Bel Esprit: Multi-Agent Framework for Building AI Model Pipelines
This addresses the need for automated pipeline construction in AI applications, but it appears incremental as it builds on existing multi-agent and pipeline integration concepts.
The paper tackles the problem of constructing AI model pipelines from ambiguous user queries by introducing Bel Esprit, a conversational multi-agent framework that clarifies requirements and builds pipelines, demonstrating effectiveness with human-curated and synthetic data.
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-defined requirements. Bel Esprit employs a multi-agent framework where subagents collaborate to clarify requirements, build, validate, and populate pipelines with appropriate models. We demonstrate the effectiveness of this framework in generating pipelines from ambiguous user queries, using both human-curated and synthetic data. A detailed error analysis highlights ongoing challenges in pipeline construction. Bel Esprit is available for a free trial at https://belesprit.aixplain.com.