Source code for langchain_community.output_parsers.rail_parser

from __future__ import annotations

from typing import Any, Callable, Dict, Optional

from langchain_core.output_parsers import BaseOutputParser


[docs]class GuardrailsOutputParser(BaseOutputParser): """Parse the output of an LLM call using Guardrails.""" guard: Any """The Guardrails object.""" api: Optional[Callable] """The LLM API passed to Guardrails during parsing. An example is `openai.completions.create`.""" # noqa: E501 args: Any """Positional arguments to pass to the above LLM API callable.""" kwargs: Any """Keyword arguments to pass to the above LLM API callable.""" @property def _type(self) -> str: return "guardrails"
[docs] @classmethod def from_rail( cls, rail_file: str, num_reasks: int = 1, api: Optional[Callable] = None, *args: Any, **kwargs: Any, ) -> GuardrailsOutputParser: """Create a GuardrailsOutputParser from a rail file. Args: rail_file: a rail file. num_reasks: number of times to re-ask the question. api: the API to use for the Guardrails object. *args: The arguments to pass to the API **kwargs: The keyword arguments to pass to the API. Returns: GuardrailsOutputParser """ try: from guardrails import Guard except ImportError: raise ImportError( "guardrails-ai package not installed. " "Install it by running `pip install guardrails-ai`." ) return cls( guard=Guard.from_rail(rail_file, num_reasks=num_reasks), api=api, args=args, kwargs=kwargs, )
[docs] @classmethod def from_rail_string( cls, rail_str: str, num_reasks: int = 1, api: Optional[Callable] = None, *args: Any, **kwargs: Any, ) -> GuardrailsOutputParser: try: from guardrails import Guard except ImportError: raise ImportError( "guardrails-ai package not installed. " "Install it by running `pip install guardrails-ai`." ) return cls( guard=Guard.from_rail_string(rail_str, num_reasks=num_reasks), api=api, args=args, kwargs=kwargs, )
[docs] @classmethod def from_pydantic( cls, output_class: Any, num_reasks: int = 1, api: Optional[Callable] = None, *args: Any, **kwargs: Any, ) -> GuardrailsOutputParser: try: from guardrails import Guard except ImportError: raise ImportError( "guardrails-ai package not installed. " "Install it by running `pip install guardrails-ai`." ) return cls( guard=Guard.from_pydantic(output_class, "", num_reasks=num_reasks), api=api, args=args, kwargs=kwargs, )
[docs] def get_format_instructions(self) -> str: return self.guard.raw_prompt.format_instructions
[docs] def parse(self, text: str) -> Dict: return self.guard.parse(text, llm_api=self.api, *self.args, **self.kwargs)