RAG models typically consist of two main components:
- Retrieval component: This component is responsible for retrieving relevant passages or snippets from a large corpus based on the input prompt or query. This component uses advanced algorithms and techniques to identify the most relevant passages that match the input query.
- Generation component: This component takes the retrieved passages as input and generates new text based on the context and the retrieved information. This component uses natural language processing techniques, such as language modeling and text generation, to create coherent and meaningful text.