LangChain - Evaluation and TestingWhich of the following is the correct syntax to define a custom evaluation metric class in Langchain?Aclass MyMetric():\n def train(self):\n passBclass MyMetric(BaseEvalMetric):\n def evaluate(self, predictions, references):\n return scoreCdef MyMetric():\n return scoreDdef evaluate_metric(predictions, references):\n return scoreCheck Answer
Step-by-Step SolutionSolution:Step 1: Recognize class-based metric definitionCustom metrics in Langchain are classes inheriting from a base metric class.Step 2: Check for evaluate method with correct parametersThe evaluate method must accept predictions and references and return a score.Final Answer:class MyMetric(BaseEvalMetric):\n def evaluate(self, predictions, references):\n return score -> Option BQuick Check:Correct syntax = Class with evaluate method [OK]Quick Trick: Define class with evaluate(predictions, references) method [OK]Common Mistakes:MISTAKESUsing functions instead of classesMissing evaluate methodDefining unrelated methods like train
Master "Evaluation and Testing" in LangChain9 interactive learning modes - each teaches the same concept differentlyLearnWhyDeepVisualTryChallengeProjectRecallPerf
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