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from functools import lru_cache
from pathlib import Path
from typing import Any
import yaml
from configs.config_models import StepModelsConfigs
@lru_cache
def load_config(config_path: Path, _format: str = "dict") -> dict[str, Any] | str:
"""
Load configuration from a YAML file into a dictionary.
Parameters
----------
config_path : Path
Path to the YAML configuration file.
_format : str, optional
The format in which to return the configuration, by default "dict".
Returns
-------
dict[str, Any] | str
A dictionary containing the configuration parameters if _format="dict",
otherwise the raw YAML content as a string.
"""
with open(config_path, "r") as file:
content = file.read()
if _format == "dict":
return yaml.safe_load(content)
else:
return content
def load_module_config(config_path, config_model=None):
"""
Load a YAML configuration file and validate against a Pydantic model.
"""
config_data = load_config(config_path)
if config_model:
return config_model(**config_data)
return config_data
PROMPT_LIBRARY = load_config(Path(__file__).parent / "prompt_library.yaml")
APP_STEPS_CONFIGS = load_module_config(
Path(__file__).parent / "config.yaml", StepModelsConfigs
)
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