@A-4824 Thanks for the question. Can you please add more details about the use case. This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo and gpt3), and vector store (Pinecone, Redis and others) or Azure cognitive search for data indexing and retrieval. The nature of AOAI calls are stateless, so to be able to create a "Cache" layer you will build solution using Cognitive Search (or other Vector DB) for custom scenarios.
The repo provides a way to upload your own data so it's ready to try end to end.
https://github.com/akshata29/chatpdf
Kindly accept the answer if it is helpful.