All Classes and Interfaces
Class
Description
Assertion utilities for evaluation-based testing.
Base class for implementing concrete evaluators.
This is a basic evaluation example that demonstrates how to:
- Create a
Dataset programmatically
- Define multiple evaluators that we want to run
- Create a simple task with an actual LLM by OpenAI
- Run an experiment and show the evaluation resultsThis example shows two ways to create custom evaluators:
A collection of examples for evaluation.
Builder for constructing datasets.
JUnit 5 ArgumentsProvider that loads
Examples from a Dataset.Thrown when a dataset cannot be correctly resolved or loading fails.
Resolves a dataset URI to a
Dataset.Singleton registry for dataset resolvers.
Provides
Examples from a Dataset as arguments to a parameterized test.The result of an evaluation.
Builder for constructing evaluation results.
A test case for evaluation.
Builder for constructing test cases with multiple inputs and outputs.
Thrown when an evaluation cannot be executed successfully.
Evaluates test cases and produces scored results.
Evaluator that checks for exact string match between actual and expected outputs.
A dataset example with inputs, expected outputs, and metadata.
Builder for constructing examples with multiple inputs and outputs.
An evaluation experiment that runs a task against a dataset and evaluates the results.
Aggregated results from an experiment run.
Evaluator that uses an LLM to check how much of the actual output is backed by the given context.
Resolves datasets from the filesystem.
A language model used for evaluation.
Simple RAG evaluation example using LangChain4j with local embeddings.
Utilities for integrating with LangChain4j.
Evaluator that uses an LLM to evaluate outputs based on the specified criteria.
Evaluator that checks if the actual output matches a regular expression pattern.