"This application utilizes a combination of OPENAI and Azure infrastructure to develop a Rag chat app. The purpose of this app is to interact with various research papers on healthcare for patient education.
The source papers used are from Google Scholar and PubMed.
Thus, this chat app is RAG-based, where Azure Search AI is employed as a Vector Database, proving to be very helpful in indexing all tokens efficiently. We have utilized Azure infrastructure with Bicep for deployment. This end-to-end deployment makes the entire process and application a production-ready RAG-based chat app
Project name
Research analytics on Patient eduction by LLM
Description
"This application utilizes a combination of OPENAI and Azure infrastructure to develop a Rag chat app. The purpose of this app is to interact with various research papers on healthcare for patient education.
The source papers used are from Google Scholar and PubMed.
Thus, this chat app is RAG-based, where Azure Search AI is employed as a Vector Database, proving to be very helpful in indexing all tokens efficiently. We have utilized Azure infrastructure with Bicep for deployment. This end-to-end deployment makes the entire process and application a production-ready RAG-based chat app
Language
ENGLISH
Project Repository URL
https://github.com/dapsrajipo/AZURE-RAG-CHAT-APP-/tree/openaidp/data
Deployed Endpoint URL
https://app-backend-pfixdhcvuuirc.azurewebsites.net/
Project video
https://youtu.be/5zyisvCZ6ng
Team members
dapsrajipo, prem28timsina,Tanushree123-hub
Showcase Consent
Yes