"""Comparison evaluators.
This module contains evaluators for comparing the output of two models,
be they LLMs, Chains, or otherwise. This can be used for scoring
preferences, measuring similarity / semantic equivalence between outputs,
or any other comparison task.
Example:
>>> from langchain_community.chat_models import ChatOpenAI
>>> from langchain.evaluation.comparison import PairwiseStringEvalChain
>>> llm = ChatOpenAI(temperature=0)
>>> chain = PairwiseStringEvalChain.from_llm(llm=llm)
>>> result = chain.evaluate_string_pairs(
... input = "What is the chemical formula for water?",
... prediction = "H2O",
... prediction_b = (
... "The chemical formula for water is H2O, which means"
... " there are two hydrogen atoms and one oxygen atom."
... reference = "The chemical formula for water is H2O.",
... )
>>> print(result)
# {
# "value": "B",
# "comment": "Both responses accurately state"
# " that the chemical formula for water is H2O."
# " However, Response B provides additional information"
# . " by explaining what the formula means.\\n[[B]]"
# }
"""
from langchain.evaluation.comparison.eval_chain import (
LabeledPairwiseStringEvalChain,
PairwiseStringEvalChain,
)
__all__ = ["PairwiseStringEvalChain", "LabeledPairwiseStringEvalChain"]