MetaGPT: The Multi-Agent Framework
Official Demo Video
Software Company as Multi-Agent System
MetaGPT takes a one line requirement as input and outputs user stories / competitive analysis / requirements / data structures / APIs / documents, etc.
Internally, MetaGPT includes product managers / architects / project managers / engineers. It provides the entire process of a software company along with carefully orchestrated SOPs.
Code = SOP(Team) is the core philosophy. We materialize SOP and apply it to teams composed of LLMs.
Usage
After installation, you can use MetaGPT at CLI
metagpt "Create a 2048 game" # this will create a repo in ./workspace
or use it as library
from metagpt.software_company import generate_repo, ProjectRepo
repo: ProjectRepo = generate_repo("Create a 2048 game") # or ProjectRepo("")
print(repo) # it will print the repo structure with files
You can also use Data Interpreter to write code:
import asyncio
from metagpt.roles.di.data_interpreter import DataInterpreter
async def main():
di = DataInterpreter()
await di.run("Run data analysis on sklearn Iris dataset, include a plot")
asyncio.run(main()) # or await main() in a jupyter notebook setting
https://github.com/geekan/MetaGPT
Official Demo Video
Software Company as Multi-Agent System
MetaGPT takes a one line requirement as input and outputs user stories / competitive analysis / requirements / data structures / APIs / documents, etc.
Internally, MetaGPT includes product managers / architects / project managers / engineers. It provides the entire process of a software company along with carefully orchestrated SOPs.
Code = SOP(Team) is the core philosophy. We materialize SOP and apply it to teams composed of LLMs.
Usage
After installation, you can use MetaGPT at CLI
metagpt "Create a 2048 game" # this will create a repo in ./workspace
or use it as library
from metagpt.software_company import generate_repo, ProjectRepo
repo: ProjectRepo = generate_repo("Create a 2048 game") # or ProjectRepo("")
print(repo) # it will print the repo structure with files
You can also use Data Interpreter to write code:
import asyncio
from metagpt.roles.di.data_interpreter import DataInterpreter
async def main():
di = DataInterpreter()
await di.run("Run data analysis on sklearn Iris dataset, include a plot")
asyncio.run(main()) # or await main() in a jupyter notebook setting
https://github.com/geekan/MetaGPT