Building more advanced retrieval mechanisms
Now we understand the basic components offered by LlamaIndex, we can build increasingly sophisticated solutions. On one hand, the retrievers we have discussed already provide efficient solutions for knowledge base querying and context enhancement in an RAG flow. On the other hand, we’ll see that there are many more advanced retrieval methods that either use specific techniques or ingeniously combine the retrievers already discussed.
The naive retrieval method
LlamaIndex provides fast query methods by default. As we have seen, in just a few lines of code, we can ingest documents, create nodes and, for example, build a VectorStoreIndex retriever, which we can then just as easily query to return the most relevant parts using a retriever that uses similarity measurement techniques.
The method is very simple and easy to implement. However, it is not an ideal method in all situations. More often than not, the naive method, as it...
