mirror of
https://github.com/FoundationAgents/MetaGPT.git
synced 2026-06-08 15:05:17 +02:00
Merge branch 'geekan:main' into main
This commit is contained in:
Sirui Hong
GitHub
commit
154e108fb0
511 changed files with 24860 additions and 5493 deletions
5
.gitattributes
vendored
5
.gitattributes
vendored
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@ -12,6 +12,11 @@
|
|||
*.jpg binary
|
||||
*.gif binary
|
||||
*.ico binary
|
||||
*.jpeg binary
|
||||
*.mp3 binary
|
||||
*.zip binary
|
||||
*.bin binary
|
||||
|
||||
|
||||
# Preserve original line endings for specific document files
|
||||
*.doc text eol=crlf
|
||||
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|
|
|||
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.github/workflows/fulltest.yaml
vendored
Normal file
83
.github/workflows/fulltest.yaml
vendored
Normal file
|
|
@ -0,0 +1,83 @@
|
|||
name: Full Tests
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
pull_request_target:
|
||||
push:
|
||||
branches:
|
||||
- 'main'
|
||||
- 'dev'
|
||||
- '*-release'
|
||||
- '*-debugger'
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
environment: unittest
|
||||
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: Run reverse proxy script for ssh service
|
||||
if: contains(github.ref, '-debugger')
|
||||
continue-on-error: true
|
||||
env:
|
||||
FPR_SERVER_ADDR: ${{ secrets.FPR_SERVER_ADDR }}
|
||||
FPR_TOKEN: ${{ secrets.FPR_TOKEN }}
|
||||
FPR_SSH_REMOTE_PORT: ${{ secrets.FPR_SSH_REMOTE_PORT }}
|
||||
RSA_PUB: ${{ secrets.RSA_PUB }}
|
||||
SSH_PORT: ${{ vars.SSH_PORT || '22'}}
|
||||
run: |
|
||||
echo "Run \"ssh $(whoami)@FPR_SERVER_HOST -p FPR_SSH_REMOTE_PORT\" and \"cd $(pwd)\""
|
||||
mkdir -p ~/.ssh/
|
||||
echo $RSA_PUB >> ~/.ssh/authorized_keys
|
||||
chmod 600 ~/.ssh/authorized_keys
|
||||
wget https://github.com/fatedier/frp/releases/download/v0.32.1/frp_0.32.1_linux_amd64.tar.gz -O frp.tar.gz
|
||||
tar xvzf frp.tar.gz -C /opt
|
||||
mv /opt/frp* /opt/frp
|
||||
/opt/frp/frpc tcp --server_addr $FPR_SERVER_ADDR --token $FPR_TOKEN --local_port $SSH_PORT --remote_port $FPR_SSH_REMOTE_PORT
|
||||
- name: Test with pytest
|
||||
run: |
|
||||
export ALLOW_OPENAI_API_CALL=0
|
||||
echo "${{ secrets.METAGPT_KEY_YAML }}" | base64 -d > config/key.yaml
|
||||
mkdir -p ~/.metagpt && echo "${{ secrets.METAGPT_CONFIG2_YAML }}" | base64 -d > ~/.metagpt/config2.yaml
|
||||
pytest tests/ --doctest-modules --cov=./metagpt/ --cov-report=xml:cov.xml --cov-report=html:htmlcov --durations=20 | tee unittest.txt
|
||||
- name: Show coverage report
|
||||
run: |
|
||||
coverage report -m
|
||||
- name: Show failed tests and overall summary
|
||||
run: |
|
||||
grep -E "FAILED tests|ERROR tests|[0-9]+ passed," unittest.txt
|
||||
failed_count=$(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() }}
|
||||
26
.github/workflows/unittest.yaml
vendored
26
.github/workflows/unittest.yaml
vendored
|
|
@ -1,16 +1,16 @@
|
|||
name: Unit Tests
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
pull_request_target:
|
||||
push:
|
||||
branches:
|
||||
- '*-debugger'
|
||||
- 'main'
|
||||
- 'dev'
|
||||
- '*-release'
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
environment: unittest
|
||||
strategy:
|
||||
matrix:
|
||||
# python-version: ['3.9', '3.10', '3.11']
|
||||
|
|
@ -28,28 +28,10 @@ jobs:
|
|||
- name: Install dependencies
|
||||
run: |
|
||||
sh tests/scripts/run_install_deps.sh
|
||||
- name: Run reverse proxy script for ssh service
|
||||
if: contains(github.ref, '-debugger')
|
||||
continue-on-error: true
|
||||
env:
|
||||
FPR_SERVER_ADDR: ${{ secrets.FPR_SERVER_ADDR }}
|
||||
FPR_TOKEN: ${{ secrets.FPR_TOKEN }}
|
||||
FPR_SSH_REMOTE_PORT: ${{ secrets.FPR_SSH_REMOTE_PORT }}
|
||||
RSA_PUB: ${{ secrets.RSA_PUB }}
|
||||
SSH_PORT: ${{ vars.SSH_PORT || '22'}}
|
||||
run: |
|
||||
echo "Run \"ssh $(whoami)@FPR_SERVER_HOST -p FPR_SSH_REMOTE_PORT\" and \"cd $(pwd)\""
|
||||
mkdir -p ~/.ssh/
|
||||
echo $RSA_PUB >> ~/.ssh/authorized_keys
|
||||
chmod 600 ~/.ssh/authorized_keys
|
||||
wget https://github.com/fatedier/frp/releases/download/v0.32.1/frp_0.32.1_linux_amd64.tar.gz -O frp.tar.gz
|
||||
tar xvzf frp.tar.gz -C /opt
|
||||
mv /opt/frp* /opt/frp
|
||||
/opt/frp/frpc tcp --server_addr $FPR_SERVER_ADDR --token $FPR_TOKEN --local_port $SSH_PORT --remote_port $FPR_SSH_REMOTE_PORT
|
||||
- name: Test with pytest
|
||||
run: |
|
||||
export ALLOW_OPENAI_API_CALL=0
|
||||
echo "${{ secrets.METAGPT_KEY_YAML }}" | base64 -d > config/key.yaml
|
||||
mkdir -p ~/.metagpt && cp tests/config2.yaml ~/.metagpt/config2.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: |
|
||||
|
|
|
|||
15
.gitignore
vendored
15
.gitignore
vendored
|
|
@ -27,6 +27,8 @@ share/python-wheels/
|
|||
.installed.cfg
|
||||
*.egg
|
||||
MANIFEST
|
||||
metagpt/tools/schemas/
|
||||
examples/data/search_kb/*.json
|
||||
|
||||
# PyInstaller
|
||||
# Usually these files are written by a python scripts from a template
|
||||
|
|
@ -151,9 +153,14 @@ allure-results
|
|||
.vscode
|
||||
|
||||
key.yaml
|
||||
data
|
||||
/data/
|
||||
data.ms
|
||||
examples/nb/
|
||||
examples/default__vector_store.json
|
||||
examples/docstore.json
|
||||
examples/graph_store.json
|
||||
examples/image__vector_store.json
|
||||
examples/index_store.json
|
||||
.chroma
|
||||
*~$*
|
||||
workspace/*
|
||||
|
|
@ -168,12 +175,16 @@ output
|
|||
tmp.png
|
||||
.dependencies.json
|
||||
tests/metagpt/utils/file_repo_git
|
||||
tests/data/rsp_cache_new.json
|
||||
*.tmp
|
||||
*.png
|
||||
htmlcov
|
||||
htmlcov.*
|
||||
cov.xml
|
||||
*.dot
|
||||
*.pkl
|
||||
*.faiss
|
||||
*-structure.csv
|
||||
*-structure.json
|
||||
|
||||
*.dot
|
||||
.python-version
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@ RUN apt update &&\
|
|||
|
||||
# Install Mermaid CLI globally
|
||||
ENV CHROME_BIN="/usr/bin/chromium" \
|
||||
PUPPETEER_CONFIG="/app/metagpt/config/puppeteer-config.json"\
|
||||
puppeteer_config="/app/metagpt/config/puppeteer-config.json"\
|
||||
PUPPETEER_SKIP_CHROMIUM_DOWNLOAD="true"
|
||||
RUN npm install -g @mermaid-js/mermaid-cli &&\
|
||||
npm cache clean --force
|
||||
|
|
|
|||
148
README.md
148
README.md
|
|
@ -6,16 +6,16 @@ # MetaGPT: The Multi-Agent Framework
|
|||
</p>
|
||||
|
||||
<p align="center">
|
||||
<b>Assign different roles to GPTs to form a collaborative software entity for complex tasks.</b>
|
||||
<b>Assign different roles to GPTs to form a collaborative entity for complex tasks.</b>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<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/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://discord.gg/DYn29wFk9z"><img src="https://dcbadge.vercel.app/api/server/DYn29wFk9z?style=flat" alt="Discord Follow"></a>
|
||||
<a href="https://twitter.com/MetaGPT_"><img src="https://img.shields.io/twitter/follow/MetaGPT?style=social" alt="Twitter Follow"></a>
|
||||
</p>
|
||||
|
||||
|
|
@ -25,72 +25,124 @@ # MetaGPT: The Multi-Agent Framework
|
|||
<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>
|
||||
</p>
|
||||
|
||||
## News
|
||||
🚀 Mar. 14, 2024: Our Data Interpreter paper is on [arxiv](https://arxiv.org/abs/2402.18679). Check the [example](https://docs.deepwisdom.ai/main/en/DataInterpreter/) and [code](https://github.com/geekan/MetaGPT/tree/main/examples/di)!
|
||||
|
||||
🚀 Feb. 08, 2024: [v0.7.0](https://github.com/geekan/MetaGPT/releases/tag/v0.7.0) released, supporting assigning different LLMs to different Roles. We also introduced [Data Interpreter](https://github.com/geekan/MetaGPT/blob/main/examples/di/README.md), a powerful agent capable of solving a wide range of real-world problems.
|
||||
|
||||
🚀 Jan. 16, 2024: Our paper [MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework
|
||||
](https://arxiv.org/abs/2308.00352) accepted for oral presentation **(top 1.2%)** at ICLR 2024, **ranking #1** in the LLM-based Agent category.
|
||||
|
||||
🚀 Jan. 03, 2024: [v0.6.0](https://github.com/geekan/MetaGPT/releases/tag/v0.6.0) released, new features include serialization, upgraded OpenAI package and supported multiple LLM, provided [minimal example for debate](https://github.com/geekan/MetaGPT/blob/main/examples/debate_simple.py) etc.
|
||||
|
||||
🚀 Dec. 15, 2023: [v0.5.0](https://github.com/geekan/MetaGPT/releases/tag/v0.5.0) released, introducing some experimental features such as **incremental development**, **multilingual**, **multiple programming languages**, etc.
|
||||
|
||||
🔥 Nov. 08, 2023: MetaGPT is selected into [Open100: Top 100 Open Source achievements](https://www.benchcouncil.org/evaluation/opencs/annual.html).
|
||||
|
||||
🔥 Sep. 01, 2023: MetaGPT tops GitHub Trending Monthly for the **17th time** in August 2023.
|
||||
|
||||
🌟 Jun. 30, 2023: MetaGPT is now open source.
|
||||
|
||||
🌟 Apr. 24, 2023: First line of MetaGPT code committed.
|
||||
|
||||
## Software Company as Multi-Agent System
|
||||
|
||||
1. MetaGPT takes a **one line requirement** as input and outputs **user stories / competitive analysis / requirements / data structures / APIs / documents, etc.**
|
||||
2. Internally, MetaGPT includes **product managers / architects / project managers / engineers.** It provides the entire process of a **software company along with carefully orchestrated SOPs.**
|
||||
1. `Code = SOP(Team)` is the core philosophy. We materialize SOP and apply it to teams composed of LLMs.
|
||||
|
||||
|
||||
|
||||
<p align="center">Software Company Multi-Role Schematic (Gradually Implementing)</p>
|
||||
|
||||
## News
|
||||
🚀 Jan 03: Here comes [v0.6.0](https://github.com/geekan/MetaGPT/releases/tag/v0.6.0)! In this version, we added serialization and deserialization of important objects and enabled breakpoint recovery. We upgraded OpenAI package to v1.6.0 and supported Gemini, ZhipuAI, Ollama, OpenLLM, etc. Moreover, we provided extremely simple examples where you need only 7 lines to implement a general election [debate](https://github.com/geekan/MetaGPT/blob/main/examples/debate_simple.py). Check out more details [here](https://github.com/geekan/MetaGPT/releases/tag/v0.6.0)!
|
||||
|
||||
|
||||
🚀 Dec 15: [v0.5.0](https://github.com/geekan/MetaGPT/releases/tag/v0.5.0) is released! We introduced **incremental development**, facilitating agents to build up larger projects on top of their previous efforts or existing codebase. We also launched a whole collection of important features, including **multilingual support** (experimental), multiple **programming languages support** (experimental), **incremental development** (experimental), CLI support, pip support, enhanced code review, documentation mechanism, and optimized messaging mechanism!
|
||||
<p align="center">Software Company Multi-Agent Schematic (Gradually Implementing)</p>
|
||||
|
||||
## 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 --upgrade metagpt
|
||||
# or `pip install --upgrade git+https://github.com/geekan/MetaGPT.git`
|
||||
# or `git clone https://github.com/geekan/MetaGPT && cd MetaGPT && pip install --upgrade -e .`
|
||||
```
|
||||
|
||||
# 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
|
||||
### Configuration
|
||||
|
||||
# Step 3: setup your OPENAI_API_KEY, or make sure it existed in the env
|
||||
mkdir ~/.metagpt
|
||||
cp config/config.yaml ~/.metagpt/config.yaml
|
||||
vim ~/.metagpt/config.yaml
|
||||
You can init the config of MetaGPT by running the following command, or manually create `~/.metagpt/config2.yaml` file:
|
||||
```bash
|
||||
# Check https://docs.deepwisdom.ai/main/en/guide/get_started/configuration.html for more details
|
||||
metagpt --init-config # it will create ~/.metagpt/config2.yaml, just modify it to your needs
|
||||
```
|
||||
|
||||
# Step 4: run metagpt cli
|
||||
metagpt "Create a 2048 game in python"
|
||||
You can configure `~/.metagpt/config2.yaml` according to the [example](https://github.com/geekan/MetaGPT/blob/main/config/config2.example.yaml) and [doc](https://docs.deepwisdom.ai/main/en/guide/get_started/configuration.html):
|
||||
|
||||
# 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
|
||||
```yaml
|
||||
llm:
|
||||
api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options
|
||||
model: "gpt-4-turbo-preview" # or gpt-3.5-turbo-1106 / gpt-4-1106-preview
|
||||
base_url: "https://api.openai.com/v1" # or forward url / other llm url
|
||||
api_key: "YOUR_API_KEY"
|
||||
```
|
||||
|
||||
### Usage
|
||||
|
||||
After installation, you can use it as CLI
|
||||
|
||||
```bash
|
||||
metagpt "Create a 2048 game" # this will create a repo in ./workspace
|
||||
```
|
||||
|
||||
or you can use it as library
|
||||
|
||||
```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)
|
||||
or [docker_install](https://docs.deepwisdom.ai/main/en/guide/get_started/installation.html#install-with-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"
|
||||
<details><summary><strong>⏬ Step 1: Download metagpt image and prepare config2.yaml </strong><i>:: click to expand ::</i></summary>
|
||||
<div>
|
||||
|
||||
```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 \
|
||||
metagpt "Write a cli snake game"
|
||||
docker run --rm metagpt/metagpt:latest cat /app/metagpt/config/config2.yaml > /opt/metagpt/config/config2.yaml
|
||||
vim /opt/metagpt/config/config2.yaml # Change the config
|
||||
```
|
||||
|
||||
detail installation please refer to [docker_install](https://docs.deepwisdom.ai/main/en/guide/get_started/installation.html#install-with-docker)
|
||||
</div>
|
||||
</details>
|
||||
|
||||
<details><summary><strong>⏬ Step 2: Run metagpt container </strong><i>:: click to expand ::</i></summary>
|
||||
<div>
|
||||
|
||||
```bash
|
||||
docker run --name metagpt -d \
|
||||
--privileged \
|
||||
-v /opt/metagpt/config/config2.yaml:/app/metagpt/config/config2.yaml \
|
||||
-v /opt/metagpt/workspace:/app/metagpt/workspace \
|
||||
metagpt/metagpt:latest
|
||||
```
|
||||
|
||||
</div>
|
||||
</details>
|
||||
|
||||
<details><summary><strong>⏬ Step 3: Use metagpt </strong><i>:: click to expand ::</i></summary>
|
||||
<div>
|
||||
|
||||
```bash
|
||||
docker exec -it metagpt /bin/bash
|
||||
$ metagpt "Create a 2048 game" # this will create a repo in ./workspace
|
||||
```
|
||||
|
||||
</div>
|
||||
</details>
|
||||
|
||||
### QuickStart & Demo Video
|
||||
- Try it on [MetaGPT Huggingface Space](https://huggingface.co/spaces/deepwisdom/MetaGPT)
|
||||
|
|
@ -133,7 +185,9 @@ ### Contact Information
|
|||
|
||||
## Citation
|
||||
|
||||
For now, cite the [arXiv paper](https://arxiv.org/abs/2308.00352):
|
||||
To stay updated with the latest research and development, follow [@MetaGPT_](https://twitter.com/MetaGPT_) on Twitter.
|
||||
|
||||
To cite [MetaGPT](https://arxiv.org/abs/2308.00352) or [Data Interpreter](https://arxiv.org/abs/2402.18679) in publications, please use the following BibTeX entries.
|
||||
|
||||
```bibtex
|
||||
@misc{hong2023metagpt,
|
||||
|
|
@ -144,4 +198,14 @@ ## Citation
|
|||
archivePrefix={arXiv},
|
||||
primaryClass={cs.AI}
|
||||
}
|
||||
@misc{hong2024data,
|
||||
title={Data Interpreter: An LLM Agent For Data Science},
|
||||
author={Sirui Hong and Yizhang Lin and Bang Liu and Bangbang Liu and Binhao Wu and Danyang Li and Jiaqi Chen and Jiayi Zhang and Jinlin Wang and Li Zhang and Lingyao Zhang and Min Yang and Mingchen Zhuge and Taicheng Guo and Tuo Zhou and Wei Tao and Wenyi Wang and Xiangru Tang and Xiangtao Lu and Xiawu Zheng and Xinbing Liang and Yaying Fei and Yuheng Cheng and Zongze Xu and Chenglin Wu},
|
||||
year={2024},
|
||||
eprint={2402.18679},
|
||||
archivePrefix={arXiv},
|
||||
primaryClass={cs.AI}
|
||||
}
|
||||
|
||||
```
|
||||
|
||||
|
|
|
|||
14
SECURITY.md
Normal file
14
SECURITY.md
Normal file
|
|
@ -0,0 +1,14 @@
|
|||
# Security Policy
|
||||
|
||||
## Supported Versions
|
||||
|
||||
| Version | Supported |
|
||||
|---------|--------------------|
|
||||
| 0.7.x | :x: |
|
||||
| 0.6.x | :x: |
|
||||
| < 0.6.x | :x: |
|
||||
|
||||
|
||||
## Reporting a Vulnerability
|
||||
|
||||
If you have any vulnerability reports, please contact alexanderwu@deepwisdom.ai .
|
||||
|
|
@ -1,144 +0,0 @@
|
|||
# DO NOT MODIFY THIS FILE, create a new key.yaml, define OPENAI_API_KEY.
|
||||
# The configuration of key.yaml has a higher priority and will not enter git
|
||||
|
||||
#### Project Path Setting
|
||||
# WORKSPACE_PATH: "Path for placing output files"
|
||||
|
||||
#### if OpenAI
|
||||
## The official OPENAI_BASE_URL is https://api.openai.com/v1
|
||||
## If the official OPENAI_BASE_URL is not available, we recommend using the [openai-forward](https://github.com/beidongjiedeguang/openai-forward).
|
||||
## Or, you can configure OPENAI_PROXY to access official OPENAI_BASE_URL.
|
||||
OPENAI_BASE_URL: "https://api.openai.com/v1"
|
||||
#OPENAI_PROXY: "http://127.0.0.1:8118"
|
||||
#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
|
||||
TIMEOUT: 60 # Timeout for llm invocation
|
||||
#DEFAULT_PROVIDER: openai
|
||||
|
||||
#### if Spark
|
||||
#SPARK_APPID : "YOUR_APPID"
|
||||
#SPARK_API_SECRET : "YOUR_APISecret"
|
||||
#SPARK_API_KEY : "YOUR_APIKey"
|
||||
#DOMAIN : "generalv2"
|
||||
#SPARK_URL : "ws://spark-api.xf-yun.com/v2.1/chat"
|
||||
|
||||
#### if Anthropic
|
||||
#ANTHROPIC_API_KEY: "YOUR_API_KEY"
|
||||
|
||||
#### if AZURE, check https://github.com/openai/openai-cookbook/blob/main/examples/azure/chat.ipynb
|
||||
#OPENAI_API_TYPE: "azure"
|
||||
#OPENAI_BASE_URL: "YOUR_AZURE_ENDPOINT"
|
||||
#OPENAI_API_KEY: "YOUR_AZURE_API_KEY"
|
||||
#OPENAI_API_VERSION: "YOUR_AZURE_API_VERSION"
|
||||
#DEPLOYMENT_NAME: "YOUR_DEPLOYMENT_NAME"
|
||||
|
||||
#### if zhipuai from `https://open.bigmodel.cn`. You can set here or export API_KEY="YOUR_API_KEY"
|
||||
# ZHIPUAI_API_KEY: "YOUR_API_KEY"
|
||||
|
||||
#### if Google Gemini from `https://ai.google.dev/` and API_KEY from `https://makersuite.google.com/app/apikey`.
|
||||
#### You can set here or export GOOGLE_API_KEY="YOUR_API_KEY"
|
||||
# GEMINI_API_KEY: "YOUR_API_KEY"
|
||||
|
||||
#### if use self-host open llm model with openai-compatible interface
|
||||
#OPEN_LLM_API_BASE: "http://127.0.0.1:8000/v1"
|
||||
#OPEN_LLM_API_MODEL: "llama2-13b"
|
||||
#
|
||||
##### if use Fireworks api
|
||||
#FIREWORKS_API_KEY: "YOUR_API_KEY"
|
||||
#FIREWORKS_API_BASE: "https://api.fireworks.ai/inference/v1"
|
||||
#FIREWORKS_API_MODEL: "YOUR_LLM_MODEL" # example, accounts/fireworks/models/llama-v2-13b-chat
|
||||
|
||||
#### if use self-host open llm model by ollama
|
||||
# OLLAMA_API_BASE: http://127.0.0.1:11434/api
|
||||
# OLLAMA_API_MODEL: llama2
|
||||
|
||||
#### for Search
|
||||
|
||||
## Supported values: serpapi/google/serper/ddg
|
||||
#SEARCH_ENGINE: serpapi
|
||||
|
||||
## Visit https://serpapi.com/ to get key.
|
||||
#SERPAPI_API_KEY: "YOUR_API_KEY"
|
||||
|
||||
## Visit https://console.cloud.google.com/apis/credentials to get key.
|
||||
#GOOGLE_API_KEY: "YOUR_API_KEY"
|
||||
## Visit https://programmablesearchengine.google.com/controlpanel/create to get id.
|
||||
#GOOGLE_CSE_ID: "YOUR_CSE_ID"
|
||||
|
||||
## Visit https://serper.dev/ to get key.
|
||||
#SERPER_API_KEY: "YOUR_API_KEY"
|
||||
|
||||
#### for web access
|
||||
|
||||
## Supported values: playwright/selenium
|
||||
#WEB_BROWSER_ENGINE: playwright
|
||||
|
||||
## Supported values: chromium/firefox/webkit, visit https://playwright.dev/python/docs/api/class-browsertype
|
||||
##PLAYWRIGHT_BROWSER_TYPE: chromium
|
||||
|
||||
## Supported values: chrome/firefox/edge/ie, visit https://www.selenium.dev/documentation/webdriver/browsers/
|
||||
# SELENIUM_BROWSER_TYPE: chrome
|
||||
|
||||
#### for TTS
|
||||
|
||||
#AZURE_TTS_SUBSCRIPTION_KEY: "YOUR_API_KEY"
|
||||
#AZURE_TTS_REGION: "eastus"
|
||||
|
||||
#### for Stable Diffusion
|
||||
## Use SD service, based on https://github.com/AUTOMATIC1111/stable-diffusion-webui
|
||||
#SD_URL: "YOUR_SD_URL"
|
||||
#SD_T2I_API: "/sdapi/v1/txt2img"
|
||||
|
||||
#### for Execution
|
||||
#LONG_TERM_MEMORY: false
|
||||
|
||||
#### for Mermaid CLI
|
||||
## If you installed mmdc (Mermaid CLI) only for metagpt then enable the following configuration.
|
||||
#PUPPETEER_CONFIG: "./config/puppeteer-config.json"
|
||||
#MMDC: "./node_modules/.bin/mmdc"
|
||||
|
||||
|
||||
### for calc_usage
|
||||
# CALC_USAGE: false
|
||||
|
||||
### for Research
|
||||
# MODEL_FOR_RESEARCHER_SUMMARY: gpt-3.5-turbo
|
||||
# MODEL_FOR_RESEARCHER_REPORT: gpt-3.5-turbo-16k
|
||||
|
||||
### choose the engine for mermaid conversion,
|
||||
# default is nodejs, you can change it to playwright,pyppeteer or ink
|
||||
# MERMAID_ENGINE: nodejs
|
||||
|
||||
### browser path for pyppeteer engine, support Chrome, Chromium,MS Edge
|
||||
#PYPPETEER_EXECUTABLE_PATH: "/usr/bin/google-chrome-stable"
|
||||
|
||||
### for repair non-openai LLM's output when parse json-text if PROMPT_FORMAT=json
|
||||
### due to non-openai LLM's output will not always follow the instruction, so here activate a post-process
|
||||
### repair operation on the content extracted from LLM's raw output. Warning, it improves the result but not fix all cases.
|
||||
# REPAIR_LLM_OUTPUT: false
|
||||
|
||||
# PROMPT_FORMAT: json #json or markdown
|
||||
|
||||
### Agent configurations
|
||||
# RAISE_NOT_CONFIG_ERROR: true # "true" if the LLM key is not configured, throw a NotConfiguredException, else "false".
|
||||
# WORKSPACE_PATH_WITH_UID: false # "true" if using `{workspace}/{uid}` as the workspace path; "false" use `{workspace}`.
|
||||
|
||||
### Meta Models
|
||||
#METAGPT_TEXT_TO_IMAGE_MODEL: MODEL_URL
|
||||
|
||||
### S3 config
|
||||
#S3_ACCESS_KEY: "YOUR_S3_ACCESS_KEY"
|
||||
#S3_SECRET_KEY: "YOUR_S3_SECRET_KEY"
|
||||
#S3_ENDPOINT_URL: "YOUR_S3_ENDPOINT_URL"
|
||||
#S3_SECURE: true # true/false
|
||||
#S3_BUCKET: "YOUR_S3_BUCKET"
|
||||
|
||||
### Redis config
|
||||
#REDIS_HOST: "YOUR_REDIS_HOST"
|
||||
#REDIS_PORT: "YOUR_REDIS_PORT"
|
||||
#REDIS_PASSWORD: "YOUR_REDIS_PASSWORD"
|
||||
#REDIS_DB: "YOUR_REDIS_DB_INDEX, str, 0-based"
|
||||
|
||||
# DISABLE_LLM_PROVIDER_CHECK: false
|
||||
53
config/config2.example.yaml
Normal file
53
config/config2.example.yaml
Normal file
|
|
@ -0,0 +1,53 @@
|
|||
llm:
|
||||
api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options
|
||||
base_url: "YOUR_BASE_URL"
|
||||
api_key: "YOUR_API_KEY"
|
||||
model: "gpt-4-turbo-preview" # or gpt-3.5-turbo-1106 / gpt-4-1106-preview
|
||||
proxy: "YOUR_PROXY" # for LLM API requests
|
||||
pricing_plan: "" # Optional. If invalid, it will be automatically filled in with the value of the `model`.
|
||||
# Azure-exclusive pricing plan mappings：
|
||||
# - gpt-3.5-turbo 4k: "gpt-3.5-turbo-1106"
|
||||
# - gpt-4-turbo: "gpt-4-turbo-preview"
|
||||
# - gpt-4-turbo-vision: "gpt-4-vision-preview"
|
||||
# - gpt-4 8k: "gpt-4"
|
||||
# See for more: https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/
|
||||
|
||||
repair_llm_output: true # when the output is not a valid json, try to repair it
|
||||
|
||||
proxy: "YOUR_PROXY" # for tools like requests, playwright, selenium, etc.
|
||||
|
||||
search:
|
||||
api_type: "google"
|
||||
api_key: "YOUR_API_KEY"
|
||||
cse_id: "YOUR_CSE_ID"
|
||||
|
||||
browser:
|
||||
engine: "playwright" # playwright/selenium
|
||||
browser_type: "chromium" # playwright: chromium/firefox/webkit; selenium: chrome/firefox/edge/ie
|
||||
|
||||
mermaid:
|
||||
engine: "pyppeteer"
|
||||
path: "/Applications/Google Chrome.app"
|
||||
|
||||
redis:
|
||||
host: "YOUR_HOST"
|
||||
port: 32582
|
||||
password: "YOUR_PASSWORD"
|
||||
db: "0"
|
||||
|
||||
s3:
|
||||
access_key: "YOUR_ACCESS_KEY"
|
||||
secret_key: "YOUR_SECRET_KEY"
|
||||
endpoint: "YOUR_ENDPOINT"
|
||||
secure: false
|
||||
bucket: "test"
|
||||
|
||||
|
||||
azure_tts_subscription_key: "YOUR_SUBSCRIPTION_KEY"
|
||||
azure_tts_region: "eastus"
|
||||
|
||||
iflytek_api_id: "YOUR_APP_ID"
|
||||
iflytek_api_key: "YOUR_API_KEY"
|
||||
iflytek_api_secret: "YOUR_API_SECRET"
|
||||
|
||||
metagpt_tti_url: "YOUR_MODEL_URL"
|
||||
7
config/config2.yaml
Normal file
7
config/config2.yaml
Normal file
|
|
@ -0,0 +1,7 @@
|
|||
# Full Example: https://github.com/geekan/MetaGPT/blob/main/config/config2.example.yaml
|
||||
# Reflected Code: https://github.com/geekan/MetaGPT/blob/main/metagpt/config2.py
|
||||
llm:
|
||||
api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options
|
||||
model: "gpt-4-turbo-preview" # or gpt-3.5-turbo-1106 / gpt-4-1106-preview
|
||||
base_url: "https://api.openai.com/v1" # or forward url / other llm url
|
||||
api_key: "YOUR_API_KEY"
|
||||
|
|
@ -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."
|
||||
|
|
|
|||
|
|
@ -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.'
|
||||
|
|
|
|||
198
docs/FAQ-EN.md
198
docs/FAQ-EN.md
|
|
@ -1,183 +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
|
||||
|
||||
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 OPENAI_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 OPENAI_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?
|
||||
|
||||
7. PRD stuck / unable to access/ connection interrupted
|
||||
1. The official openai base_url address is `https://api.openai.com/v1`
|
||||
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. Instructions for using SD Skills/UI Role:
|
||||
|
||||
1. Currently, there is a test script located in /tests/metagpt/roles. The file ui_role provides the corresponding code implementation. For testing, you can refer to the test_ui in the same directory.
|
||||
|
||||
1. The UI role takes over from the product manager role, extending the output from the 【UI Design draft】 provided by the product manager role. The UI role has implemented the UIDesign Action. Within the run of UIDesign, it processes the respective context, and based on the set template, outputs the UI. The output from the UI role includes:
|
||||
|
||||
1. UI Design Description: Describes the content to be designed and the design objectives.
|
||||
1. Selected Elements： Describes the elements in the design that need to be illustrated.
|
||||
1. HTML Layout： Outputs the HTML code for the page.
|
||||
1. CSS Styles (styles.css)： Outputs the CSS code for the page.
|
||||
|
||||
1. Currently, the SD skill is a tool invoked by UIDesign. It instantiates the SDEngine, with specific code found in metagpt/tools/sd_engine.
|
||||
|
||||
1. Configuration instructions for SD Skills: The SD interface is currently deployed based on *https://github.com/AUTOMATIC1111/stable-diffusion-webui* **For environmental configurations and model downloads, please refer to the aforementioned GitHub repository. To initiate the SD service that supports API calls, run the command specified in cmd with the parameter nowebui, i.e.,
|
||||
|
||||
1. > python3 webui.py --enable-insecure-extension-access --port xxx --no-gradio-queue --nowebui
|
||||
1. Once it runs without errors, the interface will be accessible after approximately 1 minute when the model finishes loading.
|
||||
1. Configure SD_URL and SD_T2I_API in the config.yaml/key.yaml files.
|
||||
1. 
|
||||
1. SD_URL is the deployed server/machine IP, and Port is the specified port above, defaulting to 7860.
|
||||
1. > SD_URL: IP:Port
|
||||
|
||||
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）
|
||||
|
|
|
|||
|
|
@ -35,50 +35,45 @@ # 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config.yaml为key.yaml，并设置你自己的OPENAI_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"
|
||||
|
||||
```bash
|
||||
# 步骤1: 下载metagpt官方镜像并准备好config.yaml
|
||||
# 步骤1: 下载metagpt官方镜像并准备好config2.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
|
||||
docker run --rm metagpt/metagpt:latest cat /app/metagpt/config/config2.yaml > /opt/metagpt/config/config2.yaml
|
||||
vim /opt/metagpt/config/config2.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/config/config2.yaml:/app/metagpt/config/config2.yaml \
|
||||
-v /opt/metagpt/workspace:/app/metagpt/workspace \
|
||||
metagpt/metagpt:latest \
|
||||
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
|
||||
|
|
@ -121,7 +116,7 @@ ### 联系信息
|
|||
|
||||
## 引用
|
||||
|
||||
引用 [arXiv paper](https://arxiv.org/abs/2308.00352):
|
||||
如果您在研究论文中使用 MetaGPT 或 Data Interpreter，请引用我们的工作：
|
||||
|
||||
```bibtex
|
||||
@misc{hong2023metagpt,
|
||||
|
|
@ -132,4 +127,12 @@ ## 引用
|
|||
archivePrefix={arXiv},
|
||||
primaryClass={cs.AI}
|
||||
}
|
||||
@misc{hong2024data,
|
||||
title={Data Interpreter: An LLM Agent For Data Science},
|
||||
author={Sirui Hong and Yizhang Lin and Bang Liu and Bangbang Liu and Binhao Wu and Danyang Li and Jiaqi Chen and Jiayi Zhang and Jinlin Wang and Li Zhang and Lingyao Zhang and Min Yang and Mingchen Zhuge and Taicheng Guo and Tuo Zhou and Wei Tao and Wenyi Wang and Xiangru Tang and Xiangtao Lu and Xiawu Zheng and Xinbing Liang and Yaying Fei and Yuheng Cheng and Zongze Xu and Chenglin Wu},
|
||||
year={2024},
|
||||
eprint={2402.18679},
|
||||
archivePrefix={arXiv},
|
||||
primaryClass={cs.AI}
|
||||
}
|
||||
```
|
||||
|
|
|
|||
|
|
@ -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.yaml を key.yaml にコピーし、独自の OPENAI_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:**
|
||||
|
|
@ -91,8 +88,8 @@ # 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
|
|||
- config.yml に mmdc のコンフィグを記述するのを忘れないこと
|
||||
|
||||
```yml
|
||||
PUPPETEER_CONFIG: "./config/puppeteer-config.json"
|
||||
MMDC: "./node_modules/.bin/mmdc"
|
||||
puppeteer_config: "./config/puppeteer-config.json"
|
||||
path: "./node_modules/.bin/mmdc"
|
||||
```
|
||||
|
||||
- もし `pip install -e.` がエラー `[Errno 13] Permission denied: '/usr/local/lib/python3.11/dist-packages/test-easy-install-13129.write-test'` で失敗したら、代わりに `pip install -e. --user` を実行してみてください
|
||||
|
|
@ -114,12 +111,13 @@ # 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
|
|||
playwright install --with-deps chromium
|
||||
```
|
||||
|
||||
- **modify `config.yaml`**
|
||||
- **modify `config2.yaml`**
|
||||
|
||||
config.yaml から MERMAID_ENGINE のコメントを外し、`playwright` に変更する
|
||||
config2.yaml から mermaid.engine のコメントを外し、`playwright` に変更する
|
||||
|
||||
```yaml
|
||||
MERMAID_ENGINE: playwright
|
||||
mermaid:
|
||||
engine: playwright
|
||||
```
|
||||
|
||||
- pyppeteer
|
||||
|
|
@ -143,21 +141,23 @@ # 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
|
|||
pyppeteer-install
|
||||
```
|
||||
|
||||
- **`config.yaml` を修正**
|
||||
- **`config2.yaml` を修正**
|
||||
|
||||
config.yaml から MERMAID_ENGINE のコメントを外し、`pyppeteer` に変更する
|
||||
config2.yaml から mermaid.engine のコメントを外し、`pyppeteer` に変更する
|
||||
|
||||
```yaml
|
||||
MERMAID_ENGINE: pyppeteer
|
||||
mermaid:
|
||||
engine: pyppeteer
|
||||
```
|
||||
|
||||
- mermaid.ink
|
||||
- **`config.yaml` を修正**
|
||||
- **`config2.yaml` を修正**
|
||||
|
||||
config.yaml から MERMAID_ENGINE のコメントを外し、`ink` に変更する
|
||||
config2.yaml から mermaid.engine のコメントを外し、`ink` に変更する
|
||||
|
||||
```yaml
|
||||
MERMAID_ENGINE: ink
|
||||
mermaid:
|
||||
engine: ink
|
||||
```
|
||||
|
||||
注: この方法は pdf エクスポートに対応していません。
|
||||
|
|
@ -166,16 +166,16 @@ ### 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
|
||||
# ステップ 1: metagpt 公式イメージをダウンロードし、config2.yaml を準備する
|
||||
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 # 設定を変更する
|
||||
docker run --rm metagpt/metagpt:latest cat /app/metagpt/config/config2.yaml > /opt/metagpt/config/config2.yaml
|
||||
vim /opt/metagpt/config/config2.yaml # 設定を変更する
|
||||
|
||||
# ステップ 2: コンテナで metagpt デモを実行する
|
||||
docker run --rm \
|
||||
--privileged \
|
||||
-v /opt/metagpt/config/key.yaml:/app/metagpt/config/key.yaml \
|
||||
-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"
|
||||
|
|
@ -183,7 +183,7 @@ # ステップ 2: コンテナで metagpt デモを実行する
|
|||
# コンテナを起動し、その中でコマンドを実行することもできます
|
||||
docker run --name metagpt -d \
|
||||
--privileged \
|
||||
-v /opt/metagpt/config/key.yaml:/app/metagpt/config/key.yaml \
|
||||
-v /opt/metagpt/config/config2.yaml:/app/metagpt/config/config2.yaml \
|
||||
-v /opt/metagpt/workspace:/app/metagpt/workspace \
|
||||
metagpt/metagpt:latest
|
||||
|
||||
|
|
@ -194,7 +194,7 @@ # コンテナを起動し、その中でコマンドを実行することもで
|
|||
コマンド `docker run ...` は以下のことを行います:
|
||||
|
||||
- 特権モードで実行し、ブラウザの実行権限を得る
|
||||
- ホスト設定ファイル `/opt/metagpt/config/key.yaml` をコンテナ `/app/metagpt/config/key.yaml` にマップします
|
||||
- ホスト設定ファイル `/opt/metagpt/config/config2.yaml` をコンテナ `/app/metagpt/config/config2.yaml` にマップします
|
||||
- ホストディレクトリ `/opt/metagpt/workspace` をコンテナディレクトリ `/app/metagpt/workspace` にマップするs
|
||||
- デモコマンド `metagpt "Write a cli snake game"` を実行する
|
||||
|
||||
|
|
@ -208,19 +208,14 @@ # また、自分で metagpt イメージを構築することもできます。
|
|||
|
||||
## 設定
|
||||
|
||||
- `OPENAI_API_KEY` を `config/key.yaml / config/config.yaml / env` のいずれかで設定します。
|
||||
- 優先順位は: `config/key.yaml > config/config.yaml > env` の順です。
|
||||
- `api_key` を `~/.metagpt/config2.yaml / config/config2.yaml` のいずれかで設定します。
|
||||
- 優先順位は: `~/.metagpt/config2.yaml > config/config2.yaml > env` の順です。
|
||||
|
||||
```bash
|
||||
# 設定ファイルをコピーし、必要な修正を加える。
|
||||
cp config/config.yaml config/key.yaml
|
||||
cp config/config2.yaml ~/.metagpt/config2.yaml
|
||||
```
|
||||
|
||||
| 変数名 | config/key.yaml | env |
|
||||
| --------------------------------------- | ----------------------------------------- | ----------------------------------------------- |
|
||||
| OPENAI_API_KEY # 自分のキーに置き換える | OPENAI_API_KEY: "sk-..." | export OPENAI_API_KEY="sk-..." |
|
||||
| OPENAI_BASE_URL # オプション | OPENAI_BASE_URL: "https://<YOUR_SITE>/v1" | export OPENAI_BASE_URL="https://<YOUR_SITE>/v1" |
|
||||
|
||||
## チュートリアル: スタートアップの開始
|
||||
|
||||
```shell
|
||||
|
|
@ -300,7 +295,7 @@ ## 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:
|
||||
研究論文でMetaGPTやData Interpreterを使用する場合は、以下のように当社の作業を引用してください：
|
||||
|
||||
```bibtex
|
||||
@misc{hong2023metagpt,
|
||||
|
|
@ -311,6 +306,14 @@ ## 引用
|
|||
archivePrefix={arXiv},
|
||||
primaryClass={cs.AI}
|
||||
}
|
||||
@misc{hong2024data,
|
||||
title={Data Interpreter: An LLM Agent For Data Science},
|
||||
author={Sirui Hong and Yizhang Lin and Bang Liu and Bangbang Liu and Binhao Wu and Danyang Li and Jiaqi Chen and Jiayi Zhang and Jinlin Wang and Li Zhang and Lingyao Zhang and Min Yang and Mingchen Zhuge and Taicheng Guo and Tuo Zhou and Wei Tao and Wenyi Wang and Xiangru Tang and Xiangtao Lu and Xiawu Zheng and Xinbing Liang and Yaying Fei and Yuheng Cheng and Zongze Xu and Chenglin Wu},
|
||||
year={2024},
|
||||
eprint={2402.18679},
|
||||
archivePrefix={arXiv},
|
||||
primaryClass={cs.AI}
|
||||
}
|
||||
```
|
||||
|
||||
## お問い合わせ先
|
||||
|
|
|
|||
|
|
@ -35,14 +35,14 @@ ### Tasks
|
|||
3. Strategies
|
||||
1. Support ReAct strategy (experimentation done with game agents)
|
||||
2. Support CoT strategy (experimentation done with game agents)
|
||||
3. Support ToT strategy
|
||||
3. ~~Support ToT strategy~~ (v0.6.0)
|
||||
4. Support Reflection strategy (experimentation done with game agents)
|
||||
5. Support planning
|
||||
5. ~~Support planning~~ (v0.7.0)
|
||||
4. Actions
|
||||
1. ~~Implementation: Search~~ (v0.2.1)
|
||||
2. Implementation: Knowledge search, supporting 10+ data formats
|
||||
3. Implementation: Data EDA (expected v0.7.0)
|
||||
4. Implementation: Review & Revise (expected v0.7.0)
|
||||
3. ~~Implementation: Data EDA~~ (v0.7.0)
|
||||
4. ~~Implementation: Review & Revise~~ (v0.7.0)
|
||||
5. ~~Implementation: Add Document~~ (v0.5.0)
|
||||
6. ~~Implementation: Delete Document~~ (v0.5.0)
|
||||
7. Implementation: Self-training
|
||||
|
|
@ -50,7 +50,7 @@ ### Tasks
|
|||
9. Implementation: Generate reliable unit tests based on YAPI
|
||||
10. Implementation: Self-evaluation
|
||||
11. Implementation: AI Invocation
|
||||
12. Implementation: Learning and using third-party standard libraries
|
||||
12. ~~Implementation: Learning and using third-party standard libraries~~ (v0.7.0)
|
||||
13. Implementation: Data collection
|
||||
14. Implementation: AI training
|
||||
15. ~~Implementation: Run code~~ (v0.2.1)
|
||||
|
|
@ -63,22 +63,21 @@ ### Tasks
|
|||
7. Roles
|
||||
1. Perfect the action pool/skill pool for each role
|
||||
2. E-commerce seller
|
||||
3. Data analyst (expected v0.7.0)
|
||||
3. ~~Data analyst~~ (v0.7.0)
|
||||
4. News observer
|
||||
5. ~~Institutional researcher~~ (v0.2.1)
|
||||
8. Evaluation
|
||||
1. Support an evaluation on a game dataset (experimentation done with game agents)
|
||||
2. Reproduce papers, implement full skill acquisition for a single game role, achieving SOTA results (experimentation done with game agents)
|
||||
3. Support an evaluation on a math dataset (expected v0.7.0)
|
||||
4. Reproduce papers, achieving SOTA results for current mathematical problem solving process
|
||||
3. Support an evaluation on a math dataset (expected v0.8.0)
|
||||
4. Reproduce papers, achieving SOTA results for current mathematical problem solving process (expected v0.8.0)
|
||||
9. LLM
|
||||
1. Support Claude underlying API
|
||||
2. ~~Support Azure asynchronous API~~
|
||||
3. Support streaming version of all APIs
|
||||
4. ~~Make gpt-3.5-turbo available (HARD)~~
|
||||
5. Support
|
||||
10. Other
|
||||
1. ~~Clean up existing unused code~~
|
||||
2. Unify all code styles and establish contribution standards
|
||||
2. ~~Unify all code styles and establish contribution standards~~
|
||||
3. ~~Multi-language support~~
|
||||
4. ~~Multi-programming-language support~~
|
||||
|
|
|
|||
|
|
@ -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"
|
||||
MMDC: "./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`
|
||||
|
|
@ -59,12 +72,13 @@ # Step 3: Clone the repository to your local machine, and install it.
|
|||
playwright install --with-deps chromium
|
||||
```
|
||||
|
||||
- **modify `config.yaml`**
|
||||
- **modify `config2.yaml`**
|
||||
|
||||
uncomment MERMAID_ENGINE from config.yaml and change it to `playwright`
|
||||
change mermaid.engine to `playwright`
|
||||
|
||||
```yaml
|
||||
MERMAID_ENGINE: playwright
|
||||
mermaid:
|
||||
engine: playwright
|
||||
```
|
||||
|
||||
- pyppeteer
|
||||
|
|
@ -88,22 +102,24 @@ # Step 3: Clone the repository to your local machine, and install it.
|
|||
pyppeteer-install
|
||||
```
|
||||
|
||||
- **modify `config.yaml`**
|
||||
- **modify `config2.yaml`**
|
||||
|
||||
uncomment MERMAID_ENGINE from config.yaml and change it to `pyppeteer`
|
||||
change mermaid.engine to `pyppeteer`
|
||||
|
||||
```yaml
|
||||
MERMAID_ENGINE: pyppeteer
|
||||
mermaid:
|
||||
engine: pyppeteer
|
||||
```
|
||||
|
||||
- mermaid.ink
|
||||
- **modify `config.yaml`**
|
||||
|
||||
uncomment MERMAID_ENGINE from config.yaml and change it to `ink`
|
||||
- **modify `config2.yaml`**
|
||||
|
||||
change mermaid.engine to `ink`
|
||||
|
||||
```yaml
|
||||
MERMAID_ENGINE: ink
|
||||
mermaid:
|
||||
engine: ink
|
||||
```
|
||||
|
||||
Note: this method does not support pdf export.
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -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"
|
||||
MMDC: "./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。
|
||||
|
|
|
|||
|
|
@ -3,16 +3,16 @@ ## Docker Installation
|
|||
### Use default MetaGPT image
|
||||
|
||||
```bash
|
||||
# Step 1: Download metagpt official image and prepare config.yaml
|
||||
# Step 1: Download metagpt official image and prepare config2.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
|
||||
docker run --rm metagpt/metagpt:latest cat /app/metagpt/config/config2.yaml > /opt/metagpt/config/config2.yaml
|
||||
vim /opt/metagpt/config/config2.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/config/config2.yaml:/app/metagpt/config/config2.yaml \
|
||||
-v /opt/metagpt/workspace:/app/metagpt/workspace \
|
||||
metagpt/metagpt:latest \
|
||||
metagpt "Write a cli snake game"
|
||||
|
|
@ -20,7 +20,7 @@ # Step 2: Run metagpt demo with container
|
|||
# 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/config/config2.yaml:/app/metagpt/config/config2.yaml \
|
||||
-v /opt/metagpt/workspace:/app/metagpt/workspace \
|
||||
metagpt/metagpt:latest
|
||||
|
||||
|
|
@ -31,7 +31,7 @@ # You can also start a container and execute commands in it
|
|||
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 configure file `/opt/metagpt/config/config2.yaml` to container `/app/metagpt/config/config2.yaml`
|
||||
- Map host directory `/opt/metagpt/workspace` to container `/app/metagpt/workspace`
|
||||
- Execute the demo command `metagpt "Write a cli snake game"`
|
||||
|
||||
|
|
|
|||
|
|
@ -3,16 +3,16 @@ ## 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
|
||||
# 步骤1: 下载metagpt官方镜像并准备好config2.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
|
||||
docker run --rm metagpt/metagpt:latest cat /app/metagpt/config/config2.yaml > /opt/metagpt/config/config2.yaml
|
||||
vim /opt/metagpt/config/config2.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/config/config2.yaml:/app/metagpt/config/config2.yaml \
|
||||
-v /opt/metagpt/workspace:/app/metagpt/workspace \
|
||||
metagpt/metagpt:latest \
|
||||
metagpt "Write a cli snake game"
|
||||
|
|
@ -20,7 +20,7 @@ # 步骤2: 使用容器运行metagpt演示
|
|||
# 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/config/config2.yaml:/app/metagpt/config/config2.yaml \
|
||||
-v /opt/metagpt/workspace:/app/metagpt/workspace \
|
||||
metagpt/metagpt:latest
|
||||
|
||||
|
|
@ -31,7 +31,7 @@ # 您也可以启动一个容器并在其中执行命令
|
|||
`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`
|
||||
- 将主机文件 `/opt/metagpt/config/config2.yaml` 映射到容器文件 `/app/metagpt/config/config2.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 `metagpt "Write a cli snake game"`
|
||||
|
||||
|
|
|
|||
|
|
@ -1 +1 @@
|
|||
coverage run --source ./metagpt -m pytest --durations=0 --timeout=100 && coverage report -m && coverage html && open htmlcov/index.html
|
||||
coverage run --source ./metagpt -m pytest -n 8 --durations=0 --timeout=100 && coverage report -m && coverage html && open htmlcov/index.html
|
||||
|
|
|
|||
|
|
@ -2,19 +2,14 @@ ## 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`
|
||||
- Configure your `api_key` in any of `~/.metagpt/config2.yaml / config/config2.yaml`
|
||||
- Priority order: `~/.metagpt/config2.yaml > config/config2.yaml`
|
||||
|
||||
```bash
|
||||
# Copy the configuration file and make the necessary modifications.
|
||||
cp config/config.yaml config/key.yaml
|
||||
cp config/config2.yaml ~/.metagpt/config2.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_BASE_URL # Optional | OPENAI_BASE_URL: "https://<YOUR_SITE>/v1" | export OPENAI_BASE_URL="https://<YOUR_SITE>/v1" |
|
||||
|
||||
### Initiating a startup
|
||||
|
||||
```shell
|
||||
|
|
@ -39,29 +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. │
|
||||
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
|
||||
```
|
||||
|
|
@ -2,19 +2,14 @@ ## 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`
|
||||
- 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
|
||||
# 复制配置文件并进行必要的修改
|
||||
cp config/config.yaml config/key.yaml
|
||||
cp config/config2.yaml ~/.metagpt/config2.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_BASE_URL # 可选 | OPENAI_BASE_URL: "https://<YOUR_SITE>/v1" | export OPENAI_BASE_URL="https://<YOUR_SITE>/v1" |
|
||||
|
||||
### 示例：启动一个创业公司
|
||||
|
||||
```shell
|
||||
|
|
@ -35,29 +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. │
|
||||
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
|
||||
```
|
||||
|
|
|
|||
|
|
@ -6,7 +6,7 @@ Author: garylin2099
|
|||
import re
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.config2 import config
|
||||
from metagpt.const import METAGPT_ROOT
|
||||
from metagpt.logs import logger
|
||||
from metagpt.roles import Role
|
||||
|
|
@ -48,8 +48,8 @@ class CreateAgent(Action):
|
|||
pattern = r"```python(.*)```"
|
||||
match = re.search(pattern, rsp, re.DOTALL)
|
||||
code_text = match.group(1) if match else ""
|
||||
CONFIG.workspace_path.mkdir(parents=True, exist_ok=True)
|
||||
new_file = CONFIG.workspace_path / "agent_created_agent.py"
|
||||
config.workspace.path.mkdir(parents=True, exist_ok=True)
|
||||
new_file = config.workspace.path / "agent_created_agent.py"
|
||||
new_file.write_text(code_text)
|
||||
return code_text
|
||||
|
||||
|
|
@ -61,7 +61,7 @@ class AgentCreator(Role):
|
|||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._init_actions([CreateAgent])
|
||||
self.set_actions([CreateAgent])
|
||||
|
||||
async def _act(self) -> Message:
|
||||
logger.info(f"{self._setting}: to do {self.rc.todo}({self.rc.todo.name})")
|
||||
|
|
|
|||
|
|
@ -57,7 +57,7 @@ class SimpleCoder(Role):
|
|||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._init_actions([SimpleWriteCode])
|
||||
self.set_actions([SimpleWriteCode])
|
||||
|
||||
async def _act(self) -> Message:
|
||||
logger.info(f"{self._setting}: to do {self.rc.todo}({self.rc.todo.name})")
|
||||
|
|
@ -76,7 +76,7 @@ class RunnableCoder(Role):
|
|||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._init_actions([SimpleWriteCode, SimpleRunCode])
|
||||
self.set_actions([SimpleWriteCode, SimpleRunCode])
|
||||
self._set_react_mode(react_mode=RoleReactMode.BY_ORDER.value)
|
||||
|
||||
async def _act(self) -> Message:
|
||||
|
|
|
|||
|
|
@ -46,7 +46,7 @@ class SimpleCoder(Role):
|
|||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._watch([UserRequirement])
|
||||
self._init_actions([SimpleWriteCode])
|
||||
self.set_actions([SimpleWriteCode])
|
||||
|
||||
|
||||
class SimpleWriteTest(Action):
|
||||
|
|
@ -75,7 +75,7 @@ class SimpleTester(Role):
|
|||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._init_actions([SimpleWriteTest])
|
||||
self.set_actions([SimpleWriteTest])
|
||||
# self._watch([SimpleWriteCode])
|
||||
self._watch([SimpleWriteCode, SimpleWriteReview]) # feel free to try this too
|
||||
|
||||
|
|
@ -114,7 +114,7 @@ class SimpleReviewer(Role):
|
|||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._init_actions([SimpleWriteReview])
|
||||
self.set_actions([SimpleWriteReview])
|
||||
self._watch([SimpleWriteTest])
|
||||
|
||||
|
||||
|
|
|
|||
77
examples/dalle_gpt4v_agent.py
Normal file
77
examples/dalle_gpt4v_agent.py
Normal file
|
|
@ -0,0 +1,77 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
# @Desc : use gpt4v to improve prompt and draw image with dall-e-3
|
||||
|
||||
"""set `model: "gpt-4-vision-preview"` in `config2.yaml` first"""
|
||||
|
||||
import asyncio
|
||||
|
||||
from PIL import Image
|
||||
|
||||
from metagpt.actions.action import Action
|
||||
from metagpt.logs import logger
|
||||
from metagpt.roles.role import Role
|
||||
from metagpt.schema import Message
|
||||
from metagpt.utils.common import encode_image
|
||||
|
||||
|
||||
class GenAndImproveImageAction(Action):
|
||||
save_image: bool = True
|
||||
|
||||
async def generate_image(self, prompt: str) -> Image:
|
||||
imgs = await self.llm.gen_image(model="dall-e-3", prompt=prompt)
|
||||
return imgs[0]
|
||||
|
||||
async def refine_prompt(self, old_prompt: str, image: Image) -> str:
|
||||
msg = (
|
||||
f"You are a creative painter, with the given generated image and old prompt: {old_prompt}, "
|
||||
f"please refine the prompt and generate new one. Just output the new prompt."
|
||||
)
|
||||
b64_img = encode_image(image)
|
||||
new_prompt = await self.llm.aask(msg=msg, images=[b64_img])
|
||||
return new_prompt
|
||||
|
||||
async def evaluate_images(self, old_prompt: str, images: list[Image]) -> str:
|
||||
msg = (
|
||||
"With the prompt and two generated image, to judge if the second one is better than the first one. "
|
||||
"If so, just output True else output False"
|
||||
)
|
||||
b64_imgs = [encode_image(img) for img in images]
|
||||
res = await self.llm.aask(msg=msg, images=b64_imgs)
|
||||
return res
|
||||
|
||||
async def run(self, messages: list[Message]) -> str:
|
||||
prompt = messages[-1].content
|
||||
|
||||
old_img: Image = await self.generate_image(prompt)
|
||||
new_prompt = await self.refine_prompt(old_prompt=prompt, image=old_img)
|
||||
logger.info(f"original prompt: {prompt}")
|
||||
logger.info(f"refined prompt: {new_prompt}")
|
||||
new_img: Image = await self.generate_image(new_prompt)
|
||||
if self.save_image:
|
||||
old_img.save("./img_by-dall-e_old.png")
|
||||
new_img.save("./img_by-dall-e_new.png")
|
||||
res = await self.evaluate_images(old_prompt=prompt, images=[old_img, new_img])
|
||||
opinion = f"The second generated image is better than the first one: {res}"
|
||||
logger.info(f"evaluate opinion: {opinion}")
|
||||
return opinion
|
||||
|
||||
|
||||
class Painter(Role):
|
||||
name: str = "MaLiang"
|
||||
profile: str = "Painter"
|
||||
goal: str = "to generate fine painting"
|
||||
|
||||
def __init__(self, **data):
|
||||
super().__init__(**data)
|
||||
|
||||
self.set_actions([GenAndImproveImageAction])
|
||||
|
||||
|
||||
async def main():
|
||||
role = Painter()
|
||||
await role.run(with_message="a girl with flowers")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
1
examples/data/rag/travel.txt
Normal file
1
examples/data/rag/travel.txt
Normal file
|
|
@ -0,0 +1 @@
|
|||
Bob likes traveling.
|
||||
109
examples/data/rag/writer.txt
Normal file
109
examples/data/rag/writer.txt
Normal file
|
|
@ -0,0 +1,109 @@
|
|||
Productivity
|
||||
I think I am at least somewhat more productive than average, and people sometimes ask me for productivity tips. So I decided to just write them all down in one place.
|
||||
|
||||
Compound growth gets discussed as a financial concept, but it works in careers as well, and it is magic. A small productivity gain, compounded over 50 years, is worth a lot. So it’s worth figuring out how to optimize productivity. If you get 10% more done and 1% better every day compared to someone else, the compounded difference is massive.
|
||||
|
||||
What you work on
|
||||
|
||||
Famous writers have some essential qualities, creativity and discipline
|
||||
|
||||
It doesn’t matter how fast you move if it’s in a worthless direction. Picking the right thing to work on is the most important element of productivity and usually almost ignored. So think about it more! Independent thought is hard but it’s something you can get better at with practice.
|
||||
|
||||
The most impressive people I know have strong beliefs about the world, which is rare in the general population. If you find yourself always agreeing with whomever you last spoke with, that’s bad. You will of course be wrong sometimes, but develop the confidence to stick with your convictions. It will let you be courageous when you’re right about something important that most people don’t see.
|
||||
|
||||
I make sure to leave enough time in my schedule to think about what to work on. The best ways for me to do this are reading books, hanging out with interesting people, and spending time in nature.
|
||||
|
||||
I’ve learned that I can’t be very productive working on things I don’t care about or don’t like. So I just try not to put myself in a position where I have to do them (by delegating, avoiding, or something else). Stuff that you don’t like is a painful drag on morale and momentum.
|
||||
|
||||
By the way, here is an important lesson about delegation: remember that everyone else is also most productive when they’re doing what they like, and do what you’d want other people to do for you—try to figure out who likes (and is good at) doing what, and delegate that way.
|
||||
|
||||
If you find yourself not liking what you’re doing for a long period of time, seriously consider a major job change. Short-term burnout happens, but if it isn’t resolved with some time off, maybe it’s time to do something you’re more interested in.
|
||||
|
||||
I’ve been very fortunate to find work I like so much I’d do it for free, which makes it easy to be really productive.
|
||||
|
||||
It’s important to learn that you can learn anything you want, and that you can get better quickly. This feels like an unlikely miracle the first few times it happens, but eventually you learn to trust that you can do it.
|
||||
|
||||
Doing great work usually requires colleagues of some sort. Try to be around smart, productive, happy, and positive people that don’t belittle your ambitions. I love being around people who push me and inspire me to be better. To the degree you able to, avoid the opposite kind of people—the cost of letting them take up your mental cycles is horrific.
|
||||
|
||||
You have to both pick the right problem and do the work. There aren’t many shortcuts. If you’re going to do something really important, you are very likely going to work both smart and hard. The biggest prizes are heavily competed for. This isn’t true in every field (there are great mathematicians who never spend that many hours a week working) but it is in most.
|
||||
|
||||
Prioritization
|
||||
|
||||
Writers have to work hard to be successful
|
||||
|
||||
My system has three key pillars: “Make sure to get the important shit done”, “Don’t waste time on stupid shit”, and “make a lot of lists”.
|
||||
|
||||
I highly recommend using lists. I make lists of what I want to accomplish each year, each month, and each day. Lists are very focusing, and they help me with multitasking because I don’t have to keep as much in my head. If I’m not in the mood for some particular task, I can always find something else I’m excited to do.
|
||||
|
||||
I prefer lists written down on paper. It’s easy to add and remove tasks. I can access them during meetings without feeling rude. I re-transcribe lists frequently, which forces me to think about everything on the list and gives me an opportunity to add and remove items.
|
||||
|
||||
I don’t bother with categorization or trying to size tasks or anything like that (the most I do is put a star next to really important items).
|
||||
|
||||
I try to prioritize in a way that generates momentum. The more I get done, the better I feel, and then the more I get done. I like to start and end each day with something I can really make progress on.
|
||||
|
||||
I am relentless about getting my most important projects done—I’ve found that if I really want something to happen and I push hard enough, it usually happens.
|
||||
|
||||
I try to be ruthless about saying no to stuff, and doing non-critical things in the quickest way possible. I probably take this too far—for example, I am almost sure I am terse to the point of rudeness when replying to emails.
|
||||
|
||||
Passion and adaptability are key qualities to writers
|
||||
|
||||
I generally try to avoid meetings and conferences as I find the time cost to be huge—I get the most value out of time in my office. However, it is critical that you keep enough space in your schedule to allow for chance encounters and exposure to new people and ideas. Having an open network is valuable; though probably 90% of the random meetings I take are a waste of time, the other 10% really make up for it.
|
||||
|
||||
I find most meetings are best scheduled for 15-20 minutes, or 2 hours. The default of 1 hour is usually wrong, and leads to a lot of wasted time.
|
||||
|
||||
I have different times of day I try to use for different kinds of work. The first few hours of the morning are definitely my most productive time of the day, so I don’t let anyone schedule anything then. I try to do meetings in the afternoon. I take a break, or switch tasks, whenever I feel my attention starting to fade.
|
||||
|
||||
I don’t think most people value their time enough—I am surprised by the number of people I know who make $100 an hour and yet will spend a couple of hours doing something they don’t want to do to save $20.
|
||||
|
||||
Also, don’t fall into the trap of productivity porn—chasing productivity for its own sake isn’t helpful. Many people spend too much time thinking about how to perfectly optimize their system, and not nearly enough asking if they’re working on the right problems. It doesn’t matter what system you use or if you squeeze out every second if you’re working on the wrong thing.
|
||||
|
||||
The right goal is to allocate your year optimally, not your day.
|
||||
|
||||
Physical factors
|
||||
|
||||
Very likely what is optimal for me won’t be optimal for you. You’ll have to experiment to find out what works best for your body. It’s definitely worth doing—it helps in all aspects of life, and you’ll feel a lot better and happier overall.
|
||||
|
||||
It probably took a little bit of my time every week for a few years to arrive at what works best for me, but my sense is if I do a good job at all the below I’m at least 1.5x more productive than if not.
|
||||
|
||||
Sleep seems to be the most important physical factor in productivity for me. Some sort of sleep tracker to figure out how to sleep best is helpful. I’ve found the only thing I’m consistent with are in the set-it-and-forget-it category, and I really like the Emfit QS+Active.
|
||||
|
||||
I like a cold, dark, quiet room, and a great mattress (I resisted spending a bunch of money on a great mattress for years, which was stupid—it makes a huge difference to my sleep quality. I love this one). Not eating a lot in the few hours before sleep helps. Not drinking alcohol helps a lot, though I’m not willing to do that all the time.
|
||||
|
||||
I use a Chili Pad to be cold while I sleep if I can’t get the room cold enough, which is great but loud (I set it up to have the cooler unit outside my room).
|
||||
|
||||
When traveling, I use an eye mask and ear plugs.
|
||||
|
||||
Writers usually have empathy to write good books.
|
||||
|
||||
This is likely to be controversial, but I take a low dose of sleeping pills (like a third of a normal dose) or a very low dose of cannabis whenever I can’t sleep. I am a bad sleeper in general, and a particularly bad sleeper when I travel. It likely has tradeoffs, but so does not sleeping well. If you can already sleep well, I wouldn’t recommend this.
|
||||
|
||||
I use a full spectrum LED light most mornings for about 10-15 minutes while I catch up on email. It’s great—if you try nothing else in here, this is the thing I’d try. It’s a ridiculous gain for me. I like this one, and it’s easy to travel with.
|
||||
|
||||
Exercise is probably the second most important physical factor. I tried a number of different exercise programs for a few months each and the one that seemed best was lifting heavy weights 3x a week for an hour, and high intensity interval training occasionally. In addition to productivity gains, this is also the exercise program that makes me feel the best overall.
|
||||
|
||||
The third area is nutrition. I very rarely eat breakfast, so I get about 15 hours of fasting most days (except an espresso when I wake up). I know this is contrary to most advice, and I suspect it’s not optimal for most people, but it definitely works well for me.
|
||||
|
||||
Eating lots of sugar is the thing that makes me feel the worst and that I try hardest to avoid. I also try to avoid foods that aggravate my digestion or spike up inflammation (for example, very spicy foods). I don’t have much willpower when it comes to sweet things, so I mostly just try to keep junk food out of the house.
|
||||
|
||||
I have one big shot of espresso immediately when I wake up and one after lunch. I assume this is about 200mg total of caffeine per day. I tried a few other configurations; this was the one that worked by far the best. I otherwise aggressively avoid stimulants, but I will have more coffee if I’m super tired and really need to get something done.
|
||||
|
||||
If a writer want to be super, then should include innovative thinking.
|
||||
|
||||
I’m vegetarian and have been since I was a kid, and I supplement methyl B-12, Omega-3, Iron, and Vitamin D-3. I got to this list with a year or so of quarterly blood tests; it’s worked for me ever since (I re-test maybe every year and a half or so). There are many doctors who will happily work with you on a super comprehensive blood test (and services like WellnessFX). I also go out of my way to drink a lot of protein shakes, which I hate and I wouldn’t do if I weren’t vegetarian.
|
||||
|
||||
Other stuff
|
||||
|
||||
Here’s what I like in a workspace: natural light, quiet, knowing that I won’t be interrupted if I don’t want to be, long blocks of time, and being comfortable and relaxed (I’ve got a beautiful desk with a couple of 4k monitors on it in my office, but I spend almost all my time on my couch with my laptop).
|
||||
|
||||
I wrote custom software for the annoying things I have to do frequently, which is great. I also made an effort to learn to type really fast and the keyboard shortcuts that help with my workflow.
|
||||
|
||||
Like most people, I sometimes go through periods of a week or two where I just have no motivation to do anything (I suspect it may have something to do with nutrition). This sucks and always seems to happen at inconvenient times. I have not figured out what to do about it besides wait for the fog to lift, and to trust that eventually it always does. And I generally try to avoid people and situations that put me in bad moods, which is good advice whether you care about productivity or not.
|
||||
|
||||
In general, I think it’s good to overcommit a little bit. I find that I generally get done what I take on, and if I have a little bit too much to do it makes me more efficient at everything, which is a way to train to avoid distractions (a great habit to build!). However, overcommitting a lot is disastrous.
|
||||
|
||||
Don’t neglect your family and friends for the sake of productivity—that’s a very stupid tradeoff (and very likely a net productivity loss, because you’ll be less happy). Don’t neglect doing things you love or that clear your head either.
|
||||
|
||||
Finally, to repeat one more time: productivity in the wrong direction isn’t worth anything at all. Think more about what to work on.
|
||||
|
||||
Open-Mindedness and curiosity are essential to writers
|
||||
|
||||
|
|
@ -5,6 +5,7 @@ Author: garylin2099
|
|||
@Modified By: mashenquan, 2023-11-1. In accordance with Chapter 2.1.3 of RFC 116, modify the data type of the `send_to`
|
||||
value of the `Message` object; modify the argument type of `get_by_actions`.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import platform
|
||||
from typing import Any
|
||||
|
|
@ -49,7 +50,7 @@ class Debator(Role):
|
|||
|
||||
def __init__(self, **data: Any):
|
||||
super().__init__(**data)
|
||||
self._init_actions([SpeakAloud])
|
||||
self.set_actions([SpeakAloud])
|
||||
self._watch([UserRequirement, SpeakAloud])
|
||||
|
||||
async def _observe(self) -> int:
|
||||
|
|
@ -105,4 +106,4 @@ def main(idea: str, investment: float = 3.0, n_round: int = 10):
|
|||
|
||||
|
||||
if __name__ == "__main__":
|
||||
fire.Fire(main)
|
||||
fire.Fire(main) # run as python debate.py --idea="TOPIC" --investment=3.0 --n_round=5
|
||||
|
|
|
|||
|
|
@ -8,12 +8,17 @@
|
|||
import asyncio
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.config2 import Config
|
||||
from metagpt.environment import Environment
|
||||
from metagpt.roles import Role
|
||||
from metagpt.team import Team
|
||||
|
||||
action1 = Action(name="AlexSay", instruction="Express your opinion with emotion and don't repeat it")
|
||||
action2 = Action(name="BobSay", instruction="Express your opinion with emotion and don't repeat it")
|
||||
gpt35 = Config.default()
|
||||
gpt35.llm.model = "gpt-3.5-turbo-1106"
|
||||
gpt4 = Config.default()
|
||||
gpt4.llm.model = "gpt-4-1106-preview"
|
||||
action1 = Action(config=gpt4, name="AlexSay", instruction="Express your opinion with emotion and don't repeat it")
|
||||
action2 = Action(config=gpt35, name="BobSay", instruction="Express your opinion with emotion and don't repeat it")
|
||||
alex = Role(name="Alex", profile="Democratic candidate", goal="Win the election", actions=[action1], watch=[action2])
|
||||
bob = Role(name="Bob", profile="Republican candidate", goal="Win the election", actions=[action2], watch=[action1])
|
||||
env = Environment(desc="US election live broadcast")
|
||||
|
|
|
|||
20
examples/di/README.md
Normal file
20
examples/di/README.md
Normal file
|
|
@ -0,0 +1,20 @@
|
|||
# Data Interpreter (DI)
|
||||
|
||||
## What is Data Interpreter
|
||||
Data Interpreter is an agent who solves data-related problems through codes. It understands user requirements, makes plans, writes codes for execution, and uses tools if necessary. These capabilities enable it to tackle a wide range of scenarios, please check out the examples below. For overall design and technical details, please see our [paper](https://arxiv.org/abs/2402.18679).
|
||||
|
||||
## Example List
|
||||
- Data visualization
|
||||
- Machine learning modeling
|
||||
- Image background removal
|
||||
- Solve math problems
|
||||
- Receipt OCR
|
||||
- Tool usage: web page imitation
|
||||
- Tool usage: web crawling
|
||||
- Tool usage: text2image
|
||||
- Tool usage: email summarization and response\
|
||||
- More on the way!
|
||||
|
||||
Please see the [docs](https://docs.deepwisdom.ai/main/en/guide/use_cases/agent/interpreter/intro.html) for more explanation.
|
||||
|
||||
We are continuously releasing codes, stay tuned!
|
||||
26
examples/di/arxiv_reader.py
Normal file
26
examples/di/arxiv_reader.py
Normal file
|
|
@ -0,0 +1,26 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2024/01/15
|
||||
@Author : mannaandpoem
|
||||
@File : imitate_webpage.py
|
||||
"""
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
|
||||
async def main():
|
||||
template = "https://arxiv.org/list/{tag}/pastweek?skip=0&show=300"
|
||||
tags = ["cs.ai", "cs.cl", "cs.lg", "cs.se"]
|
||||
urls = [template.format(tag=tag) for tag in tags]
|
||||
prompt = f"""This is a collection of arxiv urls: '{urls}' .
|
||||
Record each article, remove duplicates by title (they may have multiple tags), filter out papers related to
|
||||
large language model / agent / llm, print top 100 and visualize the word count of the titles"""
|
||||
di = DataInterpreter(react_mode="react", tools=["scrape_web_playwright"])
|
||||
|
||||
await di.run(prompt)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import asyncio
|
||||
|
||||
asyncio.run(main())
|
||||
40
examples/di/crawl_webpage.py
Normal file
40
examples/di/crawl_webpage.py
Normal file
|
|
@ -0,0 +1,40 @@
|
|||
# -*- encoding: utf-8 -*-
|
||||
"""
|
||||
@Date : 2024/01/24 15:11:27
|
||||
@Author : orange-crow
|
||||
@File : crawl_webpage.py
|
||||
"""
|
||||
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
PAPER_LIST_REQ = """"
|
||||
Get data from `paperlist` table in https://papercopilot.com/statistics/iclr-statistics/iclr-2024-statistics/,
|
||||
and save it to a csv file. paper title must include `multiagent` or `large language model`. *notice: print key variables*
|
||||
"""
|
||||
|
||||
ECOMMERCE_REQ = """
|
||||
Get products data from website https://scrapeme.live/shop/ and save it as a csv file.
|
||||
**Notice: Firstly parse the web page encoding and the text HTML structure;
|
||||
The first page product name, price, product URL, and image URL must be saved in the csv;**
|
||||
"""
|
||||
|
||||
NEWS_36KR_REQ = """从36kr创投平台https://pitchhub.36kr.com/financing-flash 所有初创企业融资的信息, **注意: 这是一个中文网站**;
|
||||
下面是一个大致流程, 你会根据每一步的运行结果对当前计划中的任务做出适当调整:
|
||||
1. 爬取并本地保存html结构;
|
||||
2. 直接打印第7个*`快讯`*关键词后2000个字符的html内容, 作为*快讯的html内容示例*;
|
||||
3. 反思*快讯的html内容示例*中的规律, 设计正则匹配表达式来获取*`快讯`*的标题、链接、时间;
|
||||
4. 筛选最近3天的初创企业融资*`快讯`*, 以list[dict]形式打印前5个。
|
||||
5. 将全部结果存在本地csv中
|
||||
"""
|
||||
|
||||
|
||||
async def main():
|
||||
di = DataInterpreter(tools=["scrape_web_playwright"])
|
||||
|
||||
await di.run(ECOMMERCE_REQ)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import asyncio
|
||||
|
||||
asyncio.run(main())
|
||||
14
examples/di/data_visualization.py
Normal file
14
examples/di/data_visualization.py
Normal file
|
|
@ -0,0 +1,14 @@
|
|||
import asyncio
|
||||
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
|
||||
async def main(requirement: str = ""):
|
||||
di = DataInterpreter()
|
||||
await di.run(requirement)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
requirement = "Run data analysis on sklearn Iris dataset, include a plot"
|
||||
|
||||
asyncio.run(main(requirement))
|
||||
33
examples/di/email_summary.py
Normal file
33
examples/di/email_summary.py
Normal file
|
|
@ -0,0 +1,33 @@
|
|||
# -*- encoding: utf-8 -*-
|
||||
"""
|
||||
@Date : 2024/02/07
|
||||
@Author : Tuo Zhou
|
||||
@File : email_summary.py
|
||||
"""
|
||||
import os
|
||||
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
|
||||
async def main():
|
||||
email_account = "your_email_account"
|
||||
# your password will stay only on your device and not go to LLM api
|
||||
os.environ["email_password"] = "your_email_password"
|
||||
|
||||
### Prompt for automatic email reply, uncomment to try this too ###
|
||||
# prompt = f"""I will give you your Outlook email account ({email_account}) and password (email_password item in the environment variable). You need to find the latest email in my inbox with the sender's suffix @gmail.com and reply "Thank you! I have received your email~"""""
|
||||
|
||||
### Prompt for automatic email summary ###
|
||||
prompt = f"""I will give you your Outlook email account ({email_account}) and password (email_password item in the environment variable).
|
||||
Firstly, Please help me fetch the latest 5 senders and full letter contents.
|
||||
Then, summarize each of the 5 emails into one sentence (you can do this by yourself, no need to import other models to do this) and output them in a markdown format."""
|
||||
|
||||
di = DataInterpreter()
|
||||
|
||||
await di.run(prompt)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import asyncio
|
||||
|
||||
asyncio.run(main())
|
||||
25
examples/di/imitate_webpage.py
Normal file
25
examples/di/imitate_webpage.py
Normal file
|
|
@ -0,0 +1,25 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2024/01/15
|
||||
@Author : mannaandpoem
|
||||
@File : imitate_webpage.py
|
||||
"""
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
|
||||
async def main():
|
||||
web_url = "https://pytorch.org/"
|
||||
prompt = f"""This is a URL of webpage: '{web_url}' .
|
||||
Firstly, utilize Selenium and WebDriver for rendering.
|
||||
Secondly, convert image to a webpage including HTML, CSS and JS in one go.
|
||||
Note: All required dependencies and environments have been fully installed and configured."""
|
||||
di = DataInterpreter(tools=["GPTvGenerator"])
|
||||
|
||||
await di.run(prompt)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import asyncio
|
||||
|
||||
asyncio.run(main())
|
||||
23
examples/di/machine_learning.py
Normal file
23
examples/di/machine_learning.py
Normal file
|
|
@ -0,0 +1,23 @@
|
|||
import fire
|
||||
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
WINE_REQ = "Run data analysis on sklearn Wine recognition dataset, include a plot, and train a model to predict wine class (20% as validation), and show validation accuracy."
|
||||
|
||||
DATA_DIR = "path/to/your/data"
|
||||
# sales_forecast data from https://www.kaggle.com/datasets/aslanahmedov/walmart-sales-forecast/data
|
||||
SALES_FORECAST_REQ = f"""Train a model to predict sales for each department in every store (split the last 40 weeks records as validation dataset, the others is train dataset), include plot total sales trends, print metric and plot scatter plots of
|
||||
groud truth and predictions on validation data. Dataset is {DATA_DIR}/train.csv, the metric is weighted mean absolute error (WMAE) for test data. Notice: *print* key variables to get more information for next task step.
|
||||
"""
|
||||
|
||||
REQUIREMENTS = {"wine": WINE_REQ, "sales_forecast": SALES_FORECAST_REQ}
|
||||
|
||||
|
||||
async def main(use_case: str = "wine"):
|
||||
mi = DataInterpreter()
|
||||
requirement = REQUIREMENTS[use_case]
|
||||
await mi.run(requirement)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
fire.Fire(main)
|
||||
16
examples/di/machine_learning_with_tools.py
Normal file
16
examples/di/machine_learning_with_tools.py
Normal file
|
|
@ -0,0 +1,16 @@
|
|||
import asyncio
|
||||
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
|
||||
async def main(requirement: str):
|
||||
role = DataInterpreter(use_reflection=True, tools=["<all>"])
|
||||
await role.run(requirement)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
data_path = "your/path/to/titanic"
|
||||
train_path = f"{data_path}/split_train.csv"
|
||||
eval_path = f"{data_path}/split_eval.csv"
|
||||
requirement = f"This is a titanic passenger survival dataset, your goal is to predict passenger survival outcome. The target column is Survived. Perform data analysis, data preprocessing, feature engineering, and modeling to predict the target. Report accuracy on the eval data. Train data path: '{train_path}', eval data path: '{eval_path}'."
|
||||
asyncio.run(main(requirement))
|
||||
21
examples/di/ocr_receipt.py
Normal file
21
examples/di/ocr_receipt.py
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
|
||||
async def main():
|
||||
# Notice: pip install metagpt[ocr] before using this example
|
||||
image_path = "image.jpg"
|
||||
language = "English"
|
||||
requirement = f"""This is a {language} receipt image.
|
||||
Your goal is to perform OCR on images using PaddleOCR, output text content from the OCR results and discard
|
||||
coordinates and confidence levels, then recognize the total amount from ocr text content, and finally save as table.
|
||||
Image path: {image_path}.
|
||||
NOTE: The environments for Paddle and PaddleOCR are all ready and has been fully installed."""
|
||||
di = DataInterpreter()
|
||||
|
||||
await di.run(requirement)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import asyncio
|
||||
|
||||
asyncio.run(main())
|
||||
15
examples/di/rm_image_background.py
Normal file
15
examples/di/rm_image_background.py
Normal file
|
|
@ -0,0 +1,15 @@
|
|||
import asyncio
|
||||
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
|
||||
async def main(requirement: str = ""):
|
||||
di = DataInterpreter()
|
||||
await di.run(requirement)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
image_path = "/your/path/to/the/image.jpeg"
|
||||
save_path = "/your/intended/save/path/for/image_rm_bg.png"
|
||||
requirement = f"This is a image, you need to use python toolkit rembg to remove the background of the image and save the result. image path:{image_path}; save path:{save_path}."
|
||||
asyncio.run(main(requirement))
|
||||
21
examples/di/sd_tool_usage.py
Normal file
21
examples/di/sd_tool_usage.py
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
# @Date : 1/11/2024 7:06 PM
|
||||
# @Author : stellahong (stellahong@fuzhi.ai)
|
||||
# @Desc :
|
||||
import asyncio
|
||||
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
|
||||
async def main(requirement: str = ""):
|
||||
di = DataInterpreter(tools=["SDEngine"])
|
||||
await di.run(requirement)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sd_url = "http://your.sd.service.ip:port"
|
||||
requirement = (
|
||||
f"I want to generate an image of a beautiful girl using the stable diffusion text2image tool, sd_url={sd_url}"
|
||||
)
|
||||
|
||||
asyncio.run(main(requirement))
|
||||
14
examples/di/solve_math_problems.py
Normal file
14
examples/di/solve_math_problems.py
Normal file
|
|
@ -0,0 +1,14 @@
|
|||
import asyncio
|
||||
|
||||
from metagpt.roles.di.data_interpreter import DataInterpreter
|
||||
|
||||
|
||||
async def main(requirement: str = ""):
|
||||
di = DataInterpreter()
|
||||
await di.run(requirement)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
requirement = "Solve this math problem: The greatest common divisor of positive integers m and n is 6. The least common multiple of m and n is 126. What is the least possible value of m + n?"
|
||||
# answer: 60 (m = 18, n = 42)
|
||||
asyncio.run(main(requirement))
|
||||
Binary file not shown.
Binary file not shown.
|
|
@ -13,7 +13,18 @@ from metagpt.logs import logger
|
|||
|
||||
async def main():
|
||||
llm = LLM()
|
||||
logger.info(await llm.aask("hello world"))
|
||||
# llm type check
|
||||
question = "what's your name"
|
||||
logger.info(f"{question}: ")
|
||||
logger.info(await llm.aask(question))
|
||||
logger.info("\n\n")
|
||||
|
||||
logger.info(
|
||||
await llm.aask(
|
||||
"who are you", system_msgs=["act as a robot, just answer 'I'am robot' if the question is 'who are you'"]
|
||||
)
|
||||
)
|
||||
|
||||
logger.info(await llm.aask_batch(["hi", "write python hello world."]))
|
||||
|
||||
hello_msg = [{"role": "user", "content": "count from 1 to 10. split by newline."}]
|
||||
|
|
@ -23,6 +34,10 @@ async def main():
|
|||
# streaming mode, much slower
|
||||
await llm.acompletion_text(hello_msg, stream=True)
|
||||
|
||||
# check completion if exist to test llm complete functions
|
||||
if hasattr(llm, "completion"):
|
||||
logger.info(llm.completion(hello_msg))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
|
|
|
|||
23
examples/llm_vision.py
Normal file
23
examples/llm_vision.py
Normal file
|
|
@ -0,0 +1,23 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
# @Desc : example to run the ability of LLM vision
|
||||
|
||||
import asyncio
|
||||
from pathlib import Path
|
||||
|
||||
from metagpt.llm import LLM
|
||||
from metagpt.utils.common import encode_image
|
||||
|
||||
|
||||
async def main():
|
||||
llm = LLM()
|
||||
|
||||
# check if the configured llm supports llm-vision capacity. If not, it will throw a error
|
||||
invoice_path = Path(__file__).parent.joinpath("..", "tests", "data", "invoices", "invoice-2.png")
|
||||
img_base64 = encode_image(invoice_path)
|
||||
res = await llm.aask(msg="if this is a invoice, just return True else return False", images=[img_base64])
|
||||
assert "true" in res.lower()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
211
examples/rag_pipeline.py
Normal file
211
examples/rag_pipeline.py
Normal file
|
|
@ -0,0 +1,211 @@
|
|||
"""RAG pipeline"""
|
||||
|
||||
import asyncio
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from metagpt.const import DATA_PATH, EXAMPLE_DATA_PATH
|
||||
from metagpt.logs import logger
|
||||
from metagpt.rag.engines import SimpleEngine
|
||||
from metagpt.rag.schema import (
|
||||
BM25RetrieverConfig,
|
||||
ChromaIndexConfig,
|
||||
ChromaRetrieverConfig,
|
||||
FAISSRetrieverConfig,
|
||||
LLMRankerConfig,
|
||||
)
|
||||
|
||||
DOC_PATH = EXAMPLE_DATA_PATH / "rag/writer.txt"
|
||||
QUESTION = "What are key qualities to be a good writer?"
|
||||
|
||||
TRAVEL_DOC_PATH = EXAMPLE_DATA_PATH / "rag/travel.txt"
|
||||
TRAVEL_QUESTION = "What does Bob like?"
|
||||
|
||||
LLM_TIP = "If you not sure, just answer I don't know."
|
||||
|
||||
|
||||
class Player(BaseModel):
|
||||
"""To demonstrate rag add objs."""
|
||||
|
||||
name: str = ""
|
||||
goal: str = "Win The 100-meter Sprint."
|
||||
tool: str = "Red Bull Energy Drink."
|
||||
|
||||
def rag_key(self) -> str:
|
||||
"""For search"""
|
||||
return self.goal
|
||||
|
||||
|
||||
class RAGExample:
|
||||
"""Show how to use RAG."""
|
||||
|
||||
def __init__(self):
|
||||
self.engine = SimpleEngine.from_docs(
|
||||
input_files=[DOC_PATH],
|
||||
retriever_configs=[FAISSRetrieverConfig(), BM25RetrieverConfig()],
|
||||
ranker_configs=[LLMRankerConfig()],
|
||||
)
|
||||
|
||||
async def run_pipeline(self, question=QUESTION, print_title=True):
|
||||
"""This example run rag pipeline, use faiss&bm25 retriever and llm ranker, will print something like:
|
||||
|
||||
Retrieve Result:
|
||||
0. Productivi..., 10.0
|
||||
1. I wrote cu..., 7.0
|
||||
2. I highly r..., 5.0
|
||||
|
||||
Query Result:
|
||||
Passion, adaptability, open-mindedness, creativity, discipline, and empathy are key qualities to be a good writer.
|
||||
"""
|
||||
if print_title:
|
||||
self._print_title("Run Pipeline")
|
||||
|
||||
nodes = await self.engine.aretrieve(question)
|
||||
self._print_retrieve_result(nodes)
|
||||
|
||||
answer = await self.engine.aquery(question)
|
||||
self._print_query_result(answer)
|
||||
|
||||
async def add_docs(self):
|
||||
"""This example show how to add docs.
|
||||
|
||||
Before add docs llm anwser I don't know.
|
||||
After add docs llm give the correct answer, will print something like:
|
||||
|
||||
[Before add docs]
|
||||
Retrieve Result:
|
||||
|
||||
Query Result:
|
||||
Empty Response
|
||||
|
||||
[After add docs]
|
||||
Retrieve Result:
|
||||
0. Bob like..., 10.0
|
||||
|
||||
Query Result:
|
||||
Bob likes traveling.
|
||||
"""
|
||||
self._print_title("Add Docs")
|
||||
|
||||
travel_question = f"{TRAVEL_QUESTION}{LLM_TIP}"
|
||||
travel_filepath = TRAVEL_DOC_PATH
|
||||
|
||||
logger.info("[Before add docs]")
|
||||
await self.run_pipeline(question=travel_question, print_title=False)
|
||||
|
||||
logger.info("[After add docs]")
|
||||
self.engine.add_docs([travel_filepath])
|
||||
await self.run_pipeline(question=travel_question, print_title=False)
|
||||
|
||||
async def add_objects(self, print_title=True):
|
||||
"""This example show how to add objects.
|
||||
|
||||
Before add docs, engine retrieve nothing.
|
||||
After add objects, engine give the correct answer, will print something like:
|
||||
|
||||
[Before add objs]
|
||||
Retrieve Result:
|
||||
|
||||
[After add objs]
|
||||
Retrieve Result:
|
||||
0. 100m Sprin..., 10.0
|
||||
|
||||
[Object Detail]
|
||||
{'name': 'Mike', 'goal': 'Win The 100-meter Sprint', 'tool': 'Red Bull Energy Drink'}
|
||||
"""
|
||||
if print_title:
|
||||
self._print_title("Add Objects")
|
||||
|
||||
player = Player(name="Mike")
|
||||
question = f"{player.rag_key()}"
|
||||
|
||||
logger.info("[Before add objs]")
|
||||
await self._retrieve_and_print(question)
|
||||
|
||||
logger.info("[After add objs]")
|
||||
self.engine.add_objs([player])
|
||||
|
||||
try:
|
||||
nodes = await self._retrieve_and_print(question)
|
||||
|
||||
logger.info("[Object Detail]")
|
||||
player: Player = nodes[0].metadata["obj"]
|
||||
logger.info(player.name)
|
||||
except Exception as e:
|
||||
logger.error(f"nodes is empty, llm don't answer correctly, exception: {e}")
|
||||
|
||||
async def init_objects(self):
|
||||
"""This example show how to from objs, will print something like:
|
||||
|
||||
Same as add_objects.
|
||||
"""
|
||||
self._print_title("Init Objects")
|
||||
|
||||
pre_engine = self.engine
|
||||
self.engine = SimpleEngine.from_objs(retriever_configs=[FAISSRetrieverConfig()])
|
||||
await self.add_objects(print_title=False)
|
||||
self.engine = pre_engine
|
||||
|
||||
async def init_and_query_chromadb(self):
|
||||
"""This example show how to use chromadb. how to save and load index. will print something like:
|
||||
|
||||
Query Result:
|
||||
Bob likes traveling.
|
||||
"""
|
||||
self._print_title("Init And Query ChromaDB")
|
||||
|
||||
# save index
|
||||
output_dir = DATA_PATH / "rag"
|
||||
SimpleEngine.from_docs(
|
||||
input_files=[TRAVEL_DOC_PATH],
|
||||
retriever_configs=[ChromaRetrieverConfig(persist_path=output_dir)],
|
||||
)
|
||||
|
||||
# load index
|
||||
engine = SimpleEngine.from_index(
|
||||
index_config=ChromaIndexConfig(persist_path=output_dir),
|
||||
)
|
||||
|
||||
# query
|
||||
answer = engine.query(TRAVEL_QUESTION)
|
||||
self._print_query_result(answer)
|
||||
|
||||
@staticmethod
|
||||
def _print_title(title):
|
||||
logger.info(f"{'#'*30} {title} {'#'*30}")
|
||||
|
||||
@staticmethod
|
||||
def _print_retrieve_result(result):
|
||||
"""Print retrieve result."""
|
||||
logger.info("Retrieve Result:")
|
||||
|
||||
for i, node in enumerate(result):
|
||||
logger.info(f"{i}. {node.text[:10]}..., {node.score}")
|
||||
|
||||
logger.info("")
|
||||
|
||||
@staticmethod
|
||||
def _print_query_result(result):
|
||||
"""Print query result."""
|
||||
logger.info("Query Result:")
|
||||
|
||||
logger.info(f"{result}\n")
|
||||
|
||||
async def _retrieve_and_print(self, question):
|
||||
nodes = await self.engine.aretrieve(question)
|
||||
self._print_retrieve_result(nodes)
|
||||
return nodes
|
||||
|
||||
|
||||
async def main():
|
||||
"""RAG pipeline"""
|
||||
e = RAGExample()
|
||||
await e.run_pipeline()
|
||||
await e.add_docs()
|
||||
await e.add_objects()
|
||||
await e.init_objects()
|
||||
await e.init_and_query_chromadb()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
21
examples/rag_search.py
Normal file
21
examples/rag_search.py
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
"""Agent with RAG search."""
|
||||
|
||||
import asyncio
|
||||
|
||||
from examples.rag_pipeline import DOC_PATH, QUESTION
|
||||
from metagpt.logs import logger
|
||||
from metagpt.rag.engines import SimpleEngine
|
||||
from metagpt.roles import Sales
|
||||
|
||||
|
||||
async def search():
|
||||
"""Agent with RAG search."""
|
||||
|
||||
store = SimpleEngine.from_docs(input_files=[DOC_PATH])
|
||||
role = Sales(profile="Sales", store=store)
|
||||
result = await role.run(QUESTION)
|
||||
logger.info(result)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(search())
|
||||
72
examples/reverse_engineering.py
Normal file
72
examples/reverse_engineering.py
Normal file
|
|
@ -0,0 +1,72 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import asyncio
|
||||
import shutil
|
||||
from pathlib import Path
|
||||
|
||||
import typer
|
||||
|
||||
from metagpt.actions.rebuild_class_view import RebuildClassView
|
||||
from metagpt.actions.rebuild_sequence_view import RebuildSequenceView
|
||||
from metagpt.context import Context
|
||||
from metagpt.llm import LLM
|
||||
from metagpt.logs import logger
|
||||
from metagpt.utils.git_repository import GitRepository
|
||||
from metagpt.utils.project_repo import ProjectRepo
|
||||
|
||||
app = typer.Typer(add_completion=False, pretty_exceptions_show_locals=False)
|
||||
|
||||
|
||||
@app.command("", help="Python project reverse engineering.")
|
||||
def startup(
|
||||
project_root: str = typer.Argument(
|
||||
default="",
|
||||
help="Specify the root directory of the existing project for reverse engineering.",
|
||||
),
|
||||
output_dir: str = typer.Option(default="", help="Specify the output directory path for reverse engineering."),
|
||||
):
|
||||
package_root = Path(project_root)
|
||||
if not package_root.exists():
|
||||
raise FileNotFoundError(f"{project_root} not exists")
|
||||
if not _is_python_package_root(package_root):
|
||||
raise FileNotFoundError(f'There are no "*.py" files under "{project_root}".')
|
||||
init_file = package_root / "__init__.py" # used by pyreverse
|
||||
init_file_exists = init_file.exists()
|
||||
if not init_file_exists:
|
||||
init_file.touch()
|
||||
|
||||
if not output_dir:
|
||||
output_dir = package_root / "../reverse_engineering_output"
|
||||
logger.info(f"output dir:{output_dir}")
|
||||
try:
|
||||
asyncio.run(reverse_engineering(package_root, Path(output_dir)))
|
||||
finally:
|
||||
if not init_file_exists:
|
||||
init_file.unlink(missing_ok=True)
|
||||
tmp_dir = package_root / "__dot__"
|
||||
if tmp_dir.exists():
|
||||
shutil.rmtree(tmp_dir, ignore_errors=True)
|
||||
|
||||
|
||||
def _is_python_package_root(package_root: Path) -> bool:
|
||||
for file_path in package_root.iterdir():
|
||||
if file_path.is_file():
|
||||
if file_path.suffix == ".py":
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
async def reverse_engineering(package_root: Path, output_dir: Path):
|
||||
ctx = Context()
|
||||
ctx.git_repo = GitRepository(output_dir)
|
||||
ctx.repo = ProjectRepo(ctx.git_repo)
|
||||
action = RebuildClassView(name="ReverseEngineering", i_context=str(package_root), llm=LLM(), context=ctx)
|
||||
await action.run()
|
||||
|
||||
action = RebuildSequenceView(name="ReverseEngineering", llm=LLM(), context=ctx)
|
||||
await action.run()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
app()
|
||||
|
|
@ -1,32 +0,0 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@File : search_kb.py
|
||||
@Modified By: mashenquan, 2023-12-22. Delete useless codes.
|
||||
"""
|
||||
import asyncio
|
||||
|
||||
from langchain.embeddings import OpenAIEmbeddings
|
||||
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import DATA_PATH, EXAMPLE_PATH
|
||||
from metagpt.document_store import FaissStore
|
||||
from metagpt.logs import logger
|
||||
from metagpt.roles import Sales
|
||||
|
||||
|
||||
def get_store():
|
||||
embedding = OpenAIEmbeddings(openai_api_key=CONFIG.openai_api_key, openai_api_base=CONFIG.openai_base_url)
|
||||
return FaissStore(DATA_PATH / "example.json", embedding=embedding)
|
||||
|
||||
|
||||
async def search():
|
||||
store = FaissStore(EXAMPLE_PATH / "example.json")
|
||||
role = Sales(profile="Sales", store=store)
|
||||
query = "Which facial cleanser is good for oily skin?"
|
||||
result = await role.run(query)
|
||||
logger.info(result)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(search())
|
||||
|
|
@ -4,18 +4,17 @@
|
|||
"""
|
||||
import asyncio
|
||||
|
||||
from metagpt.config2 import Config
|
||||
from metagpt.roles import Searcher
|
||||
from metagpt.tools import SearchEngineType
|
||||
from metagpt.tools.search_engine import SearchEngine
|
||||
|
||||
|
||||
async def main():
|
||||
question = "What are the most interesting human facts?"
|
||||
# Serper API
|
||||
# await Searcher(engine=SearchEngineType.SERPER_GOOGLE).run(question)
|
||||
# SerpAPI
|
||||
await Searcher(engine=SearchEngineType.SERPAPI_GOOGLE).run(question)
|
||||
# Google API
|
||||
# await Searcher(engine=SearchEngineType.DIRECT_GOOGLE).run(question)
|
||||
|
||||
search = Config.default().search
|
||||
kwargs = {"api_key": search.api_key, "cse_id": search.cse_id, "proxy": None}
|
||||
await Searcher(search_engine=SearchEngine(engine=search.api_type, **kwargs)).run(question)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
|
|
|||
60
examples/write_novel.py
Normal file
60
examples/write_novel.py
Normal file
|
|
@ -0,0 +1,60 @@
|
|||
#!/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 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.")
|
||||
|
||||
|
||||
class Chapters(BaseModel):
|
||||
chapters: List[Chapter] = Field(
|
||||
default=[
|
||||
{"name": "Chapter 1", "content": "..."},
|
||||
{"name": "Chapter 2", "content": "..."},
|
||||
{"name": "Chapter 3", "content": "..."},
|
||||
],
|
||||
description="The chapters of the novel.",
|
||||
)
|
||||
|
||||
|
||||
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.")
|
||||
|
||||
|
||||
async def generate_novel():
|
||||
instruction = (
|
||||
"Write a novel named 'Reborn in Skyrim'. "
|
||||
"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(Chapters).fill(
|
||||
context=f"### instruction\n{instruction}\n### novel\n{novel_node.content}", llm=LLM()
|
||||
)
|
||||
print(chap_node.instruct_content)
|
||||
|
||||
|
||||
asyncio.run(generate_novel())
|
||||
|
|
@ -22,6 +22,9 @@ from metagpt.actions.write_code_review import WriteCodeReview
|
|||
from metagpt.actions.write_prd import WritePRD
|
||||
from metagpt.actions.write_prd_review import WritePRDReview
|
||||
from metagpt.actions.write_test import WriteTest
|
||||
from metagpt.actions.di.execute_nb_code import ExecuteNbCode
|
||||
from metagpt.actions.di.write_analysis_code import WriteAnalysisCode
|
||||
from metagpt.actions.di.write_plan import WritePlan
|
||||
|
||||
|
||||
class ActionType(Enum):
|
||||
|
|
@ -42,6 +45,9 @@ class ActionType(Enum):
|
|||
COLLECT_LINKS = CollectLinks
|
||||
WEB_BROWSE_AND_SUMMARIZE = WebBrowseAndSummarize
|
||||
CONDUCT_RESEARCH = ConductResearch
|
||||
EXECUTE_NB_CODE = ExecuteNbCode
|
||||
WRITE_ANALYSIS_CODE = WriteAnalysisCode
|
||||
WRITE_PLAN = WritePlan
|
||||
|
||||
|
||||
__all__ = [
|
||||
|
|
|
|||
|
|
@ -10,41 +10,67 @@ from __future__ import annotations
|
|||
|
||||
from typing import Optional, Union
|
||||
|
||||
from pydantic import ConfigDict, Field, model_validator
|
||||
from pydantic import BaseModel, ConfigDict, Field, model_validator
|
||||
|
||||
from metagpt.actions.action_node import ActionNode
|
||||
from metagpt.llm import LLM
|
||||
from metagpt.provider.base_llm import BaseLLM
|
||||
from metagpt.context_mixin import ContextMixin
|
||||
from metagpt.schema import (
|
||||
CodePlanAndChangeContext,
|
||||
CodeSummarizeContext,
|
||||
CodingContext,
|
||||
RunCodeContext,
|
||||
SerializationMixin,
|
||||
TestingContext,
|
||||
)
|
||||
from metagpt.utils.project_repo import ProjectRepo
|
||||
|
||||
|
||||
class Action(SerializationMixin, is_polymorphic_base=True):
|
||||
model_config = ConfigDict(arbitrary_types_allowed=True, exclude=["llm"])
|
||||
class Action(SerializationMixin, ContextMixin, BaseModel):
|
||||
model_config = ConfigDict(arbitrary_types_allowed=True)
|
||||
|
||||
name: str = ""
|
||||
llm: BaseLLM = Field(default_factory=LLM, exclude=True)
|
||||
context: Union[dict, CodingContext, CodeSummarizeContext, TestingContext, RunCodeContext, str, None] = ""
|
||||
i_context: Union[
|
||||
dict, CodingContext, CodeSummarizeContext, TestingContext, RunCodeContext, CodePlanAndChangeContext, str, None
|
||||
] = ""
|
||||
prefix: str = "" # aask*时会加上prefix，作为system_message
|
||||
desc: str = "" # for skill manager
|
||||
node: ActionNode = Field(default=None, exclude=True)
|
||||
|
||||
@property
|
||||
def repo(self) -> ProjectRepo:
|
||||
if not self.context.repo:
|
||||
self.context.repo = ProjectRepo(self.context.git_repo)
|
||||
return self.context.repo
|
||||
|
||||
@property
|
||||
def prompt_schema(self):
|
||||
return self.config.prompt_schema
|
||||
|
||||
@property
|
||||
def project_name(self):
|
||||
return self.config.project_name
|
||||
|
||||
@project_name.setter
|
||||
def project_name(self, value):
|
||||
self.config.project_name = value
|
||||
|
||||
@property
|
||||
def project_path(self):
|
||||
return self.config.project_path
|
||||
|
||||
@model_validator(mode="before")
|
||||
@classmethod
|
||||
def set_name_if_empty(cls, values):
|
||||
if "name" not in values or not values["name"]:
|
||||
values["name"] = cls.__name__
|
||||
return values
|
||||
|
||||
@model_validator(mode="before")
|
||||
@classmethod
|
||||
def _init_with_instruction(cls, values):
|
||||
if "instruction" in values:
|
||||
name = values["name"]
|
||||
i = values["instruction"]
|
||||
i = values.pop("instruction")
|
||||
values["node"] = ActionNode(key=name, expected_type=str, instruction=i, example="", schema="raw")
|
||||
return values
|
||||
|
||||
|
|
|
|||
49
metagpt/actions/action_graph.py
Normal file
49
metagpt/actions/action_graph.py
Normal file
|
|
@ -0,0 +1,49 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2024/1/30 13:52
|
||||
@Author : alexanderwu
|
||||
@File : action_graph.py
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
# from metagpt.actions.action_node import ActionNode
|
||||
|
||||
|
||||
class ActionGraph:
|
||||
"""ActionGraph: a directed graph to represent the dependency between actions."""
|
||||
|
||||
def __init__(self):
|
||||
self.nodes = {}
|
||||
self.edges = {}
|
||||
self.execution_order = []
|
||||
|
||||
def add_node(self, node):
|
||||
"""Add a node to the graph"""
|
||||
self.nodes[node.key] = node
|
||||
|
||||
def add_edge(self, from_node: "ActionNode", to_node: "ActionNode"):
|
||||
"""Add an edge to the graph"""
|
||||
if from_node.key not in self.edges:
|
||||
self.edges[from_node.key] = []
|
||||
self.edges[from_node.key].append(to_node.key)
|
||||
from_node.add_next(to_node)
|
||||
to_node.add_prev(from_node)
|
||||
|
||||
def topological_sort(self):
|
||||
"""Topological sort the graph"""
|
||||
visited = set()
|
||||
stack = []
|
||||
|
||||
def visit(k):
|
||||
if k not in visited:
|
||||
visited.add(k)
|
||||
if k in self.edges:
|
||||
for next_node in self.edges[k]:
|
||||
visit(next_node)
|
||||
stack.insert(0, k)
|
||||
|
||||
for key in self.nodes:
|
||||
visit(key)
|
||||
|
||||
self.execution_order = stack
|
||||
|
|
@ -9,23 +9,37 @@ NOTE: You should use typing.List instead of list to do type annotation. Because
|
|||
we can use typing to extract the type of the node, but we cannot use built-in list to extract.
|
||||
"""
|
||||
import json
|
||||
from typing import Any, Dict, List, Optional, Tuple, Type
|
||||
import typing
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Optional, Tuple, Type, Union
|
||||
|
||||
from pydantic import BaseModel, create_model, model_validator
|
||||
from pydantic import BaseModel, Field, create_model, model_validator
|
||||
from tenacity import retry, stop_after_attempt, wait_random_exponential
|
||||
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.actions.action_outcls_registry import register_action_outcls
|
||||
from metagpt.llm import BaseLLM
|
||||
from metagpt.logs import logger
|
||||
from metagpt.provider.postprocess.llm_output_postprocess import llm_output_postprocess
|
||||
from metagpt.utils.common import OutputParser, general_after_log
|
||||
from metagpt.utils.human_interaction import HumanInteraction
|
||||
|
||||
|
||||
class ReviewMode(Enum):
|
||||
HUMAN = "human"
|
||||
AUTO = "auto"
|
||||
|
||||
|
||||
class ReviseMode(Enum):
|
||||
HUMAN = "human" # human revise
|
||||
HUMAN_REVIEW = "human_review" # human-review and auto-revise
|
||||
AUTO = "auto" # auto-review and auto-revise
|
||||
|
||||
|
||||
TAG = "CONTENT"
|
||||
|
||||
LANGUAGE_CONSTRAINT = "Language: Please use the same language as Human INPUT."
|
||||
FORMAT_CONSTRAINT = f"Format: output wrapped inside [{TAG}][/{TAG}] like format example, nothing else."
|
||||
|
||||
|
||||
SIMPLE_TEMPLATE = """
|
||||
## context
|
||||
{context}
|
||||
|
|
@ -45,6 +59,58 @@ SIMPLE_TEMPLATE = """
|
|||
Follow instructions of nodes, generate output and make sure it follows the format example.
|
||||
"""
|
||||
|
||||
REVIEW_TEMPLATE = """
|
||||
## context
|
||||
Compare the key's value of nodes_output and the corresponding requirements one by one. If a key's value that does not match the requirement is found, provide the comment content on how to modify it. No output is required for matching keys.
|
||||
|
||||
### nodes_output
|
||||
{nodes_output}
|
||||
|
||||
-----
|
||||
|
||||
## format example
|
||||
[{tag}]
|
||||
{{
|
||||
"key1": "comment1",
|
||||
"key2": "comment2",
|
||||
"keyn": "commentn"
|
||||
}}
|
||||
[/{tag}]
|
||||
|
||||
## nodes: "<node>: <type> # <instruction>"
|
||||
- key1: <class \'str\'> # the first key name of mismatch key
|
||||
- key2: <class \'str\'> # the second key name of mismatch key
|
||||
- keyn: <class \'str\'> # the last key name of mismatch key
|
||||
|
||||
## constraint
|
||||
{constraint}
|
||||
|
||||
## action
|
||||
Follow format example's {prompt_schema} format, generate output and make sure it follows the format example.
|
||||
"""
|
||||
|
||||
REVISE_TEMPLATE = """
|
||||
## context
|
||||
change the nodes_output key's value to meet its comment and no need to add extra comment.
|
||||
|
||||
### nodes_output
|
||||
{nodes_output}
|
||||
|
||||
-----
|
||||
|
||||
## format example
|
||||
{example}
|
||||
|
||||
## nodes: "<node>: <type> # <instruction>"
|
||||
{instruction}
|
||||
|
||||
## constraint
|
||||
{constraint}
|
||||
|
||||
## action
|
||||
Follow format example's {prompt_schema} format, generate output and make sure it follows the format example.
|
||||
"""
|
||||
|
||||
|
||||
def dict_to_markdown(d, prefix="- ", kv_sep="\n", postfix="\n"):
|
||||
markdown_str = ""
|
||||
|
|
@ -65,6 +131,8 @@ class ActionNode:
|
|||
|
||||
# Action Input
|
||||
key: str # Product Requirement / File list / Code
|
||||
func: typing.Callable # 与节点相关联的函数或LLM调用
|
||||
params: Dict[str, Type] # 输入参数的字典，键为参数名，值为参数类型
|
||||
expected_type: Type # such as str / int / float etc.
|
||||
# context: str # everything in the history.
|
||||
instruction: str # the instructions should be followed.
|
||||
|
|
@ -74,6 +142,10 @@ class ActionNode:
|
|||
content: str
|
||||
instruct_content: BaseModel
|
||||
|
||||
# For ActionGraph
|
||||
prevs: List["ActionNode"] # previous nodes
|
||||
nexts: List["ActionNode"] # next nodes
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
key: str,
|
||||
|
|
@ -91,6 +163,8 @@ class ActionNode:
|
|||
self.content = content
|
||||
self.children = children if children is not None else {}
|
||||
self.schema = schema
|
||||
self.prevs = []
|
||||
self.nexts = []
|
||||
|
||||
def __str__(self):
|
||||
return (
|
||||
|
|
@ -101,10 +175,21 @@ class ActionNode:
|
|||
def __repr__(self):
|
||||
return self.__str__()
|
||||
|
||||
def add_prev(self, node: "ActionNode"):
|
||||
"""增加前置ActionNode"""
|
||||
self.prevs.append(node)
|
||||
|
||||
def add_next(self, node: "ActionNode"):
|
||||
"""增加后置ActionNode"""
|
||||
self.nexts.append(node)
|
||||
|
||||
def add_child(self, node: "ActionNode"):
|
||||
"""增加子ActionNode"""
|
||||
self.children[node.key] = node
|
||||
|
||||
def get_child(self, key: str) -> Union["ActionNode", None]:
|
||||
return self.children.get(key, None)
|
||||
|
||||
def add_children(self, nodes: List["ActionNode"]):
|
||||
"""批量增加子ActionNode"""
|
||||
for node in nodes:
|
||||
|
|
@ -117,24 +202,38 @@ class ActionNode:
|
|||
obj.add_children(nodes)
|
||||
return obj
|
||||
|
||||
def get_children_mapping(self, exclude=None) -> Dict[str, Tuple[Type, Any]]:
|
||||
"""获得子ActionNode的字典，以key索引"""
|
||||
def _get_children_mapping(self, exclude=None) -> Dict[str, Any]:
|
||||
"""获得子ActionNode的字典，以key索引，支持多级结构。"""
|
||||
exclude = exclude or []
|
||||
return {k: (v.expected_type, ...) for k, v in self.children.items() if k not in exclude}
|
||||
|
||||
def get_self_mapping(self) -> Dict[str, Tuple[Type, Any]]:
|
||||
def _get_mapping(node: "ActionNode") -> Dict[str, Any]:
|
||||
mapping = {}
|
||||
for key, child in node.children.items():
|
||||
if key in exclude:
|
||||
continue
|
||||
# 对于嵌套的子节点，递归调用 _get_mapping
|
||||
if child.children:
|
||||
mapping[key] = _get_mapping(child)
|
||||
else:
|
||||
mapping[key] = (child.expected_type, Field(default=child.example, description=child.instruction))
|
||||
return mapping
|
||||
|
||||
return _get_mapping(self)
|
||||
|
||||
def _get_self_mapping(self) -> Dict[str, Tuple[Type, Any]]:
|
||||
"""get self key: type mapping"""
|
||||
return {self.key: (self.expected_type, ...)}
|
||||
|
||||
def get_mapping(self, mode="children", exclude=None) -> Dict[str, Tuple[Type, Any]]:
|
||||
"""get key: type mapping under mode"""
|
||||
if mode == "children" or (mode == "auto" and self.children):
|
||||
return self.get_children_mapping(exclude=exclude)
|
||||
return {} if exclude and self.key in exclude else self.get_self_mapping()
|
||||
return self._get_children_mapping(exclude=exclude)
|
||||
return {} if exclude and self.key in exclude else self._get_self_mapping()
|
||||
|
||||
@classmethod
|
||||
@register_action_outcls
|
||||
def create_model_class(cls, class_name: str, mapping: Dict[str, Tuple[Type, Any]]):
|
||||
"""基于pydantic v1的模型动态生成，用来检验结果类型正确性"""
|
||||
"""基于pydantic v2的模型动态生成，用来检验结果类型正确性"""
|
||||
|
||||
def check_fields(cls, values):
|
||||
required_fields = set(mapping.keys())
|
||||
|
|
@ -149,42 +248,85 @@ class ActionNode:
|
|||
|
||||
validators = {"check_missing_fields_validator": model_validator(mode="before")(check_fields)}
|
||||
|
||||
new_class = create_model(class_name, __validators__=validators, **mapping)
|
||||
new_fields = {}
|
||||
for field_name, field_value in mapping.items():
|
||||
if isinstance(field_value, dict):
|
||||
# 对于嵌套结构，递归创建模型类
|
||||
nested_class_name = f"{class_name}_{field_name}"
|
||||
nested_class = cls.create_model_class(nested_class_name, field_value)
|
||||
new_fields[field_name] = (nested_class, ...)
|
||||
else:
|
||||
new_fields[field_name] = field_value
|
||||
|
||||
new_class = create_model(class_name, __validators__=validators, **new_fields)
|
||||
return new_class
|
||||
|
||||
def create_children_class(self, exclude=None):
|
||||
def create_class(self, mode: str = "auto", class_name: str = None, exclude=None):
|
||||
class_name = class_name if class_name else f"{self.key}_AN"
|
||||
mapping = self.get_mapping(mode=mode, exclude=exclude)
|
||||
return self.create_model_class(class_name, mapping)
|
||||
|
||||
def _create_children_class(self, exclude=None):
|
||||
"""使用object内有的字段直接生成model_class"""
|
||||
class_name = f"{self.key}_AN"
|
||||
mapping = self.get_children_mapping(exclude=exclude)
|
||||
mapping = self._get_children_mapping(exclude=exclude)
|
||||
return self.create_model_class(class_name, mapping)
|
||||
|
||||
def to_dict(self, format_func=None, mode="auto", exclude=None) -> Dict:
|
||||
"""将当前节点与子节点都按照node: format的格式组织成字典"""
|
||||
nodes = self._to_dict(format_func=format_func, mode=mode, exclude=exclude)
|
||||
if not isinstance(nodes, dict):
|
||||
nodes = {self.key: nodes}
|
||||
return nodes
|
||||
|
||||
# 如果没有提供格式化函数，使用默认的格式化方式
|
||||
def _to_dict(self, format_func=None, mode="auto", exclude=None) -> Dict:
|
||||
"""将当前节点与子节点都按照node: format的格式组织成字典"""
|
||||
|
||||
# 如果没有提供格式化函数，则使用默认的格式化函数
|
||||
if format_func is None:
|
||||
format_func = lambda node: f"{node.instruction}"
|
||||
format_func = lambda node: node.instruction
|
||||
|
||||
# 使用提供的格式化函数来格式化当前节点的值
|
||||
formatted_value = format_func(self)
|
||||
|
||||
# 创建当前节点的键值对
|
||||
if mode == "children" or (mode == "auto" and self.children):
|
||||
node_dict = {}
|
||||
if (mode == "children" or mode == "auto") and self.children:
|
||||
node_value = {}
|
||||
else:
|
||||
node_dict = {self.key: formatted_value}
|
||||
node_value = formatted_value
|
||||
|
||||
if mode == "root":
|
||||
return node_dict
|
||||
return {self.key: node_value}
|
||||
|
||||
# 遍历子节点并递归调用 to_dict 方法
|
||||
# 递归处理子节点
|
||||
exclude = exclude or []
|
||||
for _, child_node in self.children.items():
|
||||
if child_node.key in exclude:
|
||||
for child_key, child_node in self.children.items():
|
||||
if child_key in exclude:
|
||||
continue
|
||||
node_dict.update(child_node.to_dict(format_func))
|
||||
# 递归调用 to_dict 方法并更新节点字典
|
||||
child_dict = child_node._to_dict(format_func, mode, exclude)
|
||||
node_value[child_key] = child_dict
|
||||
|
||||
return node_dict
|
||||
return node_value
|
||||
|
||||
def update_instruct_content(self, incre_data: dict[str, Any]):
|
||||
assert self.instruct_content
|
||||
origin_sc_dict = self.instruct_content.model_dump()
|
||||
origin_sc_dict.update(incre_data)
|
||||
output_class = self.create_class()
|
||||
self.instruct_content = output_class(**origin_sc_dict)
|
||||
|
||||
def keys(self, mode: str = "auto") -> list:
|
||||
if mode == "children" or (mode == "auto" and self.children):
|
||||
keys = []
|
||||
else:
|
||||
keys = [self.key]
|
||||
if mode == "root":
|
||||
return keys
|
||||
|
||||
for _, child_node in self.children.items():
|
||||
keys.append(child_node.key)
|
||||
return keys
|
||||
|
||||
def compile_to(self, i: Dict, schema, kv_sep) -> str:
|
||||
if schema == "json":
|
||||
|
|
@ -234,6 +376,17 @@ class ActionNode:
|
|||
if schema == "raw":
|
||||
return context + "\n\n## Actions\n" + LANGUAGE_CONSTRAINT + "\n" + self.instruction
|
||||
|
||||
### 直接使用 pydantic BaseModel 生成 instruction 与 example，仅限 JSON
|
||||
# child_class = self._create_children_class()
|
||||
# node_schema = child_class.model_json_schema()
|
||||
# defaults = {
|
||||
# k: str(v)
|
||||
# for k, v in child_class.model_fields.items()
|
||||
# if k not in exclude
|
||||
# }
|
||||
# instruction = node_schema
|
||||
# example = json.dumps(defaults, indent=4)
|
||||
|
||||
# FIXME: json instruction会带来格式问题，如："Project name": "web_2048 # 项目名称使用下划线",
|
||||
# compile example暂时不支持markdown
|
||||
instruction = self.compile_instruction(schema="markdown", mode=mode, exclude=exclude)
|
||||
|
|
@ -260,12 +413,13 @@ class ActionNode:
|
|||
prompt: str,
|
||||
output_class_name: str,
|
||||
output_data_mapping: dict,
|
||||
images: Optional[Union[str, list[str]]] = None,
|
||||
system_msgs: Optional[list[str]] = None,
|
||||
schema="markdown", # compatible to original format
|
||||
timeout=CONFIG.timeout,
|
||||
timeout=3,
|
||||
) -> (str, BaseModel):
|
||||
"""Use ActionOutput to wrap the output of aask"""
|
||||
content = await self.llm.aask(prompt, system_msgs, timeout=timeout)
|
||||
content = await self.llm.aask(prompt, system_msgs, images=images, timeout=timeout)
|
||||
logger.debug(f"llm raw output:\n{content}")
|
||||
output_class = self.create_model_class(output_class_name, output_data_mapping)
|
||||
|
||||
|
|
@ -294,13 +448,15 @@ class ActionNode:
|
|||
def set_context(self, context):
|
||||
self.set_recursive("context", context)
|
||||
|
||||
async def simple_fill(self, schema, mode, timeout=CONFIG.timeout, exclude=None):
|
||||
async def simple_fill(self, schema, mode, images: Optional[Union[str, list[str]]] = None, timeout=3, exclude=None):
|
||||
prompt = self.compile(context=self.context, schema=schema, mode=mode, exclude=exclude)
|
||||
|
||||
if schema != "raw":
|
||||
mapping = self.get_mapping(mode, exclude=exclude)
|
||||
class_name = f"{self.key}_AN"
|
||||
content, scontent = await self._aask_v1(prompt, class_name, mapping, schema=schema, timeout=timeout)
|
||||
content, scontent = await self._aask_v1(
|
||||
prompt, class_name, mapping, images=images, schema=schema, timeout=timeout
|
||||
)
|
||||
self.content = content
|
||||
self.instruct_content = scontent
|
||||
else:
|
||||
|
|
@ -309,7 +465,17 @@ class ActionNode:
|
|||
|
||||
return self
|
||||
|
||||
async def fill(self, context, llm, schema="json", mode="auto", strgy="simple", timeout=CONFIG.timeout, exclude=[]):
|
||||
async def fill(
|
||||
self,
|
||||
context,
|
||||
llm,
|
||||
schema="json",
|
||||
mode="auto",
|
||||
strgy="simple",
|
||||
images: Optional[Union[str, list[str]]] = None,
|
||||
timeout=3,
|
||||
exclude=[],
|
||||
):
|
||||
"""Fill the node(s) with mode.
|
||||
|
||||
:param context: Everything we should know when filling node.
|
||||
|
|
@ -325,6 +491,7 @@ class ActionNode:
|
|||
:param strgy: simple/complex
|
||||
- simple: run only once
|
||||
- complex: run each node
|
||||
:param images: the list of image url or base64 for gpt4-v
|
||||
:param timeout: Timeout for llm invocation.
|
||||
:param exclude: The keys of ActionNode to exclude.
|
||||
:return: self
|
||||
|
|
@ -335,15 +502,219 @@ class ActionNode:
|
|||
schema = self.schema
|
||||
|
||||
if strgy == "simple":
|
||||
return await self.simple_fill(schema=schema, mode=mode, timeout=timeout, exclude=exclude)
|
||||
return await self.simple_fill(schema=schema, mode=mode, images=images, timeout=timeout, exclude=exclude)
|
||||
elif strgy == "complex":
|
||||
# 这里隐式假设了拥有children
|
||||
tmp = {}
|
||||
for _, i in self.children.items():
|
||||
if exclude and i.key in exclude:
|
||||
continue
|
||||
child = await i.simple_fill(schema=schema, mode=mode, timeout=timeout, exclude=exclude)
|
||||
tmp.update(child.instruct_content.dict())
|
||||
cls = self.create_children_class()
|
||||
child = await i.simple_fill(schema=schema, mode=mode, images=images, timeout=timeout, exclude=exclude)
|
||||
tmp.update(child.instruct_content.model_dump())
|
||||
cls = self._create_children_class()
|
||||
self.instruct_content = cls(**tmp)
|
||||
return self
|
||||
|
||||
async def human_review(self) -> dict[str, str]:
|
||||
review_comments = HumanInteraction().interact_with_instruct_content(
|
||||
instruct_content=self.instruct_content, interact_type="review"
|
||||
)
|
||||
|
||||
return review_comments
|
||||
|
||||
def _makeup_nodes_output_with_req(self) -> dict[str, str]:
|
||||
instruct_content_dict = self.instruct_content.model_dump()
|
||||
nodes_output = {}
|
||||
for key, value in instruct_content_dict.items():
|
||||
child = self.get_child(key)
|
||||
nodes_output[key] = {"value": value, "requirement": child.instruction if child else self.instruction}
|
||||
return nodes_output
|
||||
|
||||
async def auto_review(self, template: str = REVIEW_TEMPLATE) -> dict[str, str]:
|
||||
"""use key's output value and its instruction to review the modification comment"""
|
||||
nodes_output = self._makeup_nodes_output_with_req()
|
||||
"""nodes_output format:
|
||||
{
|
||||
"key": {"value": "output value", "requirement": "key instruction"}
|
||||
}
|
||||
"""
|
||||
if not nodes_output:
|
||||
return dict()
|
||||
|
||||
prompt = template.format(
|
||||
nodes_output=json.dumps(nodes_output, ensure_ascii=False),
|
||||
tag=TAG,
|
||||
constraint=FORMAT_CONSTRAINT,
|
||||
prompt_schema="json",
|
||||
)
|
||||
|
||||
content = await self.llm.aask(prompt)
|
||||
# Extract the dict of mismatch key and its comment. Due to the mismatch keys are unknown, here use the keys
|
||||
# of ActionNode to judge if exist in `content` and then follow the `data_mapping` method to create model class.
|
||||
keys = self.keys()
|
||||
include_keys = []
|
||||
for key in keys:
|
||||
if f'"{key}":' in content:
|
||||
include_keys.append(key)
|
||||
if not include_keys:
|
||||
return dict()
|
||||
|
||||
exclude_keys = list(set(keys).difference(include_keys))
|
||||
output_class_name = f"{self.key}_AN_REVIEW"
|
||||
output_class = self.create_class(class_name=output_class_name, exclude=exclude_keys)
|
||||
parsed_data = llm_output_postprocess(
|
||||
output=content, schema=output_class.model_json_schema(), req_key=f"[/{TAG}]"
|
||||
)
|
||||
instruct_content = output_class(**parsed_data)
|
||||
return instruct_content.model_dump()
|
||||
|
||||
async def simple_review(self, review_mode: ReviewMode = ReviewMode.AUTO):
|
||||
# generate review comments
|
||||
if review_mode == ReviewMode.HUMAN:
|
||||
review_comments = await self.human_review()
|
||||
else:
|
||||
review_comments = await self.auto_review()
|
||||
|
||||
if not review_comments:
|
||||
logger.warning("There are no review comments")
|
||||
return review_comments
|
||||
|
||||
async def review(self, strgy: str = "simple", review_mode: ReviewMode = ReviewMode.AUTO):
|
||||
"""only give the review comment of each exist and mismatch key
|
||||
|
||||
:param strgy: simple/complex
|
||||
- simple: run only once
|
||||
- complex: run each node
|
||||
"""
|
||||
if not hasattr(self, "llm"):
|
||||
raise RuntimeError("use `review` after `fill`")
|
||||
assert review_mode in ReviewMode
|
||||
assert self.instruct_content, 'review only support with `schema != "raw"`'
|
||||
|
||||
if strgy == "simple":
|
||||
review_comments = await self.simple_review(review_mode)
|
||||
elif strgy == "complex":
|
||||
# review each child node one-by-one
|
||||
review_comments = {}
|
||||
for _, child in self.children.items():
|
||||
child_review_comment = await child.simple_review(review_mode)
|
||||
review_comments.update(child_review_comment)
|
||||
|
||||
return review_comments
|
||||
|
||||
async def human_revise(self) -> dict[str, str]:
|
||||
review_contents = HumanInteraction().interact_with_instruct_content(
|
||||
instruct_content=self.instruct_content, mapping=self.get_mapping(mode="auto"), interact_type="revise"
|
||||
)
|
||||
# re-fill the ActionNode
|
||||
self.update_instruct_content(review_contents)
|
||||
return review_contents
|
||||
|
||||
def _makeup_nodes_output_with_comment(self, review_comments: dict[str, str]) -> dict[str, str]:
|
||||
instruct_content_dict = self.instruct_content.model_dump()
|
||||
nodes_output = {}
|
||||
for key, value in instruct_content_dict.items():
|
||||
if key in review_comments:
|
||||
nodes_output[key] = {"value": value, "comment": review_comments[key]}
|
||||
return nodes_output
|
||||
|
||||
async def auto_revise(
|
||||
self, revise_mode: ReviseMode = ReviseMode.AUTO, template: str = REVISE_TEMPLATE
|
||||
) -> dict[str, str]:
|
||||
"""revise the value of incorrect keys"""
|
||||
# generate review comments
|
||||
if revise_mode == ReviseMode.AUTO:
|
||||
review_comments: dict = await self.auto_review()
|
||||
elif revise_mode == ReviseMode.HUMAN_REVIEW:
|
||||
review_comments: dict = await self.human_review()
|
||||
|
||||
include_keys = list(review_comments.keys())
|
||||
|
||||
# generate revise content, two-steps
|
||||
# step1, find the needed revise keys from review comments to makeup prompt template
|
||||
nodes_output = self._makeup_nodes_output_with_comment(review_comments)
|
||||
keys = self.keys()
|
||||
exclude_keys = list(set(keys).difference(include_keys))
|
||||
example = self.compile_example(schema="json", mode="auto", tag=TAG, exclude=exclude_keys)
|
||||
instruction = self.compile_instruction(schema="markdown", mode="auto", exclude=exclude_keys)
|
||||
|
||||
prompt = template.format(
|
||||
nodes_output=json.dumps(nodes_output, ensure_ascii=False),
|
||||
example=example,
|
||||
instruction=instruction,
|
||||
constraint=FORMAT_CONSTRAINT,
|
||||
prompt_schema="json",
|
||||
)
|
||||
|
||||
# step2, use `_aask_v1` to get revise structure result
|
||||
output_mapping = self.get_mapping(mode="auto", exclude=exclude_keys)
|
||||
output_class_name = f"{self.key}_AN_REVISE"
|
||||
content, scontent = await self._aask_v1(
|
||||
prompt=prompt, output_class_name=output_class_name, output_data_mapping=output_mapping, schema="json"
|
||||
)
|
||||
|
||||
# re-fill the ActionNode
|
||||
sc_dict = scontent.model_dump()
|
||||
self.update_instruct_content(sc_dict)
|
||||
return sc_dict
|
||||
|
||||
async def simple_revise(self, revise_mode: ReviseMode = ReviseMode.AUTO) -> dict[str, str]:
|
||||
if revise_mode == ReviseMode.HUMAN:
|
||||
revise_contents = await self.human_revise()
|
||||
else:
|
||||
revise_contents = await self.auto_revise(revise_mode)
|
||||
|
||||
return revise_contents
|
||||
|
||||
async def revise(self, strgy: str = "simple", revise_mode: ReviseMode = ReviseMode.AUTO) -> dict[str, str]:
|
||||
"""revise the content of ActionNode and update the instruct_content
|
||||
|
||||
:param strgy: simple/complex
|
||||
- simple: run only once
|
||||
- complex: run each node
|
||||
"""
|
||||
if not hasattr(self, "llm"):
|
||||
raise RuntimeError("use `revise` after `fill`")
|
||||
assert revise_mode in ReviseMode
|
||||
assert self.instruct_content, 'revise only support with `schema != "raw"`'
|
||||
|
||||
if strgy == "simple":
|
||||
revise_contents = await self.simple_revise(revise_mode)
|
||||
elif strgy == "complex":
|
||||
# revise each child node one-by-one
|
||||
revise_contents = {}
|
||||
for _, child in self.children.items():
|
||||
child_revise_content = await child.simple_revise(revise_mode)
|
||||
revise_contents.update(child_revise_content)
|
||||
self.update_instruct_content(revise_contents)
|
||||
|
||||
return revise_contents
|
||||
|
||||
@classmethod
|
||||
def from_pydantic(cls, model: Type[BaseModel], key: str = None):
|
||||
"""
|
||||
Creates an ActionNode tree from a Pydantic model.
|
||||
|
||||
Args:
|
||||
model (Type[BaseModel]): The Pydantic model to convert.
|
||||
|
||||
Returns:
|
||||
ActionNode: The root node of the created ActionNode tree.
|
||||
"""
|
||||
key = key or model.__name__
|
||||
root_node = cls(key=key, expected_type=Type[model], instruction="", example="")
|
||||
|
||||
for field_name, field_info in model.model_fields.items():
|
||||
field_type = field_info.annotation
|
||||
description = field_info.description
|
||||
default = field_info.default
|
||||
|
||||
# Recursively handle nested models if needed
|
||||
if not isinstance(field_type, typing._GenericAlias) and issubclass(field_type, BaseModel):
|
||||
child_node = cls.from_pydantic(field_type, key=field_name)
|
||||
else:
|
||||
child_node = cls(key=field_name, expected_type=field_type, instruction=description, example=default)
|
||||
|
||||
root_node.add_child(child_node)
|
||||
|
||||
return root_node
|
||||
|
|
|
|||
42
metagpt/actions/action_outcls_registry.py
Normal file
42
metagpt/actions/action_outcls_registry.py
Normal file
|
|
@ -0,0 +1,42 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
# @Desc : registry to store Dynamic Model from ActionNode.create_model_class to keep it as same Class
|
||||
# with same class name and mapping
|
||||
|
||||
from functools import wraps
|
||||
|
||||
action_outcls_registry = dict()
|
||||
|
||||
|
||||
def register_action_outcls(func):
|
||||
"""
|
||||
Due to `create_model` return different Class even they have same class name and mapping.
|
||||
In order to do a comparison, use outcls_id to identify same Class with same class name and field definition
|
||||
"""
|
||||
|
||||
@wraps(func)
|
||||
def decorater(*args, **kwargs):
|
||||
"""
|
||||
arr example
|
||||
[<class 'metagpt.actions.action_node.ActionNode'>, 'test', {'field': (str, Ellipsis)}]
|
||||
"""
|
||||
arr = list(args) + list(kwargs.values())
|
||||
"""
|
||||
outcls_id example
|
||||
"<class 'metagpt.actions.action_node.ActionNode'>_test_{'field': (str, Ellipsis)}"
|
||||
"""
|
||||
for idx, item in enumerate(arr):
|
||||
if isinstance(item, dict):
|
||||
arr[idx] = dict(sorted(item.items()))
|
||||
outcls_id = "_".join([str(i) for i in arr])
|
||||
# eliminate typing influence
|
||||
outcls_id = outcls_id.replace("typing.List", "list").replace("typing.Dict", "dict")
|
||||
|
||||
if outcls_id in action_outcls_registry:
|
||||
return action_outcls_registry[outcls_id]
|
||||
|
||||
out_cls = func(*args, **kwargs)
|
||||
action_outcls_registry[outcls_id] = out_cls
|
||||
return out_cls
|
||||
|
||||
return decorater
|
||||
|
|
@ -13,12 +13,9 @@ import re
|
|||
from pydantic import Field
|
||||
|
||||
from metagpt.actions.action import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import TEST_CODES_FILE_REPO, TEST_OUTPUTS_FILE_REPO
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import RunCodeContext, RunCodeResult
|
||||
from metagpt.utils.common import CodeParser
|
||||
from metagpt.utils.file_repository import FileRepository
|
||||
|
||||
PROMPT_TEMPLATE = """
|
||||
NOTICE
|
||||
|
|
@ -49,13 +46,10 @@ Now you should start rewriting the code:
|
|||
|
||||
|
||||
class DebugError(Action):
|
||||
name: str = "DebugError"
|
||||
context: RunCodeContext = Field(default_factory=RunCodeContext)
|
||||
i_context: RunCodeContext = Field(default_factory=RunCodeContext)
|
||||
|
||||
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 self.repo.test_outputs.get(filename=self.i_context.output_filename)
|
||||
if not output_doc:
|
||||
return ""
|
||||
output_detail = RunCodeResult.loads(output_doc.content)
|
||||
|
|
@ -64,15 +58,13 @@ class DebugError(Action):
|
|||
if matches:
|
||||
return ""
|
||||
|
||||
logger.info(f"Debug and rewrite {self.context.test_filename}")
|
||||
code_doc = await FileRepository.get_file(
|
||||
filename=self.context.code_filename, relative_path=CONFIG.src_workspace
|
||||
logger.info(f"Debug and rewrite {self.i_context.test_filename}")
|
||||
code_doc = await self.repo.with_src_path(self.context.src_workspace).srcs.get(
|
||||
filename=self.i_context.code_filename
|
||||
)
|
||||
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 self.repo.tests.get(filename=self.i_context.test_filename)
|
||||
if not test_doc:
|
||||
return ""
|
||||
prompt = PROMPT_TEMPLATE.format(code=code_doc.content, test_code=test_doc.content, logs=output_detail.stderr)
|
||||
|
|
|
|||
|
|
@ -14,18 +14,17 @@ from pathlib import Path
|
|||
from typing import Optional
|
||||
|
||||
from metagpt.actions import Action, ActionOutput
|
||||
from metagpt.actions.design_api_an import DESIGN_API_NODE
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import (
|
||||
DATA_API_DESIGN_FILE_REPO,
|
||||
PRDS_FILE_REPO,
|
||||
SEQ_FLOW_FILE_REPO,
|
||||
SYSTEM_DESIGN_FILE_REPO,
|
||||
SYSTEM_DESIGN_PDF_FILE_REPO,
|
||||
from metagpt.actions.design_api_an import (
|
||||
DATA_STRUCTURES_AND_INTERFACES,
|
||||
DESIGN_API_NODE,
|
||||
PROGRAM_CALL_FLOW,
|
||||
REFINED_DATA_STRUCTURES_AND_INTERFACES,
|
||||
REFINED_DESIGN_NODE,
|
||||
REFINED_PROGRAM_CALL_FLOW,
|
||||
)
|
||||
from metagpt.const import DATA_API_DESIGN_FILE_REPO, SEQ_FLOW_FILE_REPO
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import Document, Documents, Message
|
||||
from metagpt.utils.file_repository import FileRepository
|
||||
from metagpt.utils.mermaid import mermaid_to_file
|
||||
|
||||
NEW_REQ_TEMPLATE = """
|
||||
|
|
@ -39,36 +38,30 @@ NEW_REQ_TEMPLATE = """
|
|||
|
||||
class WriteDesign(Action):
|
||||
name: str = ""
|
||||
context: Optional[str] = None
|
||||
i_context: Optional[str] = None
|
||||
desc: str = (
|
||||
"Based on the PRD, think about the system design, and design the corresponding APIs, "
|
||||
"data structures, library tables, processes, and paths. Please provide your design, feedback "
|
||||
"clearly and in detail."
|
||||
)
|
||||
|
||||
async def run(self, with_messages: Message, schema: str = CONFIG.prompt_schema):
|
||||
# Use `git status` to identify which PRD documents have been modified in the `docs/prds` directory.
|
||||
prds_file_repo = CONFIG.git_repo.new_file_repository(PRDS_FILE_REPO)
|
||||
changed_prds = prds_file_repo.changed_files
|
||||
async def run(self, with_messages: Message, schema: str = None):
|
||||
# Use `git status` to identify which PRD documents have been modified in the `docs/prd` directory.
|
||||
changed_prds = self.repo.docs.prd.changed_files
|
||||
# Use `git status` to identify which design documents in the `docs/system_designs` directory have undergone
|
||||
# changes.
|
||||
system_design_file_repo = CONFIG.git_repo.new_file_repository(SYSTEM_DESIGN_FILE_REPO)
|
||||
changed_system_designs = system_design_file_repo.changed_files
|
||||
changed_system_designs = self.repo.docs.system_design.changed_files
|
||||
|
||||
# For those PRDs and design documents that have undergone changes, regenerate the design content.
|
||||
changed_files = Documents()
|
||||
for filename in changed_prds.keys():
|
||||
doc = await self._update_system_design(
|
||||
filename=filename, prds_file_repo=prds_file_repo, system_design_file_repo=system_design_file_repo
|
||||
)
|
||||
doc = await self._update_system_design(filename=filename)
|
||||
changed_files.docs[filename] = doc
|
||||
|
||||
for filename in changed_system_designs.keys():
|
||||
if filename in changed_files.docs:
|
||||
continue
|
||||
doc = await self._update_system_design(
|
||||
filename=filename, prds_file_repo=prds_file_repo, system_design_file_repo=system_design_file_repo
|
||||
)
|
||||
doc = await self._update_system_design(filename=filename)
|
||||
changed_files.docs[filename] = doc
|
||||
if not changed_files.docs:
|
||||
logger.info("Nothing has changed.")
|
||||
|
|
@ -76,61 +69,52 @@ class WriteDesign(Action):
|
|||
# leaving room for global optimization in subsequent steps.
|
||||
return ActionOutput(content=changed_files.model_dump_json(), instruct_content=changed_files)
|
||||
|
||||
async def _new_system_design(self, context, schema=CONFIG.prompt_schema):
|
||||
node = await DESIGN_API_NODE.fill(context=context, llm=self.llm, schema=schema)
|
||||
async def _new_system_design(self, context):
|
||||
node = await DESIGN_API_NODE.fill(context=context, llm=self.llm)
|
||||
return node
|
||||
|
||||
async def _merge(self, prd_doc, system_design_doc, schema=CONFIG.prompt_schema):
|
||||
async def _merge(self, prd_doc, system_design_doc):
|
||||
context = NEW_REQ_TEMPLATE.format(old_design=system_design_doc.content, context=prd_doc.content)
|
||||
node = await DESIGN_API_NODE.fill(context=context, llm=self.llm, schema=schema)
|
||||
node = await REFINED_DESIGN_NODE.fill(context=context, llm=self.llm)
|
||||
system_design_doc.content = node.instruct_content.model_dump_json()
|
||||
return system_design_doc
|
||||
|
||||
async def _update_system_design(self, filename, prds_file_repo, system_design_file_repo) -> Document:
|
||||
prd = await prds_file_repo.get(filename)
|
||||
old_system_design_doc = await system_design_file_repo.get(filename)
|
||||
async def _update_system_design(self, filename) -> Document:
|
||||
prd = await self.repo.docs.prd.get(filename)
|
||||
old_system_design_doc = await self.repo.docs.system_design.get(filename)
|
||||
if not old_system_design_doc:
|
||||
system_design = await self._new_system_design(context=prd.content)
|
||||
doc = Document(
|
||||
root_path=SYSTEM_DESIGN_FILE_REPO,
|
||||
doc = await self.repo.docs.system_design.save(
|
||||
filename=filename,
|
||||
content=system_design.instruct_content.model_dump_json(),
|
||||
dependencies={prd.root_relative_path},
|
||||
)
|
||||
else:
|
||||
doc = await self._merge(prd_doc=prd, system_design_doc=old_system_design_doc)
|
||||
await system_design_file_repo.save(
|
||||
filename=filename, content=doc.content, dependencies={prd.root_relative_path}
|
||||
)
|
||||
await self.repo.docs.system_design.save_doc(doc=doc, dependencies={prd.root_relative_path})
|
||||
await self._save_data_api_design(doc)
|
||||
await self._save_seq_flow(doc)
|
||||
await self._save_pdf(doc)
|
||||
await self.repo.resources.system_design.save_pdf(doc=doc)
|
||||
return doc
|
||||
|
||||
@staticmethod
|
||||
async def _save_data_api_design(design_doc):
|
||||
async def _save_data_api_design(self, design_doc):
|
||||
m = json.loads(design_doc.content)
|
||||
data_api_design = m.get("Data structures and interfaces")
|
||||
data_api_design = m.get(DATA_STRUCTURES_AND_INTERFACES.key) or m.get(REFINED_DATA_STRUCTURES_AND_INTERFACES.key)
|
||||
if not data_api_design:
|
||||
return
|
||||
pathname = CONFIG.git_repo.workdir / DATA_API_DESIGN_FILE_REPO / Path(design_doc.filename).with_suffix("")
|
||||
await WriteDesign._save_mermaid_file(data_api_design, pathname)
|
||||
pathname = self.repo.workdir / DATA_API_DESIGN_FILE_REPO / Path(design_doc.filename).with_suffix("")
|
||||
await self._save_mermaid_file(data_api_design, pathname)
|
||||
logger.info(f"Save class view to {str(pathname)}")
|
||||
|
||||
@staticmethod
|
||||
async def _save_seq_flow(design_doc):
|
||||
async def _save_seq_flow(self, design_doc):
|
||||
m = json.loads(design_doc.content)
|
||||
seq_flow = m.get("Program call flow")
|
||||
seq_flow = m.get(PROGRAM_CALL_FLOW.key) or m.get(REFINED_PROGRAM_CALL_FLOW.key)
|
||||
if not seq_flow:
|
||||
return
|
||||
pathname = CONFIG.git_repo.workdir / Path(SEQ_FLOW_FILE_REPO) / Path(design_doc.filename).with_suffix("")
|
||||
await WriteDesign._save_mermaid_file(seq_flow, pathname)
|
||||
pathname = self.repo.workdir / Path(SEQ_FLOW_FILE_REPO) / Path(design_doc.filename).with_suffix("")
|
||||
await self._save_mermaid_file(seq_flow, pathname)
|
||||
logger.info(f"Saving sequence flow to {str(pathname)}")
|
||||
|
||||
@staticmethod
|
||||
async def _save_pdf(design_doc):
|
||||
await FileRepository.save_as(doc=design_doc, with_suffix=".md", relative_path=SYSTEM_DESIGN_PDF_FILE_REPO)
|
||||
|
||||
@staticmethod
|
||||
async def _save_mermaid_file(data: str, pathname: Path):
|
||||
async def _save_mermaid_file(self, data: str, pathname: Path):
|
||||
pathname.parent.mkdir(parents=True, exist_ok=True)
|
||||
await mermaid_to_file(data, pathname)
|
||||
await mermaid_to_file(self.config.mermaid.engine, data, pathname)
|
||||
|
|
|
|||
|
|
@ -17,6 +17,15 @@ IMPLEMENTATION_APPROACH = ActionNode(
|
|||
example="We will ...",
|
||||
)
|
||||
|
||||
REFINED_IMPLEMENTATION_APPROACH = ActionNode(
|
||||
key="Refined Implementation Approach",
|
||||
expected_type=str,
|
||||
instruction="Update and extend the original implementation approach to reflect the evolving challenges and "
|
||||
"requirements due to incremental development. Outline the steps involved in the implementation process with the "
|
||||
"detailed strategies.",
|
||||
example="We will refine ...",
|
||||
)
|
||||
|
||||
PROJECT_NAME = ActionNode(
|
||||
key="Project name", expected_type=str, instruction="The project name with underline", example="game_2048"
|
||||
)
|
||||
|
|
@ -28,6 +37,14 @@ FILE_LIST = ActionNode(
|
|||
example=["main.py", "game.py"],
|
||||
)
|
||||
|
||||
REFINED_FILE_LIST = ActionNode(
|
||||
key="Refined File list",
|
||||
expected_type=List[str],
|
||||
instruction="Update and expand the original file list including only relative paths. Up to 2 files can be added."
|
||||
"Ensure that the refined file list reflects the evolving structure of the project.",
|
||||
example=["main.py", "game.py", "new_feature.py"],
|
||||
)
|
||||
|
||||
DATA_STRUCTURES_AND_INTERFACES = ActionNode(
|
||||
key="Data structures and interfaces",
|
||||
expected_type=str,
|
||||
|
|
@ -37,6 +54,16 @@ DATA_STRUCTURES_AND_INTERFACES = ActionNode(
|
|||
example=MMC1,
|
||||
)
|
||||
|
||||
REFINED_DATA_STRUCTURES_AND_INTERFACES = ActionNode(
|
||||
key="Refined Data structures and interfaces",
|
||||
expected_type=str,
|
||||
instruction="Update and extend the existing mermaid classDiagram code syntax to incorporate new classes, "
|
||||
"methods (including __init__), and functions with precise type annotations. Delineate additional "
|
||||
"relationships between classes, ensuring clarity and adherence to PEP8 standards."
|
||||
"Retain content that is not related to incremental development but important for consistency and clarity.",
|
||||
example=MMC1,
|
||||
)
|
||||
|
||||
PROGRAM_CALL_FLOW = ActionNode(
|
||||
key="Program call flow",
|
||||
expected_type=str,
|
||||
|
|
@ -45,6 +72,16 @@ PROGRAM_CALL_FLOW = ActionNode(
|
|||
example=MMC2,
|
||||
)
|
||||
|
||||
REFINED_PROGRAM_CALL_FLOW = ActionNode(
|
||||
key="Refined Program call flow",
|
||||
expected_type=str,
|
||||
instruction="Extend the existing sequenceDiagram code syntax with detailed information, accurately covering the"
|
||||
"CRUD and initialization of each object. Ensure correct syntax usage and reflect the incremental changes introduced"
|
||||
"in the classes and API defined above. "
|
||||
"Retain content that is not related to incremental development but important for consistency and clarity.",
|
||||
example=MMC2,
|
||||
)
|
||||
|
||||
ANYTHING_UNCLEAR = ActionNode(
|
||||
key="Anything UNCLEAR",
|
||||
expected_type=str,
|
||||
|
|
@ -61,4 +98,13 @@ NODES = [
|
|||
ANYTHING_UNCLEAR,
|
||||
]
|
||||
|
||||
REFINED_NODES = [
|
||||
REFINED_IMPLEMENTATION_APPROACH,
|
||||
REFINED_FILE_LIST,
|
||||
REFINED_DATA_STRUCTURES_AND_INTERFACES,
|
||||
REFINED_PROGRAM_CALL_FLOW,
|
||||
ANYTHING_UNCLEAR,
|
||||
]
|
||||
|
||||
DESIGN_API_NODE = ActionNode.from_children("DesignAPI", NODES)
|
||||
REFINED_DESIGN_NODE = ActionNode.from_children("RefinedDesignAPI", REFINED_NODES)
|
||||
|
|
|
|||
|
|
@ -13,7 +13,7 @@ from metagpt.actions.action import Action
|
|||
|
||||
class DesignReview(Action):
|
||||
name: str = "DesignReview"
|
||||
context: Optional[str] = None
|
||||
i_context: Optional[str] = None
|
||||
|
||||
async def run(self, prd, api_design):
|
||||
prompt = (
|
||||
|
|
|
|||
0
metagpt/actions/di/__init__.py
Normal file
0
metagpt/actions/di/__init__.py
Normal file
62
metagpt/actions/di/ask_review.py
Normal file
62
metagpt/actions/di/ask_review.py
Normal file
|
|
@ -0,0 +1,62 @@
|
|||
from __future__ import annotations
|
||||
|
||||
from typing import Tuple
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import Message, Plan
|
||||
|
||||
|
||||
class ReviewConst:
|
||||
TASK_REVIEW_TRIGGER = "task"
|
||||
CODE_REVIEW_TRIGGER = "code"
|
||||
CONTINUE_WORDS = ["confirm", "continue", "c", "yes", "y"]
|
||||
CHANGE_WORDS = ["change"]
|
||||
EXIT_WORDS = ["exit"]
|
||||
TASK_REVIEW_INSTRUCTION = (
|
||||
f"If you want to change, add, delete a task or merge tasks in the plan, say '{CHANGE_WORDS[0]} task task_id or current task, ... (things to change)' "
|
||||
f"If you confirm the output from the current task and wish to continue, type: {CONTINUE_WORDS[0]}"
|
||||
)
|
||||
CODE_REVIEW_INSTRUCTION = (
|
||||
f"If you want the codes to be rewritten, say '{CHANGE_WORDS[0]} ... (your change advice)' "
|
||||
f"If you want to leave it as is, type: {CONTINUE_WORDS[0]} or {CONTINUE_WORDS[1]}"
|
||||
)
|
||||
EXIT_INSTRUCTION = f"If you want to terminate the process, type: {EXIT_WORDS[0]}"
|
||||
|
||||
|
||||
class AskReview(Action):
|
||||
async def run(
|
||||
self, context: list[Message] = [], plan: Plan = None, trigger: str = ReviewConst.TASK_REVIEW_TRIGGER
|
||||
) -> Tuple[str, bool]:
|
||||
if plan:
|
||||
logger.info("Current overall plan:")
|
||||
logger.info(
|
||||
"\n".join(
|
||||
[f"{task.task_id}: {task.instruction}, is_finished: {task.is_finished}" for task in plan.tasks]
|
||||
)
|
||||
)
|
||||
|
||||
logger.info("Most recent context:")
|
||||
latest_action = context[-1].cause_by if context and context[-1].cause_by else ""
|
||||
review_instruction = (
|
||||
ReviewConst.TASK_REVIEW_INSTRUCTION
|
||||
if trigger == ReviewConst.TASK_REVIEW_TRIGGER
|
||||
else ReviewConst.CODE_REVIEW_INSTRUCTION
|
||||
)
|
||||
prompt = (
|
||||
f"This is a <{trigger}> review. Please review output from {latest_action}\n"
|
||||
f"{review_instruction}\n"
|
||||
f"{ReviewConst.EXIT_INSTRUCTION}\n"
|
||||
"Please type your review below:\n"
|
||||
)
|
||||
|
||||
rsp = input(prompt)
|
||||
|
||||
if rsp.lower() in ReviewConst.EXIT_WORDS:
|
||||
exit()
|
||||
|
||||
# Confirmation can be one of "confirm", "continue", "c", "yes", "y" exactly, or sentences containing "confirm".
|
||||
# One could say "confirm this task, but change the next task to ..."
|
||||
confirmed = rsp.lower() in ReviewConst.CONTINUE_WORDS or ReviewConst.CONTINUE_WORDS[0] in rsp.lower()
|
||||
|
||||
return rsp, confirmed
|
||||
256
metagpt/actions/di/execute_nb_code.py
Normal file
256
metagpt/actions/di/execute_nb_code.py
Normal file
|
|
@ -0,0 +1,256 @@
|
|||
# -*- encoding: utf-8 -*-
|
||||
"""
|
||||
@Date : 2023/11/17 14:22:15
|
||||
@Author : orange-crow
|
||||
@File : execute_nb_code.py
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import base64
|
||||
import re
|
||||
from typing import Literal, Tuple
|
||||
|
||||
import nbformat
|
||||
from nbclient import NotebookClient
|
||||
from nbclient.exceptions import CellTimeoutError, DeadKernelError
|
||||
from nbformat import NotebookNode
|
||||
from nbformat.v4 import new_code_cell, new_markdown_cell, new_output
|
||||
from rich.box import MINIMAL
|
||||
from rich.console import Console, Group
|
||||
from rich.live import Live
|
||||
from rich.markdown import Markdown
|
||||
from rich.panel import Panel
|
||||
from rich.syntax import Syntax
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.logs import logger
|
||||
|
||||
|
||||
class ExecuteNbCode(Action):
|
||||
"""execute notebook code block, return result to llm, and display it."""
|
||||
|
||||
nb: NotebookNode
|
||||
nb_client: NotebookClient
|
||||
console: Console
|
||||
interaction: str
|
||||
timeout: int = 600
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
nb=nbformat.v4.new_notebook(),
|
||||
timeout=600,
|
||||
):
|
||||
super().__init__(
|
||||
nb=nb,
|
||||
nb_client=NotebookClient(nb, timeout=timeout),
|
||||
timeout=timeout,
|
||||
console=Console(),
|
||||
interaction=("ipython" if self.is_ipython() else "terminal"),
|
||||
)
|
||||
|
||||
async def build(self):
|
||||
if self.nb_client.kc is None or not await self.nb_client.kc.is_alive():
|
||||
self.nb_client.create_kernel_manager()
|
||||
self.nb_client.start_new_kernel()
|
||||
self.nb_client.start_new_kernel_client()
|
||||
|
||||
async def terminate(self):
|
||||
"""kill NotebookClient"""
|
||||
if self.nb_client.km is not None and await self.nb_client.km.is_alive():
|
||||
await self.nb_client.km.shutdown_kernel(now=True)
|
||||
await self.nb_client.km.cleanup_resources()
|
||||
|
||||
channels = [
|
||||
self.nb_client.kc.stdin_channel, # The channel for handling standard input to the kernel.
|
||||
self.nb_client.kc.hb_channel, # The channel for heartbeat communication between the kernel and client.
|
||||
self.nb_client.kc.control_channel, # The channel for controlling the kernel.
|
||||
]
|
||||
|
||||
# Stops all the running channels for this kernel
|
||||
for channel in channels:
|
||||
if channel.is_alive():
|
||||
channel.stop()
|
||||
|
||||
self.nb_client.kc = None
|
||||
self.nb_client.km = None
|
||||
|
||||
async def reset(self):
|
||||
"""reset NotebookClient"""
|
||||
await self.terminate()
|
||||
|
||||
# sleep 1s to wait for the kernel to be cleaned up completely
|
||||
await asyncio.sleep(1)
|
||||
await self.build()
|
||||
self.nb_client = NotebookClient(self.nb, timeout=self.timeout)
|
||||
|
||||
def add_code_cell(self, code: str):
|
||||
self.nb.cells.append(new_code_cell(source=code))
|
||||
|
||||
def add_markdown_cell(self, markdown: str):
|
||||
self.nb.cells.append(new_markdown_cell(source=markdown))
|
||||
|
||||
def _display(self, code: str, language: Literal["python", "markdown"] = "python"):
|
||||
if language == "python":
|
||||
code = Syntax(code, "python", theme="paraiso-dark", line_numbers=True)
|
||||
self.console.print(code)
|
||||
elif language == "markdown":
|
||||
display_markdown(code)
|
||||
else:
|
||||
raise ValueError(f"Only support for python, markdown, but got {language}")
|
||||
|
||||
def add_output_to_cell(self, cell: NotebookNode, output: str):
|
||||
"""add outputs of code execution to notebook cell."""
|
||||
if "outputs" not in cell:
|
||||
cell["outputs"] = []
|
||||
else:
|
||||
cell["outputs"].append(new_output(output_type="stream", name="stdout", text=str(output)))
|
||||
|
||||
def parse_outputs(self, outputs: list[str], keep_len: int = 2000) -> Tuple[bool, str]:
|
||||
"""Parses the outputs received from notebook execution."""
|
||||
assert isinstance(outputs, list)
|
||||
parsed_output, is_success = [], True
|
||||
for i, output in enumerate(outputs):
|
||||
output_text = ""
|
||||
if output["output_type"] == "stream" and not any(
|
||||
tag in output["text"]
|
||||
for tag in ["| INFO | metagpt", "| ERROR | metagpt", "| WARNING | metagpt", "DEBUG"]
|
||||
):
|
||||
output_text = output["text"]
|
||||
elif output["output_type"] == "display_data":
|
||||
if "image/png" in output["data"]:
|
||||
self.show_bytes_figure(output["data"]["image/png"], self.interaction)
|
||||
else:
|
||||
logger.info(
|
||||
f"{i}th output['data'] from nbclient outputs dont have image/png, continue next output ..."
|
||||
)
|
||||
elif output["output_type"] == "execute_result":
|
||||
output_text = output["data"]["text/plain"]
|
||||
elif output["output_type"] == "error":
|
||||
output_text, is_success = "\n".join(output["traceback"]), False
|
||||
|
||||
# handle coroutines that are not executed asynchronously
|
||||
if output_text.strip().startswith("<coroutine object"):
|
||||
output_text = "Executed code failed, you need use key word 'await' to run a async code."
|
||||
is_success = False
|
||||
|
||||
output_text = remove_escape_and_color_codes(output_text)
|
||||
# The useful information of the exception is at the end,
|
||||
# the useful information of normal output is at the begining.
|
||||
output_text = output_text[:keep_len] if is_success else output_text[-keep_len:]
|
||||
|
||||
parsed_output.append(output_text)
|
||||
return is_success, ",".join(parsed_output)
|
||||
|
||||
def show_bytes_figure(self, image_base64: str, interaction_type: Literal["ipython", None]):
|
||||
image_bytes = base64.b64decode(image_base64)
|
||||
if interaction_type == "ipython":
|
||||
from IPython.display import Image, display
|
||||
|
||||
display(Image(data=image_bytes))
|
||||
else:
|
||||
import io
|
||||
|
||||
from PIL import Image
|
||||
|
||||
image = Image.open(io.BytesIO(image_bytes))
|
||||
image.show()
|
||||
|
||||
def is_ipython(self) -> bool:
|
||||
try:
|
||||
# 如果在Jupyter Notebook中运行，__file__ 变量不存在
|
||||
from IPython import get_ipython
|
||||
|
||||
if get_ipython() is not None and "IPKernelApp" in get_ipython().config:
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
except NameError:
|
||||
return False
|
||||
|
||||
async def run_cell(self, cell: NotebookNode, cell_index: int) -> Tuple[bool, str]:
|
||||
"""set timeout for run code.
|
||||
returns the success or failure of the cell execution, and an optional error message.
|
||||
"""
|
||||
try:
|
||||
await self.nb_client.async_execute_cell(cell, cell_index)
|
||||
return self.parse_outputs(self.nb.cells[-1].outputs)
|
||||
except CellTimeoutError:
|
||||
assert self.nb_client.km is not None
|
||||
await self.nb_client.km.interrupt_kernel()
|
||||
await asyncio.sleep(1)
|
||||
error_msg = "Cell execution timed out: Execution exceeded the time limit and was stopped; consider optimizing your code for better performance."
|
||||
return False, error_msg
|
||||
except DeadKernelError:
|
||||
await self.reset()
|
||||
return False, "DeadKernelError"
|
||||
except Exception:
|
||||
return self.parse_outputs(self.nb.cells[-1].outputs)
|
||||
|
||||
async def run(self, code: str, language: Literal["python", "markdown"] = "python") -> Tuple[str, bool]:
|
||||
"""
|
||||
return the output of code execution, and a success indicator (bool) of code execution.
|
||||
"""
|
||||
self._display(code, language)
|
||||
|
||||
if language == "python":
|
||||
# add code to the notebook
|
||||
self.add_code_cell(code=code)
|
||||
|
||||
# build code executor
|
||||
await self.build()
|
||||
|
||||
# run code
|
||||
cell_index = len(self.nb.cells) - 1
|
||||
success, outputs = await self.run_cell(self.nb.cells[-1], cell_index)
|
||||
|
||||
if "!pip" in code:
|
||||
success = False
|
||||
|
||||
return outputs, success
|
||||
|
||||
elif language == "markdown":
|
||||
# add markdown content to markdown cell in a notebook.
|
||||
self.add_markdown_cell(code)
|
||||
# return True, beacuse there is no execution failure for markdown cell.
|
||||
return code, True
|
||||
else:
|
||||
raise ValueError(f"Only support for language: python, markdown, but got {language}, ")
|
||||
|
||||
|
||||
def remove_escape_and_color_codes(input_str: str):
|
||||
# 使用正则表达式去除jupyter notebook输出结果中的转义字符和颜色代码
|
||||
# Use regular expressions to get rid of escape characters and color codes in jupyter notebook output.
|
||||
pattern = re.compile(r"\x1b\[[0-9;]*[mK]")
|
||||
result = pattern.sub("", input_str)
|
||||
return result
|
||||
|
||||
|
||||
def display_markdown(content: str):
|
||||
# Use regular expressions to match blocks of code one by one.
|
||||
matches = re.finditer(r"```(.+?)```", content, re.DOTALL)
|
||||
start_index = 0
|
||||
content_panels = []
|
||||
# Set the text background color and text color.
|
||||
style = "black on white"
|
||||
# Print the matching text and code one by one.
|
||||
for match in matches:
|
||||
text_content = content[start_index : match.start()].strip()
|
||||
code_content = match.group(0).strip()[3:-3] # Remove triple backticks
|
||||
|
||||
if text_content:
|
||||
content_panels.append(Panel(Markdown(text_content), style=style, box=MINIMAL))
|
||||
|
||||
if code_content:
|
||||
content_panels.append(Panel(Markdown(f"```{code_content}"), style=style, box=MINIMAL))
|
||||
start_index = match.end()
|
||||
|
||||
# Print remaining text (if any).
|
||||
remaining_text = content[start_index:].strip()
|
||||
if remaining_text:
|
||||
content_panels.append(Panel(Markdown(remaining_text), style=style, box=MINIMAL))
|
||||
|
||||
# Display all panels in Live mode.
|
||||
with Live(auto_refresh=False, console=Console(), vertical_overflow="visible") as live:
|
||||
live.update(Group(*content_panels))
|
||||
live.refresh()
|
||||
73
metagpt/actions/di/write_analysis_code.py
Normal file
73
metagpt/actions/di/write_analysis_code.py
Normal file
|
|
@ -0,0 +1,73 @@
|
|||
# -*- encoding: utf-8 -*-
|
||||
"""
|
||||
@Date : 2023/11/20 13:19:39
|
||||
@Author : orange-crow
|
||||
@File : write_analysis_code.py
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.prompts.di.write_analysis_code import (
|
||||
CHECK_DATA_PROMPT,
|
||||
DEBUG_REFLECTION_EXAMPLE,
|
||||
INTERPRETER_SYSTEM_MSG,
|
||||
REFLECTION_PROMPT,
|
||||
REFLECTION_SYSTEM_MSG,
|
||||
STRUCTUAL_PROMPT,
|
||||
)
|
||||
from metagpt.schema import Message, Plan
|
||||
from metagpt.utils.common import CodeParser, process_message, remove_comments
|
||||
|
||||
|
||||
class WriteAnalysisCode(Action):
|
||||
async def _debug_with_reflection(self, context: list[Message], working_memory: list[Message]):
|
||||
reflection_prompt = REFLECTION_PROMPT.format(
|
||||
debug_example=DEBUG_REFLECTION_EXAMPLE,
|
||||
context=context,
|
||||
previous_impl=working_memory,
|
||||
)
|
||||
|
||||
rsp = await self._aask(reflection_prompt, system_msgs=[REFLECTION_SYSTEM_MSG])
|
||||
reflection = json.loads(CodeParser.parse_code(block=None, text=rsp))
|
||||
|
||||
return reflection["improved_impl"]
|
||||
|
||||
async def run(
|
||||
self,
|
||||
user_requirement: str,
|
||||
plan_status: str = "",
|
||||
tool_info: str = "",
|
||||
working_memory: list[Message] = None,
|
||||
use_reflection: bool = False,
|
||||
**kwargs,
|
||||
) -> str:
|
||||
structual_prompt = STRUCTUAL_PROMPT.format(
|
||||
user_requirement=user_requirement,
|
||||
plan_status=plan_status,
|
||||
tool_info=tool_info,
|
||||
)
|
||||
|
||||
working_memory = working_memory or []
|
||||
context = process_message([Message(content=structual_prompt, role="user")] + working_memory)
|
||||
|
||||
# LLM call
|
||||
if use_reflection:
|
||||
code = await self._debug_with_reflection(context=context, working_memory=working_memory)
|
||||
else:
|
||||
rsp = await self.llm.aask(context, system_msgs=[INTERPRETER_SYSTEM_MSG], **kwargs)
|
||||
code = CodeParser.parse_code(block=None, text=rsp)
|
||||
|
||||
return code
|
||||
|
||||
|
||||
class CheckData(Action):
|
||||
async def run(self, plan: Plan) -> dict:
|
||||
finished_tasks = plan.get_finished_tasks()
|
||||
code_written = [remove_comments(task.code) for task in finished_tasks]
|
||||
code_written = "\n\n".join(code_written)
|
||||
prompt = CHECK_DATA_PROMPT.format(code_written=code_written)
|
||||
rsp = await self._aask(prompt)
|
||||
code = CodeParser.parse_code(block=None, text=rsp)
|
||||
return code
|
||||
84
metagpt/actions/di/write_plan.py
Normal file
84
metagpt/actions/di/write_plan.py
Normal file
|
|
@ -0,0 +1,84 @@
|
|||
# -*- encoding: utf-8 -*-
|
||||
"""
|
||||
@Date : 2023/11/20 11:24:03
|
||||
@Author : orange-crow
|
||||
@File : plan.py
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from copy import deepcopy
|
||||
from typing import Tuple
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import Message, Plan, Task
|
||||
from metagpt.strategy.task_type import TaskType
|
||||
from metagpt.utils.common import CodeParser
|
||||
|
||||
|
||||
class WritePlan(Action):
|
||||
PROMPT_TEMPLATE: str = """
|
||||
# Context:
|
||||
{context}
|
||||
# Available Task Types:
|
||||
{task_type_desc}
|
||||
# Task:
|
||||
Based on the context, write a plan or modify an existing plan of what you should do to achieve the goal. A plan consists of one to {max_tasks} tasks.
|
||||
If you are modifying an existing plan, carefully follow the instruction, don't make unnecessary changes. Give the whole plan unless instructed to modify only one task of the plan.
|
||||
If you encounter errors on the current task, revise and output the current single task only.
|
||||
Output a list of jsons following the format:
|
||||
```json
|
||||
[
|
||||
{{
|
||||
"task_id": str = "unique identifier for a task in plan, can be an ordinal",
|
||||
"dependent_task_ids": list[str] = "ids of tasks prerequisite to this task",
|
||||
"instruction": "what you should do in this task, one short phrase or sentence",
|
||||
"task_type": "type of this task, should be one of Available Task Types",
|
||||
}},
|
||||
...
|
||||
]
|
||||
```
|
||||
"""
|
||||
|
||||
async def run(self, context: list[Message], max_tasks: int = 5) -> str:
|
||||
task_type_desc = "\n".join([f"- **{tt.type_name}**: {tt.value.desc}" for tt in TaskType])
|
||||
prompt = self.PROMPT_TEMPLATE.format(
|
||||
context="\n".join([str(ct) for ct in context]), max_tasks=max_tasks, task_type_desc=task_type_desc
|
||||
)
|
||||
rsp = await self._aask(prompt)
|
||||
rsp = CodeParser.parse_code(block=None, text=rsp)
|
||||
return rsp
|
||||
|
||||
|
||||
def update_plan_from_rsp(rsp: str, current_plan: Plan):
|
||||
rsp = json.loads(rsp)
|
||||
tasks = [Task(**task_config) for task_config in rsp]
|
||||
|
||||
if len(tasks) == 1 or tasks[0].dependent_task_ids:
|
||||
if tasks[0].dependent_task_ids and len(tasks) > 1:
|
||||
# tasks[0].dependent_task_ids means the generated tasks are not a complete plan
|
||||
# for they depend on tasks in the current plan, in this case, we only support updating one task each time
|
||||
logger.warning(
|
||||
"Current plan will take only the first generated task if the generated tasks are not a complete plan"
|
||||
)
|
||||
# handle a single task
|
||||
if current_plan.has_task_id(tasks[0].task_id):
|
||||
# replace an existing task
|
||||
current_plan.replace_task(tasks[0])
|
||||
else:
|
||||
# append one task
|
||||
current_plan.append_task(tasks[0])
|
||||
|
||||
else:
|
||||
# add tasks in general
|
||||
current_plan.add_tasks(tasks)
|
||||
|
||||
|
||||
def precheck_update_plan_from_rsp(rsp: str, current_plan: Plan) -> Tuple[bool, str]:
|
||||
temp_plan = deepcopy(current_plan)
|
||||
try:
|
||||
update_plan_from_rsp(rsp, temp_plan)
|
||||
return True, ""
|
||||
except Exception as e:
|
||||
return False, e
|
||||
|
|
@ -13,7 +13,7 @@ from metagpt.schema import Message
|
|||
|
||||
class ExecuteTask(Action):
|
||||
name: str = "ExecuteTask"
|
||||
context: list[Message] = []
|
||||
i_context: list[Message] = []
|
||||
|
||||
async def run(self, *args, **kwargs):
|
||||
pass
|
||||
|
|
|
|||
|
|
@ -1,8 +1,6 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/9/12 17:45
|
||||
@Author : fisherdeng
|
||||
@File : generate_questions.py
|
||||
"""
|
||||
from metagpt.actions import Action
|
||||
|
|
@ -23,5 +21,5 @@ class GenerateQuestions(Action):
|
|||
|
||||
name: str = "GenerateQuestions"
|
||||
|
||||
async def run(self, context):
|
||||
async def run(self, context) -> ActionNode:
|
||||
return await QUESTIONS.fill(context=context, llm=self.llm)
|
||||
|
|
|
|||
|
|
@ -16,17 +16,14 @@ from typing import Optional
|
|||
|
||||
import pandas as pd
|
||||
from paddleocr import PaddleOCR
|
||||
from pydantic import Field
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.const import INVOICE_OCR_TABLE_PATH
|
||||
from metagpt.llm import LLM
|
||||
from metagpt.logs import logger
|
||||
from metagpt.prompts.invoice_ocr import (
|
||||
EXTRACT_OCR_MAIN_INFO_PROMPT,
|
||||
REPLY_OCR_QUESTION_PROMPT,
|
||||
)
|
||||
from metagpt.provider.base_llm import BaseLLM
|
||||
from metagpt.utils.common import OutputParser
|
||||
from metagpt.utils.file import File
|
||||
|
||||
|
|
@ -41,7 +38,7 @@ class InvoiceOCR(Action):
|
|||
"""
|
||||
|
||||
name: str = "InvoiceOCR"
|
||||
context: Optional[str] = None
|
||||
i_context: Optional[str] = None
|
||||
|
||||
@staticmethod
|
||||
async def _check_file_type(file_path: Path) -> str:
|
||||
|
|
@ -132,8 +129,7 @@ class GenerateTable(Action):
|
|||
"""
|
||||
|
||||
name: str = "GenerateTable"
|
||||
context: Optional[str] = None
|
||||
llm: BaseLLM = Field(default_factory=LLM)
|
||||
i_context: Optional[str] = None
|
||||
language: str = "ch"
|
||||
|
||||
async def run(self, ocr_results: list, filename: str, *args, **kwargs) -> dict[str, str]:
|
||||
|
|
@ -176,9 +172,6 @@ class ReplyQuestion(Action):
|
|||
|
||||
"""
|
||||
|
||||
name: str = "ReplyQuestion"
|
||||
context: Optional[str] = None
|
||||
llm: BaseLLM = Field(default_factory=LLM)
|
||||
language: str = "ch"
|
||||
|
||||
async def run(self, query: str, ocr_result: list, *args, **kwargs) -> str:
|
||||
|
|
|
|||
|
|
@ -12,39 +12,41 @@ from pathlib import Path
|
|||
from typing import Optional
|
||||
|
||||
from metagpt.actions import Action, ActionOutput
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import DOCS_FILE_REPO, REQUIREMENT_FILENAME
|
||||
from metagpt.schema import Document
|
||||
from metagpt.const import REQUIREMENT_FILENAME
|
||||
from metagpt.utils.file_repository import FileRepository
|
||||
from metagpt.utils.git_repository import GitRepository
|
||||
from metagpt.utils.project_repo import ProjectRepo
|
||||
|
||||
|
||||
class PrepareDocuments(Action):
|
||||
"""PrepareDocuments Action: initialize project folder and add new requirements to docs/requirements.txt."""
|
||||
|
||||
name: str = "PrepareDocuments"
|
||||
context: Optional[str] = None
|
||||
i_context: Optional[str] = None
|
||||
|
||||
@property
|
||||
def config(self):
|
||||
return self.context.config
|
||||
|
||||
def _init_repo(self):
|
||||
"""Initialize the Git environment."""
|
||||
if not CONFIG.project_path:
|
||||
name = CONFIG.project_name or FileRepository.new_filename()
|
||||
path = Path(CONFIG.workspace_path) / name
|
||||
if not self.config.project_path:
|
||||
name = self.config.project_name or FileRepository.new_filename()
|
||||
path = Path(self.config.workspace.path) / name
|
||||
else:
|
||||
path = Path(CONFIG.project_path)
|
||||
if path.exists() and not CONFIG.inc:
|
||||
path = Path(self.config.project_path)
|
||||
if path.exists() and not self.config.inc:
|
||||
shutil.rmtree(path)
|
||||
CONFIG.project_path = path
|
||||
CONFIG.git_repo = GitRepository(local_path=path, auto_init=True)
|
||||
self.config.project_path = path
|
||||
self.context.git_repo = GitRepository(local_path=path, auto_init=True)
|
||||
self.context.repo = ProjectRepo(self.context.git_repo)
|
||||
|
||||
async def run(self, with_messages, **kwargs):
|
||||
"""Create and initialize the workspace folder, initialize the Git environment."""
|
||||
self._init_repo()
|
||||
|
||||
# Write the newly added requirements from the main parameter idea to `docs/requirement.txt`.
|
||||
doc = Document(root_path=DOCS_FILE_REPO, filename=REQUIREMENT_FILENAME, content=with_messages[0].content)
|
||||
await FileRepository.save_file(filename=REQUIREMENT_FILENAME, content=doc.content, relative_path=DOCS_FILE_REPO)
|
||||
|
||||
doc = await self.repo.docs.save(filename=REQUIREMENT_FILENAME, content=with_messages[0].content)
|
||||
# Send a Message notification to the WritePRD action, instructing it to process requirements using
|
||||
# `docs/requirement.txt` and `docs/prds/`.
|
||||
# `docs/requirement.txt` and `docs/prd/`.
|
||||
return ActionOutput(content=doc.content, instruct_content=doc)
|
||||
|
|
|
|||
|
|
@ -13,23 +13,16 @@
|
|||
import json
|
||||
from typing import Optional
|
||||
|
||||
from metagpt.actions import ActionOutput
|
||||
from metagpt.actions.action import Action
|
||||
from metagpt.actions.project_management_an import PM_NODE
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import (
|
||||
PACKAGE_REQUIREMENTS_FILENAME,
|
||||
SYSTEM_DESIGN_FILE_REPO,
|
||||
TASK_FILE_REPO,
|
||||
TASK_PDF_FILE_REPO,
|
||||
)
|
||||
from metagpt.actions.action_output import ActionOutput
|
||||
from metagpt.actions.project_management_an import PM_NODE, REFINED_PM_NODE
|
||||
from metagpt.const import PACKAGE_REQUIREMENTS_FILENAME
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import Document, Documents
|
||||
from metagpt.utils.file_repository import FileRepository
|
||||
|
||||
NEW_REQ_TEMPLATE = """
|
||||
### Legacy Content
|
||||
{old_tasks}
|
||||
{old_task}
|
||||
|
||||
### New Requirements
|
||||
{context}
|
||||
|
|
@ -38,30 +31,23 @@ NEW_REQ_TEMPLATE = """
|
|||
|
||||
class WriteTasks(Action):
|
||||
name: str = "CreateTasks"
|
||||
context: Optional[str] = None
|
||||
i_context: Optional[str] = None
|
||||
|
||||
async def run(self, with_messages, schema=CONFIG.prompt_schema):
|
||||
system_design_file_repo = CONFIG.git_repo.new_file_repository(SYSTEM_DESIGN_FILE_REPO)
|
||||
changed_system_designs = system_design_file_repo.changed_files
|
||||
|
||||
tasks_file_repo = CONFIG.git_repo.new_file_repository(TASK_FILE_REPO)
|
||||
changed_tasks = tasks_file_repo.changed_files
|
||||
async def run(self, with_messages):
|
||||
changed_system_designs = self.repo.docs.system_design.changed_files
|
||||
changed_tasks = self.repo.docs.task.changed_files
|
||||
change_files = Documents()
|
||||
# Rewrite the system designs that have undergone changes based on the git head diff under
|
||||
# `docs/system_designs/`.
|
||||
for filename in changed_system_designs:
|
||||
task_doc = await self._update_tasks(
|
||||
filename=filename, system_design_file_repo=system_design_file_repo, tasks_file_repo=tasks_file_repo
|
||||
)
|
||||
task_doc = await self._update_tasks(filename=filename)
|
||||
change_files.docs[filename] = task_doc
|
||||
|
||||
# Rewrite the task files that have undergone changes based on the git head diff under `docs/tasks/`.
|
||||
for filename in changed_tasks:
|
||||
if filename in change_files.docs:
|
||||
continue
|
||||
task_doc = await self._update_tasks(
|
||||
filename=filename, system_design_file_repo=system_design_file_repo, tasks_file_repo=tasks_file_repo
|
||||
)
|
||||
task_doc = await self._update_tasks(filename=filename)
|
||||
change_files.docs[filename] = task_doc
|
||||
|
||||
if not change_files.docs:
|
||||
|
|
@ -70,39 +56,36 @@ class WriteTasks(Action):
|
|||
# global optimization in subsequent steps.
|
||||
return ActionOutput(content=change_files.model_dump_json(), instruct_content=change_files)
|
||||
|
||||
async def _update_tasks(self, filename, system_design_file_repo, tasks_file_repo):
|
||||
system_design_doc = await system_design_file_repo.get(filename)
|
||||
task_doc = await tasks_file_repo.get(filename)
|
||||
async def _update_tasks(self, filename):
|
||||
system_design_doc = await self.repo.docs.system_design.get(filename)
|
||||
task_doc = await self.repo.docs.task.get(filename)
|
||||
if task_doc:
|
||||
task_doc = await self._merge(system_design_doc=system_design_doc, task_doc=task_doc)
|
||||
await self.repo.docs.task.save_doc(doc=task_doc, dependencies={system_design_doc.root_relative_path})
|
||||
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.model_dump_json()
|
||||
task_doc = await self.repo.docs.task.save(
|
||||
filename=filename,
|
||||
content=rsp.instruct_content.model_dump_json(),
|
||||
dependencies={system_design_doc.root_relative_path},
|
||||
)
|
||||
await tasks_file_repo.save(
|
||||
filename=filename, content=task_doc.content, dependencies={system_design_doc.root_relative_path}
|
||||
)
|
||||
await self._update_requirements(task_doc)
|
||||
await self._save_pdf(task_doc=task_doc)
|
||||
return task_doc
|
||||
|
||||
async def _run_new_tasks(self, context, schema=CONFIG.prompt_schema):
|
||||
node = await PM_NODE.fill(context, self.llm, schema)
|
||||
async def _run_new_tasks(self, context):
|
||||
node = await PM_NODE.fill(context, self.llm, schema=self.prompt_schema)
|
||||
return node
|
||||
|
||||
async def _merge(self, system_design_doc, task_doc, schema=CONFIG.prompt_schema) -> Document:
|
||||
context = NEW_REQ_TEMPLATE.format(context=system_design_doc.content, old_tasks=task_doc.content)
|
||||
node = await PM_NODE.fill(context, self.llm, schema)
|
||||
async def _merge(self, system_design_doc, task_doc) -> Document:
|
||||
context = NEW_REQ_TEMPLATE.format(context=system_design_doc.content, old_task=task_doc.content)
|
||||
node = await REFINED_PM_NODE.fill(context, self.llm, schema=self.prompt_schema)
|
||||
task_doc.content = node.instruct_content.model_dump_json()
|
||||
return task_doc
|
||||
|
||||
@staticmethod
|
||||
async def _update_requirements(doc):
|
||||
async def _update_requirements(self, doc):
|
||||
m = json.loads(doc.content)
|
||||
packages = set(m.get("Required Python third-party packages", set()))
|
||||
file_repo = CONFIG.git_repo.new_file_repository()
|
||||
requirement_doc = await file_repo.get(filename=PACKAGE_REQUIREMENTS_FILENAME)
|
||||
packages = set(m.get("Required Python packages", set()))
|
||||
requirement_doc = await self.repo.get(filename=PACKAGE_REQUIREMENTS_FILENAME)
|
||||
if not requirement_doc:
|
||||
requirement_doc = Document(filename=PACKAGE_REQUIREMENTS_FILENAME, root_path=".", content="")
|
||||
lines = requirement_doc.content.splitlines()
|
||||
|
|
@ -110,8 +93,4 @@ class WriteTasks(Action):
|
|||
if pkg == "":
|
||||
continue
|
||||
packages.add(pkg)
|
||||
await file_repo.save(PACKAGE_REQUIREMENTS_FILENAME, content="\n".join(packages))
|
||||
|
||||
@staticmethod
|
||||
async def _save_pdf(task_doc):
|
||||
await FileRepository.save_as(doc=task_doc, with_suffix=".md", relative_path=TASK_PDF_FILE_REPO)
|
||||
await self.repo.save(filename=PACKAGE_REQUIREMENTS_FILENAME, content="\n".join(packages))
|
||||
|
|
|
|||
|
|
@ -8,7 +8,6 @@
|
|||
from typing import List
|
||||
|
||||
from metagpt.actions.action_node import ActionNode
|
||||
from metagpt.logs import logger
|
||||
|
||||
REQUIRED_PYTHON_PACKAGES = ActionNode(
|
||||
key="Required Python packages",
|
||||
|
|
@ -35,6 +34,20 @@ LOGIC_ANALYSIS = ActionNode(
|
|||
],
|
||||
)
|
||||
|
||||
REFINED_LOGIC_ANALYSIS = ActionNode(
|
||||
key="Refined Logic Analysis",
|
||||
expected_type=List[List[str]],
|
||||
instruction="Review and refine the logic analysis by merging the Legacy Content and Incremental Content. "
|
||||
"Provide a comprehensive list of files with classes/methods/functions to be implemented or modified incrementally. "
|
||||
"Include dependency analysis, consider potential impacts on existing code, and document necessary imports.",
|
||||
example=[
|
||||
["game.py", "Contains Game class and ... functions"],
|
||||
["main.py", "Contains main function, from game import Game"],
|
||||
["new_feature.py", "Introduces NewFeature class and related functions"],
|
||||
["utils.py", "Modifies existing utility functions to support incremental changes"],
|
||||
],
|
||||
)
|
||||
|
||||
TASK_LIST = ActionNode(
|
||||
key="Task list",
|
||||
expected_type=List[str],
|
||||
|
|
@ -42,6 +55,15 @@ TASK_LIST = ActionNode(
|
|||
example=["game.py", "main.py"],
|
||||
)
|
||||
|
||||
REFINED_TASK_LIST = ActionNode(
|
||||
key="Refined Task list",
|
||||
expected_type=List[str],
|
||||
instruction="Review and refine the combined task list after the merger of Legacy Content and Incremental Content, "
|
||||
"and consistent with Refined File List. Ensure that tasks are organized in a logical and prioritized order, "
|
||||
"considering dependencies for a streamlined and efficient development process. ",
|
||||
example=["new_feature.py", "utils", "game.py", "main.py"],
|
||||
)
|
||||
|
||||
FULL_API_SPEC = ActionNode(
|
||||
key="Full API spec",
|
||||
expected_type=str,
|
||||
|
|
@ -54,9 +76,19 @@ SHARED_KNOWLEDGE = ActionNode(
|
|||
key="Shared Knowledge",
|
||||
expected_type=str,
|
||||
instruction="Detail any shared knowledge, like common utility functions or configuration variables.",
|
||||
example="'game.py' contains functions shared across the project.",
|
||||
example="`game.py` contains functions shared across the project.",
|
||||
)
|
||||
|
||||
REFINED_SHARED_KNOWLEDGE = ActionNode(
|
||||
key="Refined Shared Knowledge",
|
||||
expected_type=str,
|
||||
instruction="Update and expand shared knowledge to reflect any new elements introduced. This includes common "
|
||||
"utility functions, configuration variables for team collaboration. Retain content that is not related to "
|
||||
"incremental development but important for consistency and clarity.",
|
||||
example="`new_module.py` enhances shared utility functions for improved code reusability and collaboration.",
|
||||
)
|
||||
|
||||
|
||||
ANYTHING_UNCLEAR_PM = ActionNode(
|
||||
key="Anything UNCLEAR",
|
||||
expected_type=str,
|
||||
|
|
@ -74,14 +106,15 @@ NODES = [
|
|||
ANYTHING_UNCLEAR_PM,
|
||||
]
|
||||
|
||||
REFINED_NODES = [
|
||||
REQUIRED_PYTHON_PACKAGES,
|
||||
REQUIRED_OTHER_LANGUAGE_PACKAGES,
|
||||
REFINED_LOGIC_ANALYSIS,
|
||||
REFINED_TASK_LIST,
|
||||
FULL_API_SPEC,
|
||||
REFINED_SHARED_KNOWLEDGE,
|
||||
ANYTHING_UNCLEAR_PM,
|
||||
]
|
||||
|
||||
PM_NODE = ActionNode.from_children("PM_NODE", NODES)
|
||||
|
||||
|
||||
def main():
|
||||
prompt = PM_NODE.compile(context="")
|
||||
logger.info(prompt)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
REFINED_PM_NODE = ActionNode.from_children("REFINED_PM_NODE", REFINED_NODES)
|
||||
|
|
|
|||
|
|
@ -4,15 +4,17 @@
|
|||
@Time : 2023/12/19
|
||||
@Author : mashenquan
|
||||
@File : rebuild_class_view.py
|
||||
@Desc : Rebuild class view info
|
||||
@Desc : Reconstructs class diagram from a source code project.
|
||||
Implement RFC197, https://deepwisdom.feishu.cn/wiki/VyK0wfq56ivuvjklMKJcmHQknGt
|
||||
"""
|
||||
import re
|
||||
|
||||
from pathlib import Path
|
||||
from typing import Optional, Set, Tuple
|
||||
|
||||
import aiofiles
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.config2 import config
|
||||
from metagpt.const import (
|
||||
AGGREGATION,
|
||||
COMPOSITION,
|
||||
|
|
@ -21,86 +23,144 @@ from metagpt.const import (
|
|||
GRAPH_REPO_FILE_REPO,
|
||||
)
|
||||
from metagpt.logs import logger
|
||||
from metagpt.repo_parser import RepoParser
|
||||
from metagpt.schema import ClassAttribute, ClassMethod, ClassView
|
||||
from metagpt.utils.common import split_namespace
|
||||
from metagpt.repo_parser import DotClassInfo, RepoParser
|
||||
from metagpt.schema import UMLClassView
|
||||
from metagpt.utils.common import concat_namespace, split_namespace
|
||||
from metagpt.utils.di_graph_repository import DiGraphRepository
|
||||
from metagpt.utils.graph_repository import GraphKeyword, GraphRepository
|
||||
|
||||
|
||||
class RebuildClassView(Action):
|
||||
async def run(self, with_messages=None, format=CONFIG.prompt_schema):
|
||||
graph_repo_pathname = CONFIG.git_repo.workdir / GRAPH_REPO_FILE_REPO / CONFIG.git_repo.workdir.name
|
||||
graph_db = await DiGraphRepository.load_from(str(graph_repo_pathname.with_suffix(".json")))
|
||||
repo_parser = RepoParser(base_directory=Path(self.context))
|
||||
"""
|
||||
Reconstructs a graph repository about class diagram from a source code project.
|
||||
|
||||
Attributes:
|
||||
graph_db (Optional[GraphRepository]): The optional graph repository.
|
||||
"""
|
||||
|
||||
graph_db: Optional[GraphRepository] = None
|
||||
|
||||
async def run(self, with_messages=None, format=config.prompt_schema):
|
||||
"""
|
||||
Implementation of `Action`'s `run` method.
|
||||
|
||||
Args:
|
||||
with_messages (Optional[Type]): An optional argument specifying messages to react to.
|
||||
format (str): The format for the prompt schema.
|
||||
"""
|
||||
graph_repo_pathname = self.context.git_repo.workdir / GRAPH_REPO_FILE_REPO / self.context.git_repo.workdir.name
|
||||
self.graph_db = await DiGraphRepository.load_from(str(graph_repo_pathname.with_suffix(".json")))
|
||||
repo_parser = RepoParser(base_directory=Path(self.i_context))
|
||||
# use pylint
|
||||
class_views, relationship_views, package_root = await repo_parser.rebuild_class_views(path=Path(self.context))
|
||||
await GraphRepository.update_graph_db_with_class_views(graph_db, class_views)
|
||||
await GraphRepository.update_graph_db_with_class_relationship_views(graph_db, relationship_views)
|
||||
class_views, relationship_views, package_root = await repo_parser.rebuild_class_views(path=Path(self.i_context))
|
||||
await GraphRepository.update_graph_db_with_class_views(self.graph_db, class_views)
|
||||
await GraphRepository.update_graph_db_with_class_relationship_views(self.graph_db, relationship_views)
|
||||
await GraphRepository.rebuild_composition_relationship(self.graph_db)
|
||||
# use ast
|
||||
direction, diff_path = self._diff_path(path_root=Path(self.context).resolve(), package_root=package_root)
|
||||
direction, diff_path = self._diff_path(path_root=Path(self.i_context).resolve(), package_root=package_root)
|
||||
symbols = repo_parser.generate_symbols()
|
||||
for file_info in symbols:
|
||||
# Align to the same root directory in accordance with `class_views`.
|
||||
file_info.file = self._align_root(file_info.file, direction, diff_path)
|
||||
await GraphRepository.update_graph_db_with_file_info(graph_db, file_info)
|
||||
await self._create_mermaid_class_views(graph_db=graph_db)
|
||||
await graph_db.save()
|
||||
await GraphRepository.update_graph_db_with_file_info(self.graph_db, file_info)
|
||||
await self._create_mermaid_class_views()
|
||||
await self.graph_db.save()
|
||||
|
||||
async def _create_mermaid_class_views(self, graph_db):
|
||||
path = Path(CONFIG.git_repo.workdir) / DATA_API_DESIGN_FILE_REPO
|
||||
async def _create_mermaid_class_views(self) -> str:
|
||||
"""Creates a Mermaid class diagram using data from the `graph_db` graph repository.
|
||||
|
||||
This method utilizes information stored in the graph repository to generate a Mermaid class diagram.
|
||||
Returns:
|
||||
mermaid class diagram file name.
|
||||
"""
|
||||
path = self.context.git_repo.workdir / DATA_API_DESIGN_FILE_REPO
|
||||
path.mkdir(parents=True, exist_ok=True)
|
||||
pathname = path / CONFIG.git_repo.workdir.name
|
||||
async with aiofiles.open(str(pathname.with_suffix(".mmd")), mode="w", encoding="utf-8") as writer:
|
||||
pathname = path / self.context.git_repo.workdir.name
|
||||
filename = str(pathname.with_suffix(".class_diagram.mmd"))
|
||||
async with aiofiles.open(filename, mode="w", encoding="utf-8") as writer:
|
||||
content = "classDiagram\n"
|
||||
logger.debug(content)
|
||||
await writer.write(content)
|
||||
# class names
|
||||
rows = await graph_db.select(predicate=GraphKeyword.IS, object_=GraphKeyword.CLASS)
|
||||
rows = await self.graph_db.select(predicate=GraphKeyword.IS, object_=GraphKeyword.CLASS)
|
||||
class_distinct = set()
|
||||
relationship_distinct = set()
|
||||
for r in rows:
|
||||
await RebuildClassView._create_mermaid_class(r.subject, graph_db, writer, class_distinct)
|
||||
content = await self._create_mermaid_class(r.subject)
|
||||
if content:
|
||||
await writer.write(content)
|
||||
class_distinct.add(r.subject)
|
||||
for r in rows:
|
||||
await RebuildClassView._create_mermaid_relationship(r.subject, graph_db, writer, relationship_distinct)
|
||||
content, distinct = await self._create_mermaid_relationship(r.subject)
|
||||
if content:
|
||||
logger.debug(content)
|
||||
await writer.write(content)
|
||||
relationship_distinct.update(distinct)
|
||||
logger.info(f"classes: {len(class_distinct)}, relationship: {len(relationship_distinct)}")
|
||||
|
||||
@staticmethod
|
||||
async def _create_mermaid_class(ns_class_name, graph_db, file_writer, distinct):
|
||||
if self.i_context:
|
||||
r_filename = Path(filename).relative_to(self.context.git_repo.workdir)
|
||||
await self.graph_db.insert(
|
||||
subject=self.i_context, predicate="hasMermaidClassDiagramFile", object_=str(r_filename)
|
||||
)
|
||||
logger.info(f"{self.i_context} hasMermaidClassDiagramFile {filename}")
|
||||
return filename
|
||||
|
||||
async def _create_mermaid_class(self, ns_class_name) -> str:
|
||||
"""Generates a Mermaid class diagram for a specific class using data from the `graph_db` graph repository.
|
||||
|
||||
Args:
|
||||
ns_class_name (str): The namespace-prefixed name of the class for which the Mermaid class diagram is to be created.
|
||||
|
||||
Returns:
|
||||
str: A Mermaid code block object in markdown representing the class diagram.
|
||||
"""
|
||||
fields = split_namespace(ns_class_name)
|
||||
if len(fields) > 2:
|
||||
# Ignore sub-class
|
||||
return
|
||||
return ""
|
||||
|
||||
class_view = ClassView(name=fields[1])
|
||||
rows = await graph_db.select(subject=ns_class_name)
|
||||
for r in rows:
|
||||
name = split_namespace(r.object_)[-1]
|
||||
name, visibility, abstraction = RebuildClassView._parse_name(name=name, language="python")
|
||||
if r.predicate == GraphKeyword.HAS_CLASS_PROPERTY:
|
||||
var_type = await RebuildClassView._parse_variable_type(r.object_, graph_db)
|
||||
attribute = ClassAttribute(
|
||||
name=name, visibility=visibility, abstraction=bool(abstraction), value_type=var_type
|
||||
)
|
||||
class_view.attributes.append(attribute)
|
||||
elif r.predicate == GraphKeyword.HAS_CLASS_FUNCTION:
|
||||
method = ClassMethod(name=name, visibility=visibility, abstraction=bool(abstraction))
|
||||
await RebuildClassView._parse_function_args(method, r.object_, graph_db)
|
||||
class_view.methods.append(method)
|
||||
rows = await self.graph_db.select(subject=ns_class_name, predicate=GraphKeyword.HAS_DETAIL)
|
||||
if not rows:
|
||||
return ""
|
||||
dot_class_info = DotClassInfo.model_validate_json(rows[0].object_)
|
||||
class_view = UMLClassView.load_dot_class_info(dot_class_info)
|
||||
|
||||
# update graph db
|
||||
await graph_db.insert(ns_class_name, GraphKeyword.HAS_CLASS_VIEW, class_view.model_dump_json())
|
||||
# update uml view
|
||||
await self.graph_db.insert(ns_class_name, GraphKeyword.HAS_CLASS_VIEW, class_view.model_dump_json())
|
||||
# update uml isCompositeOf
|
||||
for c in dot_class_info.compositions:
|
||||
await self.graph_db.insert(
|
||||
subject=ns_class_name,
|
||||
predicate=GraphKeyword.IS + COMPOSITION + GraphKeyword.OF,
|
||||
object_=concat_namespace("?", c),
|
||||
)
|
||||
|
||||
# update uml isAggregateOf
|
||||
for a in dot_class_info.aggregations:
|
||||
await self.graph_db.insert(
|
||||
subject=ns_class_name,
|
||||
predicate=GraphKeyword.IS + AGGREGATION + GraphKeyword.OF,
|
||||
object_=concat_namespace("?", a),
|
||||
)
|
||||
|
||||
content = class_view.get_mermaid(align=1)
|
||||
logger.debug(content)
|
||||
await file_writer.write(content)
|
||||
distinct.add(ns_class_name)
|
||||
return content
|
||||
|
||||
@staticmethod
|
||||
async def _create_mermaid_relationship(ns_class_name, graph_db, file_writer, distinct):
|
||||
async def _create_mermaid_relationship(self, ns_class_name: str) -> Tuple[Optional[str], Optional[Set]]:
|
||||
"""Generates a Mermaid class relationship diagram for a specific class using data from the `graph_db` graph repository.
|
||||
|
||||
Args:
|
||||
ns_class_name (str): The namespace-prefixed class name for which the Mermaid relationship diagram is to be created.
|
||||
|
||||
Returns:
|
||||
Tuple[str, Set]: A tuple containing the relationship diagram as a string and a set of deduplication.
|
||||
"""
|
||||
s_fields = split_namespace(ns_class_name)
|
||||
if len(s_fields) > 2:
|
||||
# Ignore sub-class
|
||||
return
|
||||
return None, None
|
||||
|
||||
predicates = {GraphKeyword.IS + v + GraphKeyword.OF: v for v in [GENERALIZATION, COMPOSITION, AGGREGATION]}
|
||||
mappings = {
|
||||
|
|
@ -109,8 +169,9 @@ class RebuildClassView(Action):
|
|||
AGGREGATION: " o-- ",
|
||||
}
|
||||
content = ""
|
||||
distinct = set()
|
||||
for p, v in predicates.items():
|
||||
rows = await graph_db.select(subject=ns_class_name, predicate=p)
|
||||
rows = await self.graph_db.select(subject=ns_class_name, predicate=p)
|
||||
for r in rows:
|
||||
o_fields = split_namespace(r.object_)
|
||||
if len(o_fields) > 2:
|
||||
|
|
@ -121,86 +182,26 @@ class RebuildClassView(Action):
|
|||
distinct.add(link)
|
||||
content += f"\t{link}\n"
|
||||
|
||||
if content:
|
||||
logger.debug(content)
|
||||
await file_writer.write(content)
|
||||
|
||||
@staticmethod
|
||||
def _parse_name(name: str, language="python"):
|
||||
pattern = re.compile(r"<I>(.*?)<\/I>")
|
||||
result = re.search(pattern, name)
|
||||
|
||||
abstraction = ""
|
||||
if result:
|
||||
name = result.group(1)
|
||||
abstraction = "*"
|
||||
if name.startswith("__"):
|
||||
visibility = "-"
|
||||
elif name.startswith("_"):
|
||||
visibility = "#"
|
||||
else:
|
||||
visibility = "+"
|
||||
return name, visibility, abstraction
|
||||
|
||||
@staticmethod
|
||||
async def _parse_variable_type(ns_name, graph_db) -> str:
|
||||
rows = await graph_db.select(subject=ns_name, predicate=GraphKeyword.HAS_TYPE_DESC)
|
||||
if not rows:
|
||||
return ""
|
||||
vals = rows[0].object_.replace("'", "").split(":")
|
||||
if len(vals) == 1:
|
||||
return ""
|
||||
val = vals[-1].strip()
|
||||
return "" if val == "NoneType" else val + " "
|
||||
|
||||
@staticmethod
|
||||
async def _parse_function_args(method: ClassMethod, ns_name: str, graph_db: GraphRepository):
|
||||
rows = await graph_db.select(subject=ns_name, predicate=GraphKeyword.HAS_ARGS_DESC)
|
||||
if not rows:
|
||||
return
|
||||
info = rows[0].object_.replace("'", "")
|
||||
|
||||
fs_tag = "("
|
||||
ix = info.find(fs_tag)
|
||||
fe_tag = "):"
|
||||
eix = info.rfind(fe_tag)
|
||||
if eix < 0:
|
||||
fe_tag = ")"
|
||||
eix = info.rfind(fe_tag)
|
||||
args_info = info[ix + len(fs_tag) : eix].strip()
|
||||
method.return_type = info[eix + len(fe_tag) :].strip()
|
||||
if method.return_type == "None":
|
||||
method.return_type = ""
|
||||
if "(" in method.return_type:
|
||||
method.return_type = method.return_type.replace("(", "Tuple[").replace(")", "]")
|
||||
|
||||
# parse args
|
||||
if not args_info:
|
||||
return
|
||||
splitter_ixs = []
|
||||
cost = 0
|
||||
for i in range(len(args_info)):
|
||||
if args_info[i] == "[":
|
||||
cost += 1
|
||||
elif args_info[i] == "]":
|
||||
cost -= 1
|
||||
if args_info[i] == "," and cost == 0:
|
||||
splitter_ixs.append(i)
|
||||
splitter_ixs.append(len(args_info))
|
||||
args = []
|
||||
ix = 0
|
||||
for eix in splitter_ixs:
|
||||
args.append(args_info[ix:eix])
|
||||
ix = eix + 1
|
||||
for arg in args:
|
||||
parts = arg.strip().split(":")
|
||||
if len(parts) == 1:
|
||||
method.args.append(ClassAttribute(name=parts[0].strip()))
|
||||
continue
|
||||
method.args.append(ClassAttribute(name=parts[0].strip(), value_type=parts[-1].strip()))
|
||||
return content, distinct
|
||||
|
||||
@staticmethod
|
||||
def _diff_path(path_root: Path, package_root: Path) -> (str, str):
|
||||
"""Returns the difference between the root path and the path information represented in the package name.
|
||||
|
||||
Args:
|
||||
path_root (Path): The root path.
|
||||
package_root (Path): The package root path.
|
||||
|
||||
Returns:
|
||||
Tuple[str, str]: A tuple containing the representation of the difference ("+", "-", "=") and the path detail of the differing part.
|
||||
|
||||
Example:
|
||||
>>> _diff_path(path_root=Path("/Users/x/github/MetaGPT"), package_root=Path("/Users/x/github/MetaGPT/metagpt"))
|
||||
"-", "metagpt"
|
||||
|
||||
>>> _diff_path(path_root=Path("/Users/x/github/MetaGPT/metagpt"), package_root=Path("/Users/x/github/MetaGPT/metagpt"))
|
||||
"=", "."
|
||||
"""
|
||||
if len(str(path_root)) > len(str(package_root)):
|
||||
return "+", str(path_root.relative_to(package_root))
|
||||
if len(str(path_root)) < len(str(package_root)):
|
||||
|
|
@ -208,7 +209,24 @@ class RebuildClassView(Action):
|
|||
return "=", "."
|
||||
|
||||
@staticmethod
|
||||
def _align_root(path: str, direction: str, diff_path: str):
|
||||
def _align_root(path: str, direction: str, diff_path: str) -> str:
|
||||
"""Aligns the path to the same root represented by `diff_path`.
|
||||
|
||||
Args:
|
||||
path (str): The path to be aligned.
|
||||
direction (str): The direction of alignment ('+', '-', '=').
|
||||
diff_path (str): The path representing the difference.
|
||||
|
||||
Returns:
|
||||
str: The aligned path.
|
||||
|
||||
Example:
|
||||
>>> _align_root(path="metagpt/software_company.py", direction="+", diff_path="MetaGPT")
|
||||
"MetaGPT/metagpt/software_company.py"
|
||||
|
||||
>>> _align_root(path="metagpt/software_company.py", direction="-", diff_path="metagpt")
|
||||
"software_company.py"
|
||||
"""
|
||||
if direction == "=":
|
||||
return path
|
||||
if direction == "+":
|
||||
|
|
|
|||
|
|
@ -4,34 +4,214 @@
|
|||
@Time : 2024/1/4
|
||||
@Author : mashenquan
|
||||
@File : rebuild_sequence_view.py
|
||||
@Desc : Rebuild sequence view info
|
||||
@Desc : Reconstruct sequence view information through reverse engineering.
|
||||
Implement RFC197, https://deepwisdom.feishu.cn/wiki/VyK0wfq56ivuvjklMKJcmHQknGt
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
from typing import List
|
||||
from typing import List, Optional, Set
|
||||
|
||||
from pydantic import BaseModel
|
||||
from tenacity import retry, stop_after_attempt, wait_random_exponential
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.config2 import config
|
||||
from metagpt.const import GRAPH_REPO_FILE_REPO
|
||||
from metagpt.logs import logger
|
||||
from metagpt.utils.common import aread, list_files
|
||||
from metagpt.repo_parser import CodeBlockInfo, DotClassInfo
|
||||
from metagpt.schema import UMLClassView
|
||||
from metagpt.utils.common import (
|
||||
add_affix,
|
||||
aread,
|
||||
auto_namespace,
|
||||
concat_namespace,
|
||||
general_after_log,
|
||||
list_files,
|
||||
parse_json_code_block,
|
||||
read_file_block,
|
||||
split_namespace,
|
||||
)
|
||||
from metagpt.utils.di_graph_repository import DiGraphRepository
|
||||
from metagpt.utils.graph_repository import GraphKeyword
|
||||
from metagpt.utils.graph_repository import SPO, GraphKeyword, GraphRepository
|
||||
|
||||
|
||||
class ReverseUseCase(BaseModel):
|
||||
"""
|
||||
Represents a reverse engineered use case.
|
||||
|
||||
Attributes:
|
||||
description (str): A description of the reverse use case.
|
||||
inputs (List[str]): List of inputs for the reverse use case.
|
||||
outputs (List[str]): List of outputs for the reverse use case.
|
||||
actors (List[str]): List of actors involved in the reverse use case.
|
||||
steps (List[str]): List of steps for the reverse use case.
|
||||
reason (str): The reason behind the reverse use case.
|
||||
"""
|
||||
|
||||
description: str
|
||||
inputs: List[str]
|
||||
outputs: List[str]
|
||||
actors: List[str]
|
||||
steps: List[str]
|
||||
reason: str
|
||||
|
||||
|
||||
class ReverseUseCaseDetails(BaseModel):
|
||||
"""
|
||||
Represents details of a reverse engineered use case.
|
||||
|
||||
Attributes:
|
||||
description (str): A description of the reverse use case details.
|
||||
use_cases (List[ReverseUseCase]): List of reverse use cases.
|
||||
relationship (List[str]): List of relationships associated with the reverse use case details.
|
||||
"""
|
||||
|
||||
description: str
|
||||
use_cases: List[ReverseUseCase]
|
||||
relationship: List[str]
|
||||
|
||||
|
||||
class RebuildSequenceView(Action):
|
||||
async def run(self, with_messages=None, format=CONFIG.prompt_schema):
|
||||
graph_repo_pathname = CONFIG.git_repo.workdir / GRAPH_REPO_FILE_REPO / CONFIG.git_repo.workdir.name
|
||||
graph_db = await DiGraphRepository.load_from(str(graph_repo_pathname.with_suffix(".json")))
|
||||
entries = await RebuildSequenceView._search_main_entry(graph_db)
|
||||
for entry in entries:
|
||||
await self._rebuild_sequence_view(entry, graph_db)
|
||||
await graph_db.save()
|
||||
"""
|
||||
Represents an action to reconstruct sequence view through reverse engineering.
|
||||
|
||||
@staticmethod
|
||||
async def _search_main_entry(graph_db) -> List:
|
||||
rows = await graph_db.select(predicate=GraphKeyword.HAS_PAGE_INFO)
|
||||
Attributes:
|
||||
graph_db (Optional[GraphRepository]): An optional instance of GraphRepository for graph database operations.
|
||||
"""
|
||||
|
||||
graph_db: Optional[GraphRepository] = None
|
||||
|
||||
async def run(self, with_messages=None, format=config.prompt_schema):
|
||||
"""
|
||||
Implementation of `Action`'s `run` method.
|
||||
|
||||
Args:
|
||||
with_messages (Optional[Type]): An optional argument specifying messages to react to.
|
||||
format (str): The format for the prompt schema.
|
||||
"""
|
||||
graph_repo_pathname = self.context.git_repo.workdir / GRAPH_REPO_FILE_REPO / self.context.git_repo.workdir.name
|
||||
self.graph_db = await DiGraphRepository.load_from(str(graph_repo_pathname.with_suffix(".json")))
|
||||
if not self.i_context:
|
||||
entries = await self._search_main_entry()
|
||||
else:
|
||||
entries = [SPO(subject=self.i_context, predicate="", object_="")]
|
||||
for entry in entries:
|
||||
await self._rebuild_main_sequence_view(entry)
|
||||
while await self._merge_sequence_view(entry):
|
||||
pass
|
||||
await self.graph_db.save()
|
||||
|
||||
@retry(
|
||||
wait=wait_random_exponential(min=1, max=20),
|
||||
stop=stop_after_attempt(6),
|
||||
after=general_after_log(logger),
|
||||
)
|
||||
async def _rebuild_main_sequence_view(self, entry: SPO):
|
||||
"""
|
||||
Reconstruct the sequence diagram for the __main__ entry of the source code through reverse engineering.
|
||||
|
||||
Args:
|
||||
entry (SPO): The SPO (Subject, Predicate, Object) object in the graph database that is related to the
|
||||
subject `__name__:__main__`.
|
||||
"""
|
||||
filename = entry.subject.split(":", 1)[0]
|
||||
rows = await self.graph_db.select(predicate=GraphKeyword.IS, object_=GraphKeyword.CLASS)
|
||||
classes = []
|
||||
prefix = filename + ":"
|
||||
for r in rows:
|
||||
if prefix in r.subject:
|
||||
classes.append(r)
|
||||
await self._rebuild_use_case(r.subject)
|
||||
participants = await self._search_participants(split_namespace(entry.subject)[0])
|
||||
class_details = []
|
||||
class_views = []
|
||||
for c in classes:
|
||||
detail = await self._get_class_detail(c.subject)
|
||||
if not detail:
|
||||
continue
|
||||
class_details.append(detail)
|
||||
view = await self._get_uml_class_view(c.subject)
|
||||
if view:
|
||||
class_views.append(view)
|
||||
|
||||
actors = await self._get_participants(c.subject)
|
||||
participants.update(set(actors))
|
||||
|
||||
use_case_blocks = []
|
||||
for c in classes:
|
||||
use_cases = await self._get_class_use_cases(c.subject)
|
||||
use_case_blocks.append(use_cases)
|
||||
prompt_blocks = ["## Use Cases\n" + "\n".join(use_case_blocks)]
|
||||
block = "## Participants\n"
|
||||
for p in participants:
|
||||
block += f"- {p}\n"
|
||||
prompt_blocks.append(block)
|
||||
block = "## Mermaid Class Views\n```mermaid\n"
|
||||
block += "\n\n".join([c.get_mermaid() for c in class_views])
|
||||
block += "\n```\n"
|
||||
prompt_blocks.append(block)
|
||||
block = "## Source Code\n```python\n"
|
||||
block += await self._get_source_code(filename)
|
||||
block += "\n```\n"
|
||||
prompt_blocks.append(block)
|
||||
prompt = "\n---\n".join(prompt_blocks)
|
||||
|
||||
rsp = await self.llm.aask(
|
||||
msg=prompt,
|
||||
system_msgs=[
|
||||
"You are a python code to Mermaid Sequence Diagram translator in function detail.",
|
||||
"Translate the given markdown text to a Mermaid Sequence Diagram.",
|
||||
"Return the merged Mermaid sequence diagram in a markdown code block format.",
|
||||
],
|
||||
stream=False,
|
||||
)
|
||||
sequence_view = rsp.removeprefix("```mermaid").removesuffix("```")
|
||||
rows = await self.graph_db.select(subject=entry.subject, predicate=GraphKeyword.HAS_SEQUENCE_VIEW)
|
||||
for r in rows:
|
||||
if r.predicate == GraphKeyword.HAS_SEQUENCE_VIEW:
|
||||
await self.graph_db.delete(subject=r.subject, predicate=r.predicate, object_=r.object_)
|
||||
await self.graph_db.insert(
|
||||
subject=entry.subject, predicate=GraphKeyword.HAS_SEQUENCE_VIEW, object_=sequence_view
|
||||
)
|
||||
await self.graph_db.insert(
|
||||
subject=entry.subject,
|
||||
predicate=GraphKeyword.HAS_SEQUENCE_VIEW_VER,
|
||||
object_=concat_namespace(datetime.now().strftime("%Y%m%d%H%M%S%f")[:-3], add_affix(sequence_view)),
|
||||
)
|
||||
for c in classes:
|
||||
await self.graph_db.insert(
|
||||
subject=entry.subject, predicate=GraphKeyword.HAS_PARTICIPANT, object_=auto_namespace(c.subject)
|
||||
)
|
||||
await self._save_sequence_view(subject=entry.subject, content=sequence_view)
|
||||
|
||||
async def _merge_sequence_view(self, entry: SPO) -> bool:
|
||||
"""
|
||||
Augments additional information to the provided SPO (Subject, Predicate, Object) entry in the sequence diagram.
|
||||
|
||||
Args:
|
||||
entry (SPO): The SPO object representing the relationship in the graph database.
|
||||
|
||||
Returns:
|
||||
bool: True if additional information has been augmented, otherwise False.
|
||||
"""
|
||||
new_participant = await self._search_new_participant(entry)
|
||||
if not new_participant:
|
||||
return False
|
||||
|
||||
await self._merge_participant(entry, new_participant)
|
||||
return True
|
||||
|
||||
async def _search_main_entry(self) -> List:
|
||||
"""
|
||||
Asynchronously searches for the SPO object that is related to `__name__:__main__`.
|
||||
|
||||
Returns:
|
||||
List: A list containing information about the main entry in the sequence diagram.
|
||||
"""
|
||||
rows = await self.graph_db.select(predicate=GraphKeyword.HAS_PAGE_INFO)
|
||||
tag = "__name__:__main__"
|
||||
entries = []
|
||||
for r in rows:
|
||||
|
|
@ -39,22 +219,395 @@ class RebuildSequenceView(Action):
|
|||
entries.append(r)
|
||||
return entries
|
||||
|
||||
async def _rebuild_sequence_view(self, entry, graph_db):
|
||||
filename = entry.subject.split(":", 1)[0]
|
||||
src_filename = RebuildSequenceView._get_full_filename(root=self.context, pathname=filename)
|
||||
content = await aread(filename=src_filename, encoding="utf-8")
|
||||
content = f"```python\n{content}\n```\n\n---\nTranslate the code above into Mermaid Sequence Diagram."
|
||||
data = await self.llm.aask(
|
||||
msg=content, system_msgs=["You are a python code to Mermaid Sequence Diagram translator in function detail"]
|
||||
@retry(
|
||||
wait=wait_random_exponential(min=1, max=20),
|
||||
stop=stop_after_attempt(6),
|
||||
after=general_after_log(logger),
|
||||
)
|
||||
async def _rebuild_use_case(self, ns_class_name: str):
|
||||
"""
|
||||
Asynchronously reconstructs the use case for the provided namespace-prefixed class name.
|
||||
|
||||
Args:
|
||||
ns_class_name (str): The namespace-prefixed class name for which the use case is to be reconstructed.
|
||||
"""
|
||||
rows = await self.graph_db.select(subject=ns_class_name, predicate=GraphKeyword.HAS_CLASS_USE_CASE)
|
||||
if rows:
|
||||
return
|
||||
|
||||
detail = await self._get_class_detail(ns_class_name)
|
||||
if not detail:
|
||||
return
|
||||
participants = set()
|
||||
participants.update(set(detail.compositions))
|
||||
participants.update(set(detail.aggregations))
|
||||
class_view = await self._get_uml_class_view(ns_class_name)
|
||||
source_code = await self._get_source_code(ns_class_name)
|
||||
|
||||
# prompt_blocks = [
|
||||
# "## Instruction\n"
|
||||
# "You are a python code to UML 2.0 Use Case translator.\n"
|
||||
# 'The generated UML 2.0 Use Case must include the roles or entities listed in "Participants".\n'
|
||||
# "The functional descriptions of Actors and Use Cases in the generated UML 2.0 Use Case must not "
|
||||
# 'conflict with the information in "Mermaid Class Views".\n'
|
||||
# 'The section under `if __name__ == "__main__":` of "Source Code" contains information about external '
|
||||
# "system interactions with the internal system.\n"
|
||||
# ]
|
||||
prompt_blocks = []
|
||||
block = "## Participants\n"
|
||||
for p in participants:
|
||||
block += f"- {p}\n"
|
||||
prompt_blocks.append(block)
|
||||
block = "## Mermaid Class Views\n```mermaid\n"
|
||||
block += class_view.get_mermaid()
|
||||
block += "\n```\n"
|
||||
prompt_blocks.append(block)
|
||||
block = "## Source Code\n```python\n"
|
||||
block += source_code
|
||||
block += "\n```\n"
|
||||
prompt_blocks.append(block)
|
||||
prompt = "\n---\n".join(prompt_blocks)
|
||||
|
||||
rsp = await self.llm.aask(
|
||||
msg=prompt,
|
||||
system_msgs=[
|
||||
"You are a python code to UML 2.0 Use Case translator.",
|
||||
'The generated UML 2.0 Use Case must include the roles or entities listed in "Participants".',
|
||||
"The functional descriptions of Actors and Use Cases in the generated UML 2.0 Use Case must not "
|
||||
'conflict with the information in "Mermaid Class Views".',
|
||||
'The section under `if __name__ == "__main__":` of "Source Code" contains information about external '
|
||||
"system interactions with the internal system.",
|
||||
"Return a markdown JSON object with:\n"
|
||||
'- a "description" key to explain what the whole source code want to do;\n'
|
||||
'- a "use_cases" key list all use cases, each use case in the list should including a `description` '
|
||||
"key describes about what the use case to do, a `inputs` key lists the input names of the use case "
|
||||
"from external sources, a `outputs` key lists the output names of the use case to external sources, "
|
||||
"a `actors` key lists the participant actors of the use case, a `steps` key lists the steps about how "
|
||||
"the use case works step by step, a `reason` key explaining under what circumstances would the "
|
||||
"external system execute this use case.\n"
|
||||
'- a "relationship" key lists all the descriptions of relationship among these use cases.\n',
|
||||
],
|
||||
stream=False,
|
||||
)
|
||||
|
||||
code_blocks = parse_json_code_block(rsp)
|
||||
for block in code_blocks:
|
||||
detail = ReverseUseCaseDetails.model_validate_json(block)
|
||||
await self.graph_db.insert(
|
||||
subject=ns_class_name, predicate=GraphKeyword.HAS_CLASS_USE_CASE, object_=detail.model_dump_json()
|
||||
)
|
||||
|
||||
@retry(
|
||||
wait=wait_random_exponential(min=1, max=20),
|
||||
stop=stop_after_attempt(6),
|
||||
after=general_after_log(logger),
|
||||
)
|
||||
async def _rebuild_sequence_view(self, ns_class_name: str):
|
||||
"""
|
||||
Asynchronously reconstructs the sequence diagram for the provided namespace-prefixed class name.
|
||||
|
||||
Args:
|
||||
ns_class_name (str): The namespace-prefixed class name for which the sequence diagram is to be reconstructed.
|
||||
"""
|
||||
await self._rebuild_use_case(ns_class_name)
|
||||
|
||||
prompts_blocks = []
|
||||
use_case_markdown = await self._get_class_use_cases(ns_class_name)
|
||||
if not use_case_markdown: # external class
|
||||
await self.graph_db.insert(subject=ns_class_name, predicate=GraphKeyword.HAS_SEQUENCE_VIEW, object_="")
|
||||
return
|
||||
block = f"## Use Cases\n{use_case_markdown}"
|
||||
prompts_blocks.append(block)
|
||||
|
||||
participants = await self._get_participants(ns_class_name)
|
||||
block = "## Participants\n" + "\n".join([f"- {s}" for s in participants])
|
||||
prompts_blocks.append(block)
|
||||
|
||||
view = await self._get_uml_class_view(ns_class_name)
|
||||
block = "## Mermaid Class Views\n```mermaid\n"
|
||||
block += view.get_mermaid()
|
||||
block += "\n```\n"
|
||||
prompts_blocks.append(block)
|
||||
|
||||
block = "## Source Code\n```python\n"
|
||||
block += await self._get_source_code(ns_class_name)
|
||||
block += "\n```\n"
|
||||
prompts_blocks.append(block)
|
||||
prompt = "\n---\n".join(prompts_blocks)
|
||||
|
||||
rsp = await self.llm.aask(
|
||||
prompt,
|
||||
system_msgs=[
|
||||
"You are a Mermaid Sequence Diagram translator in function detail.",
|
||||
"Translate the markdown text to a Mermaid Sequence Diagram.",
|
||||
"Return a markdown mermaid code block.",
|
||||
],
|
||||
stream=False,
|
||||
)
|
||||
|
||||
sequence_view = rsp.removeprefix("```mermaid").removesuffix("```")
|
||||
await self.graph_db.insert(
|
||||
subject=ns_class_name, predicate=GraphKeyword.HAS_SEQUENCE_VIEW, object_=sequence_view
|
||||
)
|
||||
|
||||
async def _get_participants(self, ns_class_name: str) -> List[str]:
|
||||
"""
|
||||
Asynchronously returns the participants list of the sequence diagram for the provided namespace-prefixed SPO
|
||||
object.
|
||||
|
||||
Args:
|
||||
ns_class_name (str): The namespace-prefixed class name for which to retrieve the participants list.
|
||||
|
||||
Returns:
|
||||
List[str]: A list of participants in the sequence diagram.
|
||||
"""
|
||||
participants = set()
|
||||
detail = await self._get_class_detail(ns_class_name)
|
||||
if not detail:
|
||||
return []
|
||||
participants.update(set(detail.compositions))
|
||||
participants.update(set(detail.aggregations))
|
||||
return list(participants)
|
||||
|
||||
async def _get_class_use_cases(self, ns_class_name: str) -> str:
|
||||
"""
|
||||
Asynchronously assembles the context about the use case information of the namespace-prefixed SPO object.
|
||||
|
||||
Args:
|
||||
ns_class_name (str): The namespace-prefixed class name for which to retrieve use case information.
|
||||
|
||||
Returns:
|
||||
str: A string containing the assembled context about the use case information.
|
||||
"""
|
||||
block = ""
|
||||
rows = await self.graph_db.select(subject=ns_class_name, predicate=GraphKeyword.HAS_CLASS_USE_CASE)
|
||||
for i, r in enumerate(rows):
|
||||
detail = ReverseUseCaseDetails.model_validate_json(r.object_)
|
||||
block += f"\n### {i + 1}. {detail.description}"
|
||||
for j, use_case in enumerate(detail.use_cases):
|
||||
block += f"\n#### {i + 1}.{j + 1}. {use_case.description}\n"
|
||||
block += "\n##### Inputs\n" + "\n".join([f"- {s}" for s in use_case.inputs])
|
||||
block += "\n##### Outputs\n" + "\n".join([f"- {s}" for s in use_case.outputs])
|
||||
block += "\n##### Actors\n" + "\n".join([f"- {s}" for s in use_case.actors])
|
||||
block += "\n##### Steps\n" + "\n".join([f"- {s}" for s in use_case.steps])
|
||||
block += "\n#### Use Case Relationship\n" + "\n".join([f"- {s}" for s in detail.relationship])
|
||||
return block + "\n"
|
||||
|
||||
async def _get_class_detail(self, ns_class_name: str) -> DotClassInfo | None:
|
||||
"""
|
||||
Asynchronously retrieves the dot format class details of the namespace-prefixed SPO object.
|
||||
|
||||
Args:
|
||||
ns_class_name (str): The namespace-prefixed class name for which to retrieve class details.
|
||||
|
||||
Returns:
|
||||
Union[DotClassInfo, None]: A DotClassInfo object representing the dot format class details,
|
||||
or None if the details are not available.
|
||||
"""
|
||||
rows = await self.graph_db.select(subject=ns_class_name, predicate=GraphKeyword.HAS_DETAIL)
|
||||
if not rows:
|
||||
return None
|
||||
dot_class_info = DotClassInfo.model_validate_json(rows[0].object_)
|
||||
return dot_class_info
|
||||
|
||||
async def _get_uml_class_view(self, ns_class_name: str) -> UMLClassView | None:
|
||||
"""
|
||||
Asynchronously retrieves the UML 2.0 format class details of the namespace-prefixed SPO object.
|
||||
|
||||
Args:
|
||||
ns_class_name (str): The namespace-prefixed class name for which to retrieve UML class details.
|
||||
|
||||
Returns:
|
||||
Union[UMLClassView, None]: A UMLClassView object representing the UML 2.0 format class details,
|
||||
or None if the details are not available.
|
||||
"""
|
||||
rows = await self.graph_db.select(subject=ns_class_name, predicate=GraphKeyword.HAS_CLASS_VIEW)
|
||||
if not rows:
|
||||
return None
|
||||
class_view = UMLClassView.model_validate_json(rows[0].object_)
|
||||
return class_view
|
||||
|
||||
async def _get_source_code(self, ns_class_name: str) -> str:
|
||||
"""
|
||||
Asynchronously retrieves the source code of the namespace-prefixed SPO object.
|
||||
|
||||
Args:
|
||||
ns_class_name (str): The namespace-prefixed class name for which to retrieve the source code.
|
||||
|
||||
Returns:
|
||||
str: A string containing the source code of the specified namespace-prefixed class.
|
||||
"""
|
||||
rows = await self.graph_db.select(subject=ns_class_name, predicate=GraphKeyword.HAS_PAGE_INFO)
|
||||
filename = split_namespace(ns_class_name=ns_class_name)[0]
|
||||
if not rows:
|
||||
src_filename = RebuildSequenceView._get_full_filename(root=self.i_context, pathname=filename)
|
||||
if not src_filename:
|
||||
return ""
|
||||
return await aread(filename=src_filename, encoding="utf-8")
|
||||
code_block_info = CodeBlockInfo.model_validate_json(rows[0].object_)
|
||||
return await read_file_block(
|
||||
filename=filename, lineno=code_block_info.lineno, end_lineno=code_block_info.end_lineno
|
||||
)
|
||||
await graph_db.insert(subject=filename, predicate=GraphKeyword.HAS_SEQUENCE_VIEW, object_=data)
|
||||
logger.info(data)
|
||||
|
||||
@staticmethod
|
||||
def _get_full_filename(root: str | Path, pathname: str | Path) -> Path | None:
|
||||
"""
|
||||
Convert package name to the full path of the module.
|
||||
|
||||
Args:
|
||||
root (Union[str, Path]): The root path or string representing the package.
|
||||
pathname (Union[str, Path]): The pathname or string representing the module.
|
||||
|
||||
Returns:
|
||||
Union[Path, None]: The full path of the module, or None if the path cannot be determined.
|
||||
|
||||
Examples:
|
||||
If `root`(workdir) is "/User/xxx/github/MetaGPT/metagpt", and the `pathname` is
|
||||
"metagpt/management/skill_manager.py", then the returned value will be
|
||||
"/User/xxx/github/MetaGPT/metagpt/management/skill_manager.py"
|
||||
"""
|
||||
if re.match(r"^/.+", pathname):
|
||||
return pathname
|
||||
files = list_files(root=root)
|
||||
postfix = "/" + str(pathname)
|
||||
for i in files:
|
||||
if str(i).endswith(postfix):
|
||||
return i
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def parse_participant(mermaid_sequence_diagram: str) -> List[str]:
|
||||
"""
|
||||
Parses the provided Mermaid sequence diagram and returns the list of participants.
|
||||
|
||||
Args:
|
||||
mermaid_sequence_diagram (str): The Mermaid sequence diagram string to be parsed.
|
||||
|
||||
Returns:
|
||||
List[str]: A list of participants extracted from the sequence diagram.
|
||||
"""
|
||||
pattern = r"participant ([a-zA-Z\.0-9_]+)"
|
||||
matches = re.findall(pattern, mermaid_sequence_diagram)
|
||||
matches = [re.sub(r"[\\/'\"]+", "", i) for i in matches]
|
||||
return matches
|
||||
|
||||
async def _search_new_participant(self, entry: SPO) -> str | None:
|
||||
"""
|
||||
Asynchronously retrieves a participant whose sequence diagram has not been augmented.
|
||||
|
||||
Args:
|
||||
entry (SPO): The SPO object representing the relationship in the graph database.
|
||||
|
||||
Returns:
|
||||
Union[str, None]: A participant whose sequence diagram has not been augmented, or None if not found.
|
||||
"""
|
||||
rows = await self.graph_db.select(subject=entry.subject, predicate=GraphKeyword.HAS_SEQUENCE_VIEW)
|
||||
if not rows:
|
||||
return None
|
||||
sequence_view = rows[0].object_
|
||||
rows = await self.graph_db.select(subject=entry.subject, predicate=GraphKeyword.HAS_PARTICIPANT)
|
||||
merged_participants = []
|
||||
for r in rows:
|
||||
name = split_namespace(r.object_)[-1]
|
||||
merged_participants.append(name)
|
||||
participants = self.parse_participant(sequence_view)
|
||||
for p in participants:
|
||||
if p in merged_participants:
|
||||
continue
|
||||
return p
|
||||
return None
|
||||
|
||||
@retry(
|
||||
wait=wait_random_exponential(min=1, max=20),
|
||||
stop=stop_after_attempt(6),
|
||||
after=general_after_log(logger),
|
||||
)
|
||||
async def _merge_participant(self, entry: SPO, class_name: str):
|
||||
"""
|
||||
Augments the sequence diagram of `class_name` to the sequence diagram of `entry`.
|
||||
|
||||
Args:
|
||||
entry (SPO): The SPO object representing the base sequence diagram.
|
||||
class_name (str): The class name whose sequence diagram is to be augmented.
|
||||
"""
|
||||
rows = await self.graph_db.select(predicate=GraphKeyword.IS, object_=GraphKeyword.CLASS)
|
||||
participants = []
|
||||
for r in rows:
|
||||
name = split_namespace(r.subject)[-1]
|
||||
if name == class_name:
|
||||
participants.append(r)
|
||||
if len(participants) == 0: # external participants
|
||||
await self.graph_db.insert(
|
||||
subject=entry.subject, predicate=GraphKeyword.HAS_PARTICIPANT, object_=concat_namespace("?", class_name)
|
||||
)
|
||||
return
|
||||
if len(participants) > 1:
|
||||
for r in participants:
|
||||
await self.graph_db.insert(
|
||||
subject=entry.subject, predicate=GraphKeyword.HAS_PARTICIPANT, object_=auto_namespace(r.subject)
|
||||
)
|
||||
return
|
||||
|
||||
participant = participants[0]
|
||||
await self._rebuild_sequence_view(participant.subject)
|
||||
sequence_views = await self.graph_db.select(
|
||||
subject=participant.subject, predicate=GraphKeyword.HAS_SEQUENCE_VIEW
|
||||
)
|
||||
if not sequence_views: # external class
|
||||
return
|
||||
rows = await self.graph_db.select(subject=entry.subject, predicate=GraphKeyword.HAS_SEQUENCE_VIEW)
|
||||
prompt = f"```mermaid\n{sequence_views[0].object_}\n```\n---\n```mermaid\n{rows[0].object_}\n```"
|
||||
|
||||
rsp = await self.llm.aask(
|
||||
prompt,
|
||||
system_msgs=[
|
||||
"You are a tool to merge sequence diagrams into one.",
|
||||
"Participants with the same name are considered identical.",
|
||||
"Return the merged Mermaid sequence diagram in a markdown code block format.",
|
||||
],
|
||||
stream=False,
|
||||
)
|
||||
|
||||
sequence_view = rsp.removeprefix("```mermaid").removesuffix("```")
|
||||
rows = await self.graph_db.select(subject=entry.subject, predicate=GraphKeyword.HAS_SEQUENCE_VIEW)
|
||||
for r in rows:
|
||||
await self.graph_db.delete(subject=r.subject, predicate=r.predicate, object_=r.object_)
|
||||
await self.graph_db.insert(
|
||||
subject=entry.subject, predicate=GraphKeyword.HAS_SEQUENCE_VIEW, object_=sequence_view
|
||||
)
|
||||
await self.graph_db.insert(
|
||||
subject=entry.subject,
|
||||
predicate=GraphKeyword.HAS_SEQUENCE_VIEW_VER,
|
||||
object_=concat_namespace(datetime.now().strftime("%Y%m%d%H%M%S%f")[:-3], add_affix(sequence_view)),
|
||||
)
|
||||
await self.graph_db.insert(
|
||||
subject=entry.subject, predicate=GraphKeyword.HAS_PARTICIPANT, object_=auto_namespace(participant.subject)
|
||||
)
|
||||
await self._save_sequence_view(subject=entry.subject, content=sequence_view)
|
||||
|
||||
async def _save_sequence_view(self, subject: str, content: str):
|
||||
pattern = re.compile(r"[^a-zA-Z0-9]")
|
||||
name = re.sub(pattern, "_", subject)
|
||||
filename = Path(name).with_suffix(".sequence_diagram.mmd")
|
||||
await self.context.repo.resources.data_api_design.save(filename=str(filename), content=content)
|
||||
|
||||
async def _search_participants(self, filename: str) -> Set:
|
||||
content = await self._get_source_code(filename)
|
||||
|
||||
rsp = await self.llm.aask(
|
||||
msg=content,
|
||||
system_msgs=[
|
||||
"You are a tool for listing all class names used in a source file.",
|
||||
"Return a markdown JSON object with: "
|
||||
'- a "class_names" key containing the list of class names used in the file; '
|
||||
'- a "reasons" key lists all reason objects, each object containing a "class_name" key for class name, a "reference" key explaining the line where the class has been used.',
|
||||
],
|
||||
)
|
||||
|
||||
class _Data(BaseModel):
|
||||
class_names: List[str]
|
||||
reasons: List
|
||||
|
||||
json_blocks = parse_json_code_block(rsp)
|
||||
data = _Data.model_validate_json(json_blocks[0])
|
||||
return set(data.class_names)
|
||||
|
|
|
|||
|
|
@ -1,16 +0,0 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2024/1/4
|
||||
@Author : mashenquan
|
||||
@File : rebuild_sequence_view_an.py
|
||||
"""
|
||||
from metagpt.actions.action_node import ActionNode
|
||||
from metagpt.utils.mermaid import MMC2
|
||||
|
||||
CODE_2_MERMAID_SEQUENCE_DIAGRAM = ActionNode(
|
||||
key="Program call flow",
|
||||
expected_type=str,
|
||||
instruction='Translate the "context" content into "format example" format.',
|
||||
example=MMC2,
|
||||
)
|
||||
|
|
@ -3,17 +3,15 @@
|
|||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
from typing import Callable, Optional, Union
|
||||
from typing import Any, Callable, Optional, Union
|
||||
|
||||
from pydantic import Field, parse_obj_as
|
||||
from pydantic import TypeAdapter, model_validator
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.llm import LLM
|
||||
from metagpt.config2 import config
|
||||
from metagpt.logs import logger
|
||||
from metagpt.provider.base_llm import BaseLLM
|
||||
from metagpt.tools.search_engine import SearchEngine
|
||||
from metagpt.tools.web_browser_engine import WebBrowserEngine, WebBrowserEngineType
|
||||
from metagpt.tools.web_browser_engine import WebBrowserEngine
|
||||
from metagpt.utils.common import OutputParser
|
||||
from metagpt.utils.text import generate_prompt_chunk, reduce_message_length
|
||||
|
||||
|
|
@ -81,12 +79,18 @@ class CollectLinks(Action):
|
|||
"""Action class to collect links from a search engine."""
|
||||
|
||||
name: str = "CollectLinks"
|
||||
context: Optional[str] = None
|
||||
i_context: Optional[str] = None
|
||||
desc: str = "Collect links from a search engine."
|
||||
|
||||
search_engine: SearchEngine = Field(default_factory=SearchEngine)
|
||||
search_func: Optional[Any] = None
|
||||
search_engine: Optional[SearchEngine] = None
|
||||
rank_func: Optional[Callable[[list[str]], None]] = None
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_engine_and_run_func(self):
|
||||
if self.search_engine is None:
|
||||
self.search_engine = SearchEngine.from_search_config(self.config.search, proxy=self.config.proxy)
|
||||
return self
|
||||
|
||||
async def run(
|
||||
self,
|
||||
topic: str,
|
||||
|
|
@ -109,7 +113,7 @@ class CollectLinks(Action):
|
|||
keywords = await self._aask(SEARCH_TOPIC_PROMPT, [system_text])
|
||||
try:
|
||||
keywords = OutputParser.extract_struct(keywords, list)
|
||||
keywords = parse_obj_as(list[str], keywords)
|
||||
keywords = TypeAdapter(list[str]).validate_python(keywords)
|
||||
except Exception as e:
|
||||
logger.exception(f"fail to get keywords related to the research topic '{topic}' for {e}")
|
||||
keywords = [topic]
|
||||
|
|
@ -129,13 +133,13 @@ class CollectLinks(Action):
|
|||
if len(remove) == 0:
|
||||
break
|
||||
|
||||
model_name = CONFIG.get_model_name(CONFIG.get_default_llm_provider_enum())
|
||||
prompt = reduce_message_length(gen_msg(), model_name, system_text, CONFIG.max_tokens_rsp)
|
||||
model_name = config.llm.model
|
||||
prompt = reduce_message_length(gen_msg(), model_name, system_text, config.llm.max_token)
|
||||
logger.debug(prompt)
|
||||
queries = await self._aask(prompt, [system_text])
|
||||
try:
|
||||
queries = OutputParser.extract_struct(queries, list)
|
||||
queries = parse_obj_as(list[str], queries)
|
||||
queries = TypeAdapter(list[str]).validate_python(queries)
|
||||
except Exception as e:
|
||||
logger.exception(f"fail to break down the research question due to {e}")
|
||||
queries = keywords
|
||||
|
|
@ -177,21 +181,20 @@ class WebBrowseAndSummarize(Action):
|
|||
"""Action class to explore the web and provide summaries of articles and webpages."""
|
||||
|
||||
name: str = "WebBrowseAndSummarize"
|
||||
context: Optional[str] = None
|
||||
llm: BaseLLM = Field(default_factory=LLM)
|
||||
i_context: Optional[str] = None
|
||||
desc: str = "Explore the web and provide summaries of articles and webpages."
|
||||
browse_func: Union[Callable[[list[str]], None], None] = None
|
||||
web_browser_engine: Optional[WebBrowserEngine] = None
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
if CONFIG.model_for_researcher_summary:
|
||||
self.llm.model = CONFIG.model_for_researcher_summary
|
||||
|
||||
self.web_browser_engine = WebBrowserEngine(
|
||||
engine=WebBrowserEngineType.CUSTOM if self.browse_func else None,
|
||||
run_func=self.browse_func,
|
||||
)
|
||||
@model_validator(mode="after")
|
||||
def validate_engine_and_run_func(self):
|
||||
if self.web_browser_engine is None:
|
||||
self.web_browser_engine = WebBrowserEngine.from_browser_config(
|
||||
self.config.browser,
|
||||
browse_func=self.browse_func,
|
||||
proxy=self.config.proxy,
|
||||
)
|
||||
return self
|
||||
|
||||
async def run(
|
||||
self,
|
||||
|
|
@ -220,9 +223,7 @@ class WebBrowseAndSummarize(Action):
|
|||
for u, content in zip([url, *urls], contents):
|
||||
content = content.inner_text
|
||||
chunk_summaries = []
|
||||
for prompt in generate_prompt_chunk(
|
||||
content, prompt_template, self.llm.model, system_text, CONFIG.max_tokens_rsp
|
||||
):
|
||||
for prompt in generate_prompt_chunk(content, prompt_template, self.llm.model, system_text, 4096):
|
||||
logger.debug(prompt)
|
||||
summary = await self._aask(prompt, [system_text])
|
||||
if summary == "Not relevant.":
|
||||
|
|
@ -247,14 +248,8 @@ class WebBrowseAndSummarize(Action):
|
|||
class ConductResearch(Action):
|
||||
"""Action class to conduct research and generate a research report."""
|
||||
|
||||
name: str = "ConductResearch"
|
||||
context: Optional[str] = None
|
||||
llm: BaseLLM = Field(default_factory=LLM)
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
if CONFIG.model_for_researcher_report:
|
||||
self.llm.model = CONFIG.model_for_researcher_report
|
||||
|
||||
async def run(
|
||||
self,
|
||||
|
|
|
|||
|
|
@ -16,12 +16,12 @@
|
|||
class.
|
||||
"""
|
||||
import subprocess
|
||||
from pathlib import Path
|
||||
from typing import Tuple
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from metagpt.actions.action import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import RunCodeContext, RunCodeResult
|
||||
from metagpt.utils.exceptions import handle_exception
|
||||
|
|
@ -42,13 +42,13 @@ 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.
|
||||
"""
|
||||
|
||||
CONTEXT = """
|
||||
TEMPLATE_CONTEXT = """
|
||||
## Development Code File Name
|
||||
{code_file_name}
|
||||
## Development Code
|
||||
|
|
@ -77,7 +77,7 @@ standard errors:
|
|||
|
||||
class RunCode(Action):
|
||||
name: str = "RunCode"
|
||||
context: RunCodeContext = Field(default_factory=RunCodeContext)
|
||||
i_context: RunCodeContext = Field(default_factory=RunCodeContext)
|
||||
|
||||
@classmethod
|
||||
async def run_text(cls, code) -> Tuple[str, str]:
|
||||
|
|
@ -89,13 +89,12 @@ class RunCode(Action):
|
|||
return "", str(e)
|
||||
return namespace.get("result", ""), ""
|
||||
|
||||
@classmethod
|
||||
async def run_script(cls, working_directory, additional_python_paths=[], command=[]) -> Tuple[str, str]:
|
||||
async def run_script(self, working_directory, additional_python_paths=[], command=[]) -> Tuple[str, str]:
|
||||
working_directory = str(working_directory)
|
||||
additional_python_paths = [str(path) for path in additional_python_paths]
|
||||
|
||||
# Copy the current environment variables
|
||||
env = CONFIG.new_environ()
|
||||
env = self.context.new_environ()
|
||||
|
||||
# Modify the PYTHONPATH environment variable
|
||||
additional_python_paths = [working_directory] + additional_python_paths
|
||||
|
|
@ -119,25 +118,25 @@ class RunCode(Action):
|
|||
return stdout.decode("utf-8"), stderr.decode("utf-8")
|
||||
|
||||
async def run(self, *args, **kwargs) -> RunCodeResult:
|
||||
logger.info(f"Running {' '.join(self.context.command)}")
|
||||
if self.context.mode == "script":
|
||||
logger.info(f"Running {' '.join(self.i_context.command)}")
|
||||
if self.i_context.mode == "script":
|
||||
outs, errs = await self.run_script(
|
||||
command=self.context.command,
|
||||
working_directory=self.context.working_directory,
|
||||
additional_python_paths=self.context.additional_python_paths,
|
||||
command=self.i_context.command,
|
||||
working_directory=self.i_context.working_directory,
|
||||
additional_python_paths=self.i_context.additional_python_paths,
|
||||
)
|
||||
elif self.context.mode == "text":
|
||||
outs, errs = await self.run_text(code=self.context.code)
|
||||
elif self.i_context.mode == "text":
|
||||
outs, errs = await self.run_text(code=self.i_context.code)
|
||||
|
||||
logger.info(f"{outs=}")
|
||||
logger.info(f"{errs=}")
|
||||
|
||||
context = CONTEXT.format(
|
||||
code=self.context.code,
|
||||
code_file_name=self.context.code_filename,
|
||||
test_code=self.context.test_code,
|
||||
test_file_name=self.context.test_filename,
|
||||
command=" ".join(self.context.command),
|
||||
context = TEMPLATE_CONTEXT.format(
|
||||
code=self.i_context.code,
|
||||
code_file_name=self.i_context.code_filename,
|
||||
test_code=self.i_context.test_code,
|
||||
test_file_name=self.i_context.test_filename,
|
||||
command=" ".join(self.i_context.command),
|
||||
outs=outs[:500], # outs might be long but they are not important, truncate them to avoid token overflow
|
||||
errs=errs[:10000], # truncate errors to avoid token overflow
|
||||
)
|
||||
|
|
@ -152,11 +151,23 @@ class RunCode(Action):
|
|||
return subprocess.run(cmd, check=check, cwd=cwd, env=env)
|
||||
|
||||
@staticmethod
|
||||
def _install_dependencies(working_directory, env):
|
||||
def _install_requirements(working_directory, env):
|
||||
file_path = Path(working_directory) / "requirements.txt"
|
||||
if not file_path.exists():
|
||||
return
|
||||
if file_path.stat().st_size == 0:
|
||||
return
|
||||
install_command = ["python", "-m", "pip", "install", "-r", "requirements.txt"]
|
||||
logger.info(" ".join(install_command))
|
||||
RunCode._install_via_subprocess(install_command, check=True, cwd=working_directory, env=env)
|
||||
|
||||
@staticmethod
|
||||
def _install_pytest(working_directory, env):
|
||||
install_pytest_command = ["python", "-m", "pip", "install", "pytest"]
|
||||
logger.info(" ".join(install_pytest_command))
|
||||
RunCode._install_via_subprocess(install_pytest_command, check=True, cwd=working_directory, env=env)
|
||||
|
||||
@staticmethod
|
||||
def _install_dependencies(working_directory, env):
|
||||
RunCode._install_requirements(working_directory, env)
|
||||
RunCode._install_pytest(working_directory, env)
|
||||
|
|
|
|||
|
|
@ -5,16 +5,14 @@
|
|||
@Author : alexanderwu
|
||||
@File : search_google.py
|
||||
"""
|
||||
from typing import Any, Optional
|
||||
from typing import Optional
|
||||
|
||||
import pydantic
|
||||
from pydantic import Field, model_validator
|
||||
from pydantic import model_validator
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.config import CONFIG, Config
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import Message
|
||||
from metagpt.tools import SearchEngineType
|
||||
from metagpt.tools.search_engine import SearchEngine
|
||||
|
||||
SEARCH_AND_SUMMARIZE_SYSTEM = """### Requirements
|
||||
|
|
@ -103,32 +101,23 @@ You are a member of a professional butler team and will provide helpful suggesti
|
|||
"""
|
||||
|
||||
|
||||
# TOTEST
|
||||
class SearchAndSummarize(Action):
|
||||
name: str = ""
|
||||
content: Optional[str] = None
|
||||
config: None = Field(default_factory=Config)
|
||||
engine: Optional[SearchEngineType] = CONFIG.search_engine
|
||||
search_func: Optional[Any] = None
|
||||
search_engine: SearchEngine = None
|
||||
result: str = ""
|
||||
|
||||
@model_validator(mode="before")
|
||||
@classmethod
|
||||
def validate_engine_and_run_func(cls, values):
|
||||
engine = values.get("engine")
|
||||
search_func = values.get("search_func")
|
||||
config = Config()
|
||||
@model_validator(mode="after")
|
||||
def validate_search_engine(self):
|
||||
if self.search_engine is None:
|
||||
try:
|
||||
config = self.config
|
||||
search_engine = SearchEngine.from_search_config(config.search, proxy=config.proxy)
|
||||
except pydantic.ValidationError:
|
||||
search_engine = None
|
||||
|
||||
if engine is None:
|
||||
engine = config.search_engine
|
||||
try:
|
||||
search_engine = SearchEngine(engine=engine, run_func=search_func)
|
||||
except pydantic.ValidationError:
|
||||
search_engine = None
|
||||
|
||||
values["search_engine"] = search_engine
|
||||
return values
|
||||
self.search_engine = search_engine
|
||||
return self
|
||||
|
||||
async def run(self, context: list[Message], system_text=SEARCH_AND_SUMMARIZE_SYSTEM) -> str:
|
||||
if self.search_engine is None:
|
||||
|
|
|
|||
|
|
@ -29,9 +29,7 @@ class ArgumentsParingAction(Action):
|
|||
|
||||
@property
|
||||
def prompt(self):
|
||||
prompt = "You are a function parser. You can convert spoken words into function parameters.\n"
|
||||
prompt += "\n---\n"
|
||||
prompt += f"{self.skill.name} function parameters description:\n"
|
||||
prompt = f"{self.skill.name} function parameters description:\n"
|
||||
for k, v in self.skill.arguments.items():
|
||||
prompt += f"parameter `{k}`: {v}\n"
|
||||
prompt += "\n---\n"
|
||||
|
|
@ -49,7 +47,11 @@ class ArgumentsParingAction(Action):
|
|||
|
||||
async def run(self, with_message=None, **kwargs) -> Message:
|
||||
prompt = self.prompt
|
||||
rsp = await self.llm.aask(msg=prompt, system_msgs=[])
|
||||
rsp = await self.llm.aask(
|
||||
msg=prompt,
|
||||
system_msgs=["You are a function parser.", "You can convert spoken words into function parameters."],
|
||||
stream=False,
|
||||
)
|
||||
logger.debug(f"SKILL:{prompt}\n, RESULT:{rsp}")
|
||||
self.args = ArgumentsParingAction.parse_arguments(skill_name=self.skill.name, txt=rsp)
|
||||
self.rsp = Message(content=rsp, role="assistant", instruct_content=self.args, cause_by=self)
|
||||
|
|
|
|||
|
|
@ -11,11 +11,8 @@ from pydantic import Field
|
|||
from tenacity import retry, stop_after_attempt, wait_random_exponential
|
||||
|
||||
from metagpt.actions.action import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import SYSTEM_DESIGN_FILE_REPO, TASK_FILE_REPO
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import CodeSummarizeContext
|
||||
from metagpt.utils.file_repository import FileRepository
|
||||
|
||||
PROMPT_TEMPLATE = """
|
||||
NOTICE
|
||||
|
|
@ -29,9 +26,9 @@ ATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenc
|
|||
{system_design}
|
||||
```
|
||||
-----
|
||||
# Tasks
|
||||
# Task
|
||||
```text
|
||||
{tasks}
|
||||
{task}
|
||||
```
|
||||
-----
|
||||
{code_blocks}
|
||||
|
|
@ -90,10 +87,9 @@ flowchart TB
|
|||
"""
|
||||
|
||||
|
||||
# TOTEST
|
||||
class SummarizeCode(Action):
|
||||
name: str = "SummarizeCode"
|
||||
context: CodeSummarizeContext = Field(default_factory=CodeSummarizeContext)
|
||||
i_context: CodeSummarizeContext = Field(default_factory=CodeSummarizeContext)
|
||||
|
||||
@retry(stop=stop_after_attempt(2), wait=wait_random_exponential(min=1, max=60))
|
||||
async def summarize_code(self, prompt):
|
||||
|
|
@ -101,20 +97,20 @@ class SummarizeCode(Action):
|
|||
return code_rsp
|
||||
|
||||
async def run(self):
|
||||
design_pathname = Path(self.context.design_filename)
|
||||
design_doc = await FileRepository.get_file(filename=design_pathname.name, relative_path=SYSTEM_DESIGN_FILE_REPO)
|
||||
task_pathname = Path(self.context.task_filename)
|
||||
task_doc = await FileRepository.get_file(filename=task_pathname.name, relative_path=TASK_FILE_REPO)
|
||||
src_file_repo = CONFIG.git_repo.new_file_repository(relative_path=CONFIG.src_workspace)
|
||||
design_pathname = Path(self.i_context.design_filename)
|
||||
design_doc = await self.repo.docs.system_design.get(filename=design_pathname.name)
|
||||
task_pathname = Path(self.i_context.task_filename)
|
||||
task_doc = await self.repo.docs.task.get(filename=task_pathname.name)
|
||||
src_file_repo = self.repo.with_src_path(self.context.src_workspace).srcs
|
||||
code_blocks = []
|
||||
for filename in self.context.codes_filenames:
|
||||
for filename in self.i_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,
|
||||
task=task_doc.content,
|
||||
code_blocks="\n".join(code_blocks),
|
||||
format_example=format_example,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -9,25 +9,31 @@
|
|||
from typing import Optional
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import DEFAULT_LANGUAGE
|
||||
from metagpt.config2 import config
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import Message
|
||||
|
||||
|
||||
# TOTEST
|
||||
class TalkAction(Action):
|
||||
context: str
|
||||
i_context: str
|
||||
history_summary: str = ""
|
||||
knowledge: str = ""
|
||||
rsp: Optional[Message] = None
|
||||
|
||||
@property
|
||||
def agent_description(self):
|
||||
return self.context.kwargs.agent_description
|
||||
|
||||
@property
|
||||
def language(self):
|
||||
return self.context.kwargs.language or config.language
|
||||
|
||||
@property
|
||||
def prompt(self):
|
||||
prompt = ""
|
||||
if CONFIG.agent_description:
|
||||
if self.agent_description:
|
||||
prompt = (
|
||||
f"You are {CONFIG.agent_description}. Your responses should align with the role-play agreement, "
|
||||
f"You are {self.agent_description}. Your responses should align with the role-play agreement, "
|
||||
f"maintaining the character's persona and habits. When faced with unrelated questions, playfully "
|
||||
f"decline to answer without revealing your AI nature to preserve the character's image.\n\n"
|
||||
)
|
||||
|
|
@ -36,10 +42,10 @@ class TalkAction(Action):
|
|||
prompt += (
|
||||
"If the information is insufficient, you can search in the historical conversation or knowledge above.\n"
|
||||
)
|
||||
language = CONFIG.language or DEFAULT_LANGUAGE
|
||||
language = self.language
|
||||
prompt += (
|
||||
f"Answer the following questions strictly in {language}, and the answers must follow the Markdown format.\n "
|
||||
f"{self.context}"
|
||||
f"{self.i_context}"
|
||||
)
|
||||
logger.debug(f"PROMPT: {prompt}")
|
||||
return prompt
|
||||
|
|
@ -47,11 +53,11 @@ class TalkAction(Action):
|
|||
@property
|
||||
def prompt_gpt4(self):
|
||||
kvs = {
|
||||
"{role}": CONFIG.agent_description or "",
|
||||
"{role}": self.agent_description or "",
|
||||
"{history}": self.history_summary or "",
|
||||
"{knowledge}": self.knowledge or "",
|
||||
"{language}": CONFIG.language or DEFAULT_LANGUAGE,
|
||||
"{ask}": self.context,
|
||||
"{language}": self.language,
|
||||
"{ask}": self.i_context,
|
||||
}
|
||||
prompt = TalkActionPrompt.FORMATION_LOOSE
|
||||
for k, v in kvs.items():
|
||||
|
|
@ -68,9 +74,9 @@ class TalkAction(Action):
|
|||
|
||||
@property
|
||||
def aask_args(self):
|
||||
language = CONFIG.language or DEFAULT_LANGUAGE
|
||||
language = self.language
|
||||
system_msgs = [
|
||||
f"You are {CONFIG.agent_description}.",
|
||||
f"You are {self.agent_description}.",
|
||||
"Your responses should align with the role-play agreement, "
|
||||
"maintaining the character's persona and habits. When faced with unrelated questions, playfully "
|
||||
"decline to answer without revealing your AI nature to preserve the character's image.",
|
||||
|
|
@ -82,11 +88,11 @@ class TalkAction(Action):
|
|||
format_msgs.append({"role": "assistant", "content": self.knowledge})
|
||||
if self.history_summary:
|
||||
format_msgs.append({"role": "assistant", "content": self.history_summary})
|
||||
return self.context, format_msgs, system_msgs
|
||||
return self.i_context, format_msgs, system_msgs
|
||||
|
||||
async def run(self, with_message=None, **kwargs) -> Message:
|
||||
msg, format_msgs, system_msgs = self.aask_args
|
||||
rsp = await self.llm.aask(msg=msg, format_msgs=format_msgs, system_msgs=system_msgs)
|
||||
rsp = await self.llm.aask(msg=msg, format_msgs=format_msgs, system_msgs=system_msgs, stream=False)
|
||||
self.rsp = Message(content=rsp, role="assistant", cause_by=self)
|
||||
return self.rsp
|
||||
|
||||
|
|
|
|||
|
|
@ -21,18 +21,13 @@ from pydantic import Field
|
|||
from tenacity import retry, stop_after_attempt, wait_random_exponential
|
||||
|
||||
from metagpt.actions.action import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import (
|
||||
BUGFIX_FILENAME,
|
||||
CODE_SUMMARIES_FILE_REPO,
|
||||
DOCS_FILE_REPO,
|
||||
TASK_FILE_REPO,
|
||||
TEST_OUTPUTS_FILE_REPO,
|
||||
)
|
||||
from metagpt.actions.project_management_an import REFINED_TASK_LIST, TASK_LIST
|
||||
from metagpt.actions.write_code_plan_and_change_an import REFINED_TEMPLATE
|
||||
from metagpt.const import BUGFIX_FILENAME, REQUIREMENT_FILENAME
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import CodingContext, Document, RunCodeResult
|
||||
from metagpt.utils.common import CodeParser
|
||||
from metagpt.utils.file_repository import FileRepository
|
||||
from metagpt.utils.project_repo import ProjectRepo
|
||||
|
||||
PROMPT_TEMPLATE = """
|
||||
NOTICE
|
||||
|
|
@ -44,8 +39,8 @@ ATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenc
|
|||
## Design
|
||||
{design}
|
||||
|
||||
## Tasks
|
||||
{tasks}
|
||||
## Task
|
||||
{task}
|
||||
|
||||
## Legacy Code
|
||||
```Code
|
||||
|
|
@ -87,7 +82,7 @@ ATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenc
|
|||
|
||||
class WriteCode(Action):
|
||||
name: str = "WriteCode"
|
||||
context: Document = Field(default_factory=Document)
|
||||
i_context: Document = Field(default_factory=Document)
|
||||
|
||||
@retry(wait=wait_random_exponential(min=1, max=60), stop=stop_after_attempt(6))
|
||||
async def write_code(self, prompt) -> str:
|
||||
|
|
@ -96,16 +91,13 @@ class WriteCode(Action):
|
|||
return code
|
||||
|
||||
async def run(self, *args, **kwargs) -> CodingContext:
|
||||
bug_feedback = await FileRepository.get_file(filename=BUGFIX_FILENAME, relative_path=DOCS_FILE_REPO)
|
||||
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
|
||||
)
|
||||
bug_feedback = await self.repo.docs.get(filename=BUGFIX_FILENAME)
|
||||
coding_context = CodingContext.loads(self.i_context.content)
|
||||
test_doc = await self.repo.test_outputs.get(filename="test_" + coding_context.filename + ".json")
|
||||
requirement_doc = await self.repo.docs.get(filename=REQUIREMENT_FILENAME)
|
||||
summary_doc = None
|
||||
if coding_context.design_doc and coding_context.design_doc.filename:
|
||||
summary_doc = await FileRepository.get_file(
|
||||
filename=coding_context.design_doc.filename, relative_path=CODE_SUMMARIES_FILE_REPO
|
||||
)
|
||||
summary_doc = await self.repo.docs.code_summary.get(filename=coding_context.design_doc.filename)
|
||||
logs = ""
|
||||
if test_doc:
|
||||
test_detail = RunCodeResult.loads(test_doc.content)
|
||||
|
|
@ -113,42 +105,109 @@ class WriteCode(Action):
|
|||
|
||||
if bug_feedback:
|
||||
code_context = coding_context.code_doc.content
|
||||
elif self.config.inc:
|
||||
code_context = await self.get_codes(
|
||||
coding_context.task_doc, exclude=self.i_context.filename, project_repo=self.repo, use_inc=True
|
||||
)
|
||||
else:
|
||||
code_context = await self.get_codes(coding_context.task_doc, exclude=self.context.filename)
|
||||
code_context = await self.get_codes(
|
||||
coding_context.task_doc,
|
||||
exclude=self.i_context.filename,
|
||||
project_repo=self.repo.with_src_path(self.context.src_workspace),
|
||||
)
|
||||
|
||||
prompt = PROMPT_TEMPLATE.format(
|
||||
design=coding_context.design_doc.content if coding_context.design_doc else "",
|
||||
tasks=coding_context.task_doc.content if coding_context.task_doc else "",
|
||||
code=code_context,
|
||||
logs=logs,
|
||||
feedback=bug_feedback.content if bug_feedback else "",
|
||||
filename=self.context.filename,
|
||||
summary_log=summary_doc.content if summary_doc else "",
|
||||
)
|
||||
if self.config.inc:
|
||||
prompt = REFINED_TEMPLATE.format(
|
||||
user_requirement=requirement_doc.content if requirement_doc else "",
|
||||
code_plan_and_change=str(coding_context.code_plan_and_change_doc),
|
||||
design=coding_context.design_doc.content if coding_context.design_doc else "",
|
||||
task=coding_context.task_doc.content if coding_context.task_doc else "",
|
||||
code=code_context,
|
||||
logs=logs,
|
||||
feedback=bug_feedback.content if bug_feedback else "",
|
||||
filename=self.i_context.filename,
|
||||
summary_log=summary_doc.content if summary_doc else "",
|
||||
)
|
||||
else:
|
||||
prompt = PROMPT_TEMPLATE.format(
|
||||
design=coding_context.design_doc.content if coding_context.design_doc else "",
|
||||
task=coding_context.task_doc.content if coding_context.task_doc else "",
|
||||
code=code_context,
|
||||
logs=logs,
|
||||
feedback=bug_feedback.content if bug_feedback else "",
|
||||
filename=self.i_context.filename,
|
||||
summary_log=summary_doc.content if summary_doc else "",
|
||||
)
|
||||
logger.info(f"Writing {coding_context.filename}..")
|
||||
code = await self.write_code(prompt)
|
||||
if not coding_context.code_doc:
|
||||
# avoid root_path pydantic ValidationError if use WriteCode alone
|
||||
root_path = CONFIG.src_workspace if CONFIG.src_workspace else ""
|
||||
root_path = self.context.src_workspace if self.context.src_workspace else ""
|
||||
coding_context.code_doc = Document(filename=coding_context.filename, root_path=str(root_path))
|
||||
coding_context.code_doc.content = code
|
||||
return coding_context
|
||||
|
||||
@staticmethod
|
||||
async def get_codes(task_doc, exclude) -> str:
|
||||
async def get_codes(task_doc: Document, exclude: str, project_repo: ProjectRepo, use_inc: bool = False) -> str:
|
||||
"""
|
||||
Get codes for generating the exclude file in various scenarios.
|
||||
|
||||
Attributes:
|
||||
task_doc (Document): Document object of the task file.
|
||||
exclude (str): The file to be generated. Specifies the filename to be excluded from the code snippets.
|
||||
project_repo (ProjectRepo): ProjectRepo object of the project.
|
||||
use_inc (bool): Indicates whether the scenario involves incremental development. Defaults to False.
|
||||
|
||||
Returns:
|
||||
str: Codes for generating the exclude file.
|
||||
"""
|
||||
if not task_doc:
|
||||
return ""
|
||||
if not task_doc.content:
|
||||
task_doc.content = FileRepository.get_file(filename=task_doc.filename, relative_path=TASK_FILE_REPO)
|
||||
task_doc = project_repo.docs.task.get(filename=task_doc.filename)
|
||||
m = json.loads(task_doc.content)
|
||||
code_filenames = m.get("Task list", [])
|
||||
code_filenames = m.get(TASK_LIST.key, []) if use_inc else m.get(REFINED_TASK_LIST.key, [])
|
||||
codes = []
|
||||
src_file_repo = CONFIG.git_repo.new_file_repository(relative_path=CONFIG.src_workspace)
|
||||
for filename in code_filenames:
|
||||
if filename == exclude:
|
||||
continue
|
||||
doc = await src_file_repo.get(filename=filename)
|
||||
if not doc:
|
||||
continue
|
||||
codes.append(f"----- {filename}\n" + doc.content)
|
||||
src_file_repo = project_repo.srcs
|
||||
|
||||
# Incremental development scenario
|
||||
if use_inc:
|
||||
src_files = src_file_repo.all_files
|
||||
# Get the old workspace contained the old codes and old workspace are created in previous CodePlanAndChange
|
||||
old_file_repo = project_repo.git_repo.new_file_repository(relative_path=project_repo.old_workspace)
|
||||
old_files = old_file_repo.all_files
|
||||
# Get the union of the files in the src and old workspaces
|
||||
union_files_list = list(set(src_files) | set(old_files))
|
||||
for filename in union_files_list:
|
||||
# Exclude the current file from the all code snippets
|
||||
if filename == exclude:
|
||||
# If the file is in the old workspace, use the old code
|
||||
# Exclude unnecessary code to maintain a clean and focused main.py file, ensuring only relevant and
|
||||
# essential functionality is included for the project’s requirements
|
||||
if filename in old_files and filename != "main.py":
|
||||
# Use old code
|
||||
doc = await old_file_repo.get(filename=filename)
|
||||
# If the file is in the src workspace, skip it
|
||||
else:
|
||||
continue
|
||||
codes.insert(0, f"-----Now, {filename} to be rewritten\n```{doc.content}```\n=====")
|
||||
# The code snippets are generated from the src workspace
|
||||
else:
|
||||
doc = await src_file_repo.get(filename=filename)
|
||||
# If the file does not exist in the src workspace, skip it
|
||||
if not doc:
|
||||
continue
|
||||
codes.append(f"----- {filename}\n```{doc.content}```")
|
||||
|
||||
# Normal scenario
|
||||
else:
|
||||
for filename in code_filenames:
|
||||
# Exclude the current file to get the code snippets for generating the current file
|
||||
if filename == exclude:
|
||||
continue
|
||||
doc = await src_file_repo.get(filename=filename)
|
||||
if not doc:
|
||||
continue
|
||||
codes.append(f"----- {filename}\n```{doc.content}```")
|
||||
|
||||
return "\n".join(codes)
|
||||
|
|
|
|||
|
|
@ -5,7 +5,7 @@
|
|||
@File : write_review.py
|
||||
"""
|
||||
import asyncio
|
||||
from typing import List
|
||||
from typing import List, Literal
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.actions.action_node import ActionNode
|
||||
|
|
@ -21,16 +21,15 @@ REVIEW = ActionNode(
|
|||
],
|
||||
)
|
||||
|
||||
LGTM = ActionNode(
|
||||
key="LGTM",
|
||||
expected_type=str,
|
||||
instruction="LGTM/LBTM. If the code is fully implemented, "
|
||||
"give a LGTM (Looks Good To Me), otherwise provide a LBTM (Looks Bad To Me).",
|
||||
REVIEW_RESULT = ActionNode(
|
||||
key="ReviewResult",
|
||||
expected_type=Literal["LGTM", "LBTM"],
|
||||
instruction="LGTM/LBTM. If the code is fully implemented, " "give a LGTM, otherwise provide a LBTM.",
|
||||
example="LBTM",
|
||||
)
|
||||
|
||||
ACTIONS = ActionNode(
|
||||
key="Actions",
|
||||
NEXT_STEPS = ActionNode(
|
||||
key="NextSteps",
|
||||
expected_type=str,
|
||||
instruction="Based on the code review outcome, suggest actionable steps. This can include code changes, "
|
||||
"refactoring suggestions, or any follow-up tasks.",
|
||||
|
|
@ -69,7 +68,7 @@ WRITE_DRAFT = ActionNode(
|
|||
)
|
||||
|
||||
|
||||
WRITE_MOVE_FUNCTION = ActionNode(
|
||||
WRITE_FUNCTION = ActionNode(
|
||||
key="WriteFunction",
|
||||
expected_type=str,
|
||||
instruction="write code for the function not implemented.",
|
||||
|
|
@ -555,8 +554,8 @@ LBTM
|
|||
"""
|
||||
|
||||
|
||||
WRITE_CODE_NODE = ActionNode.from_children("WRITE_REVIEW_NODE", [REVIEW, LGTM, ACTIONS])
|
||||
WRITE_MOVE_NODE = ActionNode.from_children("WRITE_MOVE_NODE", [WRITE_DRAFT, WRITE_MOVE_FUNCTION])
|
||||
WRITE_CODE_NODE = ActionNode.from_children("WRITE_REVIEW_NODE", [REVIEW, REVIEW_RESULT, NEXT_STEPS])
|
||||
WRITE_MOVE_NODE = ActionNode.from_children("WRITE_MOVE_NODE", [WRITE_DRAFT, WRITE_FUNCTION])
|
||||
|
||||
|
||||
CR_FOR_MOVE_FUNCTION_BY_3 = """
|
||||
|
|
@ -579,8 +578,7 @@ class WriteCodeAN(Action):
|
|||
|
||||
async def run(self, context):
|
||||
self.llm.system_prompt = "You are an outstanding engineer and can implement any code"
|
||||
return await WRITE_MOVE_FUNCTION.fill(context=context, llm=self.llm, schema="json")
|
||||
# return await WRITE_CODE_NODE.fill(context=context, llm=self.llm, schema="markdown")
|
||||
return await WRITE_MOVE_NODE.fill(context=context, llm=self.llm, schema="json")
|
||||
|
||||
|
||||
async def main():
|
||||
|
|
|
|||
228
metagpt/actions/write_code_plan_and_change_an.py
Normal file
228
metagpt/actions/write_code_plan_and_change_an.py
Normal file
|
|
@ -0,0 +1,228 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/12/26
|
||||
@Author : mannaandpoem
|
||||
@File : write_code_plan_and_change_an.py
|
||||
"""
|
||||
import os
|
||||
from typing import List
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from metagpt.actions.action import Action
|
||||
from metagpt.actions.action_node import ActionNode
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import CodePlanAndChangeContext
|
||||
|
||||
DEVELOPMENT_PLAN = ActionNode(
|
||||
key="Development Plan",
|
||||
expected_type=List[str],
|
||||
instruction="Develop a comprehensive and step-by-step incremental development plan, providing the detail "
|
||||
"changes to be implemented at each step based on the order of 'Task List'",
|
||||
example=[
|
||||
"Enhance the functionality of `calculator.py` by extending it to incorporate methods for subtraction, ...",
|
||||
"Update the existing codebase in main.py to incorporate new API endpoints for subtraction, ...",
|
||||
],
|
||||
)
|
||||
|
||||
INCREMENTAL_CHANGE = ActionNode(
|
||||
key="Incremental Change",
|
||||
expected_type=List[str],
|
||||
instruction="Write Incremental Change by making a code draft that how to implement incremental development "
|
||||
"including detailed steps based on the context. Note: Track incremental changes using the marks `+` and `-` to "
|
||||
"indicate additions and deletions, and ensure compliance with the output format of `git diff`",
|
||||
example=[
|
||||
'''```diff
|
||||
--- Old/calculator.py
|
||||
+++ New/calculator.py
|
||||
|
||||
class Calculator:
|
||||
self.result = number1 + number2
|
||||
return self.result
|
||||
|
||||
- def sub(self, number1, number2) -> float:
|
||||
+ def subtract(self, number1: float, number2: float) -> float:
|
||||
+ """
|
||||
+ Subtracts the second number from the first and returns the result.
|
||||
+
|
||||
+ Args:
|
||||
+ number1 (float): The number to be subtracted from.
|
||||
+ number2 (float): The number to subtract.
|
||||
+
|
||||
+ Returns:
|
||||
+ float: The difference of number1 and number2.
|
||||
+ """
|
||||
+ self.result = number1 - number2
|
||||
+ return self.result
|
||||
+
|
||||
def multiply(self, number1: float, number2: float) -> float:
|
||||
- pass
|
||||
+ """
|
||||
+ Multiplies two numbers and returns the result.
|
||||
+
|
||||
+ Args:
|
||||
+ number1 (float): The first number to multiply.
|
||||
+ number2 (float): The second number to multiply.
|
||||
+
|
||||
+ Returns:
|
||||
+ float: The product of number1 and number2.
|
||||
+ """
|
||||
+ self.result = number1 * number2
|
||||
+ return self.result
|
||||
+
|
||||
def divide(self, number1: float, number2: float) -> float:
|
||||
- pass
|
||||
+ """
|
||||
+ ValueError: If the second number is zero.
|
||||
+ """
|
||||
+ if number2 == 0:
|
||||
+ raise ValueError('Cannot divide by zero')
|
||||
+ self.result = number1 / number2
|
||||
+ return self.result
|
||||
+
|
||||
- def reset_result(self):
|
||||
+ def clear(self):
|
||||
+ if self.result != 0.0:
|
||||
+ print("Result is not zero, clearing...")
|
||||
+ else:
|
||||
+ print("Result is already zero, no need to clear.")
|
||||
+
|
||||
self.result = 0.0
|
||||
```''',
|
||||
"""```diff
|
||||
--- Old/main.py
|
||||
+++ New/main.py
|
||||
|
||||
def add_numbers():
|
||||
result = calculator.add_numbers(num1, num2)
|
||||
return jsonify({'result': result}), 200
|
||||
|
||||
-# TODO: Implement subtraction, multiplication, and division operations
|
||||
+@app.route('/subtract_numbers', methods=['POST'])
|
||||
+def subtract_numbers():
|
||||
+ data = request.get_json()
|
||||
+ num1 = data.get('num1', 0)
|
||||
+ num2 = data.get('num2', 0)
|
||||
+ result = calculator.subtract_numbers(num1, num2)
|
||||
+ return jsonify({'result': result}), 200
|
||||
+
|
||||
+@app.route('/multiply_numbers', methods=['POST'])
|
||||
+def multiply_numbers():
|
||||
+ data = request.get_json()
|
||||
+ num1 = data.get('num1', 0)
|
||||
+ num2 = data.get('num2', 0)
|
||||
+ try:
|
||||
+ result = calculator.divide_numbers(num1, num2)
|
||||
+ except ValueError as e:
|
||||
+ return jsonify({'error': str(e)}), 400
|
||||
+ return jsonify({'result': result}), 200
|
||||
+
|
||||
if __name__ == '__main__':
|
||||
app.run()
|
||||
```""",
|
||||
],
|
||||
)
|
||||
|
||||
CODE_PLAN_AND_CHANGE_CONTEXT = """
|
||||
## User New Requirements
|
||||
{requirement}
|
||||
|
||||
## PRD
|
||||
{prd}
|
||||
|
||||
## Design
|
||||
{design}
|
||||
|
||||
## Task
|
||||
{task}
|
||||
|
||||
## Legacy Code
|
||||
{code}
|
||||
"""
|
||||
|
||||
REFINED_TEMPLATE = """
|
||||
NOTICE
|
||||
Role: You are a professional engineer; The main goal is to complete incremental development by combining legacy code and plan and Incremental Change, ensuring the integration of new features.
|
||||
|
||||
# Context
|
||||
## User New Requirements
|
||||
{user_requirement}
|
||||
|
||||
## Code Plan And Change
|
||||
{code_plan_and_change}
|
||||
|
||||
## Design
|
||||
{design}
|
||||
|
||||
## Task
|
||||
{task}
|
||||
|
||||
## Legacy Code
|
||||
```Code
|
||||
{code}
|
||||
```
|
||||
|
||||
## Debug logs
|
||||
```text
|
||||
{logs}
|
||||
|
||||
{summary_log}
|
||||
```
|
||||
|
||||
## Bug Feedback logs
|
||||
```text
|
||||
{feedback}
|
||||
```
|
||||
|
||||
# Format example
|
||||
## Code: {filename}
|
||||
```python
|
||||
## {filename}
|
||||
...
|
||||
```
|
||||
|
||||
# Instruction: Based on the context, follow "Format example", write or rewrite code.
|
||||
## Write/Rewrite Code: Only write one file {filename}, write or rewrite complete code using triple quotes based on the following attentions and context.
|
||||
1. Only One file: do your best to implement THIS ONLY ONE FILE.
|
||||
2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.
|
||||
3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.
|
||||
4. Follow design: YOU MUST FOLLOW "Data structures and interfaces". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.
|
||||
5. Follow Code Plan And Change: If there is any "Incremental Change" that is marked by the git diff format with '+' and '-' symbols, or Legacy Code files contain "{filename} to be rewritten", you must merge it into the code file according to the "Development Plan".
|
||||
6. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.
|
||||
7. Before using a external variable/module, make sure you import it first.
|
||||
8. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.
|
||||
9. Attention: Retain details that are not related to incremental development but are important for maintaining the consistency and clarity of the old code.
|
||||
"""
|
||||
|
||||
CODE_PLAN_AND_CHANGE = [DEVELOPMENT_PLAN, INCREMENTAL_CHANGE]
|
||||
|
||||
WRITE_CODE_PLAN_AND_CHANGE_NODE = ActionNode.from_children("WriteCodePlanAndChange", CODE_PLAN_AND_CHANGE)
|
||||
|
||||
|
||||
class WriteCodePlanAndChange(Action):
|
||||
name: str = "WriteCodePlanAndChange"
|
||||
i_context: CodePlanAndChangeContext = Field(default_factory=CodePlanAndChangeContext)
|
||||
|
||||
async def run(self, *args, **kwargs):
|
||||
self.llm.system_prompt = "You are a professional software engineer, your primary responsibility is to "
|
||||
"meticulously craft comprehensive incremental development plan and deliver detailed incremental change"
|
||||
prd_doc = await self.repo.docs.prd.get(filename=self.i_context.prd_filename)
|
||||
design_doc = await self.repo.docs.system_design.get(filename=self.i_context.design_filename)
|
||||
task_doc = await self.repo.docs.task.get(filename=self.i_context.task_filename)
|
||||
context = CODE_PLAN_AND_CHANGE_CONTEXT.format(
|
||||
requirement=self.i_context.requirement,
|
||||
prd=prd_doc.content,
|
||||
design=design_doc.content,
|
||||
task=task_doc.content,
|
||||
code=await self.get_old_codes(),
|
||||
)
|
||||
logger.info("Writing code plan and change..")
|
||||
return await WRITE_CODE_PLAN_AND_CHANGE_NODE.fill(context=context, llm=self.llm, schema="json")
|
||||
|
||||
async def get_old_codes(self) -> str:
|
||||
self.repo.old_workspace = self.repo.git_repo.workdir / os.path.basename(self.config.project_path)
|
||||
old_file_repo = self.repo.git_repo.new_file_repository(relative_path=self.repo.old_workspace)
|
||||
old_codes = await old_file_repo.get_all()
|
||||
codes = [f"----- {code.filename}\n```{code.content}```" for code in old_codes]
|
||||
return "\n".join(codes)
|
||||
|
|
@ -13,7 +13,7 @@ from tenacity import retry, stop_after_attempt, wait_random_exponential
|
|||
|
||||
from metagpt.actions import WriteCode
|
||||
from metagpt.actions.action import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import REQUIREMENT_FILENAME
|
||||
from metagpt.logs import logger
|
||||
from metagpt.schema import CodingContext
|
||||
from metagpt.utils.common import CodeParser
|
||||
|
|
@ -120,7 +120,7 @@ REWRITE_CODE_TEMPLATE = """
|
|||
|
||||
class WriteCodeReview(Action):
|
||||
name: str = "WriteCodeReview"
|
||||
context: CodingContext = Field(default_factory=CodingContext)
|
||||
i_context: CodingContext = Field(default_factory=CodingContext)
|
||||
|
||||
@retry(wait=wait_random_exponential(min=1, max=60), stop=stop_after_attempt(6))
|
||||
async def write_code_review_and_rewrite(self, context_prompt, cr_prompt, filename):
|
||||
|
|
@ -136,41 +136,56 @@ class WriteCodeReview(Action):
|
|||
return result, code
|
||||
|
||||
async def run(self, *args, **kwargs) -> CodingContext:
|
||||
iterative_code = self.context.code_doc.content
|
||||
k = CONFIG.code_review_k_times or 1
|
||||
iterative_code = self.i_context.code_doc.content
|
||||
k = self.context.config.code_review_k_times or 1
|
||||
|
||||
for i in range(k):
|
||||
format_example = FORMAT_EXAMPLE.format(filename=self.context.code_doc.filename)
|
||||
task_content = self.context.task_doc.content if self.context.task_doc else ""
|
||||
code_context = await WriteCode.get_codes(self.context.task_doc, exclude=self.context.filename)
|
||||
context = "\n".join(
|
||||
[
|
||||
"## System Design\n" + str(self.context.design_doc) + "\n",
|
||||
"## Tasks\n" + task_content + "\n",
|
||||
"## Code Files\n" + code_context + "\n",
|
||||
]
|
||||
format_example = FORMAT_EXAMPLE.format(filename=self.i_context.code_doc.filename)
|
||||
task_content = self.i_context.task_doc.content if self.i_context.task_doc else ""
|
||||
code_context = await WriteCode.get_codes(
|
||||
self.i_context.task_doc,
|
||||
exclude=self.i_context.filename,
|
||||
project_repo=self.repo.with_src_path(self.context.src_workspace),
|
||||
use_inc=self.config.inc,
|
||||
)
|
||||
|
||||
ctx_list = [
|
||||
"## System Design\n" + str(self.i_context.design_doc) + "\n",
|
||||
"## Task\n" + task_content + "\n",
|
||||
"## Code Files\n" + code_context + "\n",
|
||||
]
|
||||
if self.config.inc:
|
||||
requirement_doc = await self.repo.docs.get(filename=REQUIREMENT_FILENAME)
|
||||
insert_ctx_list = [
|
||||
"## User New Requirements\n" + str(requirement_doc) + "\n",
|
||||
"## Code Plan And Change\n" + str(self.i_context.code_plan_and_change_doc) + "\n",
|
||||
]
|
||||
ctx_list = insert_ctx_list + ctx_list
|
||||
|
||||
context_prompt = PROMPT_TEMPLATE.format(
|
||||
context=context,
|
||||
context="\n".join(ctx_list),
|
||||
code=iterative_code,
|
||||
filename=self.context.code_doc.filename,
|
||||
filename=self.i_context.code_doc.filename,
|
||||
)
|
||||
cr_prompt = EXAMPLE_AND_INSTRUCTION.format(
|
||||
format_example=format_example,
|
||||
)
|
||||
len1 = len(iterative_code) if iterative_code else 0
|
||||
len2 = len(self.i_context.code_doc.content) if self.i_context.code_doc.content else 0
|
||||
logger.info(
|
||||
f"Code review and rewrite {self.context.code_doc.filename}: {i + 1}/{k} | {len(iterative_code)=}, "
|
||||
f"{len(self.context.code_doc.content)=}"
|
||||
f"Code review and rewrite {self.i_context.code_doc.filename}: {i + 1}/{k} | len(iterative_code)={len1}, "
|
||||
f"len(self.i_context.code_doc.content)={len2}"
|
||||
)
|
||||
result, rewrited_code = await self.write_code_review_and_rewrite(
|
||||
context_prompt, cr_prompt, self.context.code_doc.filename
|
||||
context_prompt, cr_prompt, self.i_context.code_doc.filename
|
||||
)
|
||||
if "LBTM" in result:
|
||||
iterative_code = rewrited_code
|
||||
elif "LGTM" in result:
|
||||
self.context.code_doc.content = iterative_code
|
||||
return self.context
|
||||
self.i_context.code_doc.content = iterative_code
|
||||
return self.i_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
|
||||
self.i_context.code_doc.content = iterative_code
|
||||
return self.i_context
|
||||
|
|
|
|||
|
|
@ -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.
|
||||
|
|
@ -161,7 +161,7 @@ class WriteDocstring(Action):
|
|||
"""
|
||||
|
||||
desc: str = "Write docstring for code."
|
||||
context: Optional[str] = None
|
||||
i_context: Optional[str] = None
|
||||
|
||||
async def run(
|
||||
self,
|
||||
|
|
|
|||
|
|
@ -14,26 +14,22 @@
|
|||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import uuid
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
from metagpt.actions import Action, ActionOutput
|
||||
from metagpt.actions.action_node import ActionNode
|
||||
from metagpt.actions.fix_bug import FixBug
|
||||
from metagpt.actions.write_prd_an import (
|
||||
COMPETITIVE_QUADRANT_CHART,
|
||||
PROJECT_NAME,
|
||||
REFINED_PRD_NODE,
|
||||
WP_IS_RELATIVE_NODE,
|
||||
WP_ISSUE_TYPE_NODE,
|
||||
WRITE_PRD_NODE,
|
||||
)
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.const import (
|
||||
BUGFIX_FILENAME,
|
||||
COMPETITIVE_ANALYSIS_FILE_REPO,
|
||||
DOCS_FILE_REPO,
|
||||
PRD_PDF_FILE_REPO,
|
||||
PRDS_FILE_REPO,
|
||||
REQUIREMENT_FILENAME,
|
||||
)
|
||||
from metagpt.logs import logger
|
||||
|
|
@ -63,135 +59,114 @@ NEW_REQ_TEMPLATE = """
|
|||
|
||||
|
||||
class WritePRD(Action):
|
||||
name: str = "WritePRD"
|
||||
content: Optional[str] = None
|
||||
"""WritePRD deal with the following situations:
|
||||
1. Bugfix: If the requirement is a bugfix, the bugfix document will be generated.
|
||||
2. New requirement: If the requirement is a new requirement, the PRD document will be generated.
|
||||
3. Requirement update: If the requirement is an update, the PRD document will be updated.
|
||||
"""
|
||||
|
||||
async def run(self, with_messages, schema=CONFIG.prompt_schema, *args, **kwargs) -> ActionOutput | Message:
|
||||
# Determine which requirement documents need to be rewritten: Use LLM to assess whether new requirements are
|
||||
# related to the PRD. If they are related, rewrite the PRD.
|
||||
docs_file_repo = CONFIG.git_repo.new_file_repository(relative_path=DOCS_FILE_REPO)
|
||||
requirement_doc = await docs_file_repo.get(filename=REQUIREMENT_FILENAME)
|
||||
if requirement_doc and await self._is_bugfix(requirement_doc.content):
|
||||
await docs_file_repo.save(filename=BUGFIX_FILENAME, content=requirement_doc.content)
|
||||
await docs_file_repo.save(filename=REQUIREMENT_FILENAME, content="")
|
||||
bug_fix = BugFixContext(filename=BUGFIX_FILENAME)
|
||||
return Message(
|
||||
content=bug_fix.model_dump_json(),
|
||||
instruct_content=bug_fix,
|
||||
role="",
|
||||
cause_by=FixBug,
|
||||
sent_from=self,
|
||||
send_to="Alex", # the name of Engineer
|
||||
)
|
||||
async def run(self, with_messages, *args, **kwargs) -> ActionOutput | Message:
|
||||
"""Run the action."""
|
||||
req: Document = await self.repo.requirement
|
||||
docs: list[Document] = await self.repo.docs.prd.get_all()
|
||||
if not req:
|
||||
raise FileNotFoundError("No requirement document found.")
|
||||
|
||||
if await self._is_bugfix(req.content):
|
||||
logger.info(f"Bugfix detected: {req.content}")
|
||||
return await self._handle_bugfix(req)
|
||||
# remove bugfix file from last round in case of conflict
|
||||
await self.repo.docs.delete(filename=BUGFIX_FILENAME)
|
||||
|
||||
# if requirement is related to other documents, update them, otherwise create a new one
|
||||
if related_docs := await self.get_related_docs(req, docs):
|
||||
logger.info(f"Requirement update detected: {req.content}")
|
||||
return await self._handle_requirement_update(req, related_docs)
|
||||
else:
|
||||
await docs_file_repo.delete(filename=BUGFIX_FILENAME)
|
||||
logger.info(f"New requirement detected: {req.content}")
|
||||
return await self._handle_new_requirement(req)
|
||||
|
||||
prds_file_repo = CONFIG.git_repo.new_file_repository(PRDS_FILE_REPO)
|
||||
prd_docs = await prds_file_repo.get_all()
|
||||
change_files = Documents()
|
||||
for prd_doc in prd_docs:
|
||||
prd_doc = await self._update_prd(
|
||||
requirement_doc=requirement_doc, prd_doc=prd_doc, prds_file_repo=prds_file_repo, *args, **kwargs
|
||||
)
|
||||
if not prd_doc:
|
||||
continue
|
||||
change_files.docs[prd_doc.filename] = prd_doc
|
||||
logger.info(f"rewrite prd: {prd_doc.filename}")
|
||||
# If there is no existing PRD, generate one using 'docs/requirement.txt'.
|
||||
if not change_files.docs:
|
||||
prd_doc = await self._update_prd(
|
||||
requirement_doc=requirement_doc, prd_doc=None, prds_file_repo=prds_file_repo, *args, **kwargs
|
||||
)
|
||||
if prd_doc:
|
||||
change_files.docs[prd_doc.filename] = prd_doc
|
||||
logger.debug(f"new prd: {prd_doc.filename}")
|
||||
# Once all files under 'docs/prds/' have been compared with the newly added requirements, trigger the
|
||||
# 'publish' message to transition the workflow to the next stage. This design allows room for global
|
||||
# optimization in subsequent steps.
|
||||
return ActionOutput(content=change_files.model_dump_json(), instruct_content=change_files)
|
||||
async def _handle_bugfix(self, req: Document) -> Message:
|
||||
# ... bugfix logic ...
|
||||
await self.repo.docs.save(filename=BUGFIX_FILENAME, content=req.content)
|
||||
await self.repo.docs.save(filename=REQUIREMENT_FILENAME, content="")
|
||||
bug_fix = BugFixContext(filename=BUGFIX_FILENAME)
|
||||
return Message(
|
||||
content=bug_fix.model_dump_json(),
|
||||
instruct_content=bug_fix,
|
||||
role="",
|
||||
cause_by=FixBug,
|
||||
sent_from=self,
|
||||
send_to="Alex", # the name of Engineer
|
||||
)
|
||||
|
||||
async def _run_new_requirement(self, requirements, schema=CONFIG.prompt_schema) -> ActionOutput:
|
||||
# sas = SearchAndSummarize()
|
||||
# # rsp = await sas.run(context=requirements, system_text=SEARCH_AND_SUMMARIZE_SYSTEM_EN_US)
|
||||
# rsp = ""
|
||||
# info = f"### Search Results\n{sas.result}\n\n### Search Summary\n{rsp}"
|
||||
# if sas.result:
|
||||
# logger.info(sas.result)
|
||||
# logger.info(rsp)
|
||||
project_name = CONFIG.project_name or ""
|
||||
context = CONTEXT_TEMPLATE.format(requirements=requirements, project_name=project_name)
|
||||
async def _handle_new_requirement(self, req: Document) -> ActionOutput:
|
||||
"""handle new requirement"""
|
||||
project_name = self.project_name
|
||||
context = CONTEXT_TEMPLATE.format(requirements=req, project_name=project_name)
|
||||
exclude = [PROJECT_NAME.key] if project_name else []
|
||||
node = await WRITE_PRD_NODE.fill(context=context, llm=self.llm, exclude=exclude) # schema=schema
|
||||
await self._rename_workspace(node)
|
||||
return node
|
||||
new_prd_doc = await self.repo.docs.prd.save(
|
||||
filename=FileRepository.new_filename() + ".json", content=node.instruct_content.model_dump_json()
|
||||
)
|
||||
await self._save_competitive_analysis(new_prd_doc)
|
||||
await self.repo.resources.prd.save_pdf(doc=new_prd_doc)
|
||||
return Documents.from_iterable(documents=[new_prd_doc]).to_action_output()
|
||||
|
||||
async def _is_relative(self, new_requirement_doc, old_prd_doc) -> bool:
|
||||
context = NEW_REQ_TEMPLATE.format(old_prd=old_prd_doc.content, requirements=new_requirement_doc.content)
|
||||
async def _handle_requirement_update(self, req: Document, related_docs: list[Document]) -> ActionOutput:
|
||||
# ... requirement update logic ...
|
||||
for doc in related_docs:
|
||||
await self._update_prd(req, doc)
|
||||
return Documents.from_iterable(documents=related_docs).to_action_output()
|
||||
|
||||
async def _is_bugfix(self, context: str) -> bool:
|
||||
if not self.repo.code_files_exists():
|
||||
return False
|
||||
node = await WP_ISSUE_TYPE_NODE.fill(context, self.llm)
|
||||
return node.get("issue_type") == "BUG"
|
||||
|
||||
async def get_related_docs(self, req: Document, docs: list[Document]) -> list[Document]:
|
||||
"""get the related documents"""
|
||||
# refine: use gather to speed up
|
||||
return [i for i in docs if await self._is_related(req, i)]
|
||||
|
||||
async def _is_related(self, req: Document, old_prd: Document) -> bool:
|
||||
context = NEW_REQ_TEMPLATE.format(old_prd=old_prd.content, requirements=req.content)
|
||||
node = await WP_IS_RELATIVE_NODE.fill(context, self.llm)
|
||||
return node.get("is_relative") == "YES"
|
||||
|
||||
async def _merge(self, new_requirement_doc, prd_doc, schema=CONFIG.prompt_schema) -> Document:
|
||||
if not CONFIG.project_name:
|
||||
CONFIG.project_name = Path(CONFIG.project_path).name
|
||||
prompt = NEW_REQ_TEMPLATE.format(requirements=new_requirement_doc.content, old_prd=prd_doc.content)
|
||||
node = await WRITE_PRD_NODE.fill(context=prompt, llm=self.llm, schema=schema)
|
||||
prd_doc.content = node.instruct_content.model_dump_json()
|
||||
async def _merge(self, req: Document, related_doc: Document) -> Document:
|
||||
if not self.project_name:
|
||||
self.project_name = Path(self.project_path).name
|
||||
prompt = NEW_REQ_TEMPLATE.format(requirements=req.content, old_prd=related_doc.content)
|
||||
node = await REFINED_PRD_NODE.fill(context=prompt, llm=self.llm, schema=self.prompt_schema)
|
||||
related_doc.content = node.instruct_content.model_dump_json()
|
||||
await self._rename_workspace(node)
|
||||
return prd_doc
|
||||
return related_doc
|
||||
|
||||
async def _update_prd(self, requirement_doc, prd_doc, prds_file_repo, *args, **kwargs) -> Document | None:
|
||||
if not prd_doc:
|
||||
prd = await self._run_new_requirement(
|
||||
requirements=[requirement_doc.content if requirement_doc else ""], *args, **kwargs
|
||||
)
|
||||
new_prd_doc = Document(
|
||||
root_path=PRDS_FILE_REPO,
|
||||
filename=FileRepository.new_filename() + ".json",
|
||||
content=prd.instruct_content.model_dump_json(),
|
||||
)
|
||||
elif await self._is_relative(requirement_doc, prd_doc):
|
||||
new_prd_doc = await self._merge(requirement_doc, prd_doc)
|
||||
else:
|
||||
return None
|
||||
await prds_file_repo.save(filename=new_prd_doc.filename, content=new_prd_doc.content)
|
||||
async def _update_prd(self, req: Document, prd_doc: Document) -> Document:
|
||||
new_prd_doc: Document = await self._merge(req, prd_doc)
|
||||
await self.repo.docs.prd.save_doc(doc=new_prd_doc)
|
||||
await self._save_competitive_analysis(new_prd_doc)
|
||||
await self._save_pdf(new_prd_doc)
|
||||
await self.repo.resources.prd.save_pdf(doc=new_prd_doc)
|
||||
return new_prd_doc
|
||||
|
||||
@staticmethod
|
||||
async def _save_competitive_analysis(prd_doc):
|
||||
async def _save_competitive_analysis(self, prd_doc: Document):
|
||||
m = json.loads(prd_doc.content)
|
||||
quadrant_chart = m.get("Competitive Quadrant Chart")
|
||||
quadrant_chart = m.get(COMPETITIVE_QUADRANT_CHART.key)
|
||||
if not quadrant_chart:
|
||||
return
|
||||
pathname = (
|
||||
CONFIG.git_repo.workdir / Path(COMPETITIVE_ANALYSIS_FILE_REPO) / Path(prd_doc.filename).with_suffix("")
|
||||
)
|
||||
if not pathname.parent.exists():
|
||||
pathname.parent.mkdir(parents=True, exist_ok=True)
|
||||
await mermaid_to_file(quadrant_chart, pathname)
|
||||
pathname = self.repo.workdir / COMPETITIVE_ANALYSIS_FILE_REPO / Path(prd_doc.filename).stem
|
||||
pathname.parent.mkdir(parents=True, exist_ok=True)
|
||||
await mermaid_to_file(self.config.mermaid.engine, quadrant_chart, pathname)
|
||||
|
||||
@staticmethod
|
||||
async def _save_pdf(prd_doc):
|
||||
await FileRepository.save_as(doc=prd_doc, with_suffix=".md", relative_path=PRD_PDF_FILE_REPO)
|
||||
|
||||
@staticmethod
|
||||
async def _rename_workspace(prd):
|
||||
if not CONFIG.project_name:
|
||||
async def _rename_workspace(self, prd):
|
||||
if not self.project_name:
|
||||
if isinstance(prd, (ActionOutput, ActionNode)):
|
||||
ws_name = prd.instruct_content.model_dump()["Project Name"]
|
||||
else:
|
||||
ws_name = CodeParser.parse_str(block="Project Name", text=prd)
|
||||
if ws_name:
|
||||
CONFIG.project_name = ws_name
|
||||
if not CONFIG.project_name: # The LLM failed to provide a project name, and the user didn't provide one either.
|
||||
CONFIG.project_name = "app" + uuid.uuid4().hex[:16]
|
||||
CONFIG.git_repo.rename_root(CONFIG.project_name)
|
||||
|
||||
async def _is_bugfix(self, context) -> bool:
|
||||
src_workspace_path = CONFIG.git_repo.workdir / CONFIG.git_repo.workdir.name
|
||||
code_files = CONFIG.git_repo.get_files(relative_path=src_workspace_path)
|
||||
if not code_files:
|
||||
return False
|
||||
node = await WP_ISSUE_TYPE_NODE.fill(context, self.llm)
|
||||
return node.get("issue_type") == "BUG"
|
||||
self.project_name = ws_name
|
||||
self.repo.git_repo.rename_root(self.project_name)
|
||||
|
|
|
|||
|
|
@ -8,7 +8,6 @@
|
|||
from typing import List
|
||||
|
||||
from metagpt.actions.action_node import ActionNode
|
||||
from metagpt.logs import logger
|
||||
|
||||
LANGUAGE = ActionNode(
|
||||
key="Language",
|
||||
|
|
@ -31,10 +30,18 @@ ORIGINAL_REQUIREMENTS = ActionNode(
|
|||
example="Create a 2048 game",
|
||||
)
|
||||
|
||||
REFINED_REQUIREMENTS = ActionNode(
|
||||
key="Refined Requirements",
|
||||
expected_type=str,
|
||||
instruction="Place the New user's original requirements here.",
|
||||
example="Create a 2048 game with a new feature that ...",
|
||||
)
|
||||
|
||||
PROJECT_NAME = ActionNode(
|
||||
key="Project Name",
|
||||
expected_type=str,
|
||||
instruction="According to the content of \"Original Requirements,\" name the project using snake case style , like 'game_2048' or 'simple_crm.",
|
||||
instruction='According to the content of "Original Requirements," name the project using snake case style , '
|
||||
"like 'game_2048' or 'simple_crm.",
|
||||
example="game_2048",
|
||||
)
|
||||
|
||||
|
|
@ -45,6 +52,18 @@ PRODUCT_GOALS = ActionNode(
|
|||
example=["Create an engaging user experience", "Improve accessibility, be responsive", "More beautiful UI"],
|
||||
)
|
||||
|
||||
REFINED_PRODUCT_GOALS = ActionNode(
|
||||
key="Refined Product Goals",
|
||||
expected_type=List[str],
|
||||
instruction="Update and expand the original product goals to reflect the evolving needs due to incremental "
|
||||
"development. Ensure that the refined goals align with the current project direction and contribute to its success.",
|
||||
example=[
|
||||
"Enhance user engagement through new features",
|
||||
"Optimize performance for scalability",
|
||||
"Integrate innovative UI enhancements",
|
||||
],
|
||||
)
|
||||
|
||||
USER_STORIES = ActionNode(
|
||||
key="User Stories",
|
||||
expected_type=List[str],
|
||||
|
|
@ -58,6 +77,20 @@ USER_STORIES = ActionNode(
|
|||
],
|
||||
)
|
||||
|
||||
REFINED_USER_STORIES = ActionNode(
|
||||
key="Refined User Stories",
|
||||
expected_type=List[str],
|
||||
instruction="Update and expand the original scenario-based user stories to reflect the evolving needs due to "
|
||||
"incremental development. Ensure that the refined user stories capture incremental features and improvements. ",
|
||||
example=[
|
||||
"As a player, I want to choose difficulty levels to challenge my skills",
|
||||
"As a player, I want a visually appealing score display after each game for a better gaming experience",
|
||||
"As a player, I want a convenient restart button displayed when I lose to quickly start a new game",
|
||||
"As a player, I want an enhanced and aesthetically pleasing UI to elevate the overall gaming experience",
|
||||
"As a player, I want the ability to play the game seamlessly on my mobile phone for on-the-go entertainment",
|
||||
],
|
||||
)
|
||||
|
||||
COMPETITIVE_ANALYSIS = ActionNode(
|
||||
key="Competitive Analysis",
|
||||
expected_type=List[str],
|
||||
|
|
@ -97,6 +130,15 @@ REQUIREMENT_ANALYSIS = ActionNode(
|
|||
example="",
|
||||
)
|
||||
|
||||
REFINED_REQUIREMENT_ANALYSIS = ActionNode(
|
||||
key="Refined Requirement Analysis",
|
||||
expected_type=List[str],
|
||||
instruction="Review and refine the existing requirement analysis to align with the evolving needs of the project "
|
||||
"due to incremental development. Ensure the analysis comprehensively covers the new features and enhancements "
|
||||
"required for the refined project scope.",
|
||||
example=["Require add/update/modify ..."],
|
||||
)
|
||||
|
||||
REQUIREMENT_POOL = ActionNode(
|
||||
key="Requirement Pool",
|
||||
expected_type=List[List[str]],
|
||||
|
|
@ -104,6 +146,14 @@ REQUIREMENT_POOL = ActionNode(
|
|||
example=[["P0", "The main code ..."], ["P0", "The game algorithm ..."]],
|
||||
)
|
||||
|
||||
REFINED_REQUIREMENT_POOL = ActionNode(
|
||||
key="Refined Requirement Pool",
|
||||
expected_type=List[List[str]],
|
||||
instruction="List down the top 5 to 7 requirements with their priority (P0, P1, P2). "
|
||||
"Cover both legacy content and incremental content. Retain content unrelated to incremental development",
|
||||
example=[["P0", "The main code ..."], ["P0", "The game algorithm ..."]],
|
||||
)
|
||||
|
||||
UI_DESIGN_DRAFT = ActionNode(
|
||||
key="UI Design draft",
|
||||
expected_type=str,
|
||||
|
|
@ -152,15 +202,22 @@ NODES = [
|
|||
ANYTHING_UNCLEAR,
|
||||
]
|
||||
|
||||
REFINED_NODES = [
|
||||
LANGUAGE,
|
||||
PROGRAMMING_LANGUAGE,
|
||||
REFINED_REQUIREMENTS,
|
||||
PROJECT_NAME,
|
||||
REFINED_PRODUCT_GOALS,
|
||||
REFINED_USER_STORIES,
|
||||
COMPETITIVE_ANALYSIS,
|
||||
COMPETITIVE_QUADRANT_CHART,
|
||||
REFINED_REQUIREMENT_ANALYSIS,
|
||||
REFINED_REQUIREMENT_POOL,
|
||||
UI_DESIGN_DRAFT,
|
||||
ANYTHING_UNCLEAR,
|
||||
]
|
||||
|
||||
WRITE_PRD_NODE = ActionNode.from_children("WritePRD", NODES)
|
||||
REFINED_PRD_NODE = ActionNode.from_children("RefinedPRD", REFINED_NODES)
|
||||
WP_ISSUE_TYPE_NODE = ActionNode.from_children("WP_ISSUE_TYPE", [ISSUE_TYPE, REASON])
|
||||
WP_IS_RELATIVE_NODE = ActionNode.from_children("WP_IS_RELATIVE", [IS_RELATIVE, REASON])
|
||||
|
||||
|
||||
def main():
|
||||
prompt = WRITE_PRD_NODE.compile(context="")
|
||||
logger.info(prompt)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
|
|
|||
|
|
@ -13,7 +13,7 @@ from metagpt.actions.action import Action
|
|||
|
||||
class WritePRDReview(Action):
|
||||
name: str = ""
|
||||
context: Optional[str] = None
|
||||
i_context: Optional[str] = None
|
||||
|
||||
prd: Optional[str] = None
|
||||
desc: str = "Based on the PRD, conduct a PRD Review, providing clear and detailed feedback"
|
||||
|
|
|
|||
|
|
@ -8,14 +8,14 @@
|
|||
from typing import Optional
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.context import Context
|
||||
from metagpt.logs import logger
|
||||
|
||||
|
||||
class WriteTeachingPlanPart(Action):
|
||||
"""Write Teaching Plan Part"""
|
||||
|
||||
context: Optional[str] = None
|
||||
i_context: Optional[str] = None
|
||||
topic: str = ""
|
||||
language: str = "Chinese"
|
||||
rsp: Optional[str] = None
|
||||
|
|
@ -24,7 +24,7 @@ class WriteTeachingPlanPart(Action):
|
|||
statement_patterns = TeachingPlanBlock.TOPIC_STATEMENTS.get(self.topic, [])
|
||||
statements = []
|
||||
for p in statement_patterns:
|
||||
s = self.format_value(p)
|
||||
s = self.format_value(p, context=self.context)
|
||||
statements.append(s)
|
||||
formatter = (
|
||||
TeachingPlanBlock.PROMPT_TITLE_TEMPLATE
|
||||
|
|
@ -35,7 +35,7 @@ class WriteTeachingPlanPart(Action):
|
|||
formation=TeachingPlanBlock.FORMATION,
|
||||
role=self.prefix,
|
||||
statements="\n".join(statements),
|
||||
lesson=self.context,
|
||||
lesson=self.i_context,
|
||||
topic=self.topic,
|
||||
language=self.language,
|
||||
)
|
||||
|
|
@ -68,20 +68,23 @@ class WriteTeachingPlanPart(Action):
|
|||
return self.topic
|
||||
|
||||
@staticmethod
|
||||
def format_value(value):
|
||||
def format_value(value, context: Context):
|
||||
"""Fill parameters inside `value` with `options`."""
|
||||
if not isinstance(value, str):
|
||||
return value
|
||||
if "{" not in value:
|
||||
return value
|
||||
|
||||
merged_opts = CONFIG.options or {}
|
||||
options = context.config.model_dump()
|
||||
for k, v in context.kwargs:
|
||||
options[k] = v # None value is allowed to override and disable the value from config.
|
||||
opts = {k: v for k, v in options.items() if v is not None}
|
||||
try:
|
||||
return value.format(**merged_opts)
|
||||
return value.format(**opts)
|
||||
except KeyError as e:
|
||||
logger.warning(f"Parameter is missing:{e}")
|
||||
|
||||
for k, v in merged_opts.items():
|
||||
for k, v in opts.items():
|
||||
value = value.replace("{" + f"{k}" + "}", str(v))
|
||||
return value
|
||||
|
||||
|
|
|
|||
|
|
@ -39,7 +39,7 @@ you should correctly import the necessary classes based on these file locations!
|
|||
|
||||
class WriteTest(Action):
|
||||
name: str = "WriteTest"
|
||||
context: Optional[TestingContext] = None
|
||||
i_context: Optional[TestingContext] = None
|
||||
|
||||
async def write_code(self, prompt):
|
||||
code_rsp = await self._aask(prompt)
|
||||
|
|
@ -55,16 +55,16 @@ class WriteTest(Action):
|
|||
return code
|
||||
|
||||
async def run(self, *args, **kwargs) -> TestingContext:
|
||||
if not self.context.test_doc:
|
||||
self.context.test_doc = Document(
|
||||
filename="test_" + self.context.code_doc.filename, root_path=TEST_CODES_FILE_REPO
|
||||
if not self.i_context.test_doc:
|
||||
self.i_context.test_doc = Document(
|
||||
filename="test_" + self.i_context.code_doc.filename, root_path=TEST_CODES_FILE_REPO
|
||||
)
|
||||
fake_root = "/data"
|
||||
prompt = PROMPT_TEMPLATE.format(
|
||||
code_to_test=self.context.code_doc.content,
|
||||
test_file_name=self.context.test_doc.filename,
|
||||
source_file_path=fake_root + "/" + self.context.code_doc.root_relative_path,
|
||||
code_to_test=self.i_context.code_doc.content,
|
||||
test_file_name=self.i_context.test_doc.filename,
|
||||
source_file_path=fake_root + "/" + self.i_context.code_doc.root_relative_path,
|
||||
workspace=fake_root,
|
||||
)
|
||||
self.context.test_doc.content = await self.write_code(prompt)
|
||||
return self.context
|
||||
self.i_context.test_doc.content = await self.write_code(prompt)
|
||||
return self.i_context
|
||||
|
|
|
|||
|
|
@ -1,287 +0,0 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Provide configuration, singleton
|
||||
@Modified By: mashenquan, 2023/11/27.
|
||||
1. According to Section 2.2.3.11 of RFC 135, add git repository support.
|
||||
2. Add the parameter `src_workspace` for the old version project path.
|
||||
"""
|
||||
import datetime
|
||||
import json
|
||||
import os
|
||||
import warnings
|
||||
from copy import deepcopy
|
||||
from enum import Enum
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
from uuid import uuid4
|
||||
|
||||
import yaml
|
||||
|
||||
from metagpt.const import DEFAULT_WORKSPACE_ROOT, METAGPT_ROOT, OPTIONS
|
||||
from metagpt.logs import logger
|
||||
from metagpt.tools import SearchEngineType, WebBrowserEngineType
|
||||
from metagpt.utils.common import require_python_version
|
||||
from metagpt.utils.cost_manager import CostManager
|
||||
from metagpt.utils.singleton import Singleton
|
||||
|
||||
|
||||
class NotConfiguredException(Exception):
|
||||
"""Exception raised for errors in the configuration.
|
||||
|
||||
Attributes:
|
||||
message -- explanation of the error
|
||||
"""
|
||||
|
||||
def __init__(self, message="The required configuration is not set"):
|
||||
self.message = message
|
||||
super().__init__(self.message)
|
||||
|
||||
|
||||
class LLMProviderEnum(Enum):
|
||||
OPENAI = "openai"
|
||||
ANTHROPIC = "anthropic"
|
||||
SPARK = "spark"
|
||||
ZHIPUAI = "zhipuai"
|
||||
FIREWORKS = "fireworks"
|
||||
OPEN_LLM = "open_llm"
|
||||
GEMINI = "gemini"
|
||||
METAGPT = "metagpt"
|
||||
AZURE_OPENAI = "azure_openai"
|
||||
OLLAMA = "ollama"
|
||||
|
||||
def __missing__(self, key):
|
||||
return self.OPENAI
|
||||
|
||||
|
||||
class Config(metaclass=Singleton):
|
||||
"""
|
||||
Regular usage method:
|
||||
config = Config("config.yaml")
|
||||
secret_key = config.get_key("MY_SECRET_KEY")
|
||||
print("Secret key:", secret_key)
|
||||
"""
|
||||
|
||||
_instance = None
|
||||
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, cost_data=""):
|
||||
global_options = OPTIONS.get()
|
||||
# cli paras
|
||||
self.project_path = ""
|
||||
self.project_name = ""
|
||||
self.inc = False
|
||||
self.reqa_file = ""
|
||||
self.max_auto_summarize_code = 0
|
||||
self.git_reinit = False
|
||||
|
||||
self._init_with_config_files_and_env(yaml_file)
|
||||
# The agent needs to be billed per user, so billing information cannot be destroyed when the session ends.
|
||||
self.cost_manager = CostManager(**json.loads(cost_data)) if cost_data else CostManager()
|
||||
self._update()
|
||||
global_options.update(OPTIONS.get())
|
||||
logger.debug("Config loading done.")
|
||||
|
||||
def get_default_llm_provider_enum(self) -> LLMProviderEnum:
|
||||
"""Get first valid LLM provider enum"""
|
||||
mappings = {
|
||||
LLMProviderEnum.OPENAI: bool(
|
||||
self._is_valid_llm_key(self.OPENAI_API_KEY) and not self.OPENAI_API_TYPE and self.OPENAI_API_MODEL
|
||||
),
|
||||
LLMProviderEnum.ANTHROPIC: self._is_valid_llm_key(self.ANTHROPIC_API_KEY),
|
||||
LLMProviderEnum.ZHIPUAI: self._is_valid_llm_key(self.ZHIPUAI_API_KEY),
|
||||
LLMProviderEnum.FIREWORKS: self._is_valid_llm_key(self.FIREWORKS_API_KEY),
|
||||
LLMProviderEnum.OPEN_LLM: self._is_valid_llm_key(self.OPEN_LLM_API_BASE),
|
||||
LLMProviderEnum.GEMINI: self._is_valid_llm_key(self.GEMINI_API_KEY),
|
||||
LLMProviderEnum.METAGPT: bool(
|
||||
self._is_valid_llm_key(self.OPENAI_API_KEY) and self.OPENAI_API_TYPE == "metagpt"
|
||||
),
|
||||
LLMProviderEnum.AZURE_OPENAI: bool(
|
||||
self._is_valid_llm_key(self.OPENAI_API_KEY)
|
||||
and self.OPENAI_API_TYPE == "azure"
|
||||
and self.DEPLOYMENT_NAME
|
||||
and self.OPENAI_API_VERSION
|
||||
),
|
||||
LLMProviderEnum.OLLAMA: self._is_valid_llm_key(self.OLLAMA_API_BASE),
|
||||
}
|
||||
provider = None
|
||||
for k, v in mappings.items():
|
||||
if v:
|
||||
provider = k
|
||||
break
|
||||
if provider is None:
|
||||
if self.DEFAULT_PROVIDER:
|
||||
provider = LLMProviderEnum(self.DEFAULT_PROVIDER)
|
||||
else:
|
||||
raise NotConfiguredException("You should config a LLM configuration first")
|
||||
|
||||
if provider is LLMProviderEnum.GEMINI and not require_python_version(req_version=(3, 10)):
|
||||
warnings.warn("Use Gemini requires Python >= 3.10")
|
||||
model_name = self.get_model_name(provider=provider)
|
||||
if model_name:
|
||||
logger.info(f"{provider} Model: {model_name}")
|
||||
if provider:
|
||||
logger.info(f"API: {provider}")
|
||||
return provider
|
||||
|
||||
def get_model_name(self, provider=None) -> str:
|
||||
provider = provider or self.get_default_llm_provider_enum()
|
||||
model_mappings = {
|
||||
LLMProviderEnum.OPENAI: self.OPENAI_API_MODEL,
|
||||
LLMProviderEnum.AZURE_OPENAI: self.DEPLOYMENT_NAME,
|
||||
}
|
||||
return model_mappings.get(provider, "")
|
||||
|
||||
@staticmethod
|
||||
def _is_valid_llm_key(k: str) -> bool:
|
||||
return bool(k and k != "YOUR_API_KEY")
|
||||
|
||||
def _update(self):
|
||||
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")
|
||||
self.zhipuai_api_key = self._get("ZHIPUAI_API_KEY")
|
||||
self.open_llm_api_base = self._get("OPEN_LLM_API_BASE")
|
||||
self.open_llm_api_model = self._get("OPEN_LLM_API_MODEL")
|
||||
self.fireworks_api_key = self._get("FIREWORKS_API_KEY")
|
||||
self.gemini_api_key = self._get("GEMINI_API_KEY")
|
||||
self.ollama_api_base = self._get("OLLAMA_API_BASE")
|
||||
self.ollama_api_model = self._get("OLLAMA_API_MODEL")
|
||||
|
||||
if not self._get("DISABLE_LLM_PROVIDER_CHECK"):
|
||||
_ = self.get_default_llm_provider_enum()
|
||||
|
||||
self.openai_base_url = self._get("OPENAI_BASE_URL")
|
||||
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)
|
||||
self.openai_api_model = self._get("OPENAI_API_MODEL", "gpt-4-1106-preview")
|
||||
self.max_tokens_rsp = self._get("MAX_TOKENS", 2048)
|
||||
self.deployment_name = self._get("DEPLOYMENT_NAME", "gpt-4")
|
||||
|
||||
self.spark_appid = self._get("SPARK_APPID")
|
||||
self.spark_api_secret = self._get("SPARK_API_SECRET")
|
||||
self.spark_api_key = self._get("SPARK_API_KEY")
|
||||
self.domain = self._get("DOMAIN")
|
||||
self.spark_url = self._get("SPARK_URL")
|
||||
|
||||
self.fireworks_api_base = self._get("FIREWORKS_API_BASE")
|
||||
self.fireworks_api_model = self._get("FIREWORKS_API_MODEL")
|
||||
|
||||
self.claude_api_key = self._get("ANTHROPIC_API_KEY")
|
||||
self.serpapi_api_key = self._get("SERPAPI_API_KEY")
|
||||
self.serper_api_key = self._get("SERPER_API_KEY")
|
||||
self.google_api_key = self._get("GOOGLE_API_KEY")
|
||||
self.google_cse_id = self._get("GOOGLE_CSE_ID")
|
||||
self.search_engine = SearchEngineType(self._get("SEARCH_ENGINE", SearchEngineType.SERPAPI_GOOGLE))
|
||||
self.web_browser_engine = WebBrowserEngineType(self._get("WEB_BROWSER_ENGINE", WebBrowserEngineType.PLAYWRIGHT))
|
||||
self.playwright_browser_type = self._get("PLAYWRIGHT_BROWSER_TYPE", "chromium")
|
||||
self.selenium_browser_type = self._get("SELENIUM_BROWSER_TYPE", "chrome")
|
||||
|
||||
self.long_term_memory = self._get("LONG_TERM_MEMORY", False)
|
||||
if self.long_term_memory:
|
||||
logger.warning("LONG_TERM_MEMORY is True")
|
||||
self.cost_manager.max_budget = self._get("MAX_BUDGET", 10.0)
|
||||
self.code_review_k_times = 2
|
||||
|
||||
self.puppeteer_config = self._get("PUPPETEER_CONFIG", "")
|
||||
self.mmdc = self._get("MMDC", "mmdc")
|
||||
self.calc_usage = self._get("CALC_USAGE", True)
|
||||
self.model_for_researcher_summary = self._get("MODEL_FOR_RESEARCHER_SUMMARY")
|
||||
self.model_for_researcher_report = self._get("MODEL_FOR_RESEARCHER_REPORT")
|
||||
self.mermaid_engine = self._get("MERMAID_ENGINE", "nodejs")
|
||||
self.pyppeteer_executable_path = self._get("PYPPETEER_EXECUTABLE_PATH", "")
|
||||
|
||||
workspace_uid = (
|
||||
self._get("WORKSPACE_UID") or f"{datetime.datetime.now().strftime('%Y%m%d%H%M%S')}-{uuid4().hex[-8:]}"
|
||||
)
|
||||
self.repair_llm_output = self._get("REPAIR_LLM_OUTPUT", False)
|
||||
self.prompt_schema = self._get("PROMPT_FORMAT", "json")
|
||||
self.workspace_path = Path(self._get("WORKSPACE_PATH", DEFAULT_WORKSPACE_ROOT))
|
||||
val = self._get("WORKSPACE_PATH_WITH_UID")
|
||||
if val and val.lower() == "true": # for agent
|
||||
self.workspace_path = self.workspace_path / workspace_uid
|
||||
self._ensure_workspace_exists()
|
||||
self.max_auto_summarize_code = self.max_auto_summarize_code or self._get("MAX_AUTO_SUMMARIZE_CODE", 1)
|
||||
self.timeout = int(self._get("TIMEOUT", 3))
|
||||
|
||||
def update_via_cli(self, project_path, project_name, inc, reqa_file, max_auto_summarize_code):
|
||||
"""update config via cli"""
|
||||
|
||||
# Use in the PrepareDocuments action according to Section 2.2.3.5.1 of RFC 135.
|
||||
if project_path:
|
||||
inc = True
|
||||
project_name = project_name or Path(project_path).name
|
||||
self.project_path = project_path
|
||||
self.project_name = project_name
|
||||
self.inc = inc
|
||||
self.reqa_file = reqa_file
|
||||
self.max_auto_summarize_code = max_auto_summarize_code
|
||||
|
||||
def _ensure_workspace_exists(self):
|
||||
self.workspace_path.mkdir(parents=True, exist_ok=True)
|
||||
logger.debug(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, self.home_yaml_file]:
|
||||
if not _yaml_file.exists():
|
||||
continue
|
||||
|
||||
# Load local YAML file
|
||||
with open(_yaml_file, "r", encoding="utf-8") as file:
|
||||
yaml_data = yaml.safe_load(file)
|
||||
if not yaml_data:
|
||||
continue
|
||||
configs.update(yaml_data)
|
||||
OPTIONS.set(configs)
|
||||
|
||||
@staticmethod
|
||||
def _get(*args, **kwargs):
|
||||
i = OPTIONS.get()
|
||||
return i.get(*args, **kwargs)
|
||||
|
||||
def get(self, key, *args, **kwargs):
|
||||
"""Retrieve values from config/key.yaml, config/config.yaml, and environment variables.
|
||||
Throw an error if not found."""
|
||||
value = self._get(key, *args, **kwargs)
|
||||
if value is None:
|
||||
raise ValueError(f"Key '{key}' not found in environment variables or in the YAML file")
|
||||
return value
|
||||
|
||||
def __setattr__(self, name: str, value: Any) -> None:
|
||||
OPTIONS.get()[name] = value
|
||||
|
||||
def __getattr__(self, name: str) -> Any:
|
||||
i = OPTIONS.get()
|
||||
return i.get(name)
|
||||
|
||||
def set_context(self, options: dict):
|
||||
"""Update current config"""
|
||||
if not options:
|
||||
return
|
||||
opts = deepcopy(OPTIONS.get())
|
||||
opts.update(options)
|
||||
OPTIONS.set(opts)
|
||||
self._update()
|
||||
|
||||
@property
|
||||
def options(self):
|
||||
"""Return all key-values"""
|
||||
return OPTIONS.get()
|
||||
|
||||
def new_environ(self):
|
||||
"""Return a new os.environ object"""
|
||||
env = os.environ.copy()
|
||||
i = self.options
|
||||
env.update({k: v for k, v in i.items() if isinstance(v, str)})
|
||||
return env
|
||||
|
||||
|
||||
CONFIG = Config()
|
||||
151
metagpt/config2.py
Normal file
151
metagpt/config2.py
Normal file
|
|
@ -0,0 +1,151 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2024/1/4 01:25
|
||||
@Author : alexanderwu
|
||||
@File : config2.py
|
||||
"""
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import Dict, Iterable, List, Literal, Optional
|
||||
|
||||
from pydantic import BaseModel, model_validator
|
||||
|
||||
from metagpt.configs.browser_config import BrowserConfig
|
||||
from metagpt.configs.llm_config import LLMConfig, LLMType
|
||||
from metagpt.configs.mermaid_config import MermaidConfig
|
||||
from metagpt.configs.redis_config import RedisConfig
|
||||
from metagpt.configs.s3_config import S3Config
|
||||
from metagpt.configs.search_config import SearchConfig
|
||||
from metagpt.configs.workspace_config import WorkspaceConfig
|
||||
from metagpt.const import CONFIG_ROOT, METAGPT_ROOT
|
||||
from metagpt.utils.yaml_model import YamlModel
|
||||
|
||||
|
||||
class CLIParams(BaseModel):
|
||||
"""CLI parameters"""
|
||||
|
||||
project_path: str = ""
|
||||
project_name: str = ""
|
||||
inc: bool = False
|
||||
reqa_file: str = ""
|
||||
max_auto_summarize_code: int = 0
|
||||
git_reinit: bool = False
|
||||
|
||||
@model_validator(mode="after")
|
||||
def check_project_path(self):
|
||||
"""Check project_path and project_name"""
|
||||
if self.project_path:
|
||||
self.inc = True
|
||||
self.project_name = self.project_name or Path(self.project_path).name
|
||||
return self
|
||||
|
||||
|
||||
class Config(CLIParams, YamlModel):
|
||||
"""Configurations for MetaGPT"""
|
||||
|
||||
# Key Parameters
|
||||
llm: LLMConfig
|
||||
|
||||
# Global Proxy. Will be used if llm.proxy is not set
|
||||
proxy: str = ""
|
||||
|
||||
# Tool Parameters
|
||||
search: SearchConfig = SearchConfig()
|
||||
browser: BrowserConfig = BrowserConfig()
|
||||
mermaid: MermaidConfig = MermaidConfig()
|
||||
|
||||
# Storage Parameters
|
||||
s3: Optional[S3Config] = None
|
||||
redis: Optional[RedisConfig] = None
|
||||
|
||||
# Misc Parameters
|
||||
repair_llm_output: bool = False
|
||||
prompt_schema: Literal["json", "markdown", "raw"] = "json"
|
||||
workspace: WorkspaceConfig = WorkspaceConfig()
|
||||
enable_longterm_memory: bool = False
|
||||
code_review_k_times: int = 2
|
||||
|
||||
# Will be removed in the future
|
||||
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 = ""
|
||||
|
||||
@classmethod
|
||||
def from_home(cls, path):
|
||||
"""Load config from ~/.metagpt/config2.yaml"""
|
||||
pathname = CONFIG_ROOT / path
|
||||
if not pathname.exists():
|
||||
return None
|
||||
return Config.from_yaml_file(pathname)
|
||||
|
||||
@classmethod
|
||||
def default(cls):
|
||||
"""Load default config
|
||||
- Priority: env < default_config_paths
|
||||
- Inside default_config_paths, the latter one overwrites the former one
|
||||
"""
|
||||
default_config_paths: List[Path] = [
|
||||
METAGPT_ROOT / "config/config2.yaml",
|
||||
CONFIG_ROOT / "config2.yaml",
|
||||
]
|
||||
|
||||
dicts = [dict(os.environ)]
|
||||
dicts += [Config.read_yaml(path) for path in default_config_paths]
|
||||
final = merge_dict(dicts)
|
||||
return Config(**final)
|
||||
|
||||
@classmethod
|
||||
def from_llm_config(cls, llm_config: dict):
|
||||
"""user config llm
|
||||
example:
|
||||
llm_config = {"api_type": "xxx", "api_key": "xxx", "model": "xxx"}
|
||||
gpt4 = Config.from_llm_config(llm_config)
|
||||
A = Role(name="A", profile="Democratic candidate", goal="Win the election", actions=[a1], watch=[a2], config=gpt4)
|
||||
"""
|
||||
llm_config = LLMConfig.model_validate(llm_config)
|
||||
dicts = [dict(os.environ)]
|
||||
dicts += [{"llm": llm_config}]
|
||||
final = merge_dict(dicts)
|
||||
return Config(**final)
|
||||
|
||||
def update_via_cli(self, project_path, project_name, inc, reqa_file, max_auto_summarize_code):
|
||||
"""update config via cli"""
|
||||
|
||||
# Use in the PrepareDocuments action according to Section 2.2.3.5.1 of RFC 135.
|
||||
if project_path:
|
||||
inc = True
|
||||
project_name = project_name or Path(project_path).name
|
||||
self.project_path = project_path
|
||||
self.project_name = project_name
|
||||
self.inc = inc
|
||||
self.reqa_file = reqa_file
|
||||
self.max_auto_summarize_code = max_auto_summarize_code
|
||||
|
||||
def get_openai_llm(self) -> Optional[LLMConfig]:
|
||||
"""Get OpenAI LLMConfig by name. If no OpenAI, raise Exception"""
|
||||
if self.llm.api_type == LLMType.OPENAI:
|
||||
return self.llm
|
||||
return None
|
||||
|
||||
def get_azure_llm(self) -> Optional[LLMConfig]:
|
||||
"""Get Azure LLMConfig by name. If no Azure, raise Exception"""
|
||||
if self.llm.api_type == LLMType.AZURE:
|
||||
return self.llm
|
||||
return None
|
||||
|
||||
|
||||
def merge_dict(dicts: Iterable[Dict]) -> Dict:
|
||||
"""Merge multiple dicts into one, with the latter dict overwriting the former"""
|
||||
result = {}
|
||||
for dictionary in dicts:
|
||||
result.update(dictionary)
|
||||
return result
|
||||
|
||||
|
||||
config = Config.default()
|
||||
|
|
@ -1,7 +1,7 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/5/11 14:44
|
||||
@Time : 2024/1/4 16:33
|
||||
@Author : alexanderwu
|
||||
@File : test_action.py
|
||||
@File : __init__.py
|
||||
"""
|
||||
20
metagpt/configs/browser_config.py
Normal file
20
metagpt/configs/browser_config.py
Normal file
|
|
@ -0,0 +1,20 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2024/1/4 19:06
|
||||
@Author : alexanderwu
|
||||
@File : browser_config.py
|
||||
"""
|
||||
from typing import Literal
|
||||
|
||||
from metagpt.tools import WebBrowserEngineType
|
||||
from metagpt.utils.yaml_model import YamlModel
|
||||
|
||||
|
||||
class BrowserConfig(YamlModel):
|
||||
"""Config for Browser"""
|
||||
|
||||
engine: WebBrowserEngineType = WebBrowserEngineType.PLAYWRIGHT
|
||||
browser_type: Literal["chromium", "firefox", "webkit", "chrome", "firefox", "edge", "ie"] = "chromium"
|
||||
"""If the engine is Playwright, the value should be one of "chromium", "firefox", or "webkit". If it is Selenium, the value
|
||||
should be either "chrome", "firefox", "edge", or "ie"."""
|
||||
90
metagpt/configs/llm_config.py
Normal file
90
metagpt/configs/llm_config.py
Normal file
|
|
@ -0,0 +1,90 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2024/1/4 16:33
|
||||
@Author : alexanderwu
|
||||
@File : llm_config.py
|
||||
"""
|
||||
from enum import Enum
|
||||
from typing import Optional
|
||||
|
||||
from pydantic import field_validator
|
||||
|
||||
from metagpt.utils.yaml_model import YamlModel
|
||||
|
||||
|
||||
class LLMType(Enum):
|
||||
OPENAI = "openai"
|
||||
ANTHROPIC = "anthropic"
|
||||
CLAUDE = "claude" # alias name of anthropic
|
||||
SPARK = "spark"
|
||||
ZHIPUAI = "zhipuai"
|
||||
FIREWORKS = "fireworks"
|
||||
OPEN_LLM = "open_llm"
|
||||
GEMINI = "gemini"
|
||||
METAGPT = "metagpt"
|
||||
AZURE = "azure"
|
||||
OLLAMA = "ollama"
|
||||
QIANFAN = "qianfan" # Baidu BCE
|
||||
DASHSCOPE = "dashscope" # Aliyun LingJi DashScope
|
||||
MOONSHOT = "moonshot"
|
||||
MISTRAL = "mistral"
|
||||
YI = "yi" # lingyiwanwu
|
||||
|
||||
def __missing__(self, key):
|
||||
return self.OPENAI
|
||||
|
||||
|
||||
class LLMConfig(YamlModel):
|
||||
"""Config for LLM
|
||||
|
||||
OpenAI: https://github.com/openai/openai-python/blob/main/src/openai/resources/chat/completions.py#L681
|
||||
Optional Fields in pydantic: https://docs.pydantic.dev/latest/migration/#required-optional-and-nullable-fields
|
||||
"""
|
||||
|
||||
api_key: str = "sk-"
|
||||
api_type: LLMType = LLMType.OPENAI
|
||||
base_url: str = "https://api.openai.com/v1"
|
||||
api_version: Optional[str] = None
|
||||
|
||||
model: Optional[str] = None # also stands for DEPLOYMENT_NAME
|
||||
pricing_plan: Optional[str] = None # Cost Settlement Plan Parameters.
|
||||
|
||||
# For Cloud Service Provider like Baidu/ Alibaba
|
||||
access_key: Optional[str] = None
|
||||
secret_key: Optional[str] = None
|
||||
endpoint: Optional[str] = None # for self-deployed model on the cloud
|
||||
|
||||
# For Spark(Xunfei), maybe remove later
|
||||
app_id: Optional[str] = None
|
||||
api_secret: Optional[str] = None
|
||||
domain: Optional[str] = None
|
||||
|
||||
# For Chat Completion
|
||||
max_token: int = 4096
|
||||
temperature: float = 0.0
|
||||
top_p: float = 1.0
|
||||
top_k: int = 0
|
||||
repetition_penalty: float = 1.0
|
||||
stop: Optional[str] = None
|
||||
presence_penalty: float = 0.0
|
||||
frequency_penalty: float = 0.0
|
||||
best_of: Optional[int] = None
|
||||
n: Optional[int] = None
|
||||
stream: bool = False
|
||||
logprobs: Optional[bool] = None # https://cookbook.openai.com/examples/using_logprobs
|
||||
top_logprobs: Optional[int] = None
|
||||
timeout: int = 60
|
||||
|
||||
# For Network
|
||||
proxy: Optional[str] = None
|
||||
|
||||
# Cost Control
|
||||
calc_usage: bool = True
|
||||
|
||||
@field_validator("api_key")
|
||||
@classmethod
|
||||
def check_llm_key(cls, v):
|
||||
if v in ["", None, "YOUR_API_KEY"]:
|
||||
raise ValueError("Please set your API key in config2.yaml")
|
||||
return v
|
||||
19
metagpt/configs/mermaid_config.py
Normal file
19
metagpt/configs/mermaid_config.py
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2024/1/4 19:07
|
||||
@Author : alexanderwu
|
||||
@File : mermaid_config.py
|
||||
"""
|
||||
from typing import Literal
|
||||
|
||||
from metagpt.utils.yaml_model import YamlModel
|
||||
|
||||
|
||||
class MermaidConfig(YamlModel):
|
||||
"""Config for Mermaid"""
|
||||
|
||||
engine: Literal["nodejs", "ink", "playwright", "pyppeteer"] = "nodejs"
|
||||
path: str = "mmdc" # mmdc
|
||||
puppeteer_config: str = ""
|
||||
pyppeteer_path: str = "/usr/bin/google-chrome-stable"
|
||||
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