From the course: Developing RAG Apps with LlamaIndex and Next.js

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Hands-on: Create a custom RAG system with LlamaIndex

Hands-on: Create a custom RAG system with LlamaIndex

From the course: Developing RAG Apps with LlamaIndex and Next.js

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Hands-on: Create a custom RAG system with LlamaIndex

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So when we look at these example.js that we created, you can see that we go through the process of loading the essay and making sure everything is loaded in and create a document object with the essay we loaded. And, of course, we create the index by splitting and creating embeddings and store them in a vector store. That's what's happening here. Just one line of code. Okay. And then we do the querying through the index by using the query engine function to create that object. And then we pass in the question, the query through, and we get the information. And of course, we are looping through the source nodes, each piece to get more information about the score and other metadata. And so all of this is great. This is good to show you how Llama Index is able to abstract out all of the intricacies in the back end. Now, I'm going to show you how you would do the same thing. But now, more manually, or in this case, show you exactly the same process by customizing things ourselves. I think…

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