An intelligent low-code platform for building task-oriented LLM-based chatbots

Task-oriented chatbots help users complete specific goals such as ordering products. We recently proposed Taskyto, a domain-specific language (DSL) for building LLM-based task-oriented chatbots. Although Taskyto simplifies development, it remains challenging for non-experts due to complex installation, required DSL knowledge, and dedicated infrastructure to run the chatbots. To address these limitations, we present Bot-Craft , a low-code platform for creating and deploying Taskyto chatbots, augmented with an intelligent assistant that generates Taskyto code from natural language requests. We report on experiments demonstrating the assistant’s usability, effectiveness, performance, and accuracy in supporting chatbot development.

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Publication Details

Journal
Journal of Computer Languages
Published
2026-05-01
DOI
https://doi.org/10.1016/j.cola.2026.101401
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00

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article

An intelligent low-code platform for building task-oriented LLM-based chatbots

Esther Guerra, Juan de Lara, Ángel Quiles
Journal of Computer Languages
AI in Service Interactions
article

An intelligent low-code platform for building task-oriented LLM-based chatbots

Esther Guerra, Juan de Lara, Ángel Quiles
article en

Abstract

Task-oriented chatbots help users complete specific goals such as ordering products. We recently proposed Taskyto, a domain-specific language (DSL) for building LLM-based task-oriented chatbots. Although Taskyto simplifies development, it remains challenging for non-experts due to complex installation, required DSL knowledge, and dedicated infrastructure to run the chatbots. To address these limitations, we present Bot-Craft , a low-code platform for creating and deploying Taskyto chatbots, augmented with an intelligent assistant that generates Taskyto code from natural language requests. We report on experiments demonstrating the assistant’s usability, effectiveness, performance, and accuracy in supporting chatbot development.

Journal of Computer LanguagesVol. 87
Universidad Autónoma de Madrid (ES)
Ministerio de Ciencia, Innovación y Universidades
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
AI in Service Interactions
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