Augmented Language Models (ALMs) empower large language models with the ability to use tools, transforming them into intelligent agents for real-world interactions. However, most existing frameworks for ALMs, to varying degrees, are deficient in the following critical features: flexible customization, collaborative democratization, and holistic evaluation. We present Gentopia, an ALM framework enabling flexible customization of agents through simple configurations, seamlessly integrating various language models, task formats, prompting modules, and plugins into a unified paradigm. Furthermore, we establish GentPool, a public platform enabling the registration and sharing of user-customized agents. Agents registered in GentPool are composable such that they can be assembled together for agent collaboration, advancing the democratization of artificial intelligence. To ensure high-quality agents, GentBench, an integral component of GentPool, is designed to thoroughly evaluate user-customized agents across diverse aspects such as safety, robustness, efficiency, etc. We release Gentopia on Github1 and will continuously move forward.
CITATION STYLE
Xu, B., Liu, X., Shen, H., Han, Z., Li, Y., Yue, M., … Xu, D. (2023). Gentopia.AI: A Collaborative Platform for Tool-Augmented LLMs. In EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings of the System Demonstrations (pp. 237–245). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.emnlp-demo.20
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