As large language models (LLM) gain popularity in various question-answering systems, retrieval-augmented generation (RAG) pipelines have also become a focal…
As large language models (LLM) gain popularity in various question-answering systems, retrieval-augmented generation (RAG) pipelines have also become a focal point. RAG pipelines combine the generation power of LLMs with external data sources and retrieval mechanisms, enabling models to access domain-specific information that may not have existed during fine-tuning.