import ast import os from typing import Dict from lm_eval import utils from lm_eval.utils import eval_logger # Prompt library. # Stores prompts in a dictionary indexed by 2 levels: # prompt category name, and prompt name. # This allows us to access prompts PROMPT_REGISTRY: Dict[str, Dict[str, str]] = { "qa-basic": { "question-newline-answer": "Question: {{question}}\nAnswer:", "q-newline-a": "Q: {{question}}\nA:", }, } def get_prompt(prompt_id: str, dataset_name: str = None, subset_name: str = None): # unpack prompt name category_name, prompt_name = prompt_id.split(":") if subset_name is None: dataset_full_name = dataset_name else: dataset_full_name = f"{dataset_name}-{subset_name}" eval_logger.info(f"Loading prompt from {category_name} for {dataset_full_name}") if category_name == "promptsource": try: from promptsource.templates import DatasetTemplates except ModuleNotFoundError: raise Exception( "Tried to load a Promptsource template, but promptsource is not installed ", "please install promptsource via pip install lm-eval[promptsource] or pip install -e .[promptsource]", ) try: if subset_name is None: prompts = DatasetTemplates(dataset_name=dataset_name) else: prompts = DatasetTemplates( dataset_name=dataset_name, subset_name=subset_name ) except Exception: raise ValueError(f"{dataset_name} and {subset_name} not found") if prompt_name in prompts.all_template_names: return prompts[prompt_name] else: raise ValueError( f"{prompt_name} not in prompt list {prompts.all_template_names}" ) elif ".yaml" in category_name: import yaml with open(category_name, "rb") as file: prompt_yaml_file = yaml.full_load(file) prompt_string = prompt_yaml_file["prompts"][prompt_name] return PromptString(prompt_string) else: try: return PROMPT_REGISTRY[category_name][prompt_name] except Exception: raise ValueError( f"expected only a single `:` as separator between \ prompt category and name, but got `{prompt_id}` instead" ) def load_prompt_list( use_prompt: str, dataset_name=None, subset_name=None, yaml_path=None, **kwargs ): category_name, prompt_name = use_prompt.split(":") if category_name == "promptsource": from promptsource.templates import DatasetTemplates if subset_name is None: prompts = DatasetTemplates(dataset_name=dataset_name) else: prompts = DatasetTemplates( dataset_name=dataset_name, subset_name=subset_name ) prompt_list = utils.pattern_match(prompt_name, prompts.all_template_names) elif ".yaml" in category_name: import yaml if yaml_path is not None: category_name = os.path.realpath(os.path.join(yaml_path, category_name)) with open(category_name, "rb") as file: prompt_yaml_file = yaml.full_load(file) prompt_list = utils.pattern_match( prompt_name, prompt_yaml_file["prompts"].keys() ) # category_name, *prompt_name = use_prompt.split(":") # TODO allow to multiple prompt naming # if len(prompt_name) > 1: # prompt_list = [] # for prompt in prompt_name: # prompt_list.append(utils.pattern_match(prompt_name, prompts.all_template_names)) # else: # prompt_list = utils.pattern_match(prompt_name, prompts.all_template_names) return [":".join([category_name, prompt]) for prompt in prompt_list] class PromptString: def __init__(self, prompt_string): self.prompt_string = prompt_string def apply(self, doc): doc_to_text = self.prompt_string["doc_to_text"] doc_to_target = self.prompt_string["doc_to_target"] # TODO need a way to process doc_to_choice if "doc_to_choice" in self.prompt_string: raise Exception("Not yet implemented to accept doc_to_choice") text_string = utils.apply_template(doc_to_text, doc) target_string = utils.apply_template(doc_to_target, doc) return [text_string, target_string]