Define Your Own Metric

You can define a custom metric by defining the measure and is_successful functions and inheriting the base Metric class. An example is provided below.

note

As of right now, we do not currently support custom metrics for our dashboard but this will be supported in an upcoming version - we apologise for the wait! For any requests of additional metrics, please feel free to e-mail jacky@confident-ai.com

import asyncio
from deepeval.metrics.metric import Metric

class LengthMetric(Metric):
    """This metric checks if the output is more than 3 letters"""
    def __init__(self, minimum_length: int=3):
        self.minimum_length = minimum_length

    def __call__(self, text: str):
        # sends to server
        score = self.measure(text)
        # Optional: Logs it to the server
        return score

    def measure(self, text: str):
        self.success = len(x) > self.minimum_length
        return a > b

    def is_successful(self):
        return self.success

    @property
    def __name__(self):
        return "Length"

metric = LengthMetric()