Initialize from LLM.
pydantic model langchain.chains.OpenAIModerationChain[source]#
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
from langchain.chains import OpenAIModerationChain
moderation = OpenAIModerationChain()
Validators
raise_deprecation » all fields
set_verbose » verbose
validate_environment » all fields
field error: bool = False#
Whether or not to error if bad content was found.
field model_name: Optional[str] = None#
Moderation model name to use.
field openai_api_key: Optional[str] = None#
field openai_organization: Optional[str] = None#
pydantic model langchain.chains.OpenAPIEndpointChain[source]#
Chain interacts with an OpenAPI endpoint using natural language.
Validators
raise_deprecation » all fields
set_verbose » verbose
field api_operation: APIOperation [Required]#
field api_request_chain: LLMChain [Required]#
field api_response_chain: Optional[LLMChain] = None#
field param_mapping: _ParamMapping [Required]#
field requests: Requests [Optional]#
field return_intermediate_steps: bool = False#
deserialize_json_input(serialized_args: str) → dict[source]#
Use the serialized typescript dictionary.
Resolve the path, query params dict, and optional requestBody dict.
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/chains.html