LLM based QA chatbot builder: A generative AI-based chatbot builder for question answering
Large language model (LLM) based interactive chatbots have been gaining popularity as a tool to serve organizational information among people. Building such a tool goes through several development phases i.e. (a) Data collection and preprocessing, (b) LLM fine-tuning, testing, and inference, and (c) Chat interface development. To streamline this development process, in this paper, we present the LLM Question–Answer (QA) builder, a web application, which assembles all the steps and makes it easy for technical and non-technical users to develop the LLM QA chatbot. The system allows the instruction fine-tuning of following LLMs: Zepyhr, Mistral, Llama-3, Phi, Flan-T5, and user provided model for organization-specific information retrieval (IR), which can be further enhanced by Retrieval Augmented Generation (RAG) techniques. We have added an automatic web crawling based RAG data scrapper. Also, our system contains a human evaluation feature and RAG metrics for assessing model quality.
Authors
- Md. Shahidul Salim (ORCID: https://orcid.org/0009-0001-7094-757X)
- Debdipta Bose (ORCID: https://orcid.org/0000-0002-1534-3837)
- Sk Imran Hossain (ORCID: https://orcid.org/0000-0002-1869-224X)
- Mohammad Jahid Ibna Basher
- Tanim Jalal
Institutions
- Chittagong University of Engineering & Technology (BD)
- Khulna University of Engineering and Technology (BD)
Publication Details
- Journal
- SoftwareX
- Published
- 2024-12-30
- DOI
- https://doi.org/10.1016/j.softx.2024.102029
- Citations
- 14
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 4.86
Funders
- Missouri University of Science and Technology
- University Grants Commission of Bangladesh