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Type | Book Chapter |
Scope | Discipline-based scholarship |
Title | PROMISE: A Framework for Model-Driven Stateful Prompt Orchestration |
Organization Unit | |
Authors |
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Editors |
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Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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Booktitle | Intelligent Information Systems |
Series Name | Lecture Notes in Business Information Processing |
ISBN | 9783031609992 |
ISSN | 1865-1348 |
Number | 520 |
Place of Publication | Cham |
Publisher | Springer |
Page Range | 157 - 165 |
Date | 2024-05-29 |
Abstract Text | The advent of increasingly powerful language models has raised expectations for conversational interactions. However, controlling these models is a challenge, emphasizing the need to be able to investigate the feasibility and value of their application. We present PROMISE (Available at: https://github.com/zhaw-iwi/promise), a framework that facilitates the development of complex conversational interactions with information systems. Its use of state machine modeling concepts enables model-driven, dynamic prompt orchestration across hierarchically nested states and transitions. This improves the control of language models’ behavior and thus enables their effective and efficient use. We show the applications of PROMISE in health information systems and demonstrate its ability to handle complex interactions. |
Digital Object Identifier | 10.1007/978-3-031-61000-4_18 |
PDF File | Download from ZORA |
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