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    Pythonlangchain-coreoutput_parsersopenai_toolsJsonOutputToolsParser
    Class●Since v0.1

    JsonOutputToolsParser

    Parse tools from OpenAI response.

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

    Bases

    BaseCumulativeTransformOutputParser[Any]

    Attributes

    attribute
    strict: bool

    Whether to allow non-JSON-compliant strings.

    See: https://docs.python.org/3/library/json.html#encoders-and-decoders

    Useful when the parsed output may include unicode characters or new lines.

    attribute
    return_id: bool

    Whether to return the tool call id.

    attribute
    first_tool_only: bool

    Whether to return only the first tool call.

    If False, the result will be a list of tool calls, or an empty list if no tool calls are found.

    If True, and multiple tool calls are found, only the first one will be returned, and the other tool calls will be ignored.

    If no tool calls are found, None will be returned.

    Methods

    method
    parse_result

    Parse the result of an LLM call to a list of tool calls.

    method
    parse

    Parse the output of an LLM call to a list of tool calls.

    Inherited fromBaseCumulativeTransformOutputParser

    Attributes

    Adiff: bool
    —

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

    Inherited fromBaseTransformOutputParser

    Methods

    MtransformMatransform

    Inherited fromBaseOutputParser

    Attributes

    AInputType: AnyAOutputType: Any

    Methods

    Minvoke
    —

    Invoke the retriever to get relevant documents.

    Mainvoke
    —

    Asynchronously invoke the retriever to get relevant documents.

    Maparse_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.

    Mget_format_instructions
    —

    Return the format instructions for the comma-separated list output.

    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
    —

    The name of the function.

    Amodel_config

    Methods

    Mto_json
    —

    Convert the graph to a JSON-serializable format.

    Mconfigurable_fieldsMconfigurable_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
    —

    Return True as this class is 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
    —

    Convert the graph to a JSON-serializable format.

    Mto_json_not_implemented
    —

    Serialize a "not implemented" object.

    Inherited fromRunnable

    Attributes

    Aname: str
    —

    The name of the function.

    AInputType: AnyAOutputType: AnyAinput_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]

    Methods

    Mget_nameMget_input_schemaMget_input_jsonschema
    —

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

    Mget_output_schemaMget_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_graphMget_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
    —

    Merge the Dict input with the output produced by the mapping argument.

    Minvoke
    —

    Invoke the retriever to get relevant documents.

    Mainvoke
    —

    Asynchronously invoke the retriever to get relevant documents.

    MbatchMbatch_as_completed
    —

    Run invoke in parallel on a list of inputs.

    MabatchMabatch_as_completed
    —

    Run ainvoke in parallel on a list of inputs.

    MstreamMastreamMastream_log
    —

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

    Mastream_events
    —

    Generate a stream of events.

    MtransformMatransformMbind
    —

    Bind arguments to a Runnable, returning a new Runnable.

    Mwith_configMwith_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
    —

    Map a function to multiple iterables.

    Mwith_fallbacks
    —

    Add fallbacks to a Runnable, returning a new Runnable.

    Mas_tool
    —

    Create a BaseTool from a Runnable.

    View source on GitHub