.png){kind=icon}
.png){kind=icon}
Return
An intelligent low-code platform for building task-oriented LLM-based chatbots
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cola.2026.101401.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Chatbots
Intelligent assistants
Low-code platforms
Large Language Models
Domain-specific languages
Journal
J
IF:
1.8
Papers:
28
Citations:
323