langchain.evaluation.string_distance.base.StringDistanceEvalChain¶
class langchain.evaluation.string_distance.base.StringDistanceEvalChain[source]¶
Bases: StringEvaluator, _RapidFuzzChainMixin
Compute string distances between the prediction and the reference.
Examples
>>> from langchain.evaluation import StringDistanceEvalChain
>>> evaluator = StringDistanceEvalChain()
>>> evaluator.evaluate_strings(
        prediction="Mindy is the CTO",
        reference="Mindy is the CEO",
    )
Using the load_evaluator function:
>>> from langchain.evaluation import load_evaluator
>>> evaluator = load_evaluator("string_distance")
>>> evaluator.evaluate_strings(
        prediction="The answer is three",
        reference="three",
    )
param callback_manager: Optional[BaseCallbackManager] = None¶
Deprecated, use callbacks instead.
param callbacks: Callbacks = None¶
Optional list of callback handlers (or callback manager). Defaults to None.
Callback handlers are called throughout the lifecycle of a call to a chain,
starting with on_chain_start, ending with on_chain_end or on_chain_error.
Each custom chain can optionally call additional callback methods, see Callback docs
for full details.
param distance: StringDistance = StringDistance.JARO_WINKLER¶
param memory: Optional[BaseMemory] = None¶
Optional memory object. Defaults to None.
Memory is a class that gets called at the start
and at the end of every chain. At the start, memory loads variables and passes
them along in the chain. At the end, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full catalog.
param metadata: Optional[Dict[str, Any]] = None¶
Optional metadata associated with the chain. Defaults to None.
This metadata will be associated with each call to this chain,