langchain.output_parsers.fix.OutputFixingParser

class langchain.output_parsers.fix.OutputFixingParser(*, parser: BaseOutputParser[T], retry_chain: LLMChain)

Bases: BaseOutputParser[T]

Wraps a parser and tries to fix parsing errors.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

param parser: langchain.schema.output_parser.BaseOutputParser[langchain.output_parsers.fix.T] [Required]

param retry_chain: langchain.chains.llm.LLMChain [Required]

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', 'instructions'], output_parser=None, partial_variables={}, template='Instructions:\n--------------\n{instructions}\n--------------\nCompletion:\n--------------\n{completion}\n--------------\n\nAbove, the Completion did not satisfy the constraints given in the Instructions.\nError:\n--------------\n{error}\n--------------\n\nPlease try again. Please only respond with an answer that satisfies the constraints laid out in the Instructions:', template_format='f-string', validate_template=True)) → OutputFixingParser[T]

Create an OutputFixingParser from a language model and a parser.

Parameters

• llm – llm to use for fixing

• parser – parser to use for parsing

• prompt – prompt to use for fixing

Returns

OutputFixingParser

get_format_instructions() → str

Instructions on how the LLM output should be formatted.

invoke(input: str | langchain.schema.messages.BaseMessage, config: langchain.schema.runnable.RunnableConfig | None = None) → T

parse(completion: str) → T

Parse a single string model output into some structure.

Parameters

text – String output of a language model.

Returns

Structured output.

parse_result(result: List[Generation]) → T

Parse a list of candidate model Generations into a specific format.

The return value is parsed from only the first Generation in the result, which

is assumed to be the highest-likelihood Generation.

Parameters

result – A list of Generations to be parsed. The Generations are assumed to be different candidate outputs for a single model input.

Returns

Structured output.

parse_with_prompt(completion: str, prompt: PromptValue) → Any

Parse the output of an LLM call with the input prompt for context.

The prompt is largely provided in the event the OutputParser wants to retry or fix the output in some way, and needs information from the prompt to do so.

Parameters

• completion – String output of a language model.

• prompt – Input PromptValue.

Returns

Structured output

to_json() → Union[SerializedConstructor, SerializedNotImplemented]

to_json_not_implemented() → SerializedNotImplemented

property lc_attributes: Dict

Return a list of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor.

property lc_namespace: List[str]

Return the namespace of the langchain object. eg. [“langchain”, “llms”, “openai”]

property lc_secrets: Dict[str, str]

Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_KEY”}

property lc_serializable: bool

Return whether or not the class is serializable.

model Config

Bases: object

extra = 'ignore'

Examples using OutputFixingParser

• Retry parser