S. Vidivelli*, Manikandan Ramachandran*, A. Dharunbalaji
CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2423-2442, 2024, DOI:10.32604/cmc.2024.054360
Abstract This exploration acquaints a momentous methodology with custom chatbot improvement that focuses on proficiency close by viability. We accomplish this by joining three key innovations: LangChain, Retrieval Augmented Generation (RAG), and enormous language models (LLMs) tweaked with execution proficient strategies like LoRA and QLoRA. LangChain takes into consideration fastidious fitting of chatbots to explicit purposes, guaranteeing engaged and important collaborations with clients. RAG’s web scratching capacities engage these chatbots to get to a tremendous store of data, empowering them to give exhaustive and enlightening reactions to requests. This recovered data is then decisively woven into… More >
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