The distance metric to use for comparing the embeddings.
Optional
embeddingThe embedding objects to vectorize the outputs.
Optional
evaluationThe name of the evaluation.
Optional
memoryOptional
skipOptional
skipEvaluate Chain or LLM output, based on optional input and label.
Optional
config: anyThe evaluation results containing the score or value. It is recommended that the dictionary contain the following keys:
Return a json-like object representing this chain.
Static
deserializeLoad a chain from a json-like object describing it.
Use embedding distances to score semantic difference between a prediction and reference.