Skip to main content
Back to portfolio
RAG, CAG and fine-tuning research overview

AI Integration

RAG, CAG & Fine-Tuning Research

Role
AI Integrator · Researcher

A college research project exploring retrieval-augmented generation (RAG), cache-augmented generation (CAG), and fine-tuning workflows. Used GPT-4o mini as the base model, Pinecone for vector retrieval, OpenAI APIs for RAG/CAG pipelines, OpenAI cloud fine-tuning for custom models, and Node.js to orchestrate the full experimentation stack.

Keynotes

  • Implemented RAG pipelines with Pinecone vector storage and OpenAI embeddings.
  • Explored CAG patterns to reduce latency and repeated retrieval cost.
  • Fine-tuned GPT-4o mini via OpenAI cloud and compared outputs across approaches.
  • Built a Node.js service layer to unify API calls, prompts, and evaluation flows.

Technologies

  • Node.js
  • TypeScript
  • OpenAI API
  • GPT-4o mini
  • Pinecone
  • RAG
  • Fine-tuning