=Ki.SrSSKJrJrJrJrJr SSKJr SSK J r SSK J r J r Jr SSKJrJr "SS\5r"S S \5rS \\\4S \4S jr"SS\5rg)zIContains the `LLMEvaluator` class for building LLM-as-a-judge evaluators.)AnyCallableOptionalUnioncast) BaseModel) warn_beta)EvaluationResultEvaluationResults RunEvaluator)ExampleRunc`\rSrSr%Sr\\S'\\\S'\\S'Sr\ \S'Sr \ \\S 'S r g) CategoricalScoreConfig z&Configuration for a categorical score.keychoices descriptionFinclude_explanationNexplanation_description) __name__ __module__ __qualname____firstlineno____doc__str__annotations__listrboolrr__static_attributes__rd/var/www/html/dynamic-report/venv/lib/python3.13/site-packages/langsmith/evaluation/llm_evaluator.pyrr s40 H #Y %%-1Xc]1r"rcl\rSrSr%Sr\\S'Sr\\S'Sr \\S'\\S'S r \ \S 'S r \ \\S 'S rg )ContinuousScoreConfigz%Configuration for a continuous score.rrminmaxrFrNrr)rrrrrrrr'floatr)rr rrr!rr"r#r%r%s</ HCNCN %%-1Xc]1r"r% score_configreturnc0n[U[5(a1SURSSRUR5S3S.US'OZ[U[5(a:SUR UR SUR S UR S 3S .US'O [S 5eUR(a!SURcS O URS.US'URURSUUR(aSS/S.$S/S.$)Nstringz%The score for the evaluation, one of z, .)typeenumrscorenumberz&The score for the evaluation, between z and z , inclusive.)r0minimummaximumrz9Invalid score type. Must be 'categorical' or 'continuous'zThe explanation for the score.)r0r explanationobject)titlerr0 propertiesrequired) isinstancerrjoinr%r'r) ValueErrorrrrr)r+r9s r#_create_score_json_schemar>!s,"$J, 677 ((Byy--./q2 7 L"7 8 8#''#''C l&6&6%7|E  7TUU'' 77?1!99 % =!!!#// (4(H(HWm $   PWi  r"c\rSrSrSrSSSS.S\\\\\\44S\\ \ 4S \ \ \ \ \/\4S \S \4 S jjr\SS .S\S\\\\\\44S\\ \ 4S \ \ \ \ \/\44Sjj5rS\\\\\\44S\\ \ 4S \ \ \ \ \/\4S\4Sjr\SS\ S\ \S\\\44Sjj5r\SS\ S\ \S\\\44Sjj5rS\ S\ \S\4SjrS\S\\\44SjrSrg) LLMEvaluatorLzA class for building LLM-as-a-judge evaluators. .. deprecated:: 0.5.0 LLMEvaluator is deprecated. Use openevals instead: https://github.com/langchain-ai/openevals Nzgpt-4oopenai) map_variables model_namemodel_providerprompt_templater+rCrDrEc SSKJn U"SXES.UD6n URXX95 g![an[S5UeSnAff=f)a5Initialize the `LLMEvaluator`. Args: prompt_template (Union[str, List[Tuple[str, str]]): The prompt template to use for the evaluation. If a string is provided, it is assumed to be a human / user message. score_config (Union[CategoricalScoreConfig, ContinuousScoreConfig]): The configuration for the score, either categorical or continuous. map_variables (Optional[Callable[[Run, Example], dict]], optional): A function that maps the run and example to the variables in the prompt. If `None`, it is assumed that the prompt only requires 'input', 'output', and 'expected'. model_name (Optional[str], optional): The model to use for the evaluation. model_provider (Optional[str], optional): The model provider to use for the evaluation. r)init_chat_modelzmLLMEvaluator requires langchain to be installed. Please install langchain by running `pip install langchain`.N)modelrEr)langchain.chat_modelsrH ImportError _initialize) selfrFr+rCrDrEkwargsrHe chat_models r#__init__LLMEvaluator.__init__Tsd8  %  ?E   R O  s% A ;A)rCrIcLURU5nURX#XA5 U$)a*Create an `LLMEvaluator` instance from a `BaseChatModel` instance. Args: model (BaseChatModel): The chat model instance to use for the evaluation. prompt_template (Union[str, List[Tuple[str, str]]): The prompt template to use for the evaluation. If a string is provided, it is assumed to be a system message. score_config (Union[CategoricalScoreConfig, ContinuousScoreConfig]): The configuration for the score, either categorical or continuous. map_variables (Optional[Callable[[Run, Example]], dict]], optional): A function that maps the run and example to the variables in the prompt. If `None`, it is assumed that the prompt only requires 'input', 'output', and 'expected'. Returns: LLMEvaluator: An instance of `LLMEvaluator`. )__new__rL)clsrIrFr+rCinstances r# from_modelLLMEvaluator.from_models'8;;s#_MQr"rPc\SSKJn SSKJn [ XE5(a[ US5(d [S5e[ U[5(aURSU4/5Ul OURU5Ul [URR51S k- (aU(d [S 5eX0l X l[UR5UlUR#UR 5nURU-Ulg![an[ S5UeSnAff=f) aShared initialization code for `__init__` and `from_model`. Args: prompt_template (Union[str, List[Tuple[str, str]]): The prompt template. score_config (Union[CategoricalScoreConfig, ContinuousScoreConfig]): The score configuration. map_variables (Optional[Callable[[Run, Example]], dict]]): Function to map variables. chat_model (BaseChatModel): The chat model instance. r) BaseChatModel)ChatPromptTemplatez|LLMEvaluator requires langchain-core to be installed. Please install langchain-core by running `pip install langchain-core`.Nwith_structured_outputzRchat_model must be an instance of BaseLanguageModel and support structured output.human>inputoutputexpectedzrmap_inputs must be provided if the prompt template contains variables other than 'input', 'output', and 'expected')*langchain_core.language_models.chat_modelsrZlangchain_core.promptsr[rKr;hasattrr=r from_messagespromptsetinput_variablesrCr+r> score_schemar\runnable)rMrFr+rCrPrZr[rOs r#rLLLMEvaluator._initializes"  P A z 1 1 $<==C  os + +,::Wo41sDsCx$99:4124IIJ41 #x/@)A4)G HI 41  41l59**!)'!2* !22 3**59**!)'!2* !22 3**7c7HW4E7$7r D U3CEV3V-W r"r@N)rtypingrrrrrpydanticr#langsmith._internal._beta_decoratorr langsmith.evaluationr r r langsmith.schemasr rrr%ror>r@rr"r#rseO779RR*2Y22I2(.0EEF( (Vb<br"