AI ASSISTANT-BASED CHATBOT APPLICATION IN SOLVING CODING SCRIPT ISSUES USING THE OLLAMA LARGE LANGUAGE MODELS - Achmad Maulana Rochman; Sumarno Sumarno; Suprianto Suprianto; Irwan Alnarus Kautsar (Journal of Artificial Intelligence and Digital Economy, 2024)
Objective: This study aims to design and implement an artificial intelligence (AI)-based chatbot to assist software developers in debugging and generating programming solutions using Large Language Models (LLM) from Ollama. Method: The system was developed using the Waterfall methodology, encompassing stages of requirements analysis, design, implementation, testing, and maintenance. The AI model operates locally through Ollama, while Streamlit serves as the user interface for interactive communication between users and the chatbot. Results: Testing results show that the chatbot provides accurate and contextually relevant responses to programming queries, effectively supporting developers in debugging and code recommendation tasks. However, optimization is needed to improve system response time and processing efficiency. Novelty: The integration of a locally deployed LLM with a Streamlit-based interface presents a practical and secure solution for AI-assisted programming support, highlighting its potential to enhance developer productivity and reduce reliance on external cloud-based AI services.