Developing an AI-Based Library Assistant: Enhancing Book Retrieval with Natural Language Processing and Machine Learning

The current college library system is hindered by inefficiencies in book searching, availability updates, identity verification, and checkout processes, resulting in delays and errors that negatively impact student experiences. This research paper presents an AI-based librarian system designed to address these challenges through automation and digital transformation. Leveraging a Large Language Model (LLM), the proposed system facilitates personalized interactions between students and library resources. Upon student verification, the AI librarian provides real-time information on book availability, location, and tailored recommendations, significantly reducing the time spent on manual searches. The streamlined checkout process allows for automated book issuance and instant confirmation notifications, minimizing human error and enhancing record- keeping. This innovative solution not only improves operational efficiency but also enriches the user experience by offering a user-friendly interface and timely assistance. Future enhancements, such as voice integration and mobile application support, are suggested to further modernize library services. This research underscores the potential of AI technologies to revolutionize library management and improve service delivery in academic settings.