dict(**kwargs: Any) → Dict¶
Return dictionary representation of output parser.
classmethod from_llm(llm: BaseLanguageModel, parser: BaseOutputParser[T], prompt: BasePromptTemplate = PromptTemplate(input_variables=['completion', 'error', 'prompt'], template='Prompt:\n{prompt}\nCompletion:\n{completion}\n\nAbove, the Completion did not satisfy the constraints given in the Prompt.\nDetails: {error}\nPlease try again:')) → RetryWithErrorOutputParser[T][source]¶
Create a RetryWithErrorOutputParser from an LLM.
Parameters
llm – The LLM to use to retry the completion.
parser – The parser to use to parse the output.
prompt – The prompt to use to retry the completion.
Returns
A RetryWithErrorOutputParser.
classmethod from_orm(obj: Any) → Model¶
get_format_instructions() → str[source]¶
Instructions on how the LLM output should be formatted.
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
invoke(input: Union[str, BaseMessage], config: Optional[RunnableConfig] = None) → T¶
classmethod is_lc_serializable() → bool¶
Is this class serializable?