Developing and Deploying an LLM-Based Tool for Generating Human-Like Responses in Offline Networks

Abstract

The Gemini MultiPDF Chatbot represents a significant advancement in natural language processing with the fusion of Retrieval-Augmented Generation with the Gemini Large Language Model. This chatbot has the ability to handle the complexity of multiple document retrieval and response generation, providing the user with accurate and contextually pertinent information across various PDF documents. Leverage the power of RAG, the system effectively enhances its understanding and response accuracy by dynamically drawing upon external knowledge bases. The process employs PDF parsing and extraction using chunking, followed by embedding creation through vector representation using FAISS indexing to achieve efficient similarity searching and correct recovery of the data. Streamlit is the interface, with a simple, user-friendly platform for uploading documents, querying, and obtaining complete answers.