This repository provides a practical tutorial demonstrating how to build a Retrieval Augmented Generation (RAG) system specifically tailored for querying medical guidelines or other healthcare documents.
Why RAG for Healthcare?
- Accuracy: Ensures Large Language Model (LLM) responses are grounded in verified medical knowledge sources provided by you.
- Verifiability: Provides references/citations, allowing users to trace answers back to the source document.
- Control: Gives you direct control over the information the LLM uses.
- Reduced Hallucinations: Minimizes the risk of the LLM generating plausible but incorrect information.
This project walks through setting up the necessary components, loading documents (including your own PDFs), and building a query system using LangChain and OpenAI.