langchain.smith.evaluation.runner_utils.TestResult

class langchain.smith.evaluation.runner_utils.TestResult[source]

A dictionary of the results of a single test run.

Methods

__init__(*args, **kwargs)

clear()

copy()

fromkeys([value])

Create a new dictionary with keys from iterable and values set to value.

get(key[, default])

Return the value for key if key is in the dictionary, else default.

get_aggregate_feedback([quantiles])

Return quantiles for the feedback scores.

items()

keys()

pop(k[,d])

If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem()

Remove and return a (key, value) pair as a 2-tuple.

setdefault(key[, default])

Insert key with a value of default if key is not in the dictionary.

to_dataframe()

Convert the results to a dataframe.

update([E, ]**F)

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values()

__init__(*args, **kwargs)
clear() None.  Remove all items from D.
copy() a shallow copy of D
fromkeys(value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

get_aggregate_feedback(quantiles: Optional[Sequence[float]] = None) pd.DataFrame[source]

Return quantiles for the feedback scores.

This method calculates and prints the quantiles for the feedback scores across all feedback keys.

Returns

A DataFrame containing the quantiles for each feedback key.

items() a set-like object providing a view on D's items
keys() a set-like object providing a view on D's keys
pop(k[, d]) v, remove specified key and return the corresponding value.

If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

to_dataframe() pd.DataFrame[source]

Convert the results to a dataframe.

update([E, ]**F) None.  Update D from dict/iterable E and F.

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() an object providing a view on D's values