o `+ iL7@sdZddlmZddlmZmZmZddlmZddl m Z m Z ddl m Z ddlmZddlmZdd lmZdd lmZmZdd lmZd efd dZGdddeeZGdddeZGdddeeZGdddeeZdS)z:String distance evaluators based on the RapidFuzz library.)Enum)AnyCallableOptional) Callbacks)AsyncCallbackManagerForChainRunCallbackManagerForChainRun)pre_init)Field)override)Chain)PairwiseStringEvaluatorStringEvaluator)RUN_KEYreturnc Cs8zddl}W|jSty}zd}t||d}~ww)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)remsgru/home/app/PaddleOCR-VL-test/.venv_paddleocr/lib/python3.10/site-packages/langchain/evaluation/string_distance/base.py_load_rapidfuzzs  rc@s(eZdZdZdZdZdZdZdZdZ dS) StringDistancea7Distance 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. Zdamerau_levenshteinZ levenshteinZjaroZ jaro_winklerZhammingZindelN) __name__ __module__ __qualname____doc__DAMERAU_LEVENSHTEIN LEVENSHTEINJARO JARO_WINKLERHAMMINGINDELrrrrr)s rc@seZdZUdZeejdZeed<eddZ e ed< e de e efde e effdd Zedee fd d Zd e e efde e effd dZeddde de defddZedefddZde de defddZdS)_RapidFuzzChainMixinz>> 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", ) rcCdS)z8 This evaluator does not require input. Frr+rrrrequires_inputz&StringDistanceEvalChain.requires_inputcCrA)z> This evaluator does not require a reference. Trr+rrrrequires_referencerCz*StringDistanceEvalChain.requires_referencecCddgS)^ Get the input keys. Returns: List[str]: The input keys. reference predictionrr+rrr input_keysz"StringDistanceEvalChain.input_keyscCs|jjdS)b Get the evaluation name. Returns: str: The evaluation name. _distancervaluer+rrrevaluation_namesz'StringDistanceEvalChain.evaluation_nameNinputs run_managercCd||d|diS)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*rGrHr9r,rPrQrrr_callszStringDistanceEvalChain._callcd||d|diS)a} 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*rGrHrSrTrrr_acallszStringDistanceEvalChain._acallF)rGinput callbackstagsmetadatainclude_run_inforHrGrXrYrZr[r\kwargsc Ks"|||d||||d} || S)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. rHrGrPrYrZr[r\r0 r,rHrGrXrYrZr[r\r]r.rrr_evaluate_stringss z)StringDistanceEvalChain._evaluate_stringsc s,|j||d||||dIdH} || S)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. r^r_NZacallr0rarrr_aevaluate_strings,s z*StringDistanceEvalChain._aevaluate_stringsN)rrrrr=r;rBrDr2r<rIrOr/rrrrUrrWr rrbrdrrrrr@s            #    r@c@s(eZdZdZedeefddZedefddZ dde ee fd e e de ee ffd d Z dde ee fd e ede ee ffd d Zddddddededede eede e ee fdede de fddZddddddededede eede e ee fdede de fddZdS)PairwiseStringDistanceEvalChainz6Compute string edit distances between two predictions.rcCrE)rFrH prediction_brr+rrrrITrJz*PairwiseStringDistanceEvalChain.input_keyscCsd|jjdS)rKZ pairwise_rLrMr+rrrrO^sz/PairwiseStringDistanceEvalChain.evaluation_nameNrPrQcCrR)aN 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*rHrgrSrTrrrrUhsz%PairwiseStringDistanceEvalChain._callcrV)ab 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*rHrgrSrTrrrrW|sz&PairwiseStringDistanceEvalChain._acallF)rYrZr[r\rHrgrYrZr[r\r]c Ks"|||d||||d}||S)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. rHrgr_r` r,rHrgrYrZr[r\r]r.rrr_evaluate_string_pairss z6PairwiseStringDistanceEvalChain._evaluate_string_pairsc s,|j||d||||dIdH}||S)a3 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. rhr_Nrcrirrr_aevaluate_string_pairss z7PairwiseStringDistanceEvalChain._aevaluate_string_pairsre)rrrrr=r2r<rIrOr/rrrrUrrWrr;rjrkrrrrrfQs           '   rfN)renumrtypingrrrZlangchain_core.callbacksrZ langchain_core.callbacks.managerrrZlangchain_core.utilsr Zpydanticr Ztyping_extensionsr Zlangchain.chains.baser Zlangchain.evaluation.schemar rZlangchain.schemarrr<rr$r@rfrrrrs"       m(