Dingent: a configurable agent framework for biological database retrieval and integration
Abstract AI-driven data search and integration represent an emerging research direction. Although several LLM-based backend frameworks and agentic frameworks have emerged, significant gap remains in developing a one-stop, configurable agent framework that supports various data sources and provides a web interface for efficient data retrieval using natural language. To address this, we present Dingent, a novel and configurable agent framework that facilitates data access from various resources and enables the flexible constructions of agent applications. We demonstrate its capabilities across three distinct application scenarios, achieving promising results. The Dingent framework can be readily applied to other fields, such as earth sciences and ecology, to facilitate data discovery.
Authors
- Bixia Tang (ORCID: https://orcid.org/0000-0003-4633-5626)
- Wenming Zhao (ORCID: https://orcid.org/0000-0002-4396-8287)
- Shaoqi Bei
- Demian Kong (ORCID: https://orcid.org/0009-0005-6007-9659)
- Yueyue Wu
Institutions
- Shanghai Center For Bioinformation Technology (CN)
Publication Details
- Journal
- Computational and Structural Biotechnology Journal
- Published
- 2026-11-03
- DOI
- https://doi.org/10.34133/csbj.0282
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chinese Academy of Sciences
- National Key Research and Development Program of China