The content from this repository has been moved to the Databricks Generative AI Cookbook which is accompanied by 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
