a ag6@sdZddlmZddlmZmZmZmZmZddl m Z m Z m Z ddl mZddlmZddlmZddlmZmZdd lmZed d d ZGd ddeeZGdddeZGdddeeZGdddeeZdS)z:String distance evaluators based on the RapidFuzz library.)Enum)AnyCallableDictListOptional)AsyncCallbackManagerForChainRunCallbackManagerForChainRun Callbacks)pre_init)Field)Chain)PairwiseStringEvaluatorStringEvaluator)RUN_KEYreturncCs.z ddl}Wnty&tdYn0|jS)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)rrw/var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/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 e e efe e efdddZeee d d d Ze e efe e efd d dZede e edddZeed ddZe e edddZdS)_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", ) rcCsdS)z8 This evaluator does not require input. Frr+rrrrequires_inputsz&StringDistanceEvalChain.requires_inputcCsdS)z> This evaluator does not require a reference. Trr+rrrrequires_referencesz*StringDistanceEvalChain.requires_referencecCsddgS)^ Get the input keys. Returns: List[str]: The input keys. reference predictionrr+rrr input_keyssz"StringDistanceEvalChain.input_keyscCs|jjdS)b Get the evaluation name. Returns: str: The evaluation name. _distancervaluer+rrrevaluation_namesz'StringDistanceEvalChain.evaluation_nameNinputs run_managerrcCsd||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*rCrDr8r,rLrMrrr_callszStringDistanceEvalChain._callcsd||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*rCrDrNrOrrr_acallszStringDistanceEvalChain._acallF)rCinput callbackstagsmetadatainclude_run_info) rDrCrRrSrTrUrVkwargsrc 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. rDrCrLrSrTrUrVr0 r,rDrCrRrSrTrUrVrWr.rrr_evaluate_stringssz)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. rXrYNZacallr0r[rrr_aevaluate_strings(s z*StringDistanceEvalChain._aevaluate_strings)N)N)rrrrr<r:r@rArr;rErJrrrr rPrrQr r/r\r^rrrrr?sn        ' r?c @seZdZdZeeedddZeedddZde ee fe e e ee fdd d Z de ee fe ee ee fdd d Zdddd deeee eee e ee fee edddZdddd deeee eee e ee fee edddZdS)PairwiseStringDistanceEvalChainz6Compute string edit distances between two predictions.rcCsddgS)rBrD prediction_brr+rrrrEOsz*PairwiseStringDistanceEvalChain.input_keyscCsd|jjdS)rFZ pairwise_rGrHr+rrrrJYsz/PairwiseStringDistanceEvalChain.evaluation_nameNrKcCsd||d|diS)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*rDr`rNrOrrrrPcsz%PairwiseStringDistanceEvalChain._callcsd||d|diS)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*rDr`rNrOrrrrQwsz&PairwiseStringDistanceEvalChain._acallF)rSrTrUrV)rDr`rSrTrUrVrWrc 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. rDr`rYrZ r,rDr`rSrTrUrVrWr.rrr_evaluate_string_pairssz6PairwiseStringDistanceEvalChain._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. rarYNr]rbrrr_aevaluate_string_pairss z7PairwiseStringDistanceEvalChain._aevaluate_string_pairs)N)N)rrrrr<rr;rErJrrrr rPrrQr r:r/rcrdrrrrr_LsZ        ' r_N)renumrtypingrrrrrZ langchain_core.callbacks.managerrr r Zlangchain_core.utilsr Zpydanticr Zlangchain.chains.baser Zlangchain.evaluation.schemarrZlangchain.schemarrr;rr$r?r_rrrrs     l&