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π The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
[ En | δΈ | Fr | ζ₯ ] Assign different roles to GPTs to form a collaborative entity for complex tasks.
π Mar. 10, 2025: π mgx.dev is the #1 Product of the Week on @ProductHunt! π
π Mar. 4, 2025: π mgx.dev is the #1 Product of the Day on @ProductHunt! π
π Feb. 19, 2025: Today we are officially launching our natural language programming product: MGX (MetaGPT X) - the world's first AI agent development team. More details on Twitter.
π Feb. 17, 2025: We introduced two papers: SPO and AOT, check the code!
π Jan. 22, 2025: Our paper AFlow: Automating Agentic Workflow Generation accepted for oral presentation (top 1.8%) at ICLR 2025, ranking #2 in the LLM-based Agent category.
ππ Earlier news
Code = SOP(Team) is the core philosophy. We materialize SOP and apply it to teams composed of LLMs.Software Company Multi-Agent Schematic (Gradually Implementing)
Ensure that Python 3.9 or later, but less than 3.12, 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
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 .`
Install node and pnpm before actual use.
For detailed installation guidance, please refer to cli_install or docker_install
You can init the config of MetaGPT by running the following command, or manually create ~/.metagpt/config2.yaml file:
# 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
You can configure ~/.metagpt/config2.yaml according to the example and doc:
llm: api_type: "openai" # or azure / ollama / groq etc. Check LLMType for more options model: "gpt-4-turbo" # or gpt-3.5-turbo base_url: "https://api.openai.com/v1" # or forward url / other llm url api_key: "YOUR_API_KEY"
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
from metagpt.utils.project_repo import ProjectRepo repo: ProjectRepo = generate_repo("Create a 2048 game") # or ProjectRepo("<path>")
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
π’ Join Our Discord Channel! Looking forward to seeing you there! π
