Build Your Own AI Assistant with RAG: A Practical Guide for GenAI Engineers

Author(s): Aayushi_Sharma

Originally published on Towards AI.

Build Your Own AI Assistant with RAG: A Practical Guide for GenAI Engineers

“How can I make ChatGPT answer questions from my own documents?”
If you’ve ever wondered that, you’re in the right place. Welcome to the world of Retrieval-Augmented Generation (RAG) — a powerful framework to make LLMs like GPT-4 smarter with your data.

This article serves as a practical guide to building AI assistants using Retrieval-Augmented Generation (RAG), outlining its core principles and methodologies, such as document ingestion, chunking data into manageable pieces, converting text into embeddings, and utilizing vector databases for storage and retrieval. Each step is supported by examples and best practices, making it accessible for engineers wishing to leverage AI for enhancing data-driven insights and generation capabilities.

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Published via Towards AI