Bangladesh travel bot: RAG application using LLM

Abstract

The ”Bangla Travel-Bot” project aims to create an intelligent and user-friendly chatbot that provides accurate, context-specific responses to travel-related queries for Bangla-speaking travelers. As travel information in Bangla is often limited, this project seeks to fill the gap by offering a platform that ensures seamless access to vital travel information in the user’s native language. The chatbot is designed to assist travelers with a variety of needs, such as recommendations for tourist destinations, transportation options, accommodation, local customs, and real-time updates on weather, events, and travel logistics. This system leverages the power of a Retrieval-Augmented Generation (RAG) framework, which enhances the bot’s ability to generate high-quality responses by retrieving relevant information from trusted travel sources. The integration of LLaMA 3, a state-of-the-art language model, ensures the chatbot can effectively process and respond in Bangla, maintaining both linguistic accuracy and cultural relevance. The chatbot is capable of understanding user queries and providing personalized recommendations based on location, preferences, and travel context. Through the use of advanced natural language processing (NLP) techniques, the ”Bangla Travel-Bot” offers an intuitive conversational interface, ensuring that users can easily interact with the system. Whether it’s helping with last-minute travel plans or offering insightful tips about a destination, the chatbot strives to enhance the overall travel experience for Bangla-speaking users. This project not only aims to simplify the process of planning and managing travel for Bangla speakers but also contributes to the development of accessible, language-specific travel assistance tools in the broader field of artificial intelligence and human-computer interaction..