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    Pythonlangchain-corerunnablesbaseRunnableEach
    Class●Since v0.1

    RunnableEach

    RunnableEach class.

    Runnable that calls another Runnable for each element of the input sequence.

    It allows you to call multiple inputs with the bounded Runnable.

    RunnableEach makes it easy to run multiple inputs for the Runnable. In the below example, we associate and run three inputs with a Runnable:

    from langchain_core.runnables.base import RunnableEach
    from langchain_openai import ChatOpenAI
    from langchain_core.prompts import ChatPromptTemplate
    from langchain_core.output_parsers import StrOutputParser
    prompt = ChatPromptTemplate.from_template("Tell me a short joke about
    {topic}")
    model = ChatOpenAI()
    output_parser = StrOutputParser()
    runnable = prompt | model | output_parser
    runnable_each = RunnableEach(bound=runnable)
    output = runnable_each.invoke([{'topic':'Computer Science'},
                                {'topic':'Art'},
                                {'topic':'Biology'}])
    print(output)  # noqa: T201
    
    Copy
    RunnableEach(
        self,
        *args: Any = (),
        **kwargs: Any = {},
    )

    Bases

    RunnableEachBase[Input, Output]

    Methods

    method
    get_name
    method
    bind
    method
    with_config
    method
    with_listeners

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

    The Run object contains information about the run, including its id, type, input, output, error, start_time, end_time, and any tags or metadata added to the run.

    method
    with_alisteners

    Bind async lifecycle listeners to a Runnable.

    Returns a new Runnable.

    The Run object contains information about the run, including its id, type, input, output, error, start_time, end_time, and any tags or metadata added to the run.

    Inherited fromRunnableEachBase

    Attributes

    Abound: Runnable[Input, Output]Amodel_configAInputType: AnyAOutputType: type[list[Output]]Aconfig_specs: list[ConfigurableFieldSpec]

    Methods

    Mget_input_schemaMget_output_schemaMget_graphMis_lc_serializable
    —

    Return True as this class is serializable.

    Mget_lc_namespace
    —

    Get the namespace of the LangChain object.

    MinvokeMainvokeMastream_events

    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_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.

    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