AhL7SrSSKJr SSKJrJrJr SSKJr SSK J r J r SSK J r SSKJr SSKJr SS KJr SS KJrJr SS KJr S \4S jr"SS\\5r"SS\5r"SS\\5r"SS\\5rg)z:String distance evaluators based on the RapidFuzz library.)Enum)AnyCallableOptional) Callbacks)AsyncCallbackManagerForChainRunCallbackManagerForChainRun)pre_init)Field)override)Chain)PairwiseStringEvaluatorStringEvaluator)RUN_KEYreturncdSSKnUR$![anSn[U5UeSnAff=f)z Load the RapidFuzz library. Raises: ImportError: If the rapidfuzz library is not installed. Returns: Any: The rapidfuzz.distance module. rNzyPlease install the rapidfuzz library to use the FuzzyMatchStringEvaluator.Please install it with `pip install rapidfuzz`.) rapidfuzz ImportErrordistance)remsgs a/var/www/html/shao/venv/lib/python3.13/site-packages/langchain/evaluation/string_distance/base.py_load_rapidfuzzrsC&    & > #A% &s /*/c0\rSrSrSrSrSrSrSrSr Sr S r g ) StringDistance)aDistance metric to use. Attributes: DAMERAU_LEVENSHTEIN: The Damerau-Levenshtein distance. LEVENSHTEIN: The Levenshtein distance. JARO: The Jaro distance. JARO_WINKLER: The Jaro-Winkler distance. HAMMING: The Hamming distance. INDEL: The Indel distance. damerau_levenshtein levenshteinjaro jaro_winklerhammingindelN) __name__ __module__ __qualname____firstlineno____doc__DAMERAU_LEVENSHTEIN LEVENSHTEINJARO JARO_WINKLERHAMMINGINDEL__static_attributes__r#rrr)s( 0K D!LG Er0rc&\rSrSr%Sr\"\RS9r\\ S'\"SS9r \ \ S'\ S\ \\4S\ \\44S j5r\S\\4S j5rS \ \\4S\ \\44S jr\S S.S\S\ S\4Sjj5r\S\4Sj5rS\S\S\4SjrSrg)_RapidFuzzChainMixin=zrAs r_prepare_output$_RapidFuzzChainMixin._prepare_output]s56'?+ f $Wo224F7O r0Fr5c SSKJn [RUR[R UR [RUR[RUR[RUR[RUR0nX;a SUS[[53n[!U5eX0nU(a UR"$UR$)z Get the distance metric function based on the distance type. Args: distance (str): The distance type. Returns: Callable: The distance metric function. Raises: ValueError: If the distance metric is invalid. r)rzInvalid distance metric: z Must be one of: )rrrr)DamerauLevenshteinr* Levenshteinr+Jaror, JaroWinklerr-Hammingr.Indellist ValueErrornormalized_distance)rr5 rf_distance module_maprmodules r _get_metric _RapidFuzzChainMixin._get_metricls 6  . . 0N0N  & & (?(?   !1!1  ' ')@)@  " "K$7$7  +"3"3 &   %+H:$T.%9$:< S/ !% -- -r0cR[RURURS9$)zY Get the distance metric function. Returns: Callable: The distance metric function. rF)r2rTrr5r=s rmetric_RapidFuzzChainMixin.metrics,$// MM 000  r0abc$URX5$)z Compute the distance between two strings. Args: a (str): The first string. b (str): The second string. Returns: float: The distance between the two strings. )rW)r>rYrZs rcompute_metric#_RapidFuzzChainMixin.compute_metrics{{1  r0r#N)r$r%r&r'r(r rr,r__annotations__r5boolr rCstrrr9propertyrNr?rD staticmethodrrTrWfloatr\r/r#r0rr2r2=sF$^-H-HIHnI!$/OT/J 4S> d38n  T#Y d38n c3h >C c t   D       ! ! ! !r0r2c\rSrSrSr\S\4Sj5r\S\4Sj5r\S\ \ 4Sj5r \S\ 4Sj5r SS \ \ \4S \\S\ \ \44S jjrSS \ \ \4S \\S\ \ \44S jjr\SSSSSS S.S\ S\\ S\\ S\S\\ \ S\\ \ \4S\S\S\ 4Sjj5r\SSSSSS S.S\ S\\ S\\ S\S\\ \ S\\ \ \4S\S\S\ 4Sjj5rSrg)StringDistanceEvalChaina+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", ) rcg)z( This evaluator does not require input. Fr#r=s rrequires_input&StringDistanceEvalChain.requires_inputs r0cg)z. This evaluator does not require a reference. Tr#r=s rrequires_reference*StringDistanceEvalChain.requires_references r0c SS/$)> Get the input keys. Returns: List[str]: The input keys. reference predictionr#r=s r input_keys"StringDistanceEvalChain.input_keyss\**r0c4URRS3$)B Get the evaluation name. Returns: str: The evaluation name. _distancervaluer=s revaluation_name'StringDistanceEvalChain.evaluation_names--%%&i00r0Ninputs run_managerc6SURUSUS50$)a Compute the string distance between the prediction and the reference. Args: inputs (Dict[str, Any]): The input values. run_manager (Optional[CallbackManagerForChainRun]): The callback manager. Returns: Dict[str, Any]: The evaluation results containing the score. r<rorpr\r>rzr{s r_callStringDistanceEvalChain._calls& ,,VK-@&BVWXXr0c># SURUSUS50$7f)a5 Asynchronously compute the string distance between the prediction and the reference. Args: inputs (Dict[str, Any]): The input values. run_manager (Optional[AsyncCallbackManagerForChainRun]: The callback manager. Returns: Dict[str, Any]: The evaluation results containing the score. r<rorpr}r~s r_acallStringDistanceEvalChain._acalls)",,VK-@&BVWXXF)roinput callbackstagsmetadatainclude_run_inforprorrrrrkwargsc <U"XS.UUUUS9n URU 5$)a Evaluate the string distance between the prediction and the reference. Args: prediction (str): The prediction string. reference (Optional[str], optional): The reference string. input (Optional[str], optional): The input string. callbacks (Callbacks, optional): The callbacks to use. kwargs: Additional keyword arguments. Returns: dict: The evaluation results containing the score. rprorzrrrrrD r>rprorrrrrrrAs r_evaluate_strings)StringDistanceEvalChain._evaluate_stringss34",E-  ##F++r0cj# URXS.UUUUS9IShvN n URU 5$N7f)a Asynchronously evaluate the string distance between the prediction and the reference. Args: prediction (str): The prediction string. reference (Optional[str], optional): The reference string. input (Optional[str], optional): The input string. callbacks (Callbacks, optional): The callbacks to use. kwargs: Additional keyword arguments. Returns: dict: The evaluation results containing the score. rrNacallrDrs r_aevaluate_strings*StringDistanceEvalChain._aevaluate_strings,sI6zz",E- "  ##F++ 313r#N)r$r%r&r'r(rar_rhrkrNr`rqrxrCrrr rrrr rrrr/r#r0rreres;, D +DI++111=AYS#XY89Y c3h Y*BFYS#XY=>Y c3h Y& $(##$(-1!&!,!,C= !, } !,  !,tCy!!,4S>*!,!,!, !,!,F $(##$(-1!&!,!,C= !, } !,  !,tCy!!,4S>*!,!,!, !,!,r0recb\rSrSrSr\S\\4Sj5r\S\4Sj5r SS\ \\ 4S\ \ S\ \\ 44S jjrSS\ \\ 4S\ \S\ \\ 44S jjrSSSS S .S \S\S\S\ \\S\ \ \\ 4S\S\ S\ 4SjjrSSSS S .S \S\S\S\ \\S\ \ \\ 4S\S\ S\ 4SjjrSrg)PairwiseStringDistanceEvalChainiQz6Compute string edit distances between two predictions.rc SS/$)rnrp prediction_br#r=s rrq*PairwiseStringDistanceEvalChain.input_keysTsn--r0c6SURRS3$)rt pairwise_rurvr=s rrx/PairwiseStringDistanceEvalChain.evaluation_name^s4==../y99r0Nrzr{c6SURUSUS50$)a Compute the string distance between two predictions. Args: inputs (Dict[str, Any]): The input values. run_manager (CallbackManagerForChainRun , optional): The callback manager. Returns: Dict[str, Any]: The evaluation results containing the score. r<rprr}r~s rr%PairwiseStringDistanceEvalChain._callhs*" T(( )=vn?UV  r0c># SURUSUS50$7f)a" Asynchronously compute the string distance between two predictions. Args: inputs (Dict[str, Any]): The input values. run_manager (AsyncCallbackManagerForChainRun , optional): The callback manager. Returns: Dict[str, Any]: The evaluation results containing the score. r<rprr}r~s rr&PairwiseStringDistanceEvalChain._acall|s-" T(( )=vn?UV  rF)rrrrrprrrrrrc <U"XS.UUUUS9nURU5$)a Evaluate the string distance between two predictions. Args: prediction (str): The first prediction string. prediction_b (str): The second prediction string. callbacks (Callbacks, optional): The callbacks to use. tags (List[str], optional): Tags to apply to traces. metadata (Dict[str, Any], optional): Metadata to apply to traces. kwargs: Additional keyword arguments. Returns: dict: The evaluation results containing the score. rprrr r>rprrrrrrrAs r_evaluate_string_pairs6PairwiseStringDistanceEvalChain._evaluate_string_pairss32",K-  ##F++r0cj# URXS.UUUUS9IShvN nURU5$N7f)a Asynchronously evaluate the string distance between two predictions. Args: prediction (str): The first prediction string. prediction_b (str): The second prediction string. callbacks (Callbacks, optional): The callbacks to use. tags (List[str], optional): Tags to apply to traces. metadata (Dict[str, Any], optional): Metadata to apply to traces. kwargs: Additional keyword arguments. Returns: dict: The evaluation results containing the score. rrNrrs r_aevaluate_string_pairs7PairwiseStringDistanceEvalChain._aevaluate_string_pairssI2zz",K- "  ##F++ rr#r)r$r%r&r'r(rarNr`rqrxrCrrr rrrrr_rrr/r#r0rrrQs@ .DI..:::=A S#X 89  c3h  .BF S#X =>  c3h  2 $$(-1!& , , ,  , tCy! ,4S>* , , ,  ,N $$(-1!& , , ,  , tCy! ,4S>* , , ,  , ,r0rN)r(enumrtypingrrrlangchain_core.callbacksr langchain_core.callbacks.managerrr langchain_core.utilsr pydanticr typing_extensionsr langchain.chains.baser langchain.evaluation.schemarrlangchain.schemarrr`rr2rerr#r0rrsz@**.*&'P$*S$(j!5j!Zd,o/Cd,NA,&=?SA,r0