tjA5dZddlmZddlmZddlmZddlmZddl m Z m Z ddl m Z ddlmZdd lmZdd lmZdd lmZmZdd lmZd efdZGddeeZGddeZGddeeZGddeeZdS)z:String distance evaluators based on the RapidFuzz library.)Callable)Enum)Any) Callbacks)AsyncCallbackManagerForChainRunCallbackManagerForChainRun)pre_init)Field)override)Chain)PairwiseStringEvaluatorStringEvaluator)RUN_KEYreturncd ddl}n$#t$r}d}t||d}~wwxYw|jS)zLoad the RapidFuzz library. Raises: ImportError: If the rapidfuzz library is not installed. Returns: The `rapidfuzz.distance` module. rNzyPlease install the rapidfuzz library to use the FuzzyMatchStringEvaluator.Please install it with `pip install rapidfuzz`.) rapidfuzz ImportErrordistance)remsgs o/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_classic/evaluation/string_distance/base.py_load_rapidfuzzrs\& &&& > #A% &  s (#(c*eZdZdZdZdZdZdZdZdZ dS) StringDistanceaCDistance 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____doc__DAMERAU_LEVENSHTEIN LEVENSHTEINJARO JARO_WINKLERHAMMINGINDELrrr)s9  0K D!LG EEEr,rcVeZdZUdZeejZeed<edZ e ed< e de e efde e effdZedee fd Zd e e efde e effd Zed d de de defdZedefdZde de defdZdS)_RapidFuzzChainMixinz)r.rLrr0r7s rmetricz_RapidFuzzChainMixin.metrics,$// M 00   r,abc.|||S)zCompute the distance between two strings. Args: a: The first string. b: The second string. Returns: The distance between the two strings. )rN)r8rOrPs rcompute_metricz#_RapidFuzzChainMixin.compute_metrics{{1a   r,N)r!r"r#r$r rr(r__annotations__r0boolr r<strrr4propertyrFr9r= staticmethodrrLrNfloatrRr+r,rr.r.=sFF$u^-HIIIHnIII!E$///OT///J 4S> d38n   X T#YX d38n c3h    >C   c t    \ D      X   ! ! ! ! ! ! ! ! !r,r.c*eZdZdZedefdZedefdZedee fdZ ede fdZ e dde e efd edzde e effd Ze dde e efd edzde e effd Ze dddddd d de de dzde dzdedee dzde e efdzdedede fdZe dddddd d de de dzde dzdedee dzde e efdzdedede fdZdS)StringDistanceEvalChaina{Compute string distances between the prediction and the reference. Examples: ---------- >>> from langchain_classic.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_classic.evaluation import load_evaluator >>> evaluator = load_evaluator("string_distance") >>> evaluator.evaluate_strings( prediction="The answer is three", reference="three", ) rcdS)z&This evaluator does not require input.Fr+r7s rrequires_inputz&StringDistanceEvalChain.requires_inputs ur,cdS)z,This evaluator does not require a reference.Tr+r7s rrequires_referencez*StringDistanceEvalChain.requires_references tr,c ddgS)JGet the input keys. Returns: The input keys. reference predictionr+r7s r input_keysz"StringDistanceEvalChain.input_keyss\**r,c |jjdS)TGet the evaluation name. Returns: The evaluation name. _distancervaluer7s revaluation_namez'StringDistanceEvalChain.evaluation_names-%0000r,Ninputs run_managercJd||d|diSzCompute the string distance between the prediction and the reference. Args: inputs: The input values. run_manager: The callback manager. Returns: The evaluation results containing the score. r6rarbrRr8rjrks r_callzStringDistanceEvalChain._calls),,VK-@&BVWWXXr,cNKd||d|diSrmrnros r_acallzStringDistanceEvalChain._acalls-,,VK-@&BVWWXXr,F)rainput callbackstagsmetadatainclude_run_inforbrarsrtrurvrwkwargsc R|||d||||} || S)a$Evaluate the string distance between the prediction and the reference. Args: prediction: The prediction string. reference: The reference string. input: The input string. callbacks: The callbacks to use. tags: The tags to apply. metadata: The metadata to use. include_run_info: Whether to include run info in the output. **kwargs: Additional keyword arguments. Returns: The evaluation results containing the score. rbrarjrtrurvrwr= r8rbrarsrtrurvrwrxr:s r_evaluate_stringsz)StringDistanceEvalChain._evaluate_stringssG8",9EE-    ##F+++r,cvK|||d||||d{V} || S)a&Evaluate the string distance between the prediction and the reference. Args: prediction: The prediction string. reference: The reference string. input: The input string. callbacks: The callbacks to use. tags: The tags to apply. metadata: The metadata to apply. include_run_info: Whether to include run info in the output. **kwargs: Additional keyword arguments. Returns: The evaluation results containing the score. rzr{Nacallr=r}s r_aevaluate_stringsz*StringDistanceEvalChain._aevaluate_stringssk8zz",9EE- "        ##F+++r,N)r!r"r#r$rVrTr\r^rFrUrcrir r<rrrprrrrr~rr+r,rrZrZs*XDX+DI+++X+1111X1:>YYS#XY0$6Y c3h YYYXY ?CYYS#XY5t;Y c3h YYYXY  !% #!%*.!&#,#,#,#,: #, Tz #,  #,3i$#,sCx.4'#,#,#, #,#,#,X#,J !% #!%*.!&",",",",: ", Tz ",  ",3i$",sCx.4'",",", ",",",X",",",r,rZceZdZdZedeefdZedefdZe dde ee fde dzde ee ffdZ e dde ee fdedzde ee ffd Ze dddd d d ed ededeedzde ee fdzdede de fdZe dddd d d ed ededeedzde ee fdzdede de fdZdS)PairwiseStringDistanceEvalChainz6Compute string edit distances between two predictions.rc ddgS)r`rb prediction_br+r7s rrcz*PairwiseStringDistanceEvalChain.input_keysHsn--r,c"d|jjdS)re pairwise_rfrgr7s rriz/PairwiseStringDistanceEvalChain.evaluation_nameQs:4=.9999r,NrjrkcJd||d|diS)zCompute the string distance between two predictions. Args: inputs: The input values. run_manager: The callback manager. Returns: The evaluation results containing the score. r6rbrrnros rrpz%PairwiseStringDistanceEvalChain._callZs- T(( )=vn?UVV  r,cNKd||d|diS)zAsynchronously compute the string distance between two predictions. Args: inputs: The input values. run_manager: The callback manager. Returns: The evaluation results containing the score. r6rbrrnros rrrz&PairwiseStringDistanceEvalChain._acallms1 T(( )=vn?UVV  r,F)rtrurvrwrbrrtrurvrwrxc R|||d||||}||S)aEvaluate the string distance between two predictions. Args: prediction: The first prediction string. prediction_b: The second prediction string. callbacks: The callbacks to use. tags: The tags to apply. metadata: The metadata to use. include_run_info: Whether to include run info in the output. **kwargs: Additional keyword arguments. Returns: The evaluation results containing the score. rbrr{r| r8rbrrtrurvrwrxr:s r_evaluate_string_pairsz6PairwiseStringDistanceEvalChain._evaluate_string_pairssG4",lKK-    ##F+++r,cvK|||d||||d{V}||S)aAsynchronously evaluate the string distance between two predictions. Args: prediction: The first prediction string. prediction_b: The second prediction string. callbacks: The callbacks to use. tags: The tags to apply. metadata: The metadata to use. include_run_info: Whether to include run info in the output. **kwargs: Additional keyword arguments. Returns: The evaluation results containing the score. rr{Nrrs r_aevaluate_string_pairsz7PairwiseStringDistanceEvalChain._aevaluate_string_pairssk4zz",lKK- "        ##F+++r,r)r!r"r#r$rVrFrUrcrir r<rrrprrrrrTrrr+r,rrrEs^@@ .DI...X.::::X::>  S#X 0$6  c3h    X $?C  S#X 5t;  c3h    X $ $!%*.!& , , , , ,  , 3i$ ,sCx.4' , , ,  , , ,X ,D $!%*.!& , , , , ,  , 3i$ ,sCx.4' , , ,  , , ,X , , ,r,rN)r$collections.abcrenumrtypingrlangchain_core.callbacksr langchain_core.callbacks.managerrrlangchain_core.utilsr pydanticr typing_extensionsr langchain_classic.chains.baser #langchain_classic.evaluation.schemar rlangchain_classic.schemarrrUrr.rZrr+r,rrs@@$$$$$$......*)))))&&&&&&//////XXXXXXXX,,,,,,(S$(e!e!e!e!e!5e!e!e!P],],],],],o/C],],],@,,,,,&=?S,,,,,r,