Hierarchy

Properties

evaluatorType: keyof EvaluatorType

The name of the evaluator to use. Example: labeled_criteria, criteria, etc.

formatEvaluatorInputs: EvaluatorInputFormatter

Convert the evaluation data into formats that can be used by the evaluator. This should most commonly be a string. Parameters are the raw input from the run, the raw output, raw reference output, and the raw run.

Example

// Chain input: { input: "some string" }
// Chain output: { output: "some output" }
// Reference example output format: { output: "some reference output" }
const formatEvaluatorInputs = ({
rawInput,
rawPrediction,
rawReferenceOutput,
}) => {
return {
input: rawInput.input,
prediction: rawPrediction.output,
reference: rawReferenceOutput.output,
};
};

Returns

The prepared data.

agentTools?: StructuredToolInterface[]

A list of tools available to the agent, for TrajectoryEvalChain.

chainOptions?: Partial<Omit<LLMEvalChainInput<EvalOutputType, BaseLanguageModelInterface>, "llm">>
criteria?: CriteriaLike

The criteria to use for the evaluator.

distanceMetric?: EmbeddingDistanceType

The distance metric to use for comparing the embeddings.

embedding?: any

The embedding objects to vectorize the outputs.

feedbackKey?: string

The feedback (or metric) name to use for the logged evaluation results. If none provided, we default to the evaluationName.

llm?: any

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