hparreao/Awesome-AI-Evaluation-Guide

A comprehensive, implementation-focused guide to evaluating Large Language Models, RAG systems, and Agentic AI in production environments.

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This guide helps AI product managers, data scientists, and MLOps engineers confidently assess the performance of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and AI agents in real-world scenarios. It provides practical code examples and decision frameworks for selecting the right evaluation metrics based on your specific application, from medical to legal domains. The guide helps you evaluate system inputs and outputs to understand their quality, safety, and reliability for production deployment.

Use this if you need to systematically evaluate your AI models and systems to ensure they meet performance, safety, and reliability standards before and after deployment.

Not ideal if you are looking for a simple API library to quickly get basic model scores without understanding the underlying evaluation methods or their real-world implications.

AI product management MLOps LLM evaluation RAG systems AI agent development
No Package No Dependents
Maintenance 6 / 25
Adoption 5 / 25
Maturity 13 / 25
Community 0 / 25

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CC0-1.0

Last pushed

Dec 05, 2025

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