j.dZddlmZmZmZmZmZddlmZddl m Z ddl m Z m Z mZddlmZmZGddeZGd d eZd eeefd efd ZGddeZy)zIContains the `LLMEvaluator` class for building LLM-as-a-judge evaluators.)AnyCallableOptionalUnioncast) BaseModel) warn_beta)EvaluationResultEvaluationResults RunEvaluator)ExampleRuncXeZdZUdZeed<eeed<eed<dZeed<dZ e eed<y) CategoricalScoreConfigz&Configuration for a categorical score.keychoices descriptionFinclude_explanationNexplanation_description) __name__ __module__ __qualname____doc__str__annotations__listrboolrrl/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langsmith/evaluation/llm_evaluator.pyrr s40 H #Y %%-1Xc]1rrcdeZdZUdZeed<dZeed<dZeed<eed<dZ e ed <d Z e eed <y ) ContinuousScoreConfigz%Configuration for a continuous score.rrminmaxrFrNr) rrrrrrr#floatr%rrrrrrr r"r"s</ HCNCN %%-1Xc]1rr" score_configreturnci}t|tr1d|jddj|jdd|d<nUt|tr:d|j |j d|j d |j d d |d<n td |jr d|jd n |jd|d<|j|jd||jrddgdSdgdS)Nstringz%The score for the evaluation, one of z, .)typeenumrscorenumberz&The score for the evaluation, between z and z , inclusive.)r,minimummaximumrz9Invalid score type. Must be 'categorical' or 'continuous'zThe explanation for the score.)r,r explanationobject)titlerr, propertiesrequired) isinstancerrjoinr"r#r% ValueErrorrrrr)r'r5s r _create_score_json_schemar:!s&"$J, 67 ((Byy--./q2 7 L"7 8#''#''C l&6&6%7|E  7TUU'' 77?1!99 % =!!!#// (4(H(HWm $   PWi  rceZdZdZdddddeeeeeeffdeee fde e e e e gefd ed ef d Zedd d edeeeeeeffdeee fde e e e e geffdZdeeeeeeffdeee fde e e e e gefdefdZe dde de e deeeffdZe dde de e deeeffdZde de e defdZdedeeeffdZy) LLMEvaluatorzA 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'r>r?r@c ddlm}|d||d|} |j|||| y#t$r}td|d}~wwxYw)aInitialize the `LLMEvaluator`. Args: prompt_template (Union[str, List[Tuple[str, str]]): The prompt template to use for the evaluation. If a string is provided, it is assumed to be a human / user message. score_config (Union[CategoricalScoreConfig, ContinuousScoreConfig]): The configuration for the score, either categorical or continuous. map_variables (Optional[Callable[[Run, Example], dict]], optional): A function that maps the run and example to the variables in the prompt. If `None`, it is assumed that the prompt only requires 'input', 'output', and 'expected'. model_name (Optional[str], optional): The model to use for the evaluation. model_provider (Optional[str], optional): The model provider to use for the evaluation. r)init_chat_modelzmLLMEvaluator requires langchain to be installed. Please install langchain by running `pip install langchain`.N)modelr@r)langchain.chat_modelsrC ImportError _initialize) selfrAr'r>r?r@kwargsrCe chat_models r __init__zLLMEvaluator.__init__Tsj8  % ^ ?E  , zR O  s( A =A)r>rDcP|j|}|j|||||S)aCreate an `LLMEvaluator` instance from a `BaseChatModel` instance. Args: model (BaseChatModel): The chat model instance to use for the evaluation. prompt_template (Union[str, List[Tuple[str, str]]): The prompt template to use for the evaluation. If a string is provided, it is assumed to be a system message. score_config (Union[CategoricalScoreConfig, ContinuousScoreConfig]): The configuration for the score, either categorical or continuous. map_variables (Optional[Callable[[Run, Example]], dict]], optional): A function that maps the run and example to the variables in the prompt. If `None`, it is assumed that the prompt only requires 'input', 'output', and 'expected'. Returns: LLMEvaluator: An instance of `LLMEvaluator`. )__new__rG)clsrDrAr'r>instances r from_modelzLLMEvaluator.from_models+8;;s#_lM5QrrKc. ddlm}ddlm}t ||r t |ds tdt |tr|jd|fg|_ n|j||_ t|jjhd z r |s td ||_ ||_t|j|_|j#|j }|j|z|_y#t$r}t d|d}~wwxYw) 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_modelsrSlangchain_core.promptsrTrFr7hasattrr9r from_messagespromptsetinput_variablesr>r'r: score_schemarUrunnable)rHrAr'r>rKrSrTrJs r rGzLLMEvaluator._initializes"  P A z= 1 $<=C  os +,::Wor^r`leninputsr9rvaluesoutputs)rHrcrdrks r rfzLLMEvaluator._prepare_variabless   %%c73 3 dkk11 13::!# (3::!# 0"&cjj&7&7&9!:1!=Ig  t{{22 2;; )3;;1$ )3;;1$ 8#'s{{'9'9';"41sDsCx$99:4124IIJ41 #x/@)A4)G HI 41  41l59**!)'!2* !22 3**59**!)'!2* !22 3**7c7HW4E7$7r D U3CEV3V-W rr<N)rtypingrrrrrpydanticr#langsmith._internal._beta_decoratorr langsmith.evaluationr r r langsmith.schemasr rrr"rgr:r<rrr rseO779RR*2Y22I2(.0EEF( (Vb<br