
Unlocking Creativity with Azure OpenAI
By :

To construct this system, we need the following essential services:
Our primary objective is to transform unstructured data into embeddings, which will be stored within a vector database. When a user submits a query, the system leverages Azure OpenAI embeddings for processing. Subsequently, a vector search operation is performed on the vector database to retrieve the top K paragraphs. These selected paragraphs are then sent to the Azure OpenAI answering prompt, which extracts the answers and delivers them to the user.
The following is a simple architecture diagram for a question-and-answer solution using Azure OpenAI:
Figure 4.1: Architecture design
In the preceding diagram, we are sending Azure OpenAI Service embeddings to a vector database, and the questions asked by the user are sent to those embeddings and the results will be extracted. Now, wewill develop a solution...