Retrieval Augmented Generation

Please visit http://ai-cookbook.io for the accompanying documentation for this repo.

This repo provides learning materials and production-ready code to build a high-quality RAG application using Databricks. The Mosaic Generative AI Cookbook provides:

• A conceptual overview and deep dive into various Generative AI design patterns, such as Prompt Engineering, Agents, RAG, and Fine Tuning
• An overview of Evaluation-Driven development
• The theory of every parameter/knob that impacts quality
• How to root cause quality issues and detemermine which knobs are relevant to experiment with for your use case
• Best practices for how to experiment with each knob

The provided code is intended for use with the Databricks platform. Specifically:

• Mosaic AI Agent Framework which provides a fast developer workflow with enterprise-ready LLMops & governance
• Mosaic AI Agent Evaluation which provides reliable, quality measurement using proprietary AI-assisted LLM judges to measure quality metrics that are powered by human feedback collected through an intuitive web-based chat UI