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🚀 Feb. 19, 2025: Today we are officially launching our natural language programming product: MGX (MetaGPT X) - the world's first AI agent development team. [Offical website](https://mgx.dev/) [Twitter](https://x.com/MetaGPT_/status/1892199535130329356)
🚀 Oct. 29, 2024: We introduced three papers: [AFLOW](https://arxiv.org/abs/2410.10762), [FACT](https://arxiv.org/abs/2410.21012), and [SELA](https://arxiv.org/abs/2410.17238), check the [code](examples)!
🚀 Mar. 29, 2024: [v0.8.0](https://github.com/geekan/MetaGPT/releases/tag/v0.8.0) released. Now you can use Data Interpreter ([arxiv](https://arxiv.org/abs/2402.18679), [example](https://docs.deepwisdom.ai/main/en/DataInterpreter/), [code](https://github.com/geekan/MetaGPT/tree/main/examples/di)) via pypi package import. Meanwhile, we integrated the RAG module and supported multiple new LLMs.
🚀 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.
](https://openreview.net/forum?id=VtmBAGCN7o) 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.
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.

<palign="center">Software Company Multi-Agent Schematic (Gradually Implementing)</p>
For detailed installation guidance, 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)
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):
📢 Join Our [Discord Channel](https://discord.gg/ZRHeExS6xv)! Looking forward to seeing you there! 🎉
### Contributor form
📝 [Fill out the form](https://airtable.com/appInfdG0eJ9J4NNL/pagK3Fh1sGclBvVkV/form) to become a contributor. We are looking forward to your participation!
- **GitHub Issues:** For more technical inquiries, you can also create a new issue in our [GitHub repository](https://github.com/geekan/metagpt/issues).
To cite [MetaGPT](https://openreview.net/forum?id=VtmBAGCN7o) or [Data Interpreter](https://arxiv.org/abs/2402.18679) in publications, please use the following BibTeX entries.
title={Meta{GPT}: Meta Programming for A Multi-Agent Collaborative Framework},
author={Sirui Hong and Mingchen Zhuge and Jonathan Chen and Xiawu Zheng and Yuheng Cheng and Jinlin Wang and Ceyao Zhang and Zili Wang and Steven Ka Shing Yau and Zijuan Lin and Liyang Zhou and Chenyu Ran and Lingfeng Xiao and Chenglin Wu and J{\"u}rgen Schmidhuber},
booktitle={The Twelfth International Conference on Learning Representations},
title={Atom of Thoughts for Markov LLM Test-Time Scaling},
author={Fengwei Teng and Zhaoyang Yu and Quan Shi and Jiayi Zhang and Chenglin Wu and Yuyu Luo},
year={2025},
eprint={2502.12018},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2502.12018},
}
@misc{xiang2025self,
title={Self-Supervised Prompt Optimization},
author={Jinyu Xiang and Jiayi Zhang and Zhaoyang Yu and Fengwei Teng and Jinhao Tu and Xinbing Liang and Sirui Hong and Chenglin Wu and Yuyu Luo},
year={2025},
eprint={2502.06855},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2502.06855},
}
@inproceedings{wang2025fact,
title={FACT: Examining the Effectiveness of Iterative Context Rewriting for Multi-fact Retrieval},
author={Jinlin Wang and Suyuchen Wang and Ziwen Xia and Sirui Hong and Yun Zhu and Bang Liu and Chenglin Wu},
booktitle={The 2025 Annual Conference of the Nations of the Americas Chapter of the ACL},
year={2025},
url={https://openreview.net/forum?id=VXOircx5h3}
}
@misc{chi2024sela,
title={SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning},
author={Yizhou Chi and Yizhang Lin and Sirui Hong and Duyi Pan and Yaying Fei and Guanghao Mei and Bangbang Liu and Tianqi Pang and Jacky Kwok and Ceyao Zhang and Bang Liu and Chenglin Wu},
author={Jiayi Zhang and Jinyu Xiang and Zhaoyang Yu and Fengwei Teng and Xiong-Hui Chen and Jiaqi Chen and Mingchen Zhuge and Xin Cheng and Sirui Hong and Jinlin Wang and Bingnan Zheng and Bang Liu and Yuyu Luo and Chenglin Wu},
booktitle={The Thirteenth International Conference on Learning Representations},
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},