o i,@sdZddlmZddlmZmZddlmZmZddl m Z ddl m Z ddl mZd Ze d ed d Z e d ed d Z e ded d Z ed dGdddeeeefZdS)zThis module defines the EvaluatorContext. The EvaluatorContext is the context object that is passed to evaluators, containing all the information needed to evaluate a task execution, including inputs, outputs, metadata, telemetry data, and more. ) annotations) dataclassfield)AnyGeneric)TypeVar)SpanTreeRecordingError)SpanTree)EvaluatorContextInputsTT)default covariantOutputT MetadataT)kw_onlyc@seZdZUdZded< ded< ded< ded < d ed < d ed < eddZded< ded< ded< edddZdS)r a#Context for evaluating a task execution. An instance of this class is the sole input to all Evaluators. It contains all the information needed to evaluate the task execution, including inputs, outputs, metadata, and telemetry data. Evaluators use this context to access the task inputs, actual output, expected output, and other information when evaluating the result of the task execution. Example: ```python from dataclasses import dataclass from pydantic_evals.evaluators import Evaluator, EvaluatorContext @dataclass class ExactMatch(Evaluator): def evaluate(self, ctx: EvaluatorContext) -> bool: # Use the context to access task inputs, outputs, and expected outputs return ctx.output == ctx.expected_output ``` z str | Nonenamer inputszMetadataT | NonemetadatazOutputT | Noneexpected_outputroutputfloatdurationF)reprz!SpanTree | SpanTreeRecordingError _span_treezdict[str, Any] attributeszdict[str, int | float]metricsreturnr cCst|jtr |j|jS)aGet the `SpanTree` for this task execution. The span tree is a graph where each node corresponds to an OpenTelemetry span recorded during the task execution, including timing information and any custom spans created during execution. Returns: The span tree for the task execution. Raises: SpanTreeRecordingError: If spans were not captured during execution of the task, e.g. due to not having the necessary dependencies installed. ) isinstancerr )selfr g/var/www/html/karishye-ai-python/venv/lib/python3.10/site-packages/pydantic_evals/evaluators/context.py span_treeUs zEvaluatorContext.span_treeN)rr ) __name__ __module__ __qualname____doc____annotations__rrpropertyr"r r r r!r s, r N)r& __future__r dataclassesrrtypingrrtyping_extensionsr otel._errorsr otel.span_treer __all__r rrr r r r r!s