Elamur Research
☰
home / papers / 2024 / OpenHands: An Open Platform for AI Software Developers as Generalist Agents

OpenHands: An Open Platform for AI Software Developers as Generalist Agents

Written for the Research library (claude-opus-5-5) from the paper text. Original — arxiv.org/pdf/2407.16741

Summary

Building LLM agents that do real software work is hard. They must write and change code inside large projects, find information while debugging, and avoid damaging the user's machine. This paper presents OpenHands (formerly OpenDevin), an open, community-built platform for creating both generalist and specialist agents of this kind. An event stream connects agents, user interfaces and execution environments, and it records every action along with the observation that follows. Actions run inside a Docker-isolated runtime that provides a bash shell, an IPython server and a Chromium browser driven by Playwright. Agents can edit files, run arbitrary code, browse the web and pass subtasks to other specialized agents. The release also includes an agent hub, a chat-based UI and an evaluation harness that covers 15 benchmarks, among them SWE-bench and WebArena. The authors use this harness to test their agents, but the supplied excerpt does not contain the actual scores. The main contribution is a shared, MIT-licensed foundation for building and comparing agents reproducibly.

Key points

  • Core abstraction: an agent maps the event history (past actions and observations) to its next action. The runtime then executes that action and returns an observation.
  • Action space: the primitives IPythonRunCellAction, CmdRunAction and BrowseInteractiveAction follow the CodeAct design. Browsing uses the action DSL from BrowserGym. Tools can be defined as ordinary Python functions, which keeps the system compatible with JSON-style function calling.
  • Agent hub: it contains more than 10 agents. The flagship is a generalist built on CodeAct, extended with web-browsing and code-editing specialists, and multi-agent delegation is supported.
  • Evaluation: the framework integrates 15 benchmarks spanning software engineering (SWE-bench), web browsing (WebArena) and other areas.
  • Community and license: the project is MIT-licensed, which allows commercial use. It has about 32K GitHub stars and over 2.1K contributions from more than 188 contributors (code: github.com/All-Hands-AI/OpenHands).

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: AI & machine learning

Cited by

167 papers of our library cite it (of the 140673 whose bibliographies we read); 4 of them have a page here, 163 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.48550/arxiv.2407.16741 · arXiv 2407.16741

@misc{wang2024openhands,
  title = {{OpenHands: An Open Platform for AI Software Developers as Generalist Agents}},
  author = {Wang, Xingyao and Li, Boxuan and Song, Yufan and Xu, Frank F. and Tang, Xiangru and Zhuge, Mingchen and Pan, Jiayi and Song, Yueqi and Li, Bowen and Singh, Jaskirat and Tran, Hoang H. and Li, Fuqiang and Ma, Ren and Zheng, Mingzhang and Qian, Bill and Shao, Yanjun and Muennighoff, Niklas and Zhang, Yizhe and Hui, Binyuan and Lin, Junyang and Brennan, Robert and Peng, Hao and Ji, Heng and Neubig, Graham},
  year = {2024},
  doi = {10.48550/arxiv.2407.16741},
  eprint = {2407.16741},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.2407.16741}
}

References

73 references, 27 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, et al. Do as i can, not as i say: Grounding language in robotic affordances. arXiv preprint arXiv:2204.01691, 2022. 1 find our card
  2. Daniil A Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes. Autonomous chemical research with large language models. Nature, 624(7992):570–578, 2023. 1 find our card
  3. Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, et al. A survey on evaluation of large language models. ACM Transactions on Intelligent Systems and Technology, 15(3):1–45, 2024. 1 find our card
  4. Harrison Chase. LangChain, October 2022. URL https://github.com/langchain-ai/langchain. 4, 6, 18 ↗
  5. Guangyao Chen, Siwei Dong, Yu Shu, Ge Zhang, Jaward Sesay, Börje F. Karlsson, Jie Fu, and Yemin Shi. Autoagents: A framework for automatic agent generation, 2024. 1, 6, 18 find
  6. Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374, 2021. 7 find our card
  7. Cognition.ai. Introducing devin, the first ai software engineer. URL https://www.cognition.ai/blog/ introducing-devin. 2 ↗
  8. CrewAI. CrewAI, October 2024. URL https://github.com/crewAIInc/crewAI. 18 ↗
  9. Jiaxi Cui, Zongjian Li, Yang Yan, Bohua Chen, and Li Yuan. Chatlaw: Open-source legal large language model with integrated external knowledge bases, 2023. 18 find
  10. Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, Léo Boisvert, Megh Thakkar, Quentin Cappart, David Vazquez, Nicolas Chapados, and Alexandre Lacoste. Workarena: How capable are web agents at solving common knowledge work tasks?, 2024. 3, 4 find
  11. Paul Gauthier. How aider scored sota 26.3% on swe bench lite \| aider. https://aider.chat/2024/05/22/ swe-bench-lite.html. Accessed: 2024-06-05. 5, 7, 8 ↗
  12. Significant Gravitas. Auto-gpt: An autonomous gpt-4 experiment, 2023. URL https://github. com/Significant-Gravitas/Auto-GPT, 2023. 6, 7, 10, 18 find
  13. Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng, Jinlin Wang, Ceyao Zhang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, et al. Metagpt: Meta programming for a multi-agent collaborative framework. In The Twelfth International Conference on Learning Representations, 2023. 1, 6, 18 find our card
  14. Dong Huang, Qingwen Bu, Jie M. Zhang, Michael Luck, and Heming Cui. Agentcoder: Multi-agent-based code generation with iterative testing and optimisation, 2024. 19 find
  15. Peter C Humphreys, David Raposo, Tobias Pohlen, Gregory Thornton, Rachita Chhaparia, Alistair Muldal, Josh Abramson, Petko Georgiev, Adam Santoro, and Timothy Lillicrap. A data-driven approach for learning to control computers. In International Conference on Machine Learning, pp. 9466–9482. PMLR, 20… find
  16. IPython. Jupyter and the future of IPython — IPython. URL https://ipython.org. 4 Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al. Mixtral of experts. arXiv preprint… ↗
  17. Carlos E Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik R Narasimhan. SWE-bench: Can Language Models Resolve Real-world Github Issues? In The Twelfth International Conference on Learning Representations, 2024. URL https://openreview.net/ forum?id=VTF8yNQM66. 1,… ↗ our card
  18. Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vard-hamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, and Christopher Potts. Dspy: Compiling declarative language model calls into self-improving pipelines. 2024.… find our card
  19. Geunwoo Kim, Pierre Baldi, and Stephen McAleer. Language models can solve computer tasks. Advances in Neural Information Processing Systems, 36, 2024. 9 find our card
  20. Hanyu Lai, Xiao Liu, Iat Long Iong, Shuntian Yao, Yuxuan Chen, Pengbo Shen, Hao Yu, Hanchen Zhang, Xiaohan Zhang, Yuxiao Dong, et al. Autowebglm: Bootstrap and reinforce a large language model-based web navigating agent. arXiv preprint arXiv:2404.03648, 2024. 7, 9 find
  21. Hareton K. N. Leung and Lee J. White. A study of integration testing and software regression at the integration level. In Proceedings of the Conference on Software Maintenance, ICSM 1990, San Diego, CA, USA, 26-29 November, 1990, pp. 290–301. find
  22. IEEE, 1990. doi: 10.1109/ICSM.1990. 131377. URL https://doi.org/10.1109/ICSM.1990.131377. 19 — [doi:10.1109/icsm.1990](https://doi.org/10.1109/icsm.1990) ↗
  23. Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, Dmitrii Khizbullin, and Bernard Ghanem. Camel: Communicative agents for" mind" exploration of large scale language model society. arXiv preprint arXiv:2303.17760, 2023a. 18 find our card
  24. Jinyang Li, Binyuan Hui, GE QU, Jiaxi Yang, Binhua Li, Bowen Li, Bailin Wang, Bowen Qin, Ruiying Geng, Nan Huo, Xuanhe Zhou, Chenhao Ma, Guoliang Li, Kevin Chang, Fei Huang, Reynold Cheng, and Yongbin Li. Can LLM already serve as a database interface? a BIg bench for large-scale database grounded te… find our card
  25. Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, Qian Liu, Evgenii Zheltonozhskii, Terry Yue Zhuo, Thomas Wang, Olivier Dehaene, Mishig Davaadorj, Joel Lamy-Poirier, João Monteiro, Oleh Shliazhko, Nicolas… find
  26. Tao Li, Gang Li, Zhiwei Deng, Bryan Wang, and Yang Li. A zero-shot language agent for computer control with structured reflection. arXiv preprint arXiv:2310.08740, 2023d. 9 find
  27. Evan Zheran Liu, Kelvin Guu, Panupong Pasupat, Tianlin Shi, and Percy Liang. Reinforcement learning on web interfaces using workflow-guided exploration. In International Conference on Learning Representations (ICLR), 2018. URL https://arxiv.org/abs/1802.08802. 6, 9, 17 ↗
  28. Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, and Jie Tang. Agentbench: Evaluating llms as age… find our card
  29. Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu, Max Tian, Denis Kocetkov, Arthur Zucker, Younes Belkada, Zijian Wang, Qian Liu, Dmitry Abulkhanov, Indraneil Paul, Zhuang Li, Wen-Ding Li,… find
  30. Grégoire Mialon, Clémentine Fourrier, Craig Swift, Thomas Wolf, Yann LeCun, and Thomas Scialom. GAIA: a benchmark for general AI assistants. CoRR, abs/2311.12983, 2023. doi: 10.48550/ARXIV.2311.12983. URL https://doi.org/10.48550/arXiv.2311.12983. 6, 9, 10, 17 ↗ our card
  31. Mozilla. Accessibility tree - MDN Web Docs Glossary: Definitions of Web-related terms \| MDN. URL https://developer.mozilla.org/en-US/docs/Glossary/Accessibility\_tree. 5 Niklas Muennighoff, Qian Liu, Armel Zebaze, Qinkai Zheng, Binyuan Hui, Terry Yue Zhuo, Swayam Singh, Xiangru Tang, Leandro von Werr… ↗
  32. Y Nakajima. Babyagi. URL https://github.com/yoheinakajima/babyagi, 2023. 18 ↗
  33. OpenAI. Chatgpt: May 2024 version. https://www.openai.com/chatgpt, 2024a. Accessed: 2024-05-29. 8, 18 ↗
  34. OpenAI. Hello gpt-4o. https://openai.com/index/hello-gpt-4o/, 2024b. Accessed: 2024-05-15. 1 ↗
  35. OpenAI, Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, Red Avila, Igor Babuschkin, Suchir Balaji, Valerie Balcom, Paul Baltescu, Haiming Bao, Mohammad Bavarian, Jeff Belgum, Irwan Bello, Ja… find our card
  36. Jiayi Pan, Yichi Zhang, Nicholas Tomlin, Yifei Zhou, Sergey Levine, and Alane Suhr. Autonomous evaluation and refinement of digital agents. arXiv preprint arXiv:2404.06474, 2024. 7, 9, 18 find
  37. Liangming Pan, Alon Albalak, Xinyi Wang, and William Yang Wang. Logic-lm: Empowering large language models with symbolic solvers for faithful logical reasoning. arXiv preprint arXiv:2305.12295, 2023. 10 find our card
  38. Joon Sung Park, Joseph C. O’Brien, Carrie J. Cai, Meredith Ringel Morris, Percy Liang, and Michael S. Bernstein. Generative agents: Interactive simulacra of human behavior, 2023. 18 find
  39. Ajay Patel, Markus Hofmarcher, Claudiu Leoveanu-Condrei, Marius-Constantin Dinu, Chris Callison-Burch, and Sepp Hochreiter. Large language models can self-improve at web agent tasks. arXiv preprint arXiv:2405.20309, 2024. 7, 9 — [arXiv:2405.20309](https://arxiv.org/abs/2405.20309) find
  40. Shishir G. Patil, Tianjun Zhang, Xin Wang, and Joseph E. Gonzalez. Gorilla: Large language model connected with massive apis. arXiv preprint arXiv:2305.15334, 2023. 6, 8, 17 find our card
  41. Playwright. Fast and reliable end-to-end testing for modern web apps \| Playwright. URL https: //playwright.dev/. 4 Chen Qian, Xin Cong, Wei Liu, Cheng Yang, Weize Chen, Yusheng Su, Yufan Dang, Jiahao Li, Juyuan Xu, Dahai Li, Zhiyuan Liu, and Maosong Sun. Communicative agents for software development… find
  42. Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, Sihan Zhao, Runchu Tian, Ruobing Xie, Jie Zhou, Mark Gerstein, Dahai Li, Zhiyuan Liu, and Maosong Sun. Toolllm: Facilitating large language models to master 16000+ real-world apis. CoRR,… find our card
  43. David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R Bowman. GPQA: A Graduate-Level Google-Proof Q&A Benchmark. arXiv preprint arXiv:2311.12022, 2023. 6, 7, 9, 10, 17, 23 find our card
  44. Aman Sanger. Near-instant full-file edits. https://www.cursor.com/blog/instant-apply. Accessed: 2024-06-05. 5 ↗
  45. ServiceNow. BrowserGym: a Gym Environment for Web Task Automation. URL https://github.com/ ServiceNow/BrowserGym. 2, 4, 18 Peter Shaw, Mandar Joshi, James Cohan, Jonathan Berant, Panupong Pasupat, Hexiang Hu, Urvashi Khandelwal, Kenton Lee, and Kristina N Toutanova. From pixels to ui actions: Learni… ↗
  46. Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. Reflexion: Language agents with verbal reinforcement learning. Advances in Neural Information Processing Systems, 36, 2024. 18 find our card
  47. Oyvind Tafjord, Bhavana Dalvi, and Peter Clark. ProofWriter: Generating implications, proofs, and abductive statements over natural language. In Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli (eds.), Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pp. 3621–3634,… find our card
  48. Xiangru Tang, Qiao Jin, Kunlun Zhu, Tongxin Yuan, Yichi Zhang, Wangchunshu Zhou, Meng Qu, Yilun Zhao, Jian Tang, Zhuosheng Zhang, et al. Prioritizing safeguarding over autonomy: Risks of llm agents for science. arXiv preprint arXiv:2402.04247, 2024a. 1 — [arXiv:2402.04247](https://arxiv.org/abs/2402.04247) find
  49. Xiangru Tang, Yuliang Liu, Zefan Cai, Yanjun Shao, Junjie Lu, Yichi Zhang, Zexuan Deng, Helan Hu, Kaikai An, Ruijun Huang, Shuzheng Si, Sheng Chen, Haozhe Zhao, Liang Chen, Yan Wang, Tianyu Liu, Zhiwei Jiang, Baobao Chang, Yin Fang, Yujia Qin, Wangchunshu Zhou, Yilun Zhao, Arman Cohan, and Mark Gers… find
  50. Xiangru Tang, Bill Qian, Rick Gao, Jiakang Chen, Xinyun Chen, and Mark B Gerstein. BioCoder: a benchmark for bioinformatics code generation with large language models. Bioinformatics, 40 (Supplement\_1):i266–i276, 06 2024c. ISSN 1367-4811. 6, 8, 17 find
  51. Xiangru Tang, Anni Zou, Zhuosheng Zhang, Ziming Li, Yilun Zhao, Xingyao Zhang, Arman Cohan, and Mark Gerstein. Medagents: Large language models as collaborators for zero-shot medical reasoning, 2024d. 18 find
  52. Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al. Gemini: a family of highly capable multimodal models. arXiv preprint arXiv:2312.11805, 2023. 1 find our card
  53. XAgent Team. Xagent: An autonomous agent for complex task solving, 2023. 6, 18 find
  54. Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. Llama: Open and efficient foundation language models. arXiv preprint… find
  55. Xingyao Wang, Yangyi Chen, Lifan Yuan, Yizhe Zhang, Yunzhu Li, Hao Peng, and Heng Ji. Executable Code Actions Elicit Better LLM Agents. In ICML, 2024a. 2, 3, 4, 5, 17 find our card
  56. Xingyao Wang, Zihan Wang, Jiateng Liu, Yangyi Chen, Lifan Yuan, Hao Peng, and Heng Ji. MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback. In ICLR, 2024b. 6, 10, 17 find our card
  57. Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Shaokun Zhang, Erkang Zhu, Beibin Li, Li Jiang, Xiaoyun Zhang, and Chi Wang. Autogen: Enabling next-gen llm applications via multi-agent conversation framework. arXiv preprint arXiv:2308.08155, 2023. 1, 6, 18 find our card
  58. Chunqiu Steven Xia, Yinlin Deng, Soren Dunn, and Lingming Zhang. Agentless: Demystifying llm-based software engineering agents. arXiv preprint, 2024. 7 find
  59. Tianbao Xie, Fan Zhou, Zhoujun Cheng, Peng Shi, Luoxuan Weng, Yitao Liu, Toh Jing Hua, Junning Zhao, Qian Liu, Che Liu, et al. Openagents: An open platform for language agents in the wild. arXiv preprint arXiv:2310.10634, 2023. 6 find
  60. Yiheng Xu, Hongjin Su, Chen Xing, Boyu Mi, Qian Liu, Weijia Shi, Binyuan Hui, Fan Zhou, Yitao Liu, Tianbao Xie, et al. Lemur: Harmonizing natural language and code for language agents. arXiv preprint arXiv:2310.06830, 2023. 7, 9 — [arXiv:2310.06830](https://arxiv.org/abs/2310.06830) find
  61. John Yang, Carlos E. Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, and Ofir Press. Swe-agent: Agent-computer interfaces enable automated software engineering, 2024. 2, 5, 6, 7, 8, 19 find our card
  62. Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R Narasimhan, and Yuan Cao. React: Synergizing reasoning and acting in language models. In The Eleventh International Conference on Learning Representations, 2023. URL https://openreview.net/forum?id=WE\_ vluYUL-X. 8 ↗ our card
  63. Yining Ye, Xin Cong, Shizuo Tian, Jiannan Cao, Hao Wang, Yujia Qin, Yaxi Lu, Heyang Yu, Huadong Wang, Yankai Lin, et al. Proagent: From robotic process automation to agentic process automation. arXiv preprint arXiv:2311.10751, 2023. 18 — [arXiv:2311.10751](https://arxiv.org/abs/2311.10751) find
  64. Lifan Yuan, Yangyi Chen, Xingyao Wang, Yi R. Fung, Hao Peng, and Heng Ji. CRAFT: customizing llms by creating and retrieving from specialized toolsets. CoRR, abs/2309.17428, 2023. doi: 10.48550/ARXIV.2309.17428. URL https://doi.org/10.48550/arXiv.2309.17428. 4 — [doi:10.48550/arxiv.2309.17428](https://doi.org/10.48550/arxiv.2309.17428) ↗
  65. Lifan Yuan, Ganqu Cui, Hanbin Wang, Ning Ding, Xingyao Wang, Jia Deng, Boji Shan, Huimin Chen, Ruobing Xie, Yankai Lin, Zhenghao Liu, Bowen Zhou, Hao Peng, Zhiyuan Liu, and Maosong Sun. Advancing llm reasoning generalists with preference trees, 2024. 10 find
  66. Yizhe Zhang, Jiarui Lu, and Navdeep Jaitly. Probing the multi-turn planning capabilities of llms via 20 question games. 2024a. 6, 10, 17 find
  67. Yuntong Zhang, Haifeng Ruan, Zhiyu Fan, and Abhik Roychoudhury. Autocoderover: Autonomous program improvement, 2024b. 6, 7, 8, 19 find
  68. Shuyan Zhou, Frank F Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, et al. Webarena: A realistic web environment for building autonomous agents. In The Twelfth International Conference on Learning Representations, 2023a. 1, 6, 7, 9, 17 find our card
  69. Wangchunshu Zhou, Yuchen Eleanor Jiang, Long Li, Jialong Wu, Tiannan Wang, Shi Qiu, Jintian Zhang, Jing Chen, Ruipu Wu, Shuai Wang, Shiding Zhu, Jiyu Chen, Wentao Zhang, Xiangru Tang, Ningyu Zhang, Huajun Chen, Peng Cui, and Mrinmaya Sachan. Agents: An open-source framework for autonomous language a… find
  70. Yuchen Zhuang, Yue Yu, Kuan Wang, Haotian Sun, and Chao Zhang. Toolqa: A dataset for llm question answering with external tools. Advances in Neural Information Processing Systems, 36, 2024. 6, 8, 17 find our card
  71. Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, et al. Mindstorms in natural language-based societies of mind. arXiv preprint arXiv:2305.17066, 2023. 18 — [arXiv:2305.17066](https://arxiv.org/abs/2305.17066) find
  72. Mingchen Zhuge, Wenyi Wang, Louis Kirsch, Francesco Faccio, Dmitrii Khizbullin, and Jurgen Schmidhuber. Language agents as optimizable graphs. arXiv preprint arXiv:2402.16823, 2024. 6, 17, 18 find
  73. Albert Örwall. Moatless tools. URL https://github.com/aorwall/moatless-tools. 7 A UTHOR C ONTRIBUTIONS ↗