Chat With Documents Using Large Language Model (LLM)

Computer Engineering

The integration of advanced language models, such as GPT3.5, into information retrieval and conversational AI has created new possibilities. This abstract explores the concept of "Chat with Documents using LLM" where users can interact with large language models to retrieve information from documents in a more natural and intuitive manner. This innovative approach goes beyond traditional keyword-based searches and allows users to engage in chat-like conversations with LLM. Users can request specific information, summaries, or insights from documents, and the language model, through its deep understanding of the document's content, generates coherent and context-aware responses. This process bridges the gap between human-like conversation and document search, revolutionizing the way we interact with textual data. One of the key advantages of this approach is its ability to handle multiple documents simultaneously. Users can ask complex questions, clarify doubts, and explore the content of various documents in a seamless manner. The language model interprets the context and learns from the user's interactions, further enhancing its understanding of the documents and improving its responses. Overall, "Chat with Documents using LLM" empowers users to retrieve information from documents in a more accessible and efficient way. It offers a more intuitive and natural conversational experience, making information retrieval a seamless part of human interaction.

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