 @@ Determine the ONE file to rewrite in order to fix the error, for example, xyz.py
Determine if all of the code works fine, if so write PASS, else FAIL,
WRITE ONLY ONE WORD, PASS OR FAIL, IN THIS SECTION
## Send To:
Please write Engineer if the errors are due to problematic development codes, and QaEngineer to problematic test codes, and NoOne if there are no errors,
WRITE ONLY ONE WORD, Engineer OR QaEngineer OR NoOne, IN THIS SECTION.
Please write NoOne if there are no errors, Engineer if the errors are due to problematic development codes, else QaEngineer,
WRITE ONLY ONE WORD, NoOne OR Engineer OR QaEngineer, IN THIS SECTION.
---
You should fill in necessary instruction, status, send to, and finally return all content between the --- segment line.
"""

2
metagpt/actions/write_docstring.py
View file

@ -16,7 +16,7 @@ Options:
Default: 'google'
Example:
python3 -m metagpt.actions.write_docstring ./metagpt/startup.py --overwrite False --style=numpy
python3 -m metagpt.actions.write_docstring ./metagpt/software_company.py --overwrite False --style=numpy
This script uses the 'fire' library to create a command-line interface. It generates docstrings for the given Python code using
the specified docstring style and adds them to the code.

17
metagpt/config2.py
View file

@ -67,17 +67,16 @@ class Config(CLIParams, YamlModel):
code_review_k_times: int = 2
# Will be removed in the future
METAGPT_TEXT_TO_IMAGE_MODEL_URL: str = ""
metagpt_tti_url: str = ""
language: str = "English"
redis_key: str = "placeholder"
IFLYTEK_APP_ID: str = ""
IFLYTEK_API_SECRET: str = ""
IFLYTEK_API_KEY: str = ""
AZURE_TTS_SUBSCRIPTION_KEY: str = ""
AZURE_TTS_REGION: str = ""
mermaid_engine: str = "nodejs"
OPENAI_VISION_MODEL: str = "gpt-4-vision-preview"
VISION_MAX_TOKENS: int = 4096
iflytek_app_id: str = ""
iflytek_api_secret: str = ""
iflytek_api_key: str = ""
azure_tts_subscription_key: str = ""
azure_tts_region: str = ""
openai_vision_model: str = "gpt-4-vision-preview"
vision_max_tokens: int = 4096
@classmethod
def from_home(cls, path):

2
metagpt/learn/text_to_image.py
View file

@ -27,7 +27,7 @@ async def text_to_image(text, size_type: str = "512x512", config: Config = metag
"""
image_declaration = "data:image/png;base64,"
model_url = config.METAGPT_TEXT_TO_IMAGE_MODEL_URL
model_url = config.metagpt_tti_url
if model_url:
binary_data = await oas3_metagpt_text_to_image(text, size_type, model_url)
elif config.get_openai_llm():

12
metagpt/learn/text_to_speech.py
View file

@ -39,8 +39,8 @@ async def text_to_speech(
"""
subscription_key = config.AZURE_TTS_SUBSCRIPTION_KEY
region = config.AZURE_TTS_REGION
subscription_key = config.azure_tts_subscription_key
region = config.azure_tts_region
if subscription_key and region:
audio_declaration = "data:audio/wav;base64,"
base64_data = await oas3_azsure_tts(text, lang, voice, style, role, subscription_key, region)
@ -50,9 +50,9 @@ async def text_to_speech(
return f"[{text}]({url})"
return audio_declaration + base64_data if base64_data else base64_data
iflytek_app_id = config.IFLYTEK_APP_ID
iflytek_api_key = config.IFLYTEK_API_KEY
iflytek_api_secret = config.IFLYTEK_API_SECRET
iflytek_app_id = config.iflytek_app_id
iflytek_api_key = config.iflytek_api_key
iflytek_api_secret = config.iflytek_api_secret
if iflytek_app_id and iflytek_api_key and iflytek_api_secret:
audio_declaration = "data:audio/mp3;base64,"
base64_data = await oas3_iflytek_tts(
@ -65,5 +65,5 @@ async def text_to_speech(
return audio_declaration + base64_data if base64_data else base64_data
raise ValueError(
"AZURE_TTS_SUBSCRIPTION_KEY, AZURE_TTS_REGION, IFLYTEK_APP_ID, IFLYTEK_API_KEY, IFLYTEK_API_SECRET error"
"azure_tts_subscription_key, azure_tts_region, iflytek_app_id, iflytek_api_key, iflytek_api_secret error"
)

2
metagpt/provider/base_llm.py
View file

@ -108,7 +108,7 @@ class BaseLLM(ABC):
def get_choice_delta_text(self, rsp: dict) -> str:
"""Required to provide the first text of stream choice"""
return rsp.get("choices")[0]["delta"]["content"]
return rsp.get("choices", [{}])[0].get("delta", {}).get("content", "")
def get_choice_function(self, rsp: dict) -> dict:
"""Required to provide the first function of choice

22
metagpt/startup.py → metagpt/software_company.py
View file

@ -17,17 +17,17 @@ app = typer.Typer(add_completion=False, pretty_exceptions_show_locals=False)
def generate_repo(
idea,
investment,
n_round,
code_review,
run_tests,
implement,
project_name,
inc,
project_path,
reqa_file,
max_auto_summarize_code,
recover_path,
investment=3.0,
n_round=5,
code_review=True,
run_tests=False,
implement=True,
project_name="",
inc=False,
project_path="",
reqa_file="",
max_auto_summarize_code=0,
recover_path=None,
) -> ProjectRepo:
"""Run the startup logic. Can be called from CLI or other Python scripts."""
from metagpt.roles import (

12
metagpt/tools/libs/gpt_v_generator.py
View file

@ -35,14 +35,10 @@ class GPTvGenerator:
def __init__(self):
from metagpt.config2 import config
OPENAI_API_BASE = config.llm.base_url
API_KEY = config.llm.api_key
MODEL = config.OPENAI_VISION_MODEL
MAX_TOKENS = config.VISION_MAX_TOKENS
self.api_key = API_KEY
self.api_base = OPENAI_API_BASE
self.model = MODEL
self.max_tokens = MAX_TOKENS
self.api_key = config.llm.api_key
self.api_base = config.llm.base_url
self.model = config.openai_vision_model
self.max_tokens = config.vision_max_tokens
def analyze_layout(self, image_path):
return self.get_result(image_path, ANALYZE_LAYOUT_PROMPT)

7
metagpt/utils/project_repo.py
View file

@ -99,6 +99,13 @@ class ProjectRepo(FileRepository):
self.tests = self._git_repo.new_file_repository(relative_path=TEST_CODES_FILE_REPO)
self.test_outputs = self._git_repo.new_file_repository(relative_path=TEST_OUTPUTS_FILE_REPO)
self._srcs_path = None
self.code_files_exists()
def __str__(self):
repo_str = f"ProjectRepo({self._git_repo.workdir})"
docs_str = f"Docs({self.docs.all_files})"
srcs_str = f"Srcs({self.srcs.all_files})"
return f"{repo_str}\n{docs_str}\n{srcs_str}"
@property
async def requirement(self):

21
metagpt/utils/repair_llm_raw_output.py
View file

@ -119,15 +119,22 @@ def repair_json_format(output: str) -> str:
logger.info(f"repair_json_format: {'}]'}")
elif output.startswith("{") and output.endswith("]"):
output = output[:-1] + "}"
# remove `#` in output json str, usually appeared in `glm-4`
# remove comments in output json string, after json value content, maybe start with #, maybe start with //
arr = output.split("\n")
new_arr = []
for line in arr:
idx = line.find("#")
if idx >= 0:
line = line[:idx]
new_arr.append(line)
for json_line in arr:
# look for # or // comments and make sure they are not inside the string value
comment_index = -1
for match in re.finditer(r"(\".*?\"|\'.*?\')|(#|//)", json_line):
if match.group(1): # if the string value
continue
if match.group(2): # if comments
comment_index = match.start(2)
break
# if comments, then delete them
if comment_index != -1:
json_line = json_line[:comment_index].rstrip()
new_arr.append(json_line)
output = "\n".join(new_arr)
return output

2
setup.py
View file

@ -76,7 +76,7 @@ setup(
},
entry_points={
"console_scripts": [
"metagpt=metagpt.startup:app",
"metagpt=metagpt.software_company:app",
],
},
)

27
tests/config2.yaml Normal file
View file

@ -0,0 +1,27 @@
llm:
base_url: "https://api.openai.com/v1"
api_key: "sk-xxx"
model: "gpt-3.5-turbo-1106"
search:
api_type: "serpapi"
api_key: "xxx"
s3:
access_key: "MOCK_S3_ACCESS_KEY"
secret_key: "MOCK_S3_SECRET_KEY"
endpoint: "http://mock:9000"
secure: false
bucket: "mock"
azure_tts_subscription_key: "xxx"
azure_tts_region: "eastus"
iflytek_app_id: "xxx"
iflytek_api_key: "xxx"
iflytek_api_secret: "xxx"
metagpt_tti_url: "http://mock.com"
repair_llm_output: true

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

@ -29,9 +29,9 @@ async def test_rebuild(context):
@pytest.mark.parametrize(
("path", "direction", "diff", "want"),
[
("metagpt/startup.py", "=", ".", "metagpt/startup.py"),
("metagpt/startup.py", "+", "MetaGPT", "MetaGPT/metagpt/startup.py"),
("metagpt/startup.py", "-", "metagpt", "startup.py"),
("metagpt/software_company.py", "=", ".", "metagpt/software_company.py"),
("metagpt/software_company.py", "+", "MetaGPT", "MetaGPT/metagpt/software_company.py"),
("metagpt/software_company.py", "-", "metagpt", "software_company.py"),
],
)
def test_align_path(path, direction, diff, want):

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

@ -23,9 +23,9 @@ class TestSkillAction:
"type": "string",
"description": "OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`",
},
"METAGPT_TEXT_TO_IMAGE_MODEL_URL": {"type": "string", "description": "Model url."},
"metagpt_tti_url": {"type": "string", "description": "Model url."},
},
"required": {"oneOf": ["OPENAI_API_KEY", "METAGPT_TEXT_TO_IMAGE_MODEL_URL"]},
"required": {"oneOf": ["OPENAI_API_KEY", "metagpt_tti_url"]},
},
parameters={
"text": Parameter(type="string", description="The text used for image conversion."),

4
tests/metagpt/learn/test_text_to_image.py
View file

@ -27,7 +27,7 @@ async def test_text_to_image(mocker):
mocker.patch.object(S3, "cache", return_value="http://mock/s3")
config = Config.default()
assert config.METAGPT_TEXT_TO_IMAGE_MODEL_URL
assert config.metagpt_tti_url
data = await text_to_image("Panda emoji", size_type="512x512", config=config)
assert "base64" in data or "http" in data
@ -52,7 +52,7 @@ async def test_openai_text_to_image(mocker):
mocker.patch.object(S3, "cache", return_value="http://mock.s3.com/0.png")
config = Config.default()
config.METAGPT_TEXT_TO_IMAGE_MODEL_URL = None
config.metagpt_tti_url = None
assert config.get_openai_llm()
data = await text_to_image("Panda emoji", size_type="512x512", config=config)

30
tests/metagpt/learn/test_text_to_speech.py
View file

@ -20,9 +20,9 @@ from metagpt.utils.s3 import S3
async def test_azure_text_to_speech(mocker):
# mock
config = Config.default()
config.IFLYTEK_API_KEY = None
config.IFLYTEK_API_SECRET = None
config.IFLYTEK_APP_ID = None
config.iflytek_api_key = None
config.iflytek_api_secret = None
config.iflytek_app_id = None
mock_result = mocker.Mock()
mock_result.audio_data = b"mock audio data"
mock_result.reason = ResultReason.SynthesizingAudioCompleted
@ -32,11 +32,11 @@ async def test_azure_text_to_speech(mocker):
mocker.patch.object(S3, "cache", return_value="http://mock.s3.com/1.wav")
# Prerequisites
assert not config.IFLYTEK_APP_ID
assert not config.IFLYTEK_API_KEY
assert not config.IFLYTEK_API_SECRET
assert config.AZURE_TTS_SUBSCRIPTION_KEY and config.AZURE_TTS_SUBSCRIPTION_KEY != "YOUR_API_KEY"
assert config.AZURE_TTS_REGION
assert not config.iflytek_app_id
assert not config.iflytek_api_key
assert not config.iflytek_api_secret
assert config.azure_tts_subscription_key and config.azure_tts_subscription_key != "YOUR_API_KEY"
assert config.azure_tts_region
config.copy()
# test azure
@ -48,8 +48,8 @@ async def test_azure_text_to_speech(mocker):
async def test_iflytek_text_to_speech(mocker):
# mock
config = Config.default()
config.AZURE_TTS_SUBSCRIPTION_KEY = None
config.AZURE_TTS_REGION = None
config.azure_tts_subscription_key = None
config.azure_tts_region = None
mocker.patch.object(IFlyTekTTS, "synthesize_speech", return_value=None)
mock_data = mocker.AsyncMock()
mock_data.read.return_value = b"mock iflytek"
@ -58,11 +58,11 @@ async def test_iflytek_text_to_speech(mocker):
mocker.patch.object(S3, "cache", return_value="http://mock.s3.com/1.mp3")
# Prerequisites
assert config.IFLYTEK_APP_ID
assert config.IFLYTEK_API_KEY
assert config.IFLYTEK_API_SECRET
assert not config.AZURE_TTS_SUBSCRIPTION_KEY or config.AZURE_TTS_SUBSCRIPTION_KEY == "YOUR_API_KEY"
assert not config.AZURE_TTS_REGION
assert config.iflytek_app_id
assert config.iflytek_api_key
assert config.iflytek_api_secret
assert not config.azure_tts_subscription_key or config.azure_tts_subscription_key == "YOUR_API_KEY"
assert not config.azure_tts_region
# test azure
data = await text_to_speech("panda emoji", config=config)

2
tests/metagpt/test_incremental_dev.py
View file

@ -14,7 +14,7 @@ from typer.testing import CliRunner
from metagpt.const import TEST_DATA_PATH
from metagpt.logs import logger
from metagpt.startup import app
from metagpt.software_company import app
runner = CliRunner()

6
tests/metagpt/test_startup.py → tests/metagpt/test_software_company.py
View file

@ -3,13 +3,13 @@
"""
@Time : 2023/5/15 11:40
@Author : alexanderwu
@File : test_startup.py
@File : test_software_company.py
"""
import pytest
from typer.testing import CliRunner
from metagpt.logs import logger
from metagpt.startup import app
from metagpt.software_company import app
from metagpt.team import Team
runner = CliRunner()
@ -23,7 +23,7 @@ async def test_empty_team(new_filename):
logger.info(history)
def test_startup(new_filename):
def test_software_company(new_filename):
args = ["Make a cli snake game"]
result = runner.invoke(app, args)
logger.info(result)

6
tests/metagpt/tools/test_azure_tts.py
View file

@ -28,10 +28,10 @@ async def test_azure_tts(mocker):
mocker.patch.object(Path, "exists", return_value=True)
# Prerequisites
assert config.AZURE_TTS_SUBSCRIPTION_KEY and config.AZURE_TTS_SUBSCRIPTION_KEY != "YOUR_API_KEY"
assert config.AZURE_TTS_REGION
assert config.azure_tts_subscription_key and config.azure_tts_subscription_key != "YOUR_API_KEY"
assert config.azure_tts_region
azure_tts = AzureTTS(subscription_key=config.AZURE_TTS_SUBSCRIPTION_KEY, region=config.AZURE_TTS_REGION)
azure_tts = AzureTTS(subscription_key=config.azure_tts_subscription_key, region=config.azure_tts_region)
text = """
女儿看见父亲走了进来，问道：
<mstts:express-as role="YoungAdultFemale" style="calm">

16
tests/metagpt/tools/test_iflytek_tts.py
View file

@ -15,8 +15,8 @@ from metagpt.tools.iflytek_tts import IFlyTekTTS, oas3_iflytek_tts
async def test_iflytek_tts(mocker):
# mock
config = Config.default()
config.AZURE_TTS_SUBSCRIPTION_KEY = None
config.AZURE_TTS_REGION = None
config.azure_tts_subscription_key = None
config.azure_tts_region = None
mocker.patch.object(IFlyTekTTS, "synthesize_speech", return_value=None)
mock_data = mocker.AsyncMock()
mock_data.read.return_value = b"mock iflytek"
@ -24,15 +24,15 @@ async def test_iflytek_tts(mocker):
mock_reader.return_value.__aenter__.return_value = mock_data
# Prerequisites
assert config.IFLYTEK_APP_ID
assert config.IFLYTEK_API_KEY
assert config.IFLYTEK_API_SECRET
assert config.iflytek_app_id
assert config.iflytek_api_key
assert config.iflytek_api_secret
result = await oas3_iflytek_tts(
text="你好，hello",
app_id=config.IFLYTEK_APP_ID,
api_key=config.IFLYTEK_API_KEY,
api_secret=config.IFLYTEK_API_SECRET,
app_id=config.iflytek_app_id,
api_key=config.iflytek_api_key,
api_secret=config.iflytek_api_secret,
)
assert result

2
tests/metagpt/tools/test_metagpt_text_to_image.py
View file

@ -24,7 +24,7 @@ async def test_draw(mocker):
mock_post.return_value.__aenter__.return_value = mock_response
# Prerequisites
assert config.METAGPT_TEXT_TO_IMAGE_MODEL_URL
assert config.metagpt_tti_url
binary_data = await oas3_metagpt_text_to_image("Panda emoji")
assert binary_data

49
tests/metagpt/tools/test_ut_writer.py
View file

@ -8,6 +8,17 @@
from pathlib import Path
import pytest
from openai.resources.chat.completions import AsyncCompletions
from openai.types import CompletionUsage
from openai.types.chat.chat_completion import (
ChatCompletion,
ChatCompletionMessage,
Choice,
)
from openai.types.chat.chat_completion_message_tool_call import (
ChatCompletionMessageToolCall,
Function,
)
from metagpt.config2 import config
from metagpt.const import API_QUESTIONS_PATH, UT_PY_PATH
@ -16,7 +27,43 @@ from metagpt.tools.ut_writer import YFT_PROMPT_PREFIX, UTGenerator
class TestUTWriter:
@pytest.mark.asyncio
async def test_api_to_ut_sample(self):
async def test_api_to_ut_sample(self, mocker):
async def mock_create(*args, **kwargs):
return ChatCompletion(
id="chatcmpl-8n5fAd21w2J1IIFkI4qxWlNfM7QRC",
choices=[
Choice(
finish_reason="stop",
index=0,
logprobs=None,
message=ChatCompletionMessage(
content=None,
role="assistant",
function_call=None,
tool_calls=[
ChatCompletionMessageToolCall(
id="call_EjjmIY7GMspHu3r9mx8gPA2k",
function=Function(
arguments='{"code":"import string\\nimport random\\n\\ndef random_string'
"(length=10):\\n return ''.join(random.choice(string.ascii_"
'lowercase) for i in range(length))"}',
name="execute",
),
type="function",
)
],
),
)
],
created=1706710532,
model="gpt-3.5-turbo-1106",
object="chat.completion",
system_fingerprint="fp_04f9a1eebf",
usage=CompletionUsage(completion_tokens=35, prompt_tokens=1982, total_tokens=2017),
)
mocker.patch.object(AsyncCompletions, "create", mock_create)
# Prerequisites
swagger_file = Path(__file__).parent / "../../data/ut_writer/yft_swaggerApi.json"
assert swagger_file.exists()

26
tests/metagpt/utils/test_repair_llm_raw_output.py
View file

@ -141,6 +141,32 @@ def test_repair_json_format():
output = repair_llm_raw_output(output=raw_output, req_keys=[None], repair_type=RepairType.JSON)
assert output == target_output
raw_output = """
{
"Language": "en_us", // define language
"Programming Language": "Python" # define code language
}
"""
target_output = """{
"Language": "en_us",
"Programming Language": "Python"
}"""
output = repair_llm_raw_output(output=raw_output, req_keys=[None], repair_type=RepairType.JSON)
assert output == target_output
raw_output = """
{
"Language": "#en_us#", // define language
"Programming Language": "//Python # Code // Language//" # define code language
}
"""
target_output = """{
"Language": "#en_us#",
"Programming Language": "//Python # Code // Language//"
}"""
output = repair_llm_raw_output(output=raw_output, req_keys=[None], repair_type=RepairType.JSON)
assert output == target_output
def test_repair_invalid_json():
from metagpt.utils.repair_llm_raw_output import repair_invalid_json

7
tests/spark.yaml Normal file
View file

@ -0,0 +1,7 @@
llm:
api_type: "spark"
app_id: "xxx"
api_key: "xxx"
api_secret: "xxx"
domain: "generalv2"
base_url: "wss://spark-api.xf-yun.com/v3.1/chat"