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
skipOptional
config: any[]Use .batch() instead. Will be removed in 0.2.0.
This feature is deprecated and will be removed in the future.
It is not recommended for use.
Call the chain on all inputs in the list
Optional
config: anyOptional
tags: string[]Use .invoke() instead. Will be removed in 0.2.0.
Run the core logic of this chain and add to output if desired.
Wraps _call and handles memory.
Check if the evaluation arguments are valid.
Optional
reference: stringThe reference label.
Optional
input: stringThe input string.
If the evaluator requires an input string but none is provided, or if the evaluator requires a reference label but none is provided.
Evaluate 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.
Generated using TypeDoc
Use embedding distances to score semantic difference between a prediction and reference.