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Merge branch 'da_change' into 'mgx_ops'

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rm redundant

See merge request pub/MetaGPT!342
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141
metagpt/actions/di/detect_intent.py
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from __future__ import annotations
import asyncio
import re
from enum import Enum
from typing import Tuple
from pydantic import BaseModel
from metagpt.actions import Action
from metagpt.schema import Message
class SOPItemDef(BaseModel):
"""
Represents an item in a Standard Operating Procedure (SOP).
Attributes:
name (str): name of the SOP item.
description (str): The description or title of the SOP.
sop (List[str]): The steps or details of the SOP.
"""
name: str
description: str
sop: list[str] = []
class SOPItem(Enum):
SOFTWARE_DEVELOPMENT = SOPItemDef(
name="software development",
description="Software development intention including developing or building software, games, app, websites, etc. EXCLUDING bug fixes, report any issues, environment setup, terminal operations, and pip install.",
sop=[
"Writes a PRD based on software requirements.",
"Writes a system design to the project repository, based on the PRD of the project. Write high-level system design instead of the actual code.",
"Writes a project plan to the project repository, based on the design of the project.",
"Writes code to implement designed features according to the project plan and adds them to the project repository.",
"Stage and commit changes for the project repository using Git.",
],
)
# FIX_BUGS = SOPItemDef(
# name="fix bugs",
# description="Fix bugs in a given project.",
# sop=[
# "Fix bugs in the project repository.",
# "Stage and commit changes for the project repository using Git.",
# ],
# )
# FORMAT_REPO = SOPItemDef(
# name="format repo",
# description="download repository from git and format the project to MetaGPT project",
# sop=[
# "Imports a project from a Git website and formats it to MetaGPT project format to enable incremental appending requirements.",
# "Stage and commit changes for the project repository using Git.",
# ],
# )
WEB_OPERATION = SOPItemDef(
name="web operation",
description="web browsing, scraping, imitation and other interaction with the web",
)
OTHER = SOPItemDef(
name="other",
description="Other intentions that do not fall into the above categories, including data science, data analysis, machine learning, deep learning and text-to-image etc.",
)
@property
def type_name(self):
return self.value.name
@classmethod
def get_type(cls, type_name):
for member in cls:
if member.type_name == type_name:
return member.value
return None
DETECT_PROMPT = """
# User Requirement
{user_requirement}
# Intentions
{intentions}
# Task
Classify user requirement into one type of the above intentions, output the index of the intention directly.
Intention index:
"""
REQ_WITH_SOP = """
{user_requirement}
## Knowledge
To meet user requirements, the following standard operating procedure(SOP) must be used:
{sop}
"""
class DetectIntent(Action):
async def run(self, with_message: Message, **kwargs) -> Tuple[str, str]:
user_requirement = with_message.content
mappings = {i + 1: si for i, si in enumerate(SOPItem)}
intentions = "\n".join([f"{i + 1}. {si.type_name}: {si.value.description}" for i, si in enumerate(SOPItem)])
prompt = DETECT_PROMPT.format(user_requirement=user_requirement, intentions=intentions)
rsp = await self._aask(prompt)
match = re.search(r"\d+", rsp)
index = len(SOPItem) + 1 # 1-based
if match:
index = int(match.group()) # 1-based
sop = mappings[index].value.sop if index in mappings else None
sop_type = mappings[index].type_name if index in mappings else SOPItem.OTHER.type_name
req_with_sop = (
REQ_WITH_SOP.format(
user_requirement=user_requirement, sop="\n".join([f"{i + 1}. {v}" for i, v in enumerate(sop)])
)
if sop
else user_requirement
)
return req_with_sop, sop_type
async def main():
# Example usage of the DetectIntent action
user_requirements = [
"Develop a 2048 game.",
"Run data analysis on sklearn wine dataset",
"帮我把pip的源设置成：https://pypi.tuna.tsinghua.edu.cn/simple",
"This is a website url does not require login: https://demosc.chinaz.net/Files/DownLoad//moban/202404/moban7767 please write a similar web page,developed in vue language, The package.json dependency must be generated",
"I would like to imitate the website available at https://demosc.chinaz.net/Files/DownLoad//moban/202404/moban7767. Could you please browse through it?",
]
detect_intent = DetectIntent()
for user_requirement in user_requirements:
req_with_sop, sop_type = await detect_intent.run(Message(role="user", content=user_requirement))
print(req_with_sop)
print(f"Detected SOP Type: {sop_type}")
if __name__ == "__main__":
asyncio.run(main())

68
metagpt/roles/di/mgx.py
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# -*- coding: utf-8 -*-
# @Author : stellahong (stellahong@fuzhi.ai)
# @Desc :
import asyncio
from typing import Dict
from metagpt.actions.di.detect_intent import DetectIntent, SOPItem
from metagpt.logs import logger
from metagpt.roles.di.data_interpreter import DataInterpreter
from metagpt.schema import Message
from metagpt.tools.tool_recommend import BM25ToolRecommender
class MGX(DataInterpreter):
use_intent: bool = True
intents: Dict = {}
async def _detect_intent(self, user_msg: Message) -> str:
todo = DetectIntent(context=self.context)
request_with_sop, sop_type = await todo.run(user_msg)
logger.info(f"{sop_type} {request_with_sop}")
if sop_type == SOPItem.SOFTWARE_DEVELOPMENT.type_name:
self.tool_recommender = BM25ToolRecommender(tools=["software development"])
else:
self.tool_recommender = BM25ToolRecommender(tools=["<all>"])
return request_with_sop
async def _plan_and_act(self) -> Message:
"""first plan, then execute an action sequence, i.e. _think (of a plan) -> _act -> _act -> ... Use llm to come up with the plan dynamically."""
# create initial plan and update it until confirmation
goal = self.rc.memory.get()[-1].content # retrieve latest user requirement
if self.use_intent: # add mode
user_message = Message(content=goal, role="user")
goal = await self._detect_intent(user_message)
logger.info(f"Goal is {goal}")
await self.planner.update_plan(goal=goal)
# take on tasks until all finished
while self.planner.current_task:
task = self.planner.current_task
logger.info(f"ready to take on task {task}")
# take on current task
task_result = await self._act_on_task(task)
# process the result, such as reviewing, confirming, plan updating
await self.planner.process_task_result(task_result)
rsp = self.planner.get_useful_memories()[0] # return the completed plan as a response
self.rc.memory.add(rsp) # add to persistent memory
return rsp
if __name__ == "__main__":
test_requirements = [
"design a game using Gym (an open source Python library), including a graphical interface and interactive gameplay"
# "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"
# "获取https://www.stats.gov.cn/sj/sjjd/202307/t20230718_1941322.html的内容，并返回上半年cpi的增长或下降幅度"
]
for requirement in test_requirements:
mgx = MGX()
rsp = asyncio.run(mgx.run(requirement))

56
tests/metagpt/actions/di/test_detect_intent.py
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import pytest
from metagpt.actions.di.detect_intent import DetectIntent
from metagpt.schema import Message
SOFTWARE_DEV_REQ1 = """
I'd like to create a personalized website that features the 'Game of Life' simulation.
"""
SOFTWARE_DEV_REQ2 = """
Create a website widget for TODO list management.
"""
SOFTWARE_DEV_REQ3 = """
Create an official website with a top bar, banner, About Us section, and footer.
"""
DI_REQ1 = """
can you finetune a 78 Llama model using https://github.com/huggingface/peft should be instructions in the Readme.
"""
DI_REQ2 = """
I came across a blog post on the website Mafengwo (https://www.mafengwo.cn/i/17171539.html) that discusses the possibility of generating images with hidden text. The post refers to a script that can be used for this purpose. Could you help me set up this script and use it to generate some images? I would like the images to have the hidden text 'MAX' and also some with 'MetaGPT' as the hidden text.
"""
DI_REQ3 = """
Extract all of the blog posts from `https://stripe.com/blog/page/1` and return a CSV with the columns `date`, `article_text`, `author` and `summary`. Generate a summary for each article yourself.
"""
FIX_BUG_REQ = """
Fix this error from the 2048 game repo: TypeError: __init__() takes 1 positional argument but 2 were given"
"""
FORMAT_REPO_REQ = """
git clone 'https://github.com/spec-first/connexion' and format to MetaGPT project
"""
@pytest.mark.asyncio
@pytest.mark.parametrize(
"requirement, expected_intent_type",
[
(SOFTWARE_DEV_REQ1, "software development"),
(SOFTWARE_DEV_REQ2, "software development"),
(SOFTWARE_DEV_REQ3, "software development"),
(DI_REQ1, "other"),
(DI_REQ2, "other"),
(DI_REQ3, "other"),
(FIX_BUG_REQ, "fix bugs"),
(FORMAT_REPO_REQ, "format repo"),
],
)
async def test_detect_intent(requirement, expected_intent_type):
di = DetectIntent()
_, intent_type = await di.run(Message(role="user", content=requirement))
assert intent_type == expected_intent_type

179
tests/metagpt/roles/di/test_mgx.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from typing import List
import pytest
from metagpt.roles.di.mgx import MGX
from metagpt.schema import Message
DEMO_CONTENT = [
{
"role": "user",
"content": "Can you build TextToSummarize which is a SMS number that I can text and it will scrape a website "
"and summarize it with ChatGPT",
},
{
"role": "assistant",
"content": "Absolutely, I can build a service like TextToSummarize for you. The process will involve setting up"
" an SMS service that can receive your texts, scraping the website content you send, and then using"
" an AI to summarize the content.\nTo get started, I'll need to set up a number for receiving SMS"
", then I'll work on the script to scrape the website content from the URLs you text, and finally."
" I'll integrate it with an AI service to Generalte the summaries.\n I'll keep you updated on my"
" progress!",
},
{"role": "user", "content": "What exactly do we need the web app for?"},
{
"role": "assistant",
"content": "The web app will service as the interface between the SMS service and the AI summarization service"
". When you send a text with a URL to the SMS number, teh web app will process that, scrape the"
" content from the URL, and then use the AI to summarize it. The summary will then be sent back to"
" you. It's the central hub that ties all the components of the service togather.",
},
]
DEMO1_CONTENT = [
{
"role": "user",
"content": "Extract all of the blog posts from `https://stripe.com/blog/page/1` and return a CSV with the"
" columns `date`, `article_text`, `author` and `summary`. Generate a summary for each article"
" yourself.",
}
]
_DEMO2_CONTENT_ASSISTANT = """
user:
## User Requirement
### User Requirement Detail
```text
2048 game
````
### Knowledge
To meet user requirements, the following standard operating procedure(SOP) must be used. SOP descriptions cannot be modified; user requirements can only be appended to the end of corresponding steps.
- Writes a PRD based on software requirements.
- Writes a design to the project repository, based on the PRD of the project.
- Writes a project plan to the project repository, based on the design of the project.
- Writes code to implement designed features according to the project plan and adds them to the project repository.
- Stage and commit changes for the project repository using Git.
## Context
## Current Plan
[
{
"task_id": "1",
"dependent_task_ids": [],
"instruction": "Write a PRD based on the software requirements.",
"task_type": "other",
"code": "from metagpt.tools.libs.software_development import write_prd\n\nasync def create_2048_game_prd():\n idea = \"Create a 2048 game\"\n prd_path = await write_prd(idea)\n return prd_path\n\nawait create_2048_game_prd()\n",
"result": ",,,,,[,CONTENT]\n{\n \"Language\": \"en_us\",\n \"Programming Language\": \"Python\",\n \"Original Requirements\": \"Create a, 2048 game\",\n \"Project Name\": \"game_2048\",\n \"Product Goals\": [\n \"Create an engaging user experience\",\n , \"Improve accessibility, be responsive\",\n \"More beautiful UI\"\n ],\n \"User Stories\": [\n \",As a player, I want to be able to choose difficulty levels\",\n \"As a player,, I want to see my score after each game\",\n \"As a player, I want, to get restart button when I lose\",\n \"As a player, I want to see beautiful UI that make me feel good\",\n \"As a player, I want to play game via mobile phone\"\n , ],\n \"Competitive Analysis\": [\n \"2048 Game, A: Simple interface, lacks responsive features\",\n \"play2048.co: Beautiful and responsive UI with my best score shown\",\n \"2048game.com: Responsive UI with my, best score shown, but many ads\"\n ],\n \"Competitive Quadrant, Chart\": \"quadrantChart\\n title, \\\"Reach and engagement of campaigns\\\"\\n x-axis \\\"Low Reach\\\" --> \\\"High Reach\\\"\\n y-axis \\\"Low Engagement\\\" --> \\\",High Engagement\\\"\\n quadrant-1 \\\"We should expand\\\"\\n quadrant-2 \\\"Need to promote\\\"\\n quadrant,-3 \\\"Re-evaluate\\\"\\n quadrant-4 \\\"May be, improved\\\"\\n \\\"Campaign A\\\": [0.3, 0.6]\\n \\\"Campaign B\\\": [0.45, 0.,23]\\n \\\"Campaign C\\\": [0.57, 0.69]\\n \\\"Campaign D\\\": [0.78, 0.34]\\n , \\\"Campaign E\\\": [0.40, 0.34]\\n \\\"Campaign, F\\\": [0.35, 0.78]\\n \\\"Our Target Product\\\": [0.5, 0.6,]\",\n \"Requirement Analysis\": \"\",\n \"Requirement Pool\": [\n [\n \"P0\",\n, \"The main code ...\"\n ],\n [\n \"P0\",\n \"The game algorithm ...\"\n ]\n, ],\n \"UI Design draft\": \"Basic function description with a simple style and layout.\",\n \"Anything UNCLEAR,\": \"\"\n}\n[/CONTENT]\n,,,,,,,,,,,,{'output': '[{\"type_\": \"str\", \"name\": \"PRD File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/docs/prd/20240401194850.json\"}, {\"type_\": \"str\", \"name\": \"Competitive Analysis\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/competitive_analysis/20240401194850.mmd\"}, {\"type_\": \"str\", \"name\": \"Competitive Analysis\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/competitive_analysis/20240401194850.pdf\"}, {\"type_\": \"str\", \"name\": \"Competitive Analysis\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/competitive_analysis/20240401194850.png\"}, {\"type_\": \"str\", \"name\": \"Competitive Analysis\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/competitive_analysis/20240401194850.svg\"}]', 'tool_name': 'write_prd'},PosixPath('/Users/iorishinier/github/MetaGPT/workspace/game_2048/docs/prd')",
"is_success": true,
"is_finished": true
},
{
"task_id": "2",
"dependent_task_ids": [
"1"
],
"instruction": "Write a design to the project repository, based on the PRD of the project.",
"task_type": "other",
"code": "from metagpt.tools.libs.software_development import write_design\n\nasync def create_2048_game_design(prd_path):\n system_design_path = await write_design(prd_path)\n return system_design_path\n\nawait create_2048_game_design('/Users/iorishinier/github/MetaGPT/workspace/game_2048/docs/prd/20240401194850.json')\n",
"result": ",[CONTENT]\n{\n \"Implementation approach\":, \"We will use the Py,game library to create the game interface and handle user input. The game logic will be implemented using Python classes and data structures to manage the game, board and tiles.\",\n \"File list\": [\n \"main.py,\",\n \"game.py\"\n, ],\n \"Data structures and interfaces\": \"\\nclassDiagram\\n class Game2048 {\\n -int[][] board,\\n -int score\\n -bool game_over\\n +__init__()\\n +reset()\\n +,move(direction: str)\\n +get_board() int[][]\\n +get_score() int\\n +is_game_over() bool\\n }\\n , class UI {\\n +display_board(board: int[][], score: int)\\n, +show_game_over()\\n }\\n Game,2048 --> UI\\n\",\n \"Program call flow\": \"\\nsequenceDiagram,\\n participant M as Main\\n participant G as Game2048,\\n participant UI as UI\\n M->>G: reset,()\\n G-->>UI: display_board(board, score)\\,n M->>G: move(direction)\\n G-->>,G: update board and score\\n G-->>UI:, display_board(board, score)\\n G->>G: is_game_over,()\\n G-->>UI: show_game_over()\\n\",\n,,,,, \"Anything UNCLEAR\": \"\"\n}\n[/CONTENT]\n,,,,,,,,,,,,,,,{'output': '[{\"type_\": \"str\", \"name\": \"Intermedia Design File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/docs/system_design/20240401194850.json\"}, {\"type_\": \"str\", \"name\": \"Design File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/system_design/20240401194850.md\"}, {\"type_\": \"str\", \"name\": \"Class Diagram File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/data_api_design/20240401194850.mmd\"}, {\"type_\": \"str\", \"name\": \"Class Diagram File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/data_api_design/20240401194850.pdf\"}, {\"type_\": \"str\", \"name\": \"Class Diagram File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/data_api_design/20240401194850.png\"}, {\"type_\": \"str\", \"name\": \"Class Diagram File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/data_api_design/20240401194850.svg\"}, {\"type_\": \"str\", \"name\": \"Sequence Diagram File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/seq_flow/20240401194850.mmd\"}, {\"type_\": \"str\", \"name\": \"Sequence Diagram File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/seq_flow/20240401194850.pdf\"}, {\"type_\": \"str\", \"name\": \"Sequence Diagram File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/seq_flow/20240401194850.png\"}, {\"type_\": \"str\", \"name\": \"Sequence Diagram File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/resources/seq_flow/20240401194850.svg\"}]', 'tool_name': 'write_design'},PosixPath('/Users/iorishinier/github/MetaGPT/workspace/game_2048/docs/system_design')",
"is_success": true,
"is_finished": true
},
{
"task_id": "3",
"dependent_task_ids": [
"2"
],
"instruction": "Write a project plan to the project repository, based on the design of the project.",
"task_type": "other",
"code": "from metagpt.tools.libs.software_development import write_project_plan\n\nasync def create_2048_game_project_plan(system_design_path):\n task_path = await write_project_plan(system_design_path)\n return task_path\n\nawait create_2048_game_project_plan('/Users/iorishinier/github/MetaGPT/workspace/game_2048/docs/system_design/20240401194850.json')\n",
"result": ",\n[CONTENT,]\n{\n \"Required Python packages\": [\n \"pygame==2.0.1\"\n ],\n \"Required, Other language third-party packages\": [\n \"No third-party dependencies required,\"\n ],\n \"Logic Analysis\": [\n , [\n \"game.py\",\n \"Contains Game2048, class and functions to manage the game board and tiles\"\n, ],\n [\n \"main.py\",\n \",Contains the main function, and imports Game2048, from game.py\"\n ]\n ],\n \"Task list,\": [\n \"game.py\",\n \"main.py\"\n, ],\n \"Full API spec\":, \"\",\n \"Shared Knowledge\": \"The Pygame library will be used, to create the game interface and handle user input. The game, logic will be implemented using Python classes and data structures to manage the game, board and tiles.\",\n \"Anything UNCLEAR\": \"No unclear aspects,,,,, mentioned.\"\n}\n[/CONTENT]\n{'output': '[{\"type_\": \"str\", \"name\": \"Project Plan\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/docs/task/20240401194850.json\"}]', 'tool_name': 'write_project_plan'},PosixPath('/Users/iorishinier/github/MetaGPT/workspace/game_2048/docs/task')",
"is_success": true,
"is_finished": true
},
{
"task_id": "4",
"dependent_task_ids": [
"3"
],
"instruction": "Write code to implement designed features according to the project plan and add them to the project repository.",
"task_type": "other",
"code": "from metagpt.tools.libs.software_development import write_codes\n\nasync def implement_2048_game_features(task_path):\n src_path = await write_codes(task_path)\n return src_path\n\nawait implement_2048_game_features('/Users/iorishinier/github/MetaGPT/workspace/game_2048/docs/task/20240401194850.json')\n",
"result": ",```python\n,## game.py\n\nclass Game2048,:\n def __init__(self):\n, self.board = [[0 for _, in range(4)] for _ in, range(4)]\n self.score =, 0\n self.game_over =, False\n\n def reset(self):\n , self.board = [[0 for _ in, range(4)] for _, in range(4)]\n self.score = 0\n self,.game_over = False\n\n , def move(self, direction: str):\n, # Implement the logic to move the, tiles in the specified direction\n, pass\n\n def get_board(self) ->, list:\n return self.board\n\n , def get_score(self) -> int:\n, return self.score\n\n def is,_game_over(self) -> bool:\n ,,,,, return self.game_over\n```\n,```,python\n## main.py\n\nimport pygame\nfrom game import Game2048\n\ndef main():\n # Initialize the game\n game = Game2048()\n game.reset()\n\n # Initialize Pygame\n, pygame.init()\n screen = pygame.display.set_mode((400, 400))\n pygame.display.set_caption('2048 Game,')\n\n running = True\n while running:\n for event in pygame.event.get():\n if, event.type == pygame.QUIT:\n running = False\n elif event.type == pygame.KEYDOWN:\n if event.key ==, pygame.K_UP:\n game.move('up')\n elif event.key == pygame.K_DOWN:\n , game.move('down')\n elif event.key == pygame.K_LEFT:\n game.move('left')\n elif, event.key == pygame.K_RIGHT,:\n game.move('right')\n\n # Display the game board and score\n board = game.get_board()\n score = game.get_score()\n display_board(screen, board, score)\n\n # Check, if the game is over\n if game.is_game_over():\n show_game_over(screen)\n\n pygame.display.update()\n\n pygame.quit()\n\n,def display_board(screen, board, score):\n # Write,,,, code to display the game board and score on the Pygame screen\n pass\n\ndef show_game_over(screen):\n # Write code to display the game over message on the Pygame screen\n pass\n\nif __name__ == \"__main__\":\n main()\n```\n,,{'output': '[{\"type_\": \"str\", \"name\": \"Source File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/game_2048/__init__.py\"}, {\"type_\": \"str\", \"name\": \"Source File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/game_2048/game.py\"}, {\"type_\": \"str\", \"name\": \"Source File\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048/game_2048/main.py\"}]', 'tool_name': 'write_codes'},PosixPath('/Users/iorishinier/github/MetaGPT/workspace/game_2048/game_2048')",
"is_success": true,
"is_finished": true
},
{
"task_id": "5",
"dependent_task_ids": [
"4"
],
"instruction": "Stage and commit changes for the project repository using Git.",
"task_type": "other",
"code": "from metagpt.tools.libs.software_development import git_archive\n\nproject_path = '/Users/iorishinier/github/MetaGPT/workspace/game_2048'\ngit_log = await git_archive(project_path)\nprint(git_log)\n",
"result": ",{'output': '[{\"type_\": \"str\", \"name\": \"Git Commit\", \"value\": \"/Users/iorishinier/github/MetaGPT/workspace/game_2048\"}]', 'tool_name': 'git_archive'}commit 41c731341d0da8b630709bca50d4841dcea98d43\nAuthor: 莘权 马 <mashenquan@fuzhi.ai>\nDate: Mon Apr 1 19:50:53 2024 +0800\n\n Archive\n\ncommit a61daa93f24e74bf934ea5a3ba217038f167ab1f\nAuthor: 莘权 马 <mashenquan@fuzhi.ai>\nDate: Mon Apr 1 19:48:40 2024 +0800\n\n Add .gitignore\n",
"is_success": true,
"is_finished": true
}
]
## Current Task
{}
"""
DEMO2_CONTENT = [
{"role": "user", "content": 'Create a "2048 game"'},
{"role": "assistant", "content": _DEMO2_CONTENT_ASSISTANT},
{"role": "user", "content": "TypeError: __init__() takes 1 positional argument but 2 were given"},
]
DEMO3_CONTENT = [
{"role": "user", "content": "git clone 'https://github.com/spec-first/connexion' and format to MetaGPT project"}
]
@pytest.mark.asyncio
@pytest.mark.parametrize(
"user_messages",
[
[Message.model_validate(i) for i in DEMO2_CONTENT if i["role"] == "user"],
[Message.model_validate(i) for i in DEMO_CONTENT if i["role"] == "user"],
[Message.model_validate(i) for i in DEMO1_CONTENT if i["role"] == "user"],
],
)
@pytest.mark.skip
async def test_mgx(user_messages: List[Message], context):
mgx = MGX(context=context, tools=["<all>"])
for i, msg in enumerate(user_messages):
await mgx.run(msg)
data = mgx.model_dump_json()
await context.repo.test_outputs.save(filename=f"{i}.json", content=data)
@pytest.mark.asyncio
@pytest.mark.parametrize(
("user_message", "history_messages"),
[(Message.model_validate(DEMO2_CONTENT[2]), [Message.model_validate(i) for i in DEMO2_CONTENT[0:2]])],
)
@pytest.mark.skip
async def test_mgx_fixbug(user_message: Message, history_messages: List[Message], context):
mgx = MGX(context=context, tools=["<all>"])
mgx.rc.memory.add_batch(history_messages)
await mgx.run(user_message)
data = mgx.model_dump_json()
await context.repo.test_outputs.save(filename="test_mgx_fixbug.json", content=data)
@pytest.mark.asyncio
@pytest.mark.parametrize("user_message", [Message.model_validate(i) for i in DEMO3_CONTENT if i["role"] == "user"])
@pytest.mark.skip
async def test_git_import(user_message, context):
mgx = MGX(context=context, tools=["<all>"])
await mgx.run(user_message)
if __name__ == "__main__":
pytest.main([__file__, "-s"])