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AutoEvals is a tool to quickly and easily evaluate AI model outputs.

Installation

RAGAS Evaluators

AnswerCorrectness

Measures answer correctness compared to ground truth using a weighted average of factuality and semantic similarity.
ScorerArgs

AnswerRelevancy

Scores the relevancy of the generated answer to the given question. Answers with incomplete, redundant or unnecessary information are penalized.
ScorerArgs

AnswerSimilarity

Scores the semantic similarity between the generated answer and ground truth.
ScorerArgs

ContextEntityRecall

Estimates context recall by estimating TP and FN using annotated answer and retrieved context.
ScorerArgs

ContextPrecision

ContextPrecision evaluator function.
ScorerArgs

ContextRecall

ContextRecall evaluator function.
ScorerArgs

ContextRelevancy

ContextRelevancy evaluator function.
ScorerArgs

Faithfulness

Measures factual consistency of the generated answer with the given context.
ScorerArgs

LLM Evaluators

Battle

Test whether an output better performs the instructions than the original (expected) value.
ScorerArgs

ClosedQA

Test whether an output answers the input using knowledge built into the model. You can specify criteria to further constrain the answer.
ScorerArgs

Factuality

Test whether an output is factual, compared to an original (expected) value.
ScorerArgs

Humor

Test whether an output is funny.
ScorerArgs

Possible

Test whether an output is a possible solution to the challenge posed in the input.
ScorerArgs

Security

Test whether an output is malicious.
ScorerArgs

Sql

Test whether a SQL query is semantically the same as a reference (output) query.
ScorerArgs

Summary

Test whether an output is a better summary of the input than the original (expected) value.
ScorerArgs

Translation

Test whether an output is as good of a translation of the input in the specified language as an expert (expected) value.
ScorerArgs

String Evaluators

EmbeddingSimilarity

A scorer that uses cosine similarity to compare two strings.
ScorerArgs

ExactMatch

A simple scorer that tests whether two values are equal. If the value is an object or array, it will be JSON-serialized and the strings compared for equality.
reflection

Levenshtein

A simple scorer that uses the Levenshtein distance to compare two strings.
reflection

LevenshteinScorer

LevenshteinScorer evaluator function.
reflection

JSON Evaluators

JSONDiff

A simple scorer that compares JSON objects, using a customizable comparison method for strings (defaults to Levenshtein) and numbers (defaults to NumericDiff).
ScorerArgs

ValidJSON

A binary scorer that evaluates the validity of JSON output, optionally validating against a JSON Schema definition (see https://json-schema.org/learn/getting-started-step-by-step#create).
ScorerArgs

Custom Evaluators

LLMClassifierFromSpec

LLMClassifierFromSpec evaluator function.
string
reflection

LLMClassifierFromSpecFile

LLMClassifierFromSpecFile evaluator function.
string
literal | literal | literal | literal | literal | literal | literal | literal | literal

LLMClassifierFromTemplate

LLMClassifierFromTemplate evaluator function.
reflection

OpenAIClassifier

OpenAIClassifier evaluator function.
ScorerArgs

buildClassificationTools

buildClassificationTools evaluator function.
boolean
array

List Evaluators

ListContains

A scorer that semantically evaluates the overlap between two lists of strings. It works by computing the pairwise similarity between each element of the output and the expected value, and then using Linear Sum Assignment to find the best matching pairs.
ScorerArgs

Moderation

Moderation

A scorer that uses OpenAI’s moderation API to determine if AI response contains ANY flagged content.
ScorerArgs

Numeric Evaluators

NumericDiff

A simple scorer that compares numbers by normalizing their difference.
reflection

Configuration

init

init evaluator function.
reflection

Utilities

makePartial

makePartial evaluator function.
Scorer
string

normalizeValue

normalizeValue evaluator function.
unknown
boolean

Source Code

For the complete TypeScript source code and additional examples, visit the autoevals GitHub repository.