Getting Started with Retrieval Augmented Generation (RAG) Using Claude Opus 3

This guide will walk you through setting up a Retrieval Augmented Generation (RAG) agent using Claude 3 Opus, Voyage Embeddings, Qdrant Vector DB, and a pre-chunked dataset from Hugging Face.

Here is the GitHub link

Why RAG?

RAG combines the strengths of retrieval-based systems with generation-based models, allowing you to fetch relevant information and generate coherent, contextually appropriate responses. It's ideal for applications like question-answering and content generation.

What You'll Need

• Google Account: For using Google Colab, or a local setup for Jupyter Notebook.
• API Keys: Secure API keys for Claude 3 Opus, Voyage Embeddings, and Qdrant Vector DB.