From the course: Hands-On AI: RAG using LlamaIndex

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Drawbacks of Naive RAG

Drawbacks of Naive RAG - LlamaIndex Tutorial

From the course: Hands-On AI: RAG using LlamaIndex

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Drawbacks of Naive RAG

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- [Instructor] I hope you're feeling proud of yourself. I hope you're feeling energized and excited because you've seen end to end what a RAG pipeline looks like. At least you've seen end to end what a Naive RAG pipeline looks like. Just to drive the point home and reiterate, let's talk about the thing that we've repeatedly been doing over the last several lessons just to drive it home one more time. Remember that it's essentially a three step process. We index, retrieve, and generate. So in indexing, we're processing data into manageable, searchable chunks and then indexing them for efficient retrieval. In retrieval, we're using the user's query to search the indexed data and then fetch the most relevant documents. For generation, we're combining the user query with the retrieved context to generate a context aware response. That's great for a Naive RAG pipeline like it works, but it has challenges. So let's talk a little bit about these challenges. One is that there's issues with…

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