Offline LLM: Generating Human Like Responses Without Internet

Project Code :TCMAPY1136

Objective

The objective is to create and implement a Large Language Model (LLM)-powered tool capable of generating human- like responses to natural language inputs, specifically designed for network environments that are not connected to the internet. This self-contained system aims to provide users with an offline solution for generating contextually relevant, coherent, and context-aware responses to a wide range of queries and interactions, enhancing communication and problem-solving capabilities in disconnected or restricted network scenarios.

Abstract

The process of gaining and absorbing the knowledge from various sources is a time-consuming process where people, mainly youth spend time surfing over the internet for relevant information. The proposed system mainly focuses on scraping the data from websites and providing the summary as well as keywords from the information extracted from various websites giving the user flexibility to select the website of their choice. The proposed system for the text summarization and keyword extraction undergoes a sequence of steps starting from data extraction from a website link, removal of outliers and irrelevant information, emphasizing on the importance of particular data extracted from the website and creating a summary of the extracted data. For the selection of relevant information from the extracted data, it is necessary to use natural language processing. The proposed project helps its users to reduce their surfing time and gives summary prepared from multiple website links and documents or keywords from a particular website or a document.

Keywords: Summarization, multi-document summarization, keyword extraction, natural language processing, Text rank algorithm.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.