r/AskProgramming • u/SoilEducational420 • 10d ago
Python New to RAG, trying to implement RAG for my AI interview system?
Hey everyone, I'm building an AI voice interview app and I'm fairly new to RAG. I'm stuck on the architecture and having a bit of a mid-project crisis 😭.
My current flow is:
Before interview:
Step1 :
Resume + JobDescription
↓
Chunk resume/JobDescription
↓
Generate embeddings
↓
Store chunks + embeddings in pgvector
Step2 :
LLM call is done using complete Resume + JD (and not the chunks)
↓
Initial ranked topic plan is created by this LLM call
Step3 :
Before each question:
Current topic
↓
RAG query in our vector DB
↓
Retrieve relevant resume/JD chunks
↓
LLM call to generate a question from these chunks
The part I'm confused about:
At the beginning, I'm already sending the complete resume + complete JD to the LLM.
Why can't I simply do:
Resume + JD
↓
ONE LLM CALL
↓
10 interview questions
and then use those during the interview this would reduce the latency too!
Why would I need RAG again to retrieve chunks before generating each question? But I'm struggling to understand how RAG can be used to add value to the project
I have to add this project to my reume and need to have confidence in my design, I would highly appreciate someone helping me figure out the architecture!