Source code for langchain.chains.moderation

"""Pass input through a moderation endpoint."""

from typing import Any, Dict, List, Optional

from langchain_core.callbacks import (
    AsyncCallbackManagerForChainRun,
    CallbackManagerForChainRun,
)
from langchain_core.utils import check_package_version, get_from_dict_or_env
from pydantic import Field, model_validator

from langchain.chains.base import Chain


[docs] class OpenAIModerationChain(Chain): """Pass input through a moderation endpoint. To use, you should have the ``openai`` python package installed, and the environment variable ``OPENAI_API_KEY`` set with your API key. Any parameters that are valid to be passed to the openai.create call can be passed in, even if not explicitly saved on this class. Example: .. code-block:: python from langchain.chains import OpenAIModerationChain moderation = OpenAIModerationChain() """ client: Any = None #: :meta private: async_client: Any = None #: :meta private: model_name: Optional[str] = None """Moderation model name to use.""" error: bool = False """Whether or not to error if bad content was found.""" input_key: str = "input" #: :meta private: output_key: str = "output" #: :meta private: openai_api_key: Optional[str] = None openai_organization: Optional[str] = None openai_pre_1_0: bool = Field(default=False) @model_validator(mode="before") @classmethod def validate_environment(cls, values: Dict) -> Any: """Validate that api key and python package exists in environment.""" openai_api_key = get_from_dict_or_env( values, "openai_api_key", "OPENAI_API_KEY" ) openai_organization = get_from_dict_or_env( values, "openai_organization", "OPENAI_ORGANIZATION", default="", ) try: import openai openai.api_key = openai_api_key if openai_organization: openai.organization = openai_organization values["openai_pre_1_0"] = False try: check_package_version("openai", gte_version="1.0") except ValueError: values["openai_pre_1_0"] = True if values["openai_pre_1_0"]: values["client"] = openai.Moderation else: values["client"] = openai.OpenAI() values["async_client"] = openai.AsyncOpenAI() except ImportError: raise ImportError( "Could not import openai python package. " "Please install it with `pip install openai`." ) return values @property def input_keys(self) -> List[str]: """Expect input key. :meta private: """ return [self.input_key] @property def output_keys(self) -> List[str]: """Return output key. :meta private: """ return [self.output_key] def _moderate(self, text: str, results: Any) -> str: if self.openai_pre_1_0: condition = results["flagged"] else: condition = results.flagged if condition: error_str = "Text was found that violates OpenAI's content policy." if self.error: raise ValueError(error_str) else: return error_str return text def _call( self, inputs: Dict[str, Any], run_manager: Optional[CallbackManagerForChainRun] = None, ) -> Dict[str, Any]: text = inputs[self.input_key] if self.openai_pre_1_0: results = self.client.create(text) output = self._moderate(text, results["results"][0]) else: results = self.client.moderations.create(input=text) output = self._moderate(text, results.results[0]) return {self.output_key: output} async def _acall( self, inputs: Dict[str, Any], run_manager: Optional[AsyncCallbackManagerForChainRun] = None, ) -> Dict[str, Any]: if self.openai_pre_1_0: return await super()._acall(inputs, run_manager=run_manager) text = inputs[self.input_key] results = await self.async_client.moderations.create(input=text) output = self._moderate(text, results.results[0]) return {self.output_key: output}