• 👋 Hi, I’m @TheScroll75
• 👀 I’m interested in ...
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• 😄 Pronouns: he ...
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from deepeval.tracing import observe, update_current_span from deepeval.test_case import LLMTestCase from deepeval.dataset import Golden from deepeval.metrics import GEval from deepeval import evaluate

correctness = GEval(name="Correctness", criteria="Determine if the 'actual output' is correct based on the 'expected output'.", evaluation_params=[LLMTestCaseParams.ACTUAL_OUTPUT, LLMTestCaseParams.EXPECTED_OUTPUT])

@observe(metrics=[correctness]) def inner_component(): # Component can be anything from an LLM call, retrieval, agent, tool use, etc. update_current_span(test_case=LLMTestCase(input="...", actual_output="...")) return

@observe def llm_app(input: str): inner_component() return

evaluate(observed_callback=llm_app, goldens=[Golden(input="Hi!")])