FAQ/RAG Example

The FAQ/RAG example demonstrates how a Retrieval-Augmented Generation (RAG) system can effectively handle frequently asked questions.

By leveraging a large language model in conjunction with a retrieval system, we can provide accurate and contextually relevant answers to user queries.

This example showcases the power of combining LLMs with a robust retrieval mechanism to enhance the accuracy and relevance of generated responses.

Check out the example below to see it in action!

Retrieve and Generate AI Component

What do you want to know about Ivan:

AI Response

Inside an application, this fetching and information retrieval is usually connected to a larger compound AI system, allowing the LLM to utilize the information in its specific response.

In such a way, the system doesn't have to be trained on all of the specified data and can fetch information in real time.