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from __future__ import annotations
from typing import Any, Callable, Dict, Optional
from langchain_core.output_parsers import BaseOutputParser
class GuardrailsOutputParser(BaseOutputParser):
"""Parse the output of an LLM call using Guardrails."""
guard: Any
"""The Guardrails object."""
api: Optional[Callable]
"""The API to use for the Guardrails object."""
args: Any
"""The arguments to pass to the API."""
kwargs: Any
"""The keyword arguments to pass to the API."""
@property
def _type(self) -> str:
return "guardrails"
@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,
)
@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,
)
@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,
)
def get_format_instructions(self) -> str:
return self.guard.raw_prompt.format_instructions
def parse(self, text: str) -> Dict:
return self.guard.parse(text, llm_api=self.api, *self.args, **self.kwargs)
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