Definition
DeepEval is an open-source testing framework used to quantify the performance of RAG pipelines and AI agents through unit-testing principles. It employs 'LLM-as-a-judge' metrics—such as faithfulness, answer relevancy, and hallucination scores—to provide deterministic-style testing for non-deterministic model outputs.
Not a deep learning training library; it is a testing and evaluation framework specifically for LLM application outputs.
"An automated Quality Control inspector at the end of a factory line who uses a checklist to grade every finished product before it can be shipped."
- G-Eval(Underlying Methodology)
- RAG Triad(Component Evaluation Framework)
- Faithfulness(Core Metric)
- LLM-as-a-judge(Prerequisite Concept)
Conceptual Overview
DeepEval is an open-source testing framework used to quantify the performance of RAG pipelines and AI agents through unit-testing principles. It employs 'LLM-as-a-judge' metrics—such as faithfulness, answer relevancy, and hallucination scores—to provide deterministic-style testing for non-deterministic model outputs.
Disambiguation
Not a deep learning training library; it is a testing and evaluation framework specifically for LLM application outputs.
Visual Analog
An automated Quality Control inspector at the end of a factory line who uses a checklist to grade every finished product before it can be shipped.