From the course: Developing RAG Apps with LlamaIndex and Next.js
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Summary
From the course: Developing RAG Apps with LlamaIndex and Next.js
Summary
So we've done a lot in this section. We continue with Llama Index, but we did a deeper, even deeper dive. So we talked about loaders, how to use this pre-defined pre-baked loaders in Llama Index. We talked about querying stages as an overview. We talked about chat engine, the whole workflow as part of a querying stage. When it comes to Llama Index, we did, of course, some hands on here, one of which is the custom rack systems with Lamaindex. So we learn how to customize ourselves the rack system using Lamaindex even further, because that is the thing that Lamaindex is good about, which is allows us to have this customization flexibility if we want to do our own thing, customize what they already have. So they have that interface, of course, that it's easier for us to just do things quicker to create our RAC systems. But if we want to go deeper and create our own synthesizer, our own response builder and everything, and pull in our own large language models and everything, we also can…
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Contents
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LlamaIndex core concepts: Loaders index3m 52s
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The querying stage: Overview2m 16s
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Querying stage: ChatEngine and querying engine full overview4m 47s
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Hands-on: Create a custom RAG system with LlamaIndex15m 7s
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Hands-on: Structured data extraction6m 47s
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Hands-on: Querying a PDF file5m 55s
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Hands-on: Interacting with a RAG system through an Express API, full hands-on14m 28s
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Summary2m 32s
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