Which components are essential in a standard RAG pipeline?

AA chunking step, an embedding model, a vector store, a retriever, and an LLM.

BA fine-tuning step, gradient checkpointing, a vector store, and an inference server.

CA tokenizer, a BERT model, a relational database, and a web scraper.

DA feature store, a Delta Lake table, a Spark cluster, and a prompt template.

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