Source code for sagemaker.train.evaluate.constants

"""Constants for SageMaker Evaluation Module.

This module contains shared constants used across the evaluation module.
"""

import uuid
from typing import Optional

from enum import Enum




class EvalType(Enum):
    """Enumeration of supported evaluation types."""

    BENCHMARK = "benchmark"
    CUSTOM_SCORER = "customscorer"
    LLM_AS_JUDGE = "llmasjudge"



# Pipeline naming convention
_PIPELINE_NAME_PREFIX = "SagemakerEvaluation"


def _get_eval_type_display_name(eval_type: EvalType) -> str:
    """Map eval type to display name for pipeline naming.
    
    Args:
        eval_type (EvalType): The evaluation type.
        
    Returns:
        str: The display name for the evaluation type.
            - BENCHMARK → "BenchmarkEvaluation"
            - CUSTOM_SCORER → "CustomScorerEvaluation"
            - LLM_AS_JUDGE → "LLMAJEvaluation"
    """
    mapping = {
        EvalType.BENCHMARK: "BenchmarkEvaluation",
        EvalType.CUSTOM_SCORER: "CustomScorerEvaluation",
        EvalType.LLM_AS_JUDGE: "LLMAJEvaluation"
    }
    return mapping[eval_type]


def _get_pipeline_name(eval_type: EvalType, unique_id: Optional[str] = None) -> str:
    """Generate pipeline name with pattern: SagemakerEvaluation-[evaluationType]-[uuid]
    
    The generated name follows the pattern: [a-zA-Z0-9](-*[a-zA-Z0-9]){0,255}
    
    Args:
        eval_type (EvalType): The evaluation type.
        unique_id (Optional[str]): Optional UUID. If not provided, generates a new one.
        
    Returns:
        str: The pipeline name (e.g., 'SagemakerEvaluation-BenchmarkEvaluation-abc123').
    """
    eval_type_name = _get_eval_type_display_name(eval_type)
    if unique_id is None:
        unique_id = str(uuid.uuid4())
    return f"{_PIPELINE_NAME_PREFIX}-{eval_type_name}-{unique_id}"


def _get_pipeline_name_prefix(eval_type: EvalType) -> str:
    """Get pipeline name prefix for searching existing pipelines.
    
    Args:
        eval_type (EvalType): The evaluation type.
        
    Returns:
        str: The pipeline name prefix (e.g., 'SagemakerEvaluation-BenchmarkEvaluation').
    """
    eval_type_name = _get_eval_type_display_name(eval_type)
    return f"{_PIPELINE_NAME_PREFIX}-{eval_type_name}"


# Tag keys for pipeline execution classification
_TAG_EVAL_TYPE_PREFIX = "sagemaker-pysdk"
_TAG_EVALUATION = "sagemaker-pysdk-evaluation"
_TAG_SAGEMAKER_MODEL_EVALUATION = "SagemakerModelEvaluation"


def _get_eval_type_tag_key(eval_type: EvalType) -> str:
    """Get the tag key for a specific evaluation type.
    
    Args:
        eval_type (EvalType): The evaluation type.
        
    Returns:
        str: The tag key (e.g., 'sagemaker-pysdk-benchmark').
    """
    return f"{_TAG_EVAL_TYPE_PREFIX}-{eval_type.value}"