eidos: A modular approach to external function integration in LLMs
Function calling allows Large Language Models (LLMs) to execute a wide range of tasks, from data analysis and mathematical computations to interacting with web services and other software systems. By harnessing the power of external tooling, LLMs can provide more dynamic, context-aware responses. Ho...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-09-01
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| Series: | SoftwareX |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711025002560 |
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| author | José F. Aldana-Martín Antonio Benítez-Hidalgo José F. Aldana-Montes |
| author_facet | José F. Aldana-Martín Antonio Benítez-Hidalgo José F. Aldana-Montes |
| author_sort | José F. Aldana-Martín |
| collection | DOAJ |
| description | Function calling allows Large Language Models (LLMs) to execute a wide range of tasks, from data analysis and mathematical computations to interacting with web services and other software systems. By harnessing the power of external tooling, LLMs can provide more dynamic, context-aware responses. However, errors in the model’s understanding of the request can lead to misinterpretations of the intended actions, resulting in function calls that are either irrelevant or incorrect for the task at hand. Without proper validation and control mechanisms, the parameters expected by the function may not align with those provided by the model, leading to incorrect operations or failures in task execution. In this paper, we present eidos, a software tool designed to streamline the integration of functions within LLMs. eidos acts as an intermediary, enabling both the seamless execution and validation of functions by LLMs. By leveraging its modular architecture, function definitions can be injected into the LLM context and invoked as if they were native functions via an API. |
| format | Article |
| id | doaj-art-4bca3d10a1b048c0b8d95323aa6e7268 |
| institution | Kabale University |
| issn | 2352-7110 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj-art-4bca3d10a1b048c0b8d95323aa6e72682025-08-20T04:02:13ZengElsevierSoftwareX2352-71102025-09-013110229010.1016/j.softx.2025.102290eidos: A modular approach to external function integration in LLMsJosé F. Aldana-Martín0Antonio Benítez-Hidalgo1José F. Aldana-Montes2Corresponding author at: ITIS Software, Edificio de Investigación Ada Byron, University of Málaga, Málaga, 29071, Spain.; ITIS Software, Edificio de Investigación Ada Byron, University of Málaga, Málaga, 29071, Spain; Dept. de Lenguajes y Ciencias de la Computación, University of Málaga, Málaga, 29071, SpainITIS Software, Edificio de Investigación Ada Byron, University of Málaga, Málaga, 29071, Spain; Dept. de Lenguajes y Ciencias de la Computación, University of Málaga, Málaga, 29071, SpainITIS Software, Edificio de Investigación Ada Byron, University of Málaga, Málaga, 29071, Spain; Dept. de Lenguajes y Ciencias de la Computación, University of Málaga, Málaga, 29071, SpainFunction calling allows Large Language Models (LLMs) to execute a wide range of tasks, from data analysis and mathematical computations to interacting with web services and other software systems. By harnessing the power of external tooling, LLMs can provide more dynamic, context-aware responses. However, errors in the model’s understanding of the request can lead to misinterpretations of the intended actions, resulting in function calls that are either irrelevant or incorrect for the task at hand. Without proper validation and control mechanisms, the parameters expected by the function may not align with those provided by the model, leading to incorrect operations or failures in task execution. In this paper, we present eidos, a software tool designed to streamline the integration of functions within LLMs. eidos acts as an intermediary, enabling both the seamless execution and validation of functions by LLMs. By leveraging its modular architecture, function definitions can be injected into the LLM context and invoked as if they were native functions via an API.http://www.sciencedirect.com/science/article/pii/S2352711025002560Large Language ModelsFunction callingValidationRetrieval-Augmented Generation |
| spellingShingle | José F. Aldana-Martín Antonio Benítez-Hidalgo José F. Aldana-Montes eidos: A modular approach to external function integration in LLMs SoftwareX Large Language Models Function calling Validation Retrieval-Augmented Generation |
| title | eidos: A modular approach to external function integration in LLMs |
| title_full | eidos: A modular approach to external function integration in LLMs |
| title_fullStr | eidos: A modular approach to external function integration in LLMs |
| title_full_unstemmed | eidos: A modular approach to external function integration in LLMs |
| title_short | eidos: A modular approach to external function integration in LLMs |
| title_sort | eidos a modular approach to external function integration in llms |
| topic | Large Language Models Function calling Validation Retrieval-Augmented Generation |
| url | http://www.sciencedirect.com/science/article/pii/S2352711025002560 |
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