Authors - Mangesh Salunke, Tilak Shah, Vishal Bhokre, R. Sreemathy Abstract - Chatbot also known as conversational agents is an interactive software that responds to users’ queries using artificial intelligence. While traditional machine-learning chatbots have shown promise, LLM-powered chatbots offer more natural and relevant conversations, enhancing the user experience. The rise of OpenAI’s ChatGPT, Google’s Gemini, LangChain, etc has widened the horizon of applications of chatbots to almost every sector including education, healthcare, banking, entertainment, e-commerce and telecommunications. The main objective of this comprehensive study is to explore and analyze the current advancements in chatbot development using different artificial techniques. This survey paper examines key trends in the development of chatbots, the components and techniques used, and the evaluation metrics employed to measure performance. We discuss different metrics used to evaluate chatbots' performance like accuracy, BLEU, ROUGE and relevancy. The results suggest that LLM-powered chatbots facilitate more natural and contextually appropriate conversations than traditional machine-learning models, leading to a marked enhancement in user experience. By synthesizing insights from existing research, we aim to provide a comprehensive understanding of RAG-based chatbot technology.
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