Abstract
As the demand for artificial intelligence (AI) grows to address complex real-world tasks, single models are often insufficient, requiring the integration of multiple models into pipelines. This paper introduces Bel Esprit, a conversational agent designed to construct AI model pipelines based on user requirements. Bel Esprit uses a multi-agent framework where subagents collaborate to clarify requirements, build, validate, and populate pipelines with appropriate models. We demonstrate its effectiveness in generating pipelines from ambiguous user queries, using both human-curated and synthetic data. A detailed error analysis highlights ongoing challenges in pipeline building. Bel Esprit is available for a free trial at https://belesprit.aixplain.com1
Cite
CITATION STYLE
Kim, Y., Abdelaziz, A. E., Ferreira, T. C., Al-Badrashiny, M., & Sawaf, H. (2025). Bel Esprit: Multi-Agent Framework for Building AI Model Pipelines. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (Vol. 3, pp. 329–339). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2025.acl-demo.32
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