I made a personalized AI web app with RAG

So during my 4th Year of my college my team had decided to build a Personalized AI Assistant that can understand the user's behavior and give results accordingly.

We had implemented reinforcement learning in the backend server, so based on the feedback given by the user it gives the output.

During the later stages of the project I glimpsed on something called RAG (Retrieval Augmented Generation).

Because the problem statement and research were already done on reinforcement learning my teammates were not interested in RAG.

What is RAG?

Retrieval Augmented Generation (RAG) is basically an AI technique that enhances the LLM's result by retrieving information from a Knowledge Graph.

The Knowledge Graph can be anything:-

• User's interests and traits


• Your Netflix viewing genres, actors etc


• YouTube Recommendations
  and so much more..

Backend: https://github.com/J0seph-Mart1n/Persona_Backend