deepeval_pytest_answer_relevancy_metric_test_case.py

1import pytest
2from deepeval import assert_test
3from deepeval.test_case import LLMTestCase
4from deepeval.metrics import AnswerRelevancyMetric
5
6def test_answer_relevancy():
7    # 1. Define the metric you want to use
8    answer_relevancy_metric = AnswerRelevancyMetric(threshold=0.7)
9
10    # 2. Define the test case (input, actual_output, and retrieval_context)
11    test_case = LLMTestCase(
12        input="What are the primary ingredients in a Margherita pizza?",
13        # Replace this with your actual LLM application output
14        actual_output="The primary ingredients in a Margherita pizza are tomatoes, mozzarella cheese, fresh basil, salt, and extra-virgin olive oil.",
15        retrieval_context=[
16            "Margherita pizza is a typical Neapolitan pizza, made with San Marzano tomatoes, mozzarella cheese, fresh basil, salt and extra-virgin olive oil."
17        ]
18    )
19
20    # 3. Assert the test case against the metric
21    assert_test(test_case, [answer_relevancy_metric])