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    Pythonlangchain-coreoutput_parsersjsonJsonOutputParser
    Class●Since v0.1

    JsonOutputParser

    Parse the output of an LLM call to a JSON object.

    Probably the most reliable output parser for getting structured data that does not use function calling.

    When used in streaming mode, it will yield partial JSON objects containing all the keys that have been returned so far.

    In streaming, if diff is set to True, yields JSONPatch operations describing the difference between the previous and the current object.

    Copy
    JsonOutputParser(
        self,
        *args: Any = (),
        **kwargs: Any = {},
    )

    Bases

    BaseCumulativeTransformOutputParser[Any]

    Attributes

    attribute
    pydantic_object: Annotated[type[TBaseModel] | None, SkipValidation()]

    The Pydantic object to use for validation.

    If None, no validation is performed.

    Methods

    method
    parse_result

    Parse the result of an LLM call to a JSON object.

    method
    parse

    Parse the output of an LLM call to a JSON object.

    method
    get_format_instructions

    Return the format instructions for the JSON output.

    Inherited fromBaseCumulativeTransformOutputParser

    Attributes

    Adiff: bool
    —

    In streaming mode, whether to yield diffs between the previous and current parsed

    Inherited fromBaseTransformOutputParser

    Methods

    Mtransform
    —

    Transform the input into the output format.

    Matransform
    —

    Async transform the input into the output format.

    Inherited fromBaseOutputParser

    Attributes

    AInputType: Any
    —

    Return the input type for the parser.

    AOutputType: type[T]
    —

    Return the output type for the parser.

    Methods

    MinvokeMainvokeMaparse_result
    —

    Parse a list of candidate model Generation objects into a specific format.

    Maparse
    —

    Async parse a single string model output into some structure.

    Mparse_with_prompt
    —

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

    Mdict
    —

    Return dictionary representation of output parser.

    Inherited fromBaseLLMOutputParser

    Methods

    Maparse_result
    —

    Parse a list of candidate model Generation objects into a specific format.

    Inherited fromRunnableSerializable

    Attributes

    Aname: str | None
    —

    The name of the Runnable.

    Amodel_config

    Methods

    Mto_json
    —

    Serialize the Runnable to JSON.

    Mconfigurable_fields
    —

    Configure particular Runnable fields at runtime.

    Mconfigurable_alternatives
    —

    Configure alternatives for Runnable objects that can be set at runtime.

    Inherited fromSerializable

    Attributes

    Alc_secrets: dict[str, str]
    —

    A map of constructor argument names to secret ids.

    Alc_attributes: dict
    —

    List of attribute names that should be included in the serialized kwargs.

    Amodel_config

    Methods

    Mis_lc_serializable
    —

    Is this class serializable?

    Mget_lc_namespace
    —

    Get the namespace of the LangChain object.

    Mlc_id
    —

    Return a unique identifier for this class for serialization purposes.

    Mto_json
    —

    Serialize the object to JSON.

    Mto_json_not_implemented
    —

    Serialize a "not implemented" object.

    Inherited fromRunnable

    Attributes

    Aname: str | None
    —

    The name of the Runnable. Used for debugging and tracing.

    AInputType: type[Input]
    —

    Input type.

    AOutputType: type[Output]
    —

    Output Type.

    Ainput_schema: type[BaseModel]
    —

    The type of input this Runnable accepts specified as a Pydantic model.

    Aoutput_schema: type[BaseModel]
    —

    Output schema.

    Aconfig_specs: list[ConfigurableFieldSpec]
    —

    List configurable fields for this Runnable.

    Methods

    Mget_name
    —

    Get the name of the Runnable.

    Mget_input_schema
    —

    Get a Pydantic model that can be used to validate input to the Runnable.

    Mget_input_jsonschema
    —

    Get a JSON schema that represents the input to the Runnable.

    Mget_output_schema
    —

    Get a Pydantic model that can be used to validate output to the Runnable.

    Mget_output_jsonschema
    —

    Get a JSON schema that represents the output of the Runnable.

    Mconfig_schema
    —

    The type of config this Runnable accepts specified as a Pydantic model.

    Mget_config_jsonschema
    —

    Get a JSON schema that represents the config of the Runnable.

    Mget_graph
    —

    Return a graph representation of this Runnable.

    Mget_prompts
    —

    Return a list of prompts used by this Runnable.

    Mpipe
    —

    Pipe Runnable objects.

    Mpick
    —

    Pick keys from the output dict of this Runnable.

    Massign
    —

    Assigns new fields to the dict output of this Runnable.

    Minvoke
    —

    Transform a single input into an output.

    Mainvoke
    —

    Transform a single input into an output.

    Mbatch
    —

    Default implementation runs invoke in parallel using a thread pool executor.

    Mbatch_as_completed
    —

    Run invoke in parallel on a list of inputs.

    Mabatch
    —

    Default implementation runs ainvoke in parallel using asyncio.gather.

    Mabatch_as_completed
    —

    Run ainvoke in parallel on a list of inputs.

    Mstream
    —

    Default implementation of stream, which calls invoke.

    Mastream
    —

    Default implementation of astream, which calls ainvoke.

    Mastream_log
    —

    Stream all output from a Runnable, as reported to the callback system.

    Mastream_events
    —

    Generate a stream of events.

    Mtransform
    —

    Transform inputs to outputs.

    Matransform
    —

    Transform inputs to outputs.

    Mbind
    —

    Bind arguments to a Runnable, returning a new Runnable.

    Mwith_config
    —

    Bind config to a Runnable, returning a new Runnable.

    Mwith_listeners
    —

    Bind lifecycle listeners to a Runnable, returning a new Runnable.

    Mwith_alisteners
    —

    Bind async lifecycle listeners to a Runnable.

    Mwith_types
    —

    Bind input and output types to a Runnable, returning a new Runnable.

    Mwith_retry
    —

    Create a new Runnable that retries the original Runnable on exceptions.

    Mmap
    —

    Return a new Runnable that maps a list of inputs to a list of outputs.

    Mwith_fallbacks
    —

    Add fallbacks to a Runnable, returning a new Runnable.

    Mas_tool
    —

    Create a BaseTool from a Runnable.

    View source on GitHub