| from typing import Dict |
|
|
| from .llm_as_judge_constants import ( |
| EVALUATORS_METADATA, |
| MODEL_RENAMINGS, |
| EvaluatorMetadata, |
| EvaluatorNameEnum, |
| ModelProviderEnum, |
| ) |
|
|
|
|
| def get_parsed_context(context: Dict[str, str]): |
| return ( |
| "\n".join([f"{key}: {value}" for key, value in context.items()]) |
| if len(context) > 1 |
| or not (len(context) == 1 and next(iter(context.keys())).lower() == "context") |
| else context[next(iter(context.keys()))] |
| ) |
|
|
|
|
| def get_evaluator_metadata( |
| name: EvaluatorNameEnum |
| ) -> EvaluatorMetadata: |
| evaluator_search = [ |
| e for e in EVALUATORS_METADATA if e.name == name |
| ] |
| if len(evaluator_search) == 0: |
| |
| raise ValueError(f"An evaluator with id {name} does not exist.") |
| if len(evaluator_search) > 1: |
| |
| raise ValueError(f"An evaluator with id {name} matched several models.") |
| return evaluator_search[0] |
|
|
|
|
| def rename_model_if_required(model_name: str, provider: ModelProviderEnum) -> str: |
| if provider in MODEL_RENAMINGS and model_name in MODEL_RENAMINGS[provider]: |
| return MODEL_RENAMINGS[provider][model_name] |
| return model_name |
|
|
|
|
| def rank_indexes(numbers): |
| |
| indices = list(range(len(numbers))) |
|
|
| |
| sorted_indices = sorted(indices, key=lambda x: -numbers[x]) |
|
|
| |
| rankings = [0] * len(numbers) |
|
|
| |
| current_rank = 0 |
| for i in range(len(sorted_indices)): |
| if i > 0 and numbers[sorted_indices[i]] != numbers[sorted_indices[i - 1]]: |
| current_rank = i |
| rankings[sorted_indices[i]] = current_rank |
|
|
| return rankings |
|
|