Interactive chatbot for PDF content conversation using an LLM language model - Ting Tin Tin; Seow Yu Xuan; Wong Man Ee; Lee Kuok Tiung; Ali Aitizaz (The Science and Information (SAI) Organization Limited, 2024)
Natural Language Processing (NLP) leverages Artificial Intelligence (AI) to enable computer programs to understand and generate human language. ChatGPT has recently become popular in assignment accomplishment. This project aims to develop and improve an interactive PDF chat application using OpenAI's language model (LLM), specifically GPT-3.5, integrated with Streamlit and LangChain frameworks to assist in learning process. The application enhances user interaction with documents by providing real-time text extraction, summarization, translation, and user-defined question-answering to increase learning opportunities. Key features include obtaining document summaries, multilingual support for improved accessibility, and a document preview section with features such as zoom, rotation, and download. Although it currently faces limitations in handling image-rich PDFs, future enhancements include better image rendering, conversation history, and query download features. Overall, this interactive chatbot model aims to streamline document interaction, making information retrieval efficient and user-friendly.