Skip to content

README.md

Latest commit

 

History

History
17 lines (10 loc) · 759 Bytes

README.md

File metadata and controls

17 lines (10 loc) · 759 Bytes

An version based on Pixegami’s RAG Tutorial — rebuilt with OpenAI embeddings and ChatGPT integration.

Overview

This repository is a functional and tested variant of Pixegami’s RAG Tutorial v2.
It demonstrates how to build a lightweight, local Retrieval-Augmented Generation (RAG) pipeline using OpenAI embeddings and ChatGPT models for answering questions over PDF documents.

This version preserves the overall project structure of Pixegami’s original tutorial but introduces key improvements:

  • Replaces AWS Bedrock with OpenAI API (no AWS credentials needed)
  • Adds interactive question answering using GPT
  • Simplifies configuration (automatic environment variable handling)