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
skipRun the core logic of this chain and add to output if desired.
Wraps _call and handles memory.
Optional
config: BaseCallbackConfig | CallbacksOptional
tags: string[]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: BaseCallbackConfig | CallbacksThe evaluation results containing the score or value. It is recommended that the dictionary contain the following keys:
Invoke the chain with the provided input and returns the output.
Input values for the chain run.
Optional
config: BaseCallbackConfigOptional configuration for the Runnable.
Promise that resolves with the output of the chain run.
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.