langchain.schema.runnable.RunnableBinding

class langchain.schema.runnable.RunnableBinding(*, bound: Runnable[Input, Output], kwargs: Mapping[str, Any])

Bases: Serializable, Runnable[Input, Output]

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 bound: langchain.schema.runnable.Runnable[langchain.schema.runnable.Input, langchain.schema.runnable.Output] [Required]

param kwargs: Mapping[str, Any] [Required]

async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, max_concurrency: Optional[int] = None) → List[Output]

async ainvoke(input: Input, config: Optional[RunnableConfig] = None) → Output

async astream(input: Input, config: Optional[RunnableConfig] = None) → AsyncIterator[Output]

batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, max_concurrency: Optional[int] = None) → List[Output]

bind(**kwargs: Any) → Runnable[Input, Output]

Bind arguments to a Runnable, returning a new Runnable.

invoke(input: Input, config: Optional[RunnableConfig] = None) → Output

stream(input: Input, config: Optional[RunnableConfig] = None) → Iterator[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

arbitrary_types_allowed = True