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← Retrieval Augmented Generation
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Question
In a RAG application, what happens after the user's question is turned into a vector?
1
The question is sent straight to the model with no extra context added
2
A new embedding model is trained on the user's question
3
The closest document chunks are retrieved and added to the prompt
4
The model's weights are updated using the question
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