Generative AI refers to algorithms and models in artificial intelligence that are capable of generating new data or content that is similar to existing data. These models are trained on large datasets and learn to generate new examples that mimic the patterns and characteristics of the original data.
There are always those who say that their child looks more like their mother or their father. How about using math and Artificial Intelligence to be sure? The facial-matching application can answer you.
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How to set up RAG for OpenAI agents using IRIS Vector DB in Python
In this article, I’ll walk you through an example of using InterSystems IRIS Vector DB to store embeddings and integrate them with an OpenAI agent.
To demonstrate this, we’ll create an OpenAI agent with knowledge of InterSystems technology. We’ll achieve this by storing embeddings of some InterSystems documentation in IRIS and then using IRIS vector search to retrieve relevant content—enabling a Retrieval-Augmented Generation (RAG) workflow.
Note: Section 1 details how process text into embeddings.